D2287R00103 Observational study of obstructive lung...

Non-Interventional Study Protocol

Study Code D2287R00103

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Date 18 December 2015

D2287R00103 Observational study of obstructive lung disease (NOVELTY)

A NOVEL observational longiTudinal studY on patients with a diagnosis or

suspected diagnosis of asthma and/or COPD to describe patient

characteristics, treatment patterns and the burden of illness over time and

to identify phenotypes and endotypes associated with differential outcomes

that may support future development of personalised treatment strategies

TITLE PAGE

Sponsor:

AstraZeneca AB

Karlebyhus, Astraallén

151 85 Södertälje, Sweden

T: +46 (0)8 553 260 00

F: +46 (0)8 553 290 00

Non-Interventional Study Protocol Study Code D2287R00103

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TABLE OF CONTENTS PAGE

TITLE PAGE ........................................................................................................... 1

TABLE OF CONTENTS ......................................................................................... 2

RESPONSIBLE PARTIES ...................................................................................... 8

PROTOCOL SYNOPSIS ......................................................................................... 9

AMENDMENT HISTORY ................................................................................... 16

MILESTONES ....................................................................................................... 17

1. BACKGROUND AND RATIONALE .................................................................. 18

1.1 Background ............................................................................................................ 18

1.2 Rationale ................................................................................................................ 20

2. OBJECTIVES ........................................................................................................ 24

2.1 Primary Objectives ................................................................................................. 24

2.2 Secondary Objectives ............................................................................................. 24

2.3 Exploratory objectives ........................................................................................... 25

3. METHODOLOGY ................................................................................................ 25

3.1 Study Design � General Aspects ............................................................................ 25

3.1.1 Data Source(s) ........................................................................................................ 26

3.2 Study Population .................................................................................................... 28

3.3 Inclusion Criteria ................................................................................................... 28

3.4 Exclusion Criteria .................................................................................................. 29

3.5 Patient Follow-up ................................................................................................... 29

3.5.1 Discontinuation of patients .................................................................................... 29

3.5.2 Procedures for discontinuation .............................................................................. 29

3.5.3 Discontinuation of study ........................................................................................ 30

4. VARIABLES AND EPIDEMIOLOGICAL MEASUREMENTS ........................ 30

4.1 Exposure to treatments ........................................................................................... 32

4.2 Outcomes ............................................................................................................... 33

4.2.1 Primary endpoints .................................................................................................. 33

4.2.2 Secondary and exploratory endpoints .................................................................... 33

5. STATISTICAL ANALYSIS PLAN ...................................................................... 34

5.1 Statistical Methods � General Aspects................................................................... 34

5.1.1 Yearly descriptive analyses .................................................................................... 34


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5.1.2 End of study descriptive analyses .......................................................................... 35

5.1.3 Multivariable Data Analysis .................................................................................. 35

5.1.4 Exploratory Analyses ............................................................................................. 36

5.2 Handling of Missing Data ...................................................................................... 37

5.3 Bias ........................................................................................................................ 37

5.3.1 Strengths and Limitations ...................................................................................... 37

5.3.2 Bias and Methods to Minimize Bias ...................................................................... 38

5.4 Interim Analyses .................................................................................................... 39

5.5 Sample Size and Power Calculations ..................................................................... 39

6. STUDY CONDUCT AND REGULATORY DETAILS....................................... 41

6.1 Data Management .................................................................................................. 41

6.1.1 Data Entry/Electronic Data Capture (EDC) ........................................................... 41

6.1.2 Study Flow Chart and Plan .................................................................................... 42

6.1.3 Procedures .............................................................................................................. 44

6.1.3.1 Specific procedures for Patient-reported Outcomes questionnaires ...................... 45

6.1.3.2 Specific procedures for Laboratory Tests .............................................................. 47

6.1.4 Quality Control (QC) ............................................................................................. 47

6.1.5 Storage and Retention ............................................................................................ 48

6.2 Protection of Human Subjects................................................................................ 49

6.2.1 Patient Informed Consent ...................................................................................... 49

6.2.2 Confidentiality of Study/Patient Data .................................................................... 50

6.3 Management and Report of Adverse Drug Reactions ........................................... 51

6.3.1 Definition of Adverse Drug Reaction (ADR) and Serious ADR ........................... 51

6.3.2 Reporting of Adverse Drug Reactions (ADRs) and Serious ADRs....................... 51

6.4 Study Governance and Committees ....................................................................... 51

6.5 Communication Plan .............................................................................................. 52

6.5.1 Publication Plan ..................................................................................................... 52

6.5.2 Compliance with Study Registration and Results Posting Requirements ............. 52

6.5.3 Compliance with Financial Disclosure Requirements ........................................... 53

6.5.4 Changes to the Protocol ......................................................................................... 53

7. LIST OF REFERENCES ....................................................................................... 54

8. APPENDICES ....................................................................................................... 56

8.1 List of countries and targeted number of patients .................................................. 56

8.2 Specific procedures for Laboratory Tests .............................................................. 58

8.3 International Airline Transportation Association (IATA) 6.2 Guidance

Document ............................................................................................................... 61

8.4 EMR feasibility study overview ............................................................................ 62

9. ATTACHMENTS .................................................................................................. 64


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10. SIGNATURES ....................................................................................................... 65


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LIST OF ABBREVIATIONS

Abbreviation or

special term

Explanation

6MWD 6-min walk distance

ACT Asthma Control Test

ADR Adverse Drug Reaction

AZ AstraZeneca

BMI Body Mass Index

CAPTURE COPD Foundation Primary Care Tool for Undiagnosed Respiratory Disease

and Exacerbation Risk

CAAT Chronic Airways Assessment Test

CAT COPD Assessment Test

CDNA Consolidated Data Network Approach

CI Confidence Interval

COPD Chronic Obstructive Pulmonary Disease

CPRD Clinical Practice Research Datalink

CRO Contract Research Organisation

CRP C-Reactive Protein

CT Computed tomography

DBL Database lock

DGR Dangerous Goods Regulations

DLCO Diffusion Capacity of the lung for Carbon Monoxide

DMP Data Management Plan

DNA Deoxyrribonucleic acid

ECLIPSE Evaluation of COPD Longitudinally to Identify Predictive Surrogate

Endpoint

eCRF electronic Case Report Form

EDC Electronic Data Capture

EMR Electronic Medical Record

EQ-5D-5L EuroQol 5 Dimensions 5 Levels health questionnaire

FDA Food and Drug Administration

FEF25-75% Forced Expiratory Flow at 25-75% of the forced vital capacity

FENO Fractional Exhaled Nitric Oxide

FEV1 Forced Expiratory Volume in 1 second

FPA Full Prospective Approach


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Abbreviation or

special term

Explanation

FPI First Patient In

FVC Forced Vital Capacity

GCP Good Clinical Practice

GINA Global Initiative for Asthma

GMA AstraZeneca�s Global Medical Affairs

GMD AstraZeneca�s Global Medicines Development

GOLD Global Initiative for Chronic Obstructive Lung Disease

GPP Good Pharmacoepidemiology Practices

GPSS Global Product & Portfolio Strategy

HDM House-Dust Mite

HRQoL Health-Related Quality of Life

IA Integrated Approach

IATA International Airline Transportation Association

IC Inspiratory Capacity

ICF Informed Consent Form

ICH International Conference on Harmonisation of Technical Requirements for

Registration of Pharmaceuticals for Human Use

ICSR Individual Case Safety Report

ID Identification Number

IEC Independent Ethics Committee

IL Interleukin

IRB Institutional Review Board

LPI Last Patient In

LPLV Last Patient Last Visit

LTE4 Leukotriene E4

MC Marketing Company

MEOR AstraZeneca�s Medical Evidence & Observational Research

mMRC modified Medical Research Council

NOVELTY NOVEL observational longiTudinal studY

PBRER Periodic Benefit-Risk Evaluation Report

PEF Peak Expiratory Flow

PRO Patient-Reported Outcome


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Abbreviation or

special term

Explanation

QC Quality Control

REP Rapid Evaluation Process

RNA Ribonucleic acid

RSQ Respiratory Symptoms Questionnaire

RTI Respiratory Tract Infection

SAP Statistical Analysis Plan

SGRQ St. George�s Respiratory Questionnaire

SPIROMICS Subpopulations and Intermediate Outcomes in COPD Study

STROBE STrengthening the Reporting of OBservational studies in Epidemiology

THIN The Health Improvement Network

U-BIOPRED Unbiased BIOmarkers in PREDiction of respiratory disease outcomes

UK United Kingdom

US United States

WPAI Work Productivity and Activity Impairment


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RESPONSIBLE PARTIES

Name Professional

Title

Role in Study Affiliation Email Address

Maria

Gerhardsson

de Verdier

Director

Epidemiology Scientific lead Medical Evidence &

Observational Research

Centre (MEOR),

Global Medical Affairs

(GMA),Global Product

& Portfolio Strategy

(GPPS),

AstraZeneca

Gothenburg

SE-431 83 Mölndal,

Sweden

Maria.Gerhardsson

@astrazeneca.com

Javier Nuevo Director

Epidemiology

Epidemiology

support

MEOR, GMA, GPPS,

AstraZeneca

Madrid, Spain

Javier.Nuevo@astra

zeneca.com

Alecka

Sveréus

Study Program

Director

Operational

Lead

MEOR, GMA, GPPS,

AstraZeneca

Gothenburg SE-431 83

Mölndal, Sweden

Alecka.Svereus@as

trazeneca.com

Fredrik

Nyberg

Group Director

Epidemiology,

RIA

Sponsor MEOR, GMA, GPPS,

AstraZeneca

Gothenburg SE-431 83

Mölndal, Sweden

Fredrik.Nyberg@as

trazeneca.com

Pierre Engel Associate

Director

Epidemiology

Clinical

Research

Organisation

(CRO) -

protocol

writing

Quintiles, 5 Rue

Maurice Ravel

92594 Levallois-Perret

Cedex, France

Pierre.Engel@Quin

tiles.com

Sophie

Questat

Project Director CRO -

Operational

Lead

PAREXEL International

Limited, The Quays,

101-105 Oxford Road,

Uxbridge, Middlesex

UB8 1LZ

Sophie.Questat@Pa

rexel.com


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PROTOCOL SYNOPSIS

A NOVEL observational longiTudinal studY on patients with a diagnosis or suspected

diagnosis of asthma and/or COPD to describe patient characteristics, treatment patterns

and the burden of illness over time and to identify phenotypes and endotypes associated

with differential outcomes that may support future development of personalised

treatment strategies

Background/Rationale:

The two major obstructive lung diseases, asthma and Chronic Obstructive Pulmonary Disease

(COPD), are multifaceted diseases that are associated with significant impairment and risk of

health deterioration, and both currently have a therapeutic response that is highly variable.

Asthma and COPD have traditionally been viewed as distinct clinical entities. Recently,

however, attention has also been focused on patients with overlapping features of both asthma

and COPD. The concept of the asthma and COPD overlap focuses attention on the need to

accelerate beyond the information available at present on populations with physician

diagnoses of asthma and COPD. The aim should be to identify phenotypes and endotypes

(mechanisms)* to help develop targeted treatments for patients across the range of obstructive

lung diseases and to generate a new taxonomy of obstructive lung disease. In an attempt to

better characterise and treat asthma and COPD, many studies have been performed over the

last decade to define different phenotypes. A variety of parameters have been identified for

such definitions, including: clinical and functional characteristics, frequency of exacerbations,

age of onset, presence of allergy, geographical localisation, and different biomarkers.

However, many of these studies have been performed in patients identified by conventional

diagnostic labels, or who satisfy stringent enrolment criteria for clinical trials; the latter

patients may only represent around 4-5% of patients with asthma or COPD in the general

community, and those with asthma-COPD overlap are almost invariably excluded. In addition,

one phenotype may relate to different endotypes and vice versa so distinct pathogenic profiles

need to be more clearly identified in order to develop personalised treatment strategies

directed towards disease/mechanism-specific features, which can be expected to improve

patients� outcomes.

* An endotype is a subtype of a condition, which is defined by a distinct functional or pathobiological

mechanism. This is distinct from a phenotype, which is any observable characteristic or trait of a disease, such as

morphology, development, biochemical or physiological properties, or behaviour, without necessarily any

implication of a mechanism.


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There is a need for new broad and consistent prospective, observational data on patients with

obstructive lung disease, despite the availability of many current data sources, as well as many

stand-alone respiratory studies and cohorts. This is because very few data sources span across

disease labels, countries or regions and generally do not collect detailed information on patient

characteristics such as patient reported outcomes (PRO), functional measurements, and

healthcare resource use. Furthermore, there is very limited availability of emerging biomarker

data (especially linked to other data types), which are key to understanding novel phenotypes

and endotypes, disease mechanism, and disease progression, and to drive scientific discovery

in obstructive lung disease.

To overcome these limitations, the NOVELTY study will recruit patients with a diagnosis or

suspected diagnosis of asthma and/or COPD, and collect data currently lacking to allow for

multinational data collection to fill regional/local gaps and improve comparability across

regions.

The diversity of data collection approaches will enable capture of rich clinical data on enrolled

patients. The use of advanced statistical analysis tools will allow characterisation of

phenotypes and endotypes associated with future symptom burden, clinical progression and/or

health care utilisation.

Furthermore, it is expected that the data platform created by the study will continue to be a

useful resource even once the objectives of the core study are met, generating new insight for

the broader community of patients, physicians, payers, regulators, and for the scientific

community.

Objectives:

The primary objectives are:

· To describe patient characteristics, treatment patterns and the burden of illness over time

for individuals in clinical practice with a diagnosis, or suspected diagnosis,� of asthma

and/or COPD. Data will be described for the population overall and by pre-specified

subgroups, including by country, demographics, exposures, symptom history, treatment

history, concurrent clinical features, treatment setting, socioeconomic setting and access

to healthcare

· To identify phenotypes and endotypes, based on biomarkers and/or clinical parameters,

that are associated with differential outcomes for symptom burden, clinical evolution

and healthcare resource utilisation, in individuals with a diagnosis, or suspected

diagnosis, of asthma and/or COPD

� Suspected diagnosis means a patient with respiratory symptoms consistent with asthma or COPD, who has not

had diagnostic investigations, or has not received a formal diagnosis of asthma or COPD


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The secondary objectives are:

· In patients with a diagnosis or suspected diagnosis of asthma and/or COPD, to compare

their current diagnostic labels and physician-assessed disease severity with existing

international criteria and phenotypic groupings

· To describe patient characteristics, symptom burden, quality of life, exacerbation rates

and clinical progression over time, by phenotype/endotype for: (a) patients with recent-

onset chronic respiratory disease, (b) patients considered by physician assessment or by

specified criteria to have mild disease at enrolment and (c) patients considered by

physician assessment or by specified criteria to have severe disease at enrolment

· To describe the association between specified biomarkers, at enrolment and over time,

and evaluate their stability over time, factors affecting their variability, and their

relationship with clinical features, among patients with airways disease

Exploratory objectives are:

· To describe healthcare resource use overall and related to respiratory diseases

· To describe PROs, e.g. symptom assessment, disease control, impact on daily activity

and quality of life

· To assess the occurrence of exacerbations and other conditions, including upper and

lower Respiratory Tract Infections (RTIs), including seasonal variations, and their

relationship with clinical outcomes

· To assess the adequacy of EMR in some countries for obtaining data about

characteristics, clinical progress and treatment of patients with obstructive airways

disease

Methods:

Study design:

This study is a multi-country�, multicentre, observational, prospective, longitudinal

cohort study which will include patients with a physician diagnosis, or suspected

diagnosis, of asthma and/or COPD. Patients will undergo clinical assessments and

receive standard medical care as determined by the treating physician. All patients

enrolled in the NOVELTY study will be followed up yearly by their treating physician

for a total duration of three years. In addition, patients are expected to be followed up

remotely once every quarter.

� Country participation to this protocol is flexible, but core countries planned for the study include countries from

North America (e.g. Canada, US), Europe (e.g. France, Germany, Italy, Spain, UK, Nordic countries � Denmark,

Norway and Sweden), Asia (e.g. China mainland, Japan, South Korea) and Oceania (e.g. Australia).


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Data Source(s):

Data for the NOVELTY study population will come from several different sources:

electronic Case Report Form (eCRF), PRO, centralised spirometry data, biological data

and EMR (some countries). The core of the data collection will come from the eCRF,

which will be implemented in all countries and will therefore provide a consistently

collected set of variables aligned to the study objectives. These data will be enriched

by PRO, functional measurements and biospecimen sample collection (when

voluntarily consented). In the countries in which EMR data are extracted, both eCRF

and EMR will be used as source of patient�s information and the eCRF will be used as

a reference to validate the adequacy of existent EMR.

Study Population:

It is estimated that approximately 7,700 patients with suspected or primary diagnosis

of asthma and 7,100 patients with suspected or primary diagnosis of COPD will be

enrolled by a diverse set of physicians (e.g. primary care physicians, allergists,

pulmonologists) from community and hospital outpatient settings within the countries

targeted for NOVELTY.

Patients meeting the following inclusion criteria will be included:

· Diagnosis, or suspected diagnosis (patients with respiratory symptoms consistent

with asthma or COPD) of asthma and/or COPD, according to clinician�s

judgement

· Age !12 years (note: in most countries it will only be feasible to include patients

aged !18 years)

· Willing and able to sign written, informed consent (or having a responsible,

legally authorised representative acting on patient�s behalf)

· Enrolment from an active clinical practice

The following patients will be excluded from the study:

· Patients who participated in any respiratory interventional trial during the 12

months prior to, or at enrolment

· Patients who, in the opinion of the physician, are unlikely to complete 3 years of

follow-up, e.g. poor literacy, substance abuse, life-threatening co-morbidity

· Patients whose primary respiratory diagnosis (i.e. the condition causing most of

their respiratory symptoms) is not asthma or COPD (however, a co-diagnosis of

another respiratory disease such as bronchiectasis or interstitial lung disease

together with asthma or COPD will be accepted)

In addition, the following are considered criteria for exclusion from the exploratory

genetic research (donation of blood for DNA and RNA analysis)

· Previous allogeneic bone marrow transplant


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· Non-leukocyte depleted whole blood transfusion within 120 days of the date of the

genetic sample collection

Exposure(s):

The NOVELTY study is a longitudinal cohort study which does not involve or study a

specific medicinal product; it will constitute a disease registry. Information about

exposure to treatments as part of routine care will be collected (frequency, treatment,

duration).

Outcome(s):

The primary endpoints are the following, reported for the study population as a whole,

by country, by disease (i.e. asthma, COPD and asthma-COPD overlap when

considered appropriate) and by specified sub-groups:

· Baseline distribution of enrolled patients diagnosed with asthma and/or COPD as

per the physician�s clinical judgement, by disease severity and/or control, by site

type, by physician characteristics, etc.

· Baseline summary statistics (e.g. demographics, physiological, disease

information, productivity/HRQoL, treatments, risk factors, healthcare resources

use, biomarkers, etc.) of patients by disease severity and/or control, by site type,

by physician characteristics, etc.

· Longitudinal (at each follow-up assessment) summary statistics, as suggested

above, of patients by current disease severity and/or control, by site type, by

physician characteristics, etc.

· Identification of phenotypic and endotypic groups, based on clinical parameters

and biomarkers, that are associated with differential outcomes over time for

symptom burden, clinical evolution (including decline in lung function) and

healthcare utilisation. The characteristics of these groups at baseline and at each

follow-up assessment will be described.

· Predictors of phenotypic and endotypic groups, including history of childhood

respiratory symptoms, exposure to tobacco smoke, treatment, etc

· Correlation between biomarkers and phenotypes and endotypes at baseline and at

each follow-up assessment

The secondary and exploratory endpoints will include the following, reported for the

study population as a whole, by country, by disease (i.e. asthma, COPD and asthma-

COPD overlap when considered appropriate) and by specified sub-groups:

· Concordance by severity and/or control between diagnosis according to guidelines

(using the data available at baseline) and according to the initial clinician

diagnosis at recruitment

· Frequency of treatment modification (dosage change, switch, discontinuation) and

reason for modifications between each follow-up assessment


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· Correlation between biomarkers, disease severity and/or control and different

measures of response to treatment.

· Factors associated with treatment at baseline and patient-reported treatment

satisfaction and preference at baseline and at each follow-up assessment

· Level of symptom control at baseline and at each follow-up assessment

· Frequency of exacerbations according to seasonal variations and conditions,

including RTI, in the year prior to enrolment and during the study

· Summary scores of PROs overall and by specific subgroups (e.g. treatment

patterns, phenotype/endotype, etc.) if considered appropriate, at baseline and at


· Direct and indirect healthcare resource use by resources categories overall and

those related with respiratory disease at baseline and at each follow-up assessment

· Presence of known risk factors for development of airways disease

· Levels of biomarker parameters, lung function, and risk factors at each follow-up

assessment, and variability in these measures.

· Relationship between disease control, Health-Related Quality of Life (HRQoL),

exacerbations, and healthcare resource use stratified by severity of disease

· Reasons for non-adherence to treatment

Sample Size Estimations:

The target minimum number of 100 patients per diagnostic label (asthma or COPD),

physician-assessed severity level and country has been chosen to support many basic

local reimbursement specific requirements with reasonable precision, and to provide

large sample size for scientific questions applicable across severities and countries.

Therefore, considering the targeted countries, it is estimated that approximately 7,700

patients with asthma and 7,100 patients with COPD will be enrolled.

Statistical Analysis:

The statistical analyses will be fully described in Statistical Analysis Plan (SAP) as

appropriate.

After baseline data collection and each annual data collection, data will be summarized

for the population overall and by pre specified subgroups, including by country,

demographics, exposures, symptom history, treatment history, concurrent clinical

features, treatment setting, socioeconomic setting and access to healthcare, where

relevant.

Patients� changes regarding their treatment, disease or severity among and other

variables that are observed between baseline and follow-up visits, will also be

described.

To identify potential differences in disease diagnosis and severity classifications

between physicians and guidelines, data collected on lung function results, symptom


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questionnaires, exacerbation occurrences and medication will allow the formal and

consistent classification of the patients according to relevant international guidelines

and other current and future phenotypic/diagnostic classifications.

Multivariable models will be used to assess the following: the occurrence of

exacerbations and other conditions, including upper and lower Respiratory Tract

Infections (RTIs) and their relationship with clinical outcomes, the relationship

between PRO and disease control with impact on daily activity and quality of life, and

the relationship between healthcare resource use overall and related to respiratory

diseases with disease severity, clinical outcomes, disease type, etc.

Multivariable analysis techniques will be used to identify phenotypes and endotypes,

based on biomarkers and/or clinical parameters that are associated with differential

outcomes for symptom burden, clinical evolution and healthcare utilisation.


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AMENDMENT HISTORY

Date Brief description of change Administrative Change / Amendment /

New Protocol Version.

N/A N/A N/A


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MILESTONES

Date Milestone

December 2015 Final Study Protocol

2/3Q 2016 First Patient In (FPI)

2/3Q 2017 Last Patient In (LPI)

2/3Q 2020 Last Patient Last Visit (LPLV)

2017-2020 Interim analyses

2020 Final database lock (DBL)

2021 Final report of core analysis (after 3 years of follow-up)

2020-- Continued availability of database platform for research. Continued longitudinal

follow-up through Electronic Medical Record (EMR)

Note: Q: Quarter.


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1. BACKGROUND AND RATIONALE

1.1 Background

The two major obstructive lung diseases, asthma and chronic obstructive pulmonary disease

(COPD), are multifaceted diseases that are associated with significant impairment and risk of

health deterioration, and both currently have a therapeutic response that is highly variable.1,2

Treatment progress has stalled

Optimally used, current treatments for obstructive lung disease, including asthma and COPD,

can often control symptoms relatively effectively for patients with mild-to-moderate disease.

However, underdiagnoses and misdiagnoses, inadequate clinical evaluation, poor treatment

adherence, lifestyle habits (e.g. smoking) and comorbidities lead to a considerable proportion

of patients with uncontrolled symptoms and an increased risk of adverse outcomes.

Insufficient disease control, or lack of targeting of specific underlying mechanisms, may

contribute to risk of symptoms, exacerbations or progression to more severe disease. Patients

with more severe or more long-standing disease are often less responsive to current disease

management, and there remains an unmet need for agents with properties that may achieve

control in these individuals. Despite increasing investment in treatment of obstructive lung

disease, progress has stalled during the last ten years, and there has not been comparable

advancement in the development of new treatments for asthma and COPD as has been seen

for many other diseases. New thinking is therefore needed.

Paradigm shift in disease understanding

Asthma and COPD have traditionally been viewed as distinct clinical entities. Recently,

however, attention has also been focused on patients with overlapping features of both asthma

and COPD.3,4,5,6,7,8,9

Although agreement on definitions is still lacking, approximately 15-25%

of patients with a diagnosis of asthma or COPD have both diagnoses.10,11

When basing the

diagnosis on lung function criteria, the estimated prevalence of asthma-COPD overlap has

varied from 17% to 60%.8 The concept of the asthma COPD overlap focuses attention on the

need to accelerate beyond the information available at present on populations with physician

diagnoses of asthma or COPD. The aim should be to identify phenotypes and endotypes

(mechanisms)§ to help develop targeted treatments for patients across the range of obstructive

lung diseases and to generate a new taxonomy of obstructive lung disease.8,9

To better

understand and treat these patients, research is needed to improve the understanding of the

different clinical profiles, including asthma-COPD overlap, how these profiles correlate with

§ An endotype is a subtype of a condition, which is defined by a distinct functional or pathobiological

mechanism. This is distinct from a phenotype, which is any observable characteristic or trait of a disease, such as

morphology, development, biochemical or physiological properties, or behaviour, without necessarily any

implication of a mechanism.


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specific phenotypes and endotypes, and to achieve better management strategies targeted to

diverse underlying mechanisms.

In an attempt to better characterise and treat asthma and COPD, many studies have been

performed over the last decade to define different phenotypes.12,13,14,15,16,17

A variety of

parameters have been identified for such definitions, including: clinical and functional

characteristics, frequency of exacerbations, age of onset, presence of allergy, geographical

localisation, and different biomarkers. Further, it is often difficult to distinguish features of

subtypes of disease from measures of disease severity that progress over time. Since one

phenotype may relate to different endotypes and vice versa, distinct pathogenic profiles need

to be more clearly identified in order to develop personalised treatment strategies. These

personalised treatments will thus be directed towards disease/mechanism-specific features,

which can be expected to improve outcomes in these patients.

There is ongoing research to identify bioactive molecules that contribute to the

pathophysiology of asthma and COPD, and many of these have been identified as potential

therapeutic targets to improve control of obstructive lung disease. As a consequence of these

efforts, monoclonal antibodies and small molecules with specific targets are under

development and are expected to show better effectiveness in the treatment of asthma and

COPD.

However, the study of the efficacy of new molecules has been challenged by the fact that

typically, most clinical trials in asthma and COPD, particularly those designed to test new

medications, exclude up to 95% of the patient population potentially eligible for treatment18,19

and patients with asthma-COPD overlap are almost invariably excluded from such studies.

Therefore, the phenotypes presented in these controlled settings may not be representative of

the real-world population. In addition, patients are often studied late in the course of the

disease, when the original underlying mechanisms may be obscured by the effects of ageing,

exposures, treatment and psychosocial factors. Thus, the effectiveness of targeted treatments

which are dependent on the predictive value of biomarkers needs to be verified in longitudinal

studies on patients in real life, including patients with recent disease onset. In addition, current

treatment guidelines are based on clinical trials which may exclude the majority of patients,

and consequently may under-represent pathogenic profiles of interest, e.g., comorbidity is

often an exclusion criterion in clinical trials, although comorbidity contributes to the burden of

illness in both asthma and COPD.

Existing knowledge gaps remain in real life data: driving novel science

Adequate and comparable data sources to describe patient characteristics, treatment patterns

and the burden of illness in current clinical practice over time, as well as to explore new target

populations, are currently lacking, including comparable data across disease entities, disease

severities and countries. In fact, despite the availability of many data sources (e.g. multi-

purpose health care databases such as the Clinical Practice Research Datalink [CPRD] / The

Health Improvement Network [THIN] in the UK; IMS Disease Analyser in the United

Kingdom [UK], France and Germany; registries in the Nordic countries; PHARMO in the

Netherlands; MarketScan, Humedica and Healthcore in United States [US]; as well as many


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stand-alone respiratory studies and cohorts), there is a need for new, broad and consistent

prospective, observational data on patients with obstructive lung disease. This is because very

few data sources span across countries or regions. Even in better-supplied geographical areas,

available data sources generally do not collect detailed data on change over time (e.g. data on

lung function, smoking habits, Body Mass Index [BMI], Health-Related Quality of Life

[HRQoL], symptom control, and healthcare resources use are missing and/or not comparable).

Furthermore, there is very limited availability of emerging biomarker data (especially linked

to other types of data), which is key to understanding novel phenotypes and endotypes,

disease mechanism, and disease progression, and to drive scientific discovery in obstructive

lung disease. Current front-line scientific collaborations in respiratory diseases (such as

Unbiased BIOmarkers in PREDiction of respiratory disease outcomes [U-BIOPRED]20

and

Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints [ECLIPSE]21

)

tend to be restricted to small or selected populations of either asthma or COPD patients

(generally excluding patients with overlapping features and some comorbidities), and/or with

limited data on burden of illness, healthcare resources use, comorbidities, and other important

factors vital for driving better insight into obstructive lung disorder phenotypes and endotypes.

In addition, the complexity of the measurements included in these studies tend to bias the

selection of sites and patients to exclude the vast majority of patients that generally are not

included in clinical trials or other research studies.

Additional observational studies involving relatively larger cohorts, such as Subpopulations

and Intermediate Outcomes in COPD Study (SPIROMICS)22

and COPDGene23

are underway

but lack comparability with asthma patients and other countries since they are restricted to

COPD and largely US based.

1.2 Rationale

To forcefully continue to drive improvements in the understanding and management of

obstructive lung disease there is an increasing demand for longitudinal observational data on

patients across the spectrum of obstructive lung disease.

These data are needed first and foremost to describe the clinical profile of patients and to

explore novel ways of classifying patients with obstructive lung disease according to their

trajectory over time for symptom burden, clinical progression and need for health care

utilisation. When combined with biomarker data, these classifications will drive future

insights to allow a better understanding of disease phenotypes and their respective underlying

pathogenic mechanism(s). This will provide an opportunity to evolve from a �one size fits all�

therapeutic approach to a targeted personalised approach.

The NOVEL observational longiTudinal studY (NOVELTY) study here proposed is thus

unique, and differentiates itself from other studies that have been conducted to explore

phenotypes and endotypes in chronic respiratory diseases, in six key aspects:

1) The study will recruit participants across the whole spectrum of chronic airways

disease, rather than only those with existing diagnostic labels of asthma or COPD


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2) The study aims to define new groups not only by collecting a broad range of

clinical and diagnostic parameters but also by taking into account the disease

pathways and patient management in real world practice. It aims to do so by

having a broad inclusion of patients, representative of the different spectrum of

disease severity and care practices, in different countries/regions, and collecting

variables related with treatment patterns, patient-reported outcomes (PROs) and

healthcare resources used. The study outcomes will thus be meaningful for

patients in a real world context

3) The use of advanced analysis methods will allow the identification of phenotypic

and endotypic groups according to their association with differential outcomes for

symptom burden, clinical evolution and healthcare utilisation over time; and not

by their similarity at baseline, as in many past cluster analyses. The aim is that, in

the future, through a simple collection of appropriate biological samples and/or

clinical data from a patient, disease progression and appropriate treatment

regimens could be predicted more easily

4) The subset of participants with newly-diagnosed respiratory disease will increase

the potential for identifying modifiable treatment targets.

5) Carefully designed electronic case report forms (eCRFs) will be used to collect

core data. In addition, data will be enriched by PRO collection, biologic sample

collection for patients who voluntarily consent to provide them and collection of

EMR data in some countries about characteristics, clinical progress and treatment

of patients with obstructive airways disease. The diversity of data collected

through these tools will enable the capture of rich clinical data on study patients

required for defining new phenotypes and endotypes.

6) It is expected that the data platform created by the study will continue to be a

useful resource even once the objectives of the core study are met. For example, it

could accommodate add-on studies and activities, with options to include patients

who are prescribed novel treatments, to extend follow-up of already recruited

patient groups (e.g. based on the routinely collected EMR data), to add additional

measurements or sampling in specific subgroups where NOVELTY could serve as

a recruitment platform, and to expand e-tool use to incorporate disease

management support.

In summary, NOVELTY will be the largest coordinated global prospective cohort study of its

kind in the broad patient population with obstructive lung disease (including asthma, COPD,

and their overlap). Building on current front-line science to enable deeper and broader disease

insights, NOVELTY will create a real-world evidence data platform useful not only for

AstraZeneca (AZ), but also for the broader community of patients, physicians, payers,

regulators, and the scientific community.24,25

Scientific rationale for lung function tests

Lung function tests are paramount in the diagnosis and management of obstructive respiratory

diseases and will be collected in the study.


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Spirometry is currently the gold standard for accurate and repeatable measurement of lung

function. Spirometry confirms chronic airflow limitation but is of limited value in

distinguishing between asthma with fixed airflow obstruction, COPD, and asthma-COPD

overlap (also called Asthma-COPD overlap syndrome).3 The following physiological

parameters will be collected: Forced Expiratory Volume in 1 second (FEV1), Forced Vital

Capacity (FVC), Peak Expiratory Flow (PEF), Forced Expiratory Flow at 25-75% of the FVC

[FEF25-75%,], Inspiratory Capacity [IC], and bronchodilator reversibility. From these

measurements, the following will be calculated: FEV1/FVC ratio and FEV1 % predicted.

FEV1 % predicted will be calculated according to Quanjer et al 2012.26

The fractional concentration of exhaled nitric oxide (FENO) will also be measured. FENO is

often measured in asthma patients as it is increased in eosinophilic asthma, but also in non-

asthma conditions (e.g. eosinophilic bronchitis, atopy and allergic rhinitis). In COPD, FENO

is usually normal and hence not measured as standard of care.3

Scientific rationale for Biomarker collection and analyses

Several observational studies including ENFUMOSA, U-BIOPRED,20

NHLBI-SARP,27

ECLIPSE,21

COPDGene,23

SPIROMICS,22

have aimed to better characterise asthma and

COPD phenotypes through biomarker profiling in separate disease cohorts. The goal of

NOVELTY is to further build on these foundations in a relatively larger cohort of patients

(~14,800patients) with asthma, COPD and those with clinical features of both asthma and

COPD. The patient�s consent to the use of donated biology samples is optional. A separate

laboratory manual will detail the sample processing, handling, shipment and storage

information.

Biomarker sampling is included in NOVELTY to better understand disease pathways and

heterogeneity of patients with asthma and COPD, and to translate these findings into ways to

accurately identify phenotypic groups, endotypes and potential biomarkers for drug response,

and to support further development of novel therapies.

If a patient consents, biospecimen samples (e.g. blood and urine, listed in Table 2) for

NOVELTY will be collected using standardised techniques. Elucidation of surrogate soluble

biomarkers, meaningful for both asthma and COPD, will be achieved by measuring systemic

analytes present in the blood and urine that would reflect cellular and molecular processes

occurring in the diseased airways. For example, elevated desmosine levels in urine have been

proposed as a surrogate biomarker of lung matrix destruction in COPD patients.28

Likewise, the proposed genomic research through collection and analysis of genetic blood

samples collected from patients will also be used to better understand underlying mechanisms

of disease and help identify subpopulations of asthma and COPD as these patients are

followed longitudinally.

This sub-section describes (but is not limited to) assays that may be performed for biomarker

analyses using patient samples collected during the NOVELTY study. Biomarkers will be


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collected from all consenting participants, not based on their initial diagnostic label of asthma

or COPD.

1. Blood - Haematology

Blood differentials can act as surrogate biomarkers to indicate what type of asthma a patient is

suffering from e.g. eosinophilic or neutrophilic asthma.29,30,31

Blood eosinophils can also be a

useful biomarker for predicting treatment response to anti-interleukin (IL)-5 biologic therapies

in both asthma and COPD patients (e.g. mepolizumab, benralizumab). For participants who

have blood drawn around the time of an exacerbation, these studies will also further inform in

which subgroup of patients specialized leukocytes play a pathological role during

exacerbations.

2. Blood - Plasma and Serum for biomarker and metabolomics and proteomics

analyses

Profiling of relevant biomarkers in blood samples will help to investigate mechanisms of

disease, for example, to evaluate associations between peripheral blood soluble biomarker

profiles and disease activity and/or severity markers (e.g. periostin for anti-IL-13 therapies,

collagen"elastin degradation profiles such as desmosine).

Newer technologies, such as metabolomics, can be used to profile expression of low

molecular weight circulating metabolites, including lipids, sugars, nucleotides, organic acids

and amino acids. Leading medical universities, such as the Karolinska Institute, routinely

perform metabolomics on clinical samples, including from asthmatic patients.20

Using this

technique, the profiling of circulating metabolites that serve as substrates and products in

metabolic pathways would be highly relevant for investigating disease mechanisms in asthma

and COPD.

3. Blood � deoxyrribonucleic acid (DNA) and ribonucleic acid (RNA) analysis

The aim of the proposed genomic research is to investigate whether patients with asthma and

COPD have an increased frequency of certain genotypes that predispose them to disease

pathogenesis, poor disease control and clinical progression. These genetic data will help to

assess the degree of correlation between specific genotypes, and relating sets of genotypes to

phenotypes. Similarly, candidate gene studies in the form of genetic association studies could

aid in finding asthma-susceptibility genes. The PAXgene technique is used routinely for the

isolation and purification of intracellular ribonucleic acid (RNA) from whole blood. Whole

transcriptional analysis in peripheral blood from phenotypic groups associated with symptom

burden, clinical progression and/or health care utilisation may uncover novel biological

pathways and also help identify new therapeutic targets and sub-sets of patients who are more

likely to respond to particular treatments.


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4. Urine

Collection and detailed analysis of metabolites in urine will help identify subpopulations of

asthma and COPD patients. As such, metabolomics can be used to establish expression

profiles of relevant biomarkers in urine samples and to investigate mechanisms of disease (e.g.

using the mentioned metabolomics technology).20

Mechanistically, further examples include,

evaluating urinary elastin degradation products (e.g. desmosine) for COPD and measuring

stable metabolites of the leukotriene pathway (e.g. leukotriene E4 [LTE4]), for example in

distinct subsets of individuals such as those suffering from aspirin-intolerant asthma.32

2. OBJECTIVES

The overall aims of this study are:

· To comprehensively describe patient characteristics, treatment patterns and the burden

of illness over time for individuals in clinical practice with a diagnosis, or suspected

diagnosis,** of asthma and/or COPD

· To identify novel phenotypes and endotypes by their association with differential

outcomes, in order to support future development of personalised treatment strategies

for obstructive lung disease, including those directed towards underlying mechanisms

2.1 Primary Objectives

The primary objectives are:

· To describe patient characteristics, treatment patterns and the burden of illness over time

for individuals in clinical practice with a diagnosis, or suspected diagnosis, of asthma

and/or COPD. Data will be described for the population overall and by pre- specified

subgroups, including by country, demographics, exposures, symptom history, treatment

history, concurrent clinical features, treatment setting, socioeconomic setting and access

to healthcare

· To identify phenotypes and endotypes, based on biomarkers and/or clinical parameters

that are associated with differential outcomes for symptom burden, clinical evolution

and healthcare resource utilisation, in individuals with a diagnosis, or suspected

diagnosis, of asthma and/or COPD.

2.2 Secondary Objectives

The secondary objectives are:

**

�Suspected diagnosis� means a patient with respiratory symptoms consistent with asthma or COPD, who has

not had diagnostic investigations, or has not received a formal diagnosis of asthma or COPD


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· In patients with a diagnosis or suspected diagnosis of asthma and/or COPD, to compare

their current diagnostic labels and physician-assessed disease severity with existing

international criteria and phenotypic groupings

· To describe patient characteristics, symptom burden, quality of life, exacerbation rates

and clinical progression over time, by phenotype and endotype, for: (a) patients with

recent-onset chronic respiratory disease, (b) patients considered by physician assessment

or by specified criteria to have mild disease at enrolment and (c) patients considered by

physician assessment or by specified criteria to have severe disease at enrolment

· To describe the association between specified biomarkers, at enrolment and over time,

and evaluate their stability over time, factors affecting their variability, and their

relationships with clinical features, among patients with airways disease.

2.3 Exploratory objectives

In patients with a diagnosis or suspected diagnosis of asthma and/or COPD:

· To describe healthcare resource use overall and related to respiratory diseases

· To describe PROs, e.g. symptom assessment, disease control, impact on daily activity

and quality of life


lower Respiratory Tract Infections (RTIs), including seasonal variations, and their

relationship with clinical outcomes

· To assess the adequacy of EMR in some countries for obtaining data about

characteristics, clinical progress and treatment of patients with obstructive airways

disease

Analyses and subgroups of interest will be further defined in more detail in a Statistical

Analysis Plan (SAP) prior to the start of data collection.

3. METHODOLOGY

3.1 Study Design � General Aspects

This study is a multi-country��

, multicentre, observational, prospective, longitudinal cohort

study which will include patients with a physician diagnosis, or suspected diagnosis, of

asthma and/or COPD.

��

Country participation to this protocol is flexible, but core countries planned for the study include countries

from North America (e.g. Canada, US), Europe (e.g. France, Germany, Italy, Spain, UK, Nordic countries �

Denmark, Norway and Sweden), Asia (e.g. China mainland, Japan, South Korea) and Oceania (e.g. Australia).


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The study will have a core component in which key variables will be collected to create a data

platform in which more specific studies addressing particular objectives will be embedded.

The details of the substudies will be designed, and reviewed by a Scientific Committee at a

later stage, and submitted to the applicable health authority(ies). Each substudy within the

NOVELTY study will have specific research questions, analyses and communication plans, as

well as consent forms approved by the institutional review board (IRB)/independent ethic

committee (IEC) and any applicable health authority(ies).

Patients will undergo clinical assessments and receive standard medical care as determined by

their treating physician. Patients will not receive any experimental disease management

intervention or experimental treatment as a consequence of their participation in the study.

All patients enrolled in the NOVELTY study will be followed up yearly by their treating

physician for a total duration of three years. In addition, patients are expected to be followed

up remotely once every quarter. Patients� existing EMR data (some countries) will be

collected and compared with prospectively collected data through the eCRF.

3.1.1 Data Source(s)

Data for the NOVELTY study population will come from several different sources: eCRF,

centralized spirometry, PRO, biological data and EMR (some countries), see Figure 1 below.

The core of the data collection will come from the eCRF, which will be implemented in all

countries and will therefore provide a consistently collected set of variables aligned to the

study objectives. These data will be enriched by PRO, functional measurements and

biospecimen sample collection (when voluntarily consented). EMR data for patients within

the NOVELTY study in some countries will also be collected through either: a) standing

EMR-based data collection systems or b) extracted from study sites at regular intervals. The

data captured in the eCRF and the data extracted from EMR will be linked at the patient level

via a common identifier, which will allow assessment of the adequacy of existent EMRs

captured during routine care, by comparing data from eCRF with the data in the EMRs.

Figure 1 Data infrastructure & sources

EMR data Data collected from

patients (PRO/Mobile)

Results of biospecimen

analyses

NOVELTY Study database

Data sources for all patients in study Data source in some

countries

Data collected from

physician (eCRF &

centralized spirometry)


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The scope of each data source is briefly described below:

Electronic Medical Records (EMRs)

EMR data comprises information recorded by health care professionals about specific

patients, e.g. during office visits. EMRs are intended to provide the physicians with a

documented record of the patients� health to be used to assist with prognosis and treatment.

EMRs are not typically designed for research purposes and physicians will enter data into the

EMR based on need or patient visit rather than as part of a study requirement. In most

countries, the EMR is separate from health claims information used for reimbursement.

Therefore, while EMRs provide a reasonably accurate capture of the physician treatment of

the patient, there might be a number of fields in the EMR that are not consistently completed.

electronic Case Report Form (eCRF)

The eCRF will be used to collect variables about patients through their physicians or study

personnel. The eCRF guides the investigator through the registration of patients, collection of

data and management of the study. Since it will be critical to be able to analyse data collected

across multiple countries, the eCRF will be used to ensure a consistent core data collection for

each physician involved in the NOVELTY study. The eCRF will be accessed through secure

web-based portals.

Functional measurements such as spirometry (FEV1, FVC, FEF25-75%, PEF, IC, bronchodilator

reversibility) will be centrally collected (where spirometry equipment is provided to sites) or

will be recorded in the eCRFs (where sites use their own spirometry equipment) � see section

6.1.3 for further details. From the spirometry measurements, the following will be calculated:

FEV1/FVC ratio and FEV1 % predicted. FEV1 % predicted will be calculated according to

Quanjer et al 2012.26

Diffusion Capacity in the lungs for Carbon Monoxide (DLCO),

computed tomography (CT) scan and 6-min walk distance (6MWD) will not be performed

specifically for this study. However, if they have been performed as part of the patient�s

routine care and the results are available in the patient�s medical records, the data will be

recorded in the eCRFs.

Patient-Reported Outcome (PRO) questionnaires and Mobile Health

PRO questionnaires will collect information about symptoms/ symptom control, HRQoL, and

work productivity. The patients will complete the questionnaires through the use of a web-

based application (or telephone interviews) during their annual visits and between visits.

Wherever possible, PROs for each participant will be collected by the same mode (web-based,

telephone) during clinical visits and home-based follow-ups.

In addition, subset(s) of patients, will be presented with the possibility of being voluntarily

included in substudies to assessing daily activities and disease relevant clinical parameters -

measured by Mobile Health devices such as activity monitors.


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Collection of biospecimen samples

The collection of optional biospecimen samples from the patients will contribute to the

identification of novel disease subgroups. Collection will be performed at baseline and then,

for some biomarkers, at follow-up. Some patients may have more frequent biomarker

collection, to better inform analyses where specific biomarkers have higher variability. Blood

and urine samples will be collected and stored in a central repository, as far as possible, to

serve as the study biobank. A central laboratory will be used for the haematology analysis.

Biospecimen sample collection and analysis will be covered in a separate section of the

informed consent (see section 6.2.1) as it is an optional component of the core study. The

informed consent will describe the scientific value of this component, and the procedures.

3.2 Study Population

It is estimated that approximately 7,700 patients with suspected or primary diagnosis of

asthma and 7,100 patients with suspected or primary diagnosis of COPD will be enrolled by a

diverse set of physicians (e.g. primary care physicians, allergists, pulmonologists) from

community and hospital outpatient settings within the countries targeted for NOVELTY, in

order to recruit a patient population that is as representative as possible of the overall

obstructive lung disease population and severity spectrum.

The current list of countries and number of patients to be recruited is presented in Appendix

8.1. Patients will be enrolled based on diagnosis and severity as assessed by their physician.

Given the known under-diagnosis of both asthma and COPD, patients who have not been

given a diagnosis of asthma or COPD, but who have respiratory symptoms consistent with

asthma or COPD, will also be included.

A screening log will be maintained at each site to record the disposition of non-eligible

patients and reasons for non-eligibility.

3.3 Inclusion Criteria

Patients meeting the following inclusion criteria will be included:

· Diagnosis, or suspected diagnosis��, of asthma and/or COPD, according to

clinician�s judgement

· Age !12 years (note: in most countries it will only be feasible to include patients

aged !18 years)

· Willing and able to sign written, informed consent (or having a responsible, legally

authorised representative acting on patient�s behalf)

· Enrolment from an active clinical practice

��

Suspected diagnosis means a patient with respiratory symptoms consistent with asthma or COPD, who has not

had diagnostic investigations, or has not received a formal diagnosis of asthma or COPD


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3.4 Exclusion Criteria

The following patients will be excluded from the study (to be documented in the screening

log):

· Patients who participated in any respiratory interventional trial during the 12

months prior to enrolment or at enrolment

· Patients who, in the opinion of the physician, are unlikely to complete 3 years of

follow-up, e.g. poor literacy, substance abuse, life-threatening co-morbidity

· Patients whose primary respiratory diagnosis (i.e. the condition causing most of

their respiratory symptoms) is not asthma or COPD (however, a co-diagnosis of

another respiratory disease such as bronchiectasis or interstitial lung disease

together with asthma or COPD will be accepted)

In addition, the following are considered criteria for exclusion from the exploratory genetic

research (donation of blood for DNA and RNA analysis)

· Previous allogeneic bone marrow transplant

· Non-leukocyte depleted whole blood transfusion within 120 days of the date of the

genetic sample collection

3.5 Patient Follow-up

Eligible patients will be enrolled in the study at the time they routinely visit their physician

and consent to participate in the study. For participants enrolled during an exacerbation of

airways disease, baseline data will be collected six weeks later. Patients will then be followed

for a period of three years or until study discontinuation, whichever occurs first, according to

the plan described in section 6.1.2.

In addition, as stated in section 1, the sponsor intends to make the data platform created in this

study accessible for future use under the study governance structure described in section 6.4.

Therefore, after this study is completed and upon a specific informed consent procedure,

follow-up may continue via the EMR platform.

3.5.1 Discontinuation of patients

As participation is voluntary, patients are free to discontinue their participation at any time

and without prejudice to their subsequent medical treatment. Patients who withdraw

prematurely will not be replaced.

3.5.2 Procedures for discontinuation

Patients who decide to withdrawn from the study should be asked about the reason(s), and a

follow-up call will be made at the time of withdrawal for final data collection, if possible.

The reason for withdrawal should be documented in the database (e.g. safety reason/change of

address/death/voluntary withdrawal). All information already collected as part of the study


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will be retained for analysis; however, no further efforts will be made to obtain or record

additional information regarding the patient other than the reason for withdrawal.

However, if a patient discontinues the study for any reason but wants to continue to be follow-

up by EMR data collection that would be possible, and will be covered by a separate ICF to be

signed at that timepoint.

3.5.3 Discontinuation of study

Should AZ decide to discontinue the study prior to the date established in this protocol, the

investigator, and relevant authorities should receive written notice describing the reasons why

the study was terminated at an earlier date. The investigator will immediately notify the

patients taking part in the study; they will continue to receive their treatment according to

usual clinical practice.

4. VARIABLES AND EPIDEMIOLOGICAL MEASUREMENTS

The variables will be collected during routine clinical visits. The NOVELTY study is a

longitudinal cohort study, constituting a disease registry; it does not involve or study a specific

medicinal product and therefore will fall under the scope of the regulations and guidelines

applicable to observational studies. The majority of variables to be collected are part of

routine general health assessment or specific guidelines for the management of COPD and

asthma patients, and are/should be routinely collected, according to international respiratory

care guidelines and/or recommended medical practice guidelines. All variables can be

collected through non-invasive procedures, except for blood sample collection.

It is acknowledged that some of the variables of interest in this study might not be part of the

site/physician standard practice. However, given that one of the main goals of the study is the

identification of meaningful new patient profiles based on variables such as lung function

measurements, PROs and biomarkers, the physicians will be reminded of the importance of

following the protocol consistently if consented by their patients, as this will ensure the

validity of the results therefore making their participation beneficial (section 6.2 provides

more details on the information to be communicated to the patient).

The following list covers the types of variables for which collection is envisioned.

Information obtained only once per participating investigator:

· Study site type (e.g. Primary Care centre, Hospital, Specialists centre, site size)

· Physician current area of practice (e.g. Primary Care, Pulmonologist, Allergist,

Internist or other)

· Physician characteristics, including:

o Age

o Gender

o Years in practice


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o Years in current position.

Patients� variables (collected at baseline / follow-up data collection points described in

section 6.1.2):

· Demographic variables (as allowed by local regulations):

o Age

o Ethnicity

o Gender

o Socioeconomic status/income

o Insurance status/ payee

o History of participation in respiratory interventional trial(s) longer than 12

months before enrolment

o Occupation type and period (to capture occupational risk factors to

asthma/COPD)

· Physiological variables:

o Height and weight (for BMI calculation)

o Waist circumference

o Heart rate

o If female, pregnancy status

· Asthma/COPD information:

o Diagnosis (asthma/COPD/both) and disease severity:

§ The attribution of the diagnosis of asthma and/or COPD and the

severity/control level will be done according to physician�s clinical

judgment at baseline along with the rationale for their assessment

(e.g. local/international guidelines/other)

o Age at first diagnosis of disease

o Personal and family history of asthma/COPD

o Personal and family history of allergies (and test results if available)

o Comorbidities

o Occurrences and timing of asthma/COPD complications, exacerbations in

the previous 12 months

o Occurrences and timing of other respiratory infections and respiratory

diseases (e.g. RTI, pneumonia, allergic rhinitis) in the previous 12 months

o Symptom and physiological assessment

§ Lung function measurements including spirometry (FEV1, FVC,

PEF, FEF25-75%, IC), and bronchodilator reversibility test. From the

spirometry measurements, the following will be calculated:

FEV1/FVC ratio and FEV1 % predicted.

§ FENO

§ PROs: Chronic Airways Assessment Test (CAAT), modified

Medical Research Council score for dyspnoea (mMRC),

Respiratory Symptoms Questionnaire (RSQ), Asthma Control Test

(ACT, only for patients with a diagnosis of asthma), and COPD


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Foundation Primary Care Tool for Undiagnosed Respiratory

Disease and Exacerbation Risk (CAPTURE).

· Risk factor assessment (e.g. smoking status and its history [including Mother�s

smoking history during pregnancy and childhood / passive smoke exposure],

occupational exposure to pollutants, allergies)

· Productivity loss PROs (Work Productivity and Activity Impairment [WPAI])

· HRQoL PROs: St. George�s Respiratory Questionnaire (SGRQ) and EuroQol 5

Dimensions 5 Levels health questionnaire (EQ-5D-5L)

· Asthma/COPD treatment

o Duration and posology (in the previous 12 months)

o Patterns of use and treatment adherence

o Burden of out of pocket medication expenses

o Reasons for treatment switches/interruptions/discontinuations

o Asthma/COPD Treatment satisfaction

· Concomitant medications related to diseases under consideration

· Healthcare resource use (medications, emergency and non-emergency physician

visits, invasive and non-invasive ventilator use, hospitalizations, procedures, out of

pocket expenses)

· Biomarkers (optional): from blood samples including assessment of haematology

and collection for storage of serum, plasma, DNA, RNA, and urine samples

· Substudy: Mobile Health measures (non-invasive, disease-relevant measurements

such as activity, body posture, heart rate, respiratory rate, skin temperature,

medication use and environmental conditions).

Variables to collect only if available in patient�s medical records

The variables listed below will not be performed specifically for this study. However, if they

have been performed as part of the patient�s routine care and the results are available in the

patient�s medical records, the data will be collected in the eCRF:

· FENO at follow-up visits

· DLCO

· CT imaging of the chest

· Exercise tolerance as measured by the 6MWD

· Blood clinical chemistry (e.g. Immunoglobulin E, phadiatop, fibrinogen, C-

reactive protein)

4.1 Exposure to treatments

The NOVELTY study is a longitudinal cohort study, constituting a disease registry, which

does not involve or study a specific medicinal product. Information about exposure to

treatments as part of routine care will be collected (frequency, treatment and duration).


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4.2 Outcomes

4.2.1 Primary endpoints

The primary endpoints are the following, reported for the study population as a whole,

by country, by disease (i.e. asthma, COPD and asthma-COPD overlap when

considered appropriate) and by specified sub-groups:

· Baseline distribution of enrolled patients diagnosed with asthma and/or COPD as

per the physician�s clinical judgement, by disease severity and/or control, by site

type, by physician characteristics, etc.

· Baseline summary statistics (e.g. demographics, physiological, disease

information, productivity/HRQoL, treatments, risk factors, healthcare resources

use, biomarkers, etc.) of patients by disease severity and/or control, by site type, by


· Longitudinal (at each follow-up assessment) summary statistics, as suggested

above, of patients by current disease severity and/or control, by site type, by


· Identification of phenotypic and endotypic groups, based on clinical parameters

and biomarkers, that are associated with differential outcomes over time for

symptom burden, clinical evolution (including decline in lung function) and

healthcare utilisation. The characteristics of these groups at baseline and at each

follow-up assessment will be described.

· Predictors of phenotypic and endotypic groups, including history of childhood

respiratory symptoms, exposure to tobacco smoke, treatment, etc.

· Correlation between biomarkers and phenotypes and endotypes at baseline and at


4.2.2 Secondary and exploratory endpoints

The secondary and exploratory endpoints will include the following, reported for the

study population as a whole, by country, by disease (i.e. asthma, COPD and asthma-

COPD overlap when considered appropriate) and by specified sub-groups:

· Concordance by severity and/or control between diagnosis according to guidelines

(using the data available at baseline) and according to the initial clinician

diagnosis at recruitment

· Frequency of treatment modification (dosage change, switch, discontinuation) and

reason for modifications between each follow-up assessment

· Correlation between biomarkers, disease severity and/or control and different

measures of response to treatment.

· Factors associated with treatment at baseline and patient-reported treatment

satisfaction and preference at baseline and at each follow-up assessment

· Level of symptom control at baseline and at each follow-up assessment


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· Frequency of exacerbations according to seasonal variations and conditions,

including RTI, in the year prior to enrolment and during the study

· Summary scores of PROs overall and by specific subgroups (e.g. treatment

patterns, pheno/endpotype, etc.) if considered appropriate, at baseline and at each

follow-up assessment

· Direct and indirect healthcare resource use by resources categories overall and

those related with respiratory disease at baseline and at each follow-up assessment

· Presence of known risk factors for development of airways disease

· Levels of biomarker parameters, lung function, and risk factors at each follow-up

assessment, and variability in these measures.

· Relationship between disease control, Health-Related Quality of Life (HRQoL),

exacerbations, and healthcare resource use stratified by severity of disease

· Reasons for non-adherence to treatment

5. STATISTICAL ANALYSIS PLAN

5.1 Statistical Methods � General Aspects

Unless otherwise specified, computations and generation of tables, listings, and figures will be

performed using SAS® version 9.2 or higher (SAS Institute, Cary, NC, USA).

The statistical analyses will be fully described in SAPs as appropriate. Furthermore, for

additional proposed substudies and analyses for exploiting the NOVELTY database, a Rapid

Evaluation Process (REP) for the statistical analysis will be utilized to address additional

inquiries and analyses that may be identified as important during the course of the study. The

REP process is described in section 5.1.4. A Scientific Committee will prioritise and

approve/reject new analysis proposals during and beyond the core three-year period.

Data will be summarized for the population overall and by pre specified subgroups, including

by country, demographics, exposures, symptom history, treatment history, concurrent clinical

features, treatment setting, socioeconomic setting and access to healthcare, where relevant.

Additionally, other geographical categorisations could be considered (e.g. Europe, Asia, etc.).

If considered appropriate, selected analyses could be weighted by estimated severity of

disease per country or other selection sampling weights.

For patients participating in NOVELTY study that subsequently enrol in an interventional trial

and therefore discontinue from NOVELTY, or otherwise leave the study or are lost to follow-

up, data will be censored from that time point and discontinued from NOVELTY.

5.1.1 Yearly descriptive analyses

After baseline data collection and each annual data collection, descriptive analyses will be

performed to gain an understanding of the qualitative and quantitative nature of the data

collected and the characteristics of the sample studied. These analyses will be performed for


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all variables listed in section 4 addressing the outcomes listed in section 4.2. The results will

be presented for aggregate data only.

Patients� changes regarding their treatment, disease severity and other variables observed

between follow-up visits, will also be described. This analysis will be further described in the

SAP.

5.1.2 End of study descriptive analyses

Descriptive analyses will be performed at the end of the study for all variables listed in section

4 addressing the outcomes listed in section 4.2. Data will be summarized for the population

overall and by pre specified subgroups, including by country, demographics, exposures,

symptom history, treatment history, concurrent clinical features, treatment setting,

socioeconomic setting and access to healthcare where possible.

Patients� changes regarding their treatment, disease or severity among and other variables that

are observed between baseline and follow-up visits, will also be described.

To identify potential differences in disease diagnosis and severity classifications between

physicians and guidelines, data collected on lung function results, symptom questionnaires,

exacerbation occurrences and medication will allow the formal and consistent classification of

the patients according to relevant international guidelines and other current and future

phenotypic/diagnostic classifications. For each patient a physician-assigned diagnosis at entry

and one or more derived standardised diagnoses will be assigned. The proportion of

differences in classification by severity and level of control according to guidelines or other

standardized classifications versus clinician judgement data will be examined.

Where EMR data are available, cross tabulations will be used to assess the adequacy of EMR

for obtaining data about disease characteristics, clinical progress and treatment of patients

with obstructive airways disease.

These analyses will be further described in the SAP.

5.1.3 Multivariable Data Analysis

Multivariable models will be used to assess the following:


lower Respiratory Tract Infections (RTIs) and their relationship with clinical outcomes

· To assess the relationship between Patient-Reported Outcomes (PROs), e.g. symptom

assessment, and disease control with impact on daily activity and quality of life

· To assess the relationship between healthcare resource use overall and related to

respiratory diseases with disease severity, clinical outcomes, disease type, etc.


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Multivariable analyses techniques will be used to identify phenotypes and endotypes, based on

biomarkers and/or clinical parameters that are associated with differential outcomes for

symptom burden, clinical evolution and healthcare utilisation.

Model development may use techniques such as cluster analysis,33,34

random forests, principal

components analysis, and/or system biology analysis. The selected methods will be further

justified and described in the SAP(s).

The novel patient subgroups derived from the multivariable data analysis methodology will be

described and compared. The longitudinal collection of data throughout the study will allow

not only the description of subgroups at baseline, but also with a time dimension. The use of

time dependent covariates will be considered to accommodate such factors that change during

the course of the study, for example treatment regimens.

Model development may be done on randomly selected subsets of the data so that validation

of the models could be done on the remainder.

5.1.4 Exploratory Analyses

Additional exploratory analyses may be performed. The REP process described below will be

followed, and the Scientific Committee will assess and approve such exploratory analyses.

Rapid Evaluation Process (REP)

Recognizing that during the course of this study, new research questions are likely to arise as

the science and environment changes, the REP can be used to evaluate such new exploratory

ideas. For example, scientific advances may become available that require additional

questions to be posed (e.g. potential subgroups that may selectively benefit from treatment,

stakeholders develop new questions, such as dosing, treatment combinations, treatment

sequences, treatment alternatives, etc.).

The key elements of the REP require three steps are followed: 1) Research questions are

defined at the outset; 2) The analytic plan is agreed on in advance, usually consisting of a

small number of tables and/or figures; and 3) Costs are minimized by deferring parallel

programming and extensive analyses until needed. Prior to execution, the analysis plan

prepared by an analyst from the scientific team undergoes senior review by appropriate

members of the Scientific Committee. This process is used as a Quality Control (QC) check to

examine content and format, that the correct data set is used, inclusion and exclusion criteria

for the analytic data set, and how missing data are addressed. Additional inferential review

may be added. Prior to delivery, results undergo senior scientific review for clarity and

plausibility. An appropriate deliverable timeline is created and agreed on. If expedited

delivery is requested, QC and senior review may occur in parallel.

As appropriate, analyses will be extended to support conference presentations and/or

manuscripts, in dialogue with the Scientific Committee, and will include more extensive QC

checks if needed.


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EMR analyses

An EMR based analysis will be conducted in parallel for the enrolled patients in some

countries where EMR extraction is planned to be executed at the time of enrolment (all

retrospective EMR data), during the study and post study (up to 5 years). Together with other

data captured in the study it will generate the evidence hub with long back data trail and

sustainable prospective data platform. The EMR analyses will be descriptive in nature and add

data on patients in treatment patterns, observed comorbidities and health resource utilization

over time.

Secondly the algorithm (see 8.4) used to identify COPD and asthma diagnosis in the different

EMR datasets will be contrasted and compared with diagnoses obtained from the

prospectively collected eCRF data.

Lastly, the variable comparisons of EMR vs. eCRF will further allow the assessment of the

validity of EMR data sources and guide their optimisation so that future studies could rely on

these data sources as the primary data collection.

5.2 Handling of Missing Data

Full details on handling of missing data, will be described separately in the SAP(s). The

proportion of missing data will be reported for each measured variable in the study. Where

appropriate, full or available data analysis will be performed, or missing will be presented as a

separate category.

The SAP(s) will describe where more refined missing data methods may be applied, the

techniques for identifying the type of missing data and the appropriate imputation methods to

be used, if any. Proposed sensitivity analyses to assess the effect of different imputation

methods on the study results will also be described in the SAP(s), if applicable.

5.3 Bias

5.3.1 Strengths and Limitations

A major strength of the study is its magnitude and scope: NOVELTY is expected to enrol

approximately 14,800 patients with either diagnosis (or suspected diagnosis) of asthma,

COPD or both by a representative set of physicians from community and hospital outpatient

settings, from more than 10 countries and with a minimum of inclusion and exclusion criteria.

It is an observational study that will aim to include a diverse sample of patients and treatment

patterns.

The primary data collection tool will be an eCRF. The main advantage of using a primary data

source is to maintain the consistency of a single approach for prospective data thus ensuring

comparability of data across geographies.


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In addition, the collection of data directly from the patients through the PRO questionnaires

provides a unique perspective and enables the collection of HRQoL outcomes, symptom

assessments, and other health information that may not be recorded by their physicians.

However, in some countries in which EMR data are available and assessed via a feasibility

study (see section 8.4), these EMR data sources will be assessed by comparisons with the

primary collected data to allow for analyses to assess if the use of these data sources is

appropriate in future studies. The advantages of using EMR data in general terms are 1)

efficient access to a large number of patients with some important data already collected, and

2) improvement upon the recruitment strategy by allowing the identification and targeting of

sites that will favour the enrolment of a representative sample of asthma and COPD patients.

Despite the above mentioned strengths of the study approach, this study is subject to

limitations as all studies are.

Selection bias: recruitment through clinical practice could bias the study population towards

those with more frequent health care utilisation. In addition, regarding the collection of

biospecimens, given the fact that ideally blood samples are to be collected from all patients

included in the study, there could be a potential for selection of patients with more severe

disease, for example, if they are more willing to provide samples. In addition, due to

differences in health systems among the participating countries, the availability of biologic

samples could also vary depending on the country. Although it is highly desirable to have

biospecimens collected for all patients, the procedure will not be mandatory (see section 6.2).

Information bias: as in clinical practice there is potential for misclassification in most data

elements (e.g. diagnosis, severity, level of control assessment, exacerbations, etc.). There is

also the possibility that physician assessments of disease may be biased by the knowledge that

their diagnoses will be compared against guidelines. The results of the interim analyses have

the potential to alter clinical practice from that time forward; however, this is unavoidable in

any study of this nature.

5.3.2 Bias and Methods to Minimize Bias

In order to minimise the above mentioned limitations the following strategies will be

implemented:

Selection bias: The use of EMR data, in some countries, will minimise the risk of a severe

selection bias as there will be an a priori knowledge of patient eligibility, which enables

comparison with the characteristics of all the patients with similar diagnoses not being

enrolled on an ongoing basis.

In the countries where the use of EMR is not possible, the risk of selection bias would be

higher. Here too, the representativeness of the selected sites and patients will be periodically

reviewed by assessing the distribution of the enrolled sample across meaningful characteristics

(disease severity and/or control, gender, age distribution, type of physicians/sites, etc.) so that

it reflects the characteristics of the real-world population of patients with asthma and/or


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COPD. This will be performed by comparison with valid data sources such as recent literature

reviews and also by consulting with regional experts.

An enrolment log will be maintained across sites to assess the characteristics of patients

included and excluded among the eligible patients. In addition to the enrolment log, a record

of the patients lost to follow-up will also be maintained. In addition, it will be possible to

assess the characteristics of the patients that provided the samples versus those who did not

provide them, thus enabling the assessment of patients� representativeness.

Information bias: Clinician assessments will be able to be compared with the novel diagnostic

and assessment criteria developed during the course of the study.

5.4 Interim Analyses

As described in section 5.1.1 interim analyses will be performed yearly on accruing data (after

DBL of baseline data, first-year data and second-year data). Similarly, data collected on a

more frequent basis will be analysed after accrual. No hypotheses testing will be done at these

interim analyses, therefore no provisions for protecting the overall alpha for any potential

analyses at the end of the study are required. At regular intervals during recruitment, the

sample will be assessed to evaluate if it is containing a distribution cross age, gender and

disease severity, so that adjustments can be made if needed for optimized study population

recruitment. Exact structure of analyses will be determined by each respective SAP, as

assessed by the Scientific Committee.

5.5 Sample Size and Power Calculations

The minimum target number of 100 patients per diagnostic label (asthma or COPD), physician

assessed severity level and country has been chosen to support many basic local

reimbursement specific requirements with reasonable precision, and to provide large sample

size for scientific questions applicable across severities and countries. This study uses a

hypothesis-free approach focused on multiple exploratory and descriptive analyses to

understand the heterogeneity of obstructive lung disease, and thus power calculation for any

specific outcome is not strictly relevant; the large sample size overall and in subgroups was

chosen to support a large range of analyses from overall general scientific questions to

specific regional or subgroup questions with sufficient precision. The sample size will ensure

that the descriptive data mandated by the primary objectives in relation to disease, patient and

treatment characteristics are sufficiently precise and meaningful at a country or subgroup

level.

With a sample size of at least 100 (smallest subgroup) or 600 patients (largest subgroup), the

estimated exact binomial 95%CI for any given proportion of a patient characteristic is shown

in Several subgroup sizes have been considered to allow us to cover all the different

possibilities:

· Considering country, disease and severity: 200 patients (100 patients in the worst case

scenario)


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· Considering country and disease: 600 patients (300 patients in the worst case scenario)

.

Several subgroup sizes have been considered to allow us to cover all the different possibilities:

· Considering country, disease and severity: 200 patients (100 patients in the worst case

scenario)

· Considering country and disease: 600 patients (300 patients in the worst case scenario)

Table 1 � Exact binomial 95%CI for estimated proportions

Expected

proportion

100 patients

(smaller subgroup) 200 patients 300 patients

600 patients

(largest subgroup)

95%CI 95%CI 95%CI 95%CI

Lower

limit

Upper

limit

Lower

limit

Upper

limit

Lower

limit

Upper

limit

Lower

limit

Upper

limit

5% 1.64% 11.28% 2.42% 9.00% 2.83% 8.11% 3.40% 7.06%

10% 4.90% 17.62% 6.22% 15.02% 6.85% 13.97% 7.72% 12.68%

30% 21.24% 39.98% 23.74% 36.87% 24.87% 35.53% 26.36% 33.84%

50% 39.83% 60.17% 42.87% 57.13% 44.20% 55.80% 45.92% 54.08%

70% 60.02% 78.76% 63.13% 76.26% 64.47% 75.13% 66.16% 73.64%

90% 82.38% 95.10% 84.98% 93.78% 86.03% 93.15% 87.32% 92.28%

95% 88.72% 98.36% 91.00% 97.58% 91.89% 97.17% 92.94% 96.60%

This means that regarding any binary variable or classification at a frequency of 5% to 95%,

and for subgroups with a sample size of 600 patients, in the worst case (i.e. expected

proportion of 50%) the precision would be approximately ± 4%. With a sample size of 100

patients, the precision would be approximately ± 10% which is also scientifically acceptable

in many cases (Figure 2).

Figure 2. 95%CI (exact binomial distribution) for smaller and largest subgroups


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For data pooled across all countries and severities, the precision would be good even for rarer

characteristics (frequency <5% and >95%).

6. STUDY CONDUCT AND REGULATORY DETAILS

6.1 Data Management

A data management plan (DMP) will be created before data collection begins and will

describe all functions, processes, and specifications for data collection, cleaning and

validation. The eCRFs will include programmable edits to obtain immediate feedback if data

are missing, out of range, illogical or potentially erroneous. Concurrent manual data review

will be performed based on parameters dictated by the plan. Ad hoc queries will be generated

within the Electronic Data Capture (EDC) system and followed up for resolution.

High data quality standards will be maintained, and processes and procedures utilised to

repeatedly ensure that the data are as clean and accurate as possible when presented for

analysis. Data quality will be enhanced through a series of programmed data quality checks

that automatically detect out-of-range or anomalous data. All the modifications to the data will

be recorded in an audit trail.

6.1.1 Data Entry/Electronic Data Capture (EDC)

All prospective data will be entered directly into an EDC system. All data (e.g. primary and

PRO data) and existing data will be will be linked with a unique patient Identification Number

(ID) but stored in a pseudo-anonymised way.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

95%CI (exact binomial distribution)

100 patients

(smaller subgroup)

600 patients

(largest subgroup)

Expected proportion


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All participating sites will have access to the data entered for patients enrolled at their site. All

sites will be fully trained on using the EDC, including eCRF completion guidelines and help

files. Sites will be responsible for entering extracted patient data into a secure internet-based

EDC database via eCRFs. Data entered in the eCRF will be immediately saved to a central

database and changes tracked to provide an audit trail. Physicians and site personnel will be

able to access their account with a username and password. All eCRFs should be completed

by designated, trained personnel or the study coordinator, as appropriate. When data have

been entered, reviewed and edited, the eCRFs should be reviewed, electronically signed, and

dated by the physician. Data will then be locked to prevent further editing. A copy of the

eCRF will be archived at the site.

6.1.2 Study Flow Chart and Plan

The Study Flow diagram is presented below (Figure 3) and represents the most relevant study

milestones (protocol submission, recruitment period, baseline assessment and the three annual

visits).

Figure 3 � Study Flow Chart

1up to five years after the study completes.

Note: Annual data collection can be performed with ±3 months interval and 3-monthly follow-up with

±3 weeks interval. EMR: Electronic Medical Record; ICF: Informed Consent Form; Q: Quarter.

The data elements to be collected at each data collection point (baseline, and then approximately with a

3-monthly and 12-monthly periodicity) are provided in the Study Plan (Table 2) below.


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Table 2 � Study Plan

Variables

Baseline

collection

(Visit 1)

3-monthly

(±1 month)

collection

(intermediate

contact with

patient)

12-monthly

(±3 months)

collection

(Visit 2, 3, 4)

Informed Consent X

Demography (as

allowed by local

regulations)

Age, Ethnicity, Gender, Socioeconomic

status/Income, insurance status/payee,

history of participation in respiratory

interventional trial(s)

X

Occupation X X

Physiological data Height, Weight, calculated BMI, Waist

circumference, Heart rate, Pregnancy

status

X X

Asthma/COPD

information

Patient diagnosis, disease severity, age at

diagnosis, personal and family history of

asthma/COPD and allergies

X

Comorbidities X X

Asthma/COPD complications,

exacerbations, respiratory diseases (e.g.

RTI)

X X X

Symptom assessments / disease control

status (PRO)

X X X

CAPTURE screening tool X

Lung function measurements (FEV1, FVC,

PEF, FEF25-75%, IC, calculated FEV1/FVC

ratio and calculated FEV1 % predicted)

X X

Bronchodilator reversibility test X

FENO X

Risk factor

assessments

Smoking status and history, occupational

exposure to pollutants, allergens

X X

Impact on daily

activity and

quality of life

HRQoL X X X

Work productivity and activity

impairment (PRO)

X X

Treatment(s)

during previous

12 months

Asthma/COPD treatments (treatment

duration and posology)

X X

Patterns of use and treatment adherence

for asthma/COPD treatments

X X

Burden of out of pocket asthma/COPD

treatment expenses1

X X

Reasons for switching/interruptions/

discontinuations of asthma/COPD

treatments

X X

Asthma/COPD Treatment satisfaction X X

Concomitant medications X X


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Variables

Baseline

collection

(Visit 1)

3-monthly

(±1 month)

collection

(intermediate

contact with

patient)

12-monthly

(±3 months)

collection

(Visit 2, 3, 4)

Healthcare

resource use

during previous

12 months

Medications; emergency and non-

emergency physician visits; invasive and

non-invasive ventilator use, hospitalizations and procedures, out of

pocket expenses

X X

Emergency room visits, hospitalisations

and procedures due to exacerbations

X X X

Biomarkers

(optional)

Blood sample [Haematology]

Blood sample [Serum]

Blood sample [Plasma]

Blood sample [DNA]

Blood sample [RNA]

X

X

X

X

X

X

X (year 1 only)

X (year 1 only)

Urine sample X

Mobile Health

(optional, in sub-

study)

Non-invasive, disease-relevant

measurements such as activity, body

posture, heart rate, respiratory rate, skin

temperature, medication use and

environmental conditions.

X X X

Note: For participants enrolled during an exacerbation of airways disease, baseline data will be collected 6 weeks later.

Abbreviations: BMI: Body Mass Index: CAPTURE: COPD Foundation Primary Care Tool for Undiagnosed Respiratory

Disease and Exacerbation Risk; COPD: Chronic Obstructive Pulmonary Disease; DNA: Deoxyribonucleic acid; FEF25-75%:

Forced Expiratory Flow at 25-75%; FENO: Fractional Exhaled Nitric Oxide; FEV1: Forced Expiratory Volume at 1 second:

FVC: Forced Vital capacity; IC: Inspiratory capacity; PEF: Peak Expiratory Flow; PRO: Patient Reported Outcome; RNA:

Ribonucleic acid; RTI: Respiratory Tract Infection. 1 Burden of out of pocket treatment expenses will also be collected 12 months prior to baseline.

6.1.3 Procedures

As already described in previous sections, patients will be enrolled by their physicians who

will collect prospective data at baseline and annually during a 3-year period. Moreover, in

countries where EMR data are available, relevant data for the variables mentioned in the

previous section will be extracted from the EMR to be further validated against the eCRF

data.

Operational procedures will be put in place in each country aiming to collect all the variables

listed above to the extent that is feasible from a regulatory and logistical perspective and with

maintaining the voluntary decision to perform the measurements with the physician and the

patient.

Spirometry (FEV1, FVC, PEF, FEF25-75%, IC) will be performed locally by site personnel

according to the ATS/ERS criteria (Miller et al, 2005).35

From the spirometry measurements, the following will be calculated: FEV1/FVC ratio and

FEV1 % predicted. FEV1 % predicted will be calculated according to Quanjer et al 2012.26


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Reversibility of airway obstruction will be assessed at baseline only, by measuring pre- and

post-bronchodilator values of FEV1 and FVC as part of the evaluation of lung function.

Patients should withhold their short acting bronchodilation medication(s) for at least six hours

prior to visits when performing reversibility testing and long acting bronchodilators (with or

without ICS) should be withheld for 12-24 hours depending on whether the patient is using

twice or once-daily therapy. The post-bronchodilator spirometry should be performed a

minimum of 15 minutes after taking the bronchodilator. The percent reversibility will be

calculated as follows:36

At the annual follow up visits, only post-bronchodilator spirometry will be performed.

Sites that do not have suitable spirometry equipment will be provided with a spirometer for

the duration of the study. For sites that will use their own spirometry equipment, the

equipment must comply with the ATS/ERS criteria.

The spirometers provided to sites will centrally collect the spirometry data and therefore this

data will not be entered into the eCRF. For sites that use their own spirometry equipment, the

spirometry data will need to be entered into the eCRF.

All sites will receive basic spirometry training. At sites provided with a spirometer, site staff

performing spirometry will also receive training on the spirometry device and will undergo a

proficiency test (spirometry data will be centrally checked for quality).

At all sites, a proportion of baseline spirometry data will be centrally reviewed to check

quality.

FENO will be measured locally by site personnel according to recommendation of the

equipment manufacturer and ATS/ERS guidelines. Sites that do not have suitable FENO

equipment will be provided with a FENO device for the duration of the study. For sites that

will use their own FENO device, the device must comply with the ATS/ERS guidelines and

be CE marked or 510(k) approved. All FENO data will be entered into the eCRF. All sites will

receive basic FENO training. At sites provided with a FENO device, site staff performing

FENO will also receive training on the FENO device.

6.1.3.1 Specific procedures for Patient-reported Outcomes questionnaires

Some variables will be collected directly from patients through PRO questionnaires. The

patients will complete the questionnaires through the use of a web-based application (or

telephone interviews) during their annual visits and between visits, with the same method used

at each visit wherever possible. Analyses of PRO data will take consideration that a small

proportion of data will have been collected using the phone rather than the web. Details of


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sensitivity and other analyses appropriate to the composition of final data sets will be provided

in the SAP(s). The patient should be informed about the purpose and importance of

completing the questionnaires and be given adequate time to complete all items. The questions

should be completed in a quiet place without influence from family, friends, or study

personnel, in a pre-defined order.

The PROs will be used to capture the constructs of symptoms/symptom control, HRQoL, and

work productivity. Symptoms/symptom control will be assessed using the CAAT, the RSQ,

and the mMRC. The COPD Assessment Test (CAT) is a brief symptoms and health status

questionnaire that has been developed and validated for COPD, and in order to also assess

patients without a COPD diagnosis a slightly modified version that excludes all references to

COPD in the instructions will be used (here referred to as the CAAT). A small subset of

COPD patients will, in addition to completing the CAAT, also complete the original CAT at

baseline and at the year 1 clinical visit in order to evaluate equivalence of the CAT and the

CAAT. The RSQ is a measure of symptom control that captures and categorizes symptom

control in line with Global Initiative for Asthma (GINA) strategy report (i.e. well-controlled,

partly controlled, or uncontrolled). The mMRC is a single item measure of patient�s level of

dyspnoea. In addition, the Asthma Control Test (ACT) will also be used to assess asthma

control, but only in patients with an asthma diagnosis. Except for ACT, all PROs will be

administered to all patients regardless of diagnosis

HRQoL will be assessed with SGRQ and EQ-5D-5L. The SGRQ is a disease specific HRQoL

measure developed and validated for both asthma and COPD patients. The EQ-5D-5L is a

generic health status and health utility questionnaire, developed and used across all diseases.

Employment status and work productivity will be captured using the WPAI questionnaire, a

generic measure of health-related work, productivity loss and activity impairment.

In addition, a new patient-reported screening tool, developed to identify undiagnosed patients

with clinically significant COPD, labelled CAPTURE, will be included at baseline.

Table 3 below summarises the instruments planned to be administered in NOVELTY:


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Table 3 � Patient Reported Outcomes (PRO) tools and frequency of administration

Baseline 3-monthly Yearly

Symptoms/ symptom

control

CAAT CAAT CAAT

RSQ RSQ RSQ

ACT* ACT*

mMRC

HRQoL

SGRQ

SGRQ

EQ-5D-5L EQ-5D-5L EQ-5D-5L

Work productivity WPAI WPAI

Screening tool CAPTURE

*ACT will only be administered to patients with an asthma diagnosis

Abbreviations: ACT: Asthma Control Test; CAPTURE: COPD Foundation Primary Care Tool for Undiagnosed Respiratory Disease and

Exacerbation Risk; CAAT: Chronic Airways Assessment Test; EQ-5D-5L: EuroQol 5 Dimensions 5 Levels health questionnaire; mMRC: medical Research Council dyspnoea score; RSQ: Respiratory Symptoms Questionnaire; SGRQ: St George�s Respiratory Questionnaire;

WPAI: Work Productivity and Activity Impairment.

6.1.3.2 Specific procedures for Laboratory Tests

At baseline and each annual data collection point, the site personnel will collect optional

biospecimen samples (with patient consent) to be analysed or stored for later analysis in a

central biospecimen repository (biobank). In approved substudies, biospecimen samples may

also be taken on a more frequent basis in sub-populations e.g. during exacerbation of disease.

Patients in substudies may be asked to wear non-invasive monitors to record heart rate,

activity, or other physiological variables, medication use and environmental conditions.

6.1.4 Quality Control (QC)

Monitoring

Before the first patient is recruited into the study, the local Marketing Company (MC), the

Medical Evidence & Observational Research (MEOR) representative or the Contract Research

Organisation (CRO)�s Representative will:

· Discuss with the physicians (and other personnel involved with the study) their

responsibilities with regards to protocol compliance, and the responsibilities of AZ

or its representatives. This will be documented in an observational study Primary

Agreement between AZ/delegate and the physician.


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During the study the local MC representative or CRO representative can implement different

activities to assure compliance with AZ standards of quality. These activities could include

but are not limited to:

Contact with the sites to:

· Provide information and support to the physicians and other site personnel

· Confirm that the research team is complying with the protocol and that data are

being accurately recorded in the eCRFs

· Ensure that the patient Informed Consent Forms (ICFs) are signed and stored at the

site

· Ensure that the eCRFs are completed properly and with adequate quality.

Monitoring activities for:

· Checking a sample of ICFs

· Checking that patients exist in medical records (a sample).

A study monitoring plan, including for-cause monitoring, that is appropriate for the study

design will be developed and implemented.

Different signals (e.g. high rejection rate in a site) should be used as potential identification of

insufficient protocol compliance by the site personnel.

If these, or any other signal occurs or if the local coordinator is suspicious of a potential non-

optimal level of protocol compliance by the site personnel, specific measures should be

adopted to evaluate the situation, identify the issue and implement specific action plans to

correct the situation.

Training of Study Site Personnel

The Principal Investigator will ensure that appropriate training relevant to the observational

study is given to site personnel, and that any new information relevant to the performance of

this observational study is forwarded to the staff involved.

Representatives of the Sponsor�s quality assurance unit/monitoring team and competent

regulatory authorities must be permitted to inspect all study-related documents and other

materials at the site, including the Investigator Site File, the completed eCRFs and the

patients� original medical records. Audits may be conducted at any time during or after the

study to ensure the validity and integrity of the study data.

6.1.5 Storage and Retention

Upon completion of DBL and at the agreed time point, data from the NOVELTY Study

database including data captured from EMR, EDC and PRO will be transferred to AZ via a

secure file transfer portal in the pre agreed format.


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All original source documentation is expected to be stored at the site for the longest possible

time as required by local applicable regulations or as specified in the contract, whichever is

longer. The records must be available for review in the event the site is selected for

monitoring, audits, or inspections and must be safely archived following the study conclusion,

according to local regulations or as specified in the contract, whichever is longer.

Essential documents, as listed below, must be retained by the investigator for as long as

needed to comply with national regulations. Essential documents include:

· IRB/IEC approvals for the study protocol and all amendments

· All source documents

· eCRF contents

· Patients' or next of kin/legal representative�s ICFs (with study number and title)

· Any other pertinent study document.

AZ will notify the investigators/institutions when the study-related records are no longer

required. The investigator agrees to adhere to the document retention procedures by signing

the protocol. In the event that archiving of the file is no longer possible at the site, the site will

be instructed to notify AZ.

6.2 Protection of Human Subjects

This observational study will be performed in accordance with ethical principles that are

consistent with the Declaration of Helsinki, International Conference on Harmonisation of

Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) Good

Clinical Practices (GCPs), Good Pharmacoepidemiology Practices (GPP) and applicable

legislation for observational studies.

The site physicians will perform data collection for the observational study in accordance with

the regulations and guidelines governing medical practice and ethics in each country of the

observational study and in accordance with currently acceptable techniques and know-how.

The final protocol of the observational study, including the final version of the ICF, must be

approved or given a favourable opinion in writing by the appropriate Ethics

Committee/IRB/IEC in each country /region.

The Ethics Committee/IRB/IEC must also approve amendments to the protocol, including any

substudies requiring direct contact with patients, and all advertising used to recruit patients for

the study, according to local regulations.

6.2.1 Patient Informed Consent

The physician at each site will ensure that the patient is given full and adequate oral and

written information about the nature, purpose, possible risk and benefit of the observational

study. Patients must also be notified that they are free to discontinue from the observational


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study at any time. The patients should be given the opportunity to ask questions and allowed

time to consider the information provided.

As previously explained, the collection of biospecimen samples is optional and the decision to

collect these variables remains with the patient and the physician and will be voluntary.

The rationale behind the need to collect those variables will be clearly explained to the patient

and is aligned with the ethical pillars for observational research that patients should be only

invited for research activities aimed at doing beneficence (the data provided by the patient will

support the understanding of the needs and therapeutic options for patients with respiratory

obstructive diseases), non-maleficence (all the data collection procedures are well-established

and involve minimal discomfort for the patients), privileging autonomy (the patient consent is

based on comprehensive understanding of the study and is voluntary) and justice (all the

individuals participating in the study should equally benefit from the results of the study).

Therefore, in particular, it will be clearly explained to the patient that the study aims to

conduct lung function measurements such as spirometry, FENO and collect biologic samples,

techniques and procedures which are considered routine best practices according to

international guidelines and will not involve any additional risk for the patients. The

frequency of those measurements, the methods to guarantee no personal data is disclosed and

the right of the patient to access and, in case of withdrawal of consent, ask for complete

deletion of his/her information at any time during the study will all be transmitted to the

patient in a clear and unambiguous way.

The signed and dated patient�s informed consent must be obtained before any specific

procedure for the observational study is performed, including:

· Interview with the physician

· Filling out the questionnaires

· eCRF completion

· Lung function measurements

· Biologic samples collection (subject to a specific ICF)

The physician or delegate site personnel must store the original, signed ICF. A copy of the

signed ICF must be given to the patient.

As stated in section 3.5, for the purpose of extending the follow-up of the patients in the

platform to accommodate further studies, a specific informed consent, other than the one

required for the participation in this 3-year study will be obtained.

6.2.2 Confidentiality of Study/Patient Data

The patient�s ICF will incorporate wording that complies with relevant data protection and

privacy legislation. Pursuant to this wording, patients will authorise the collection, use and

disclosure of their personal data by the physician and by those persons who need that

information for the purposes of the observational study.


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The ICF will explain that observational study data will be stored in a computer database,

maintaining confidentiality in accordance with local laws for Data Protection.

The ICF will explain that for quality check purposes, a monitor of AZ or a monitor of

company /organisation representing AZ, will require direct access to the signed ICFs. In case

source data verification will be planned as quality check, the ICF will explain that for data

verification purposes, and for follow-up of potential Adverse Drug Reactions (ADRs),

monitor of AZ or a monitor of company representing AZ may require direct access to source

documents that are part of the hospital or practice records relevant to the observational study.

The biologic sample collection is subject to patients� informed consent. The link between the

patient enrolment code and the biologic sample number will be maintained and stored in a

secure environment, with restricted access. Additional details are presented in section 8.

6.3 Management and Report of Adverse Drug Reactions

6.3.1 Definition of Adverse Drug Reaction (ADR) and Serious ADR

An ADR is the development of an undesirable medical condition or the deterioration of a pre-

existing medical condition following or during exposure to a medicinal product, suspected to

be causally related to the product.

6.3.2 Reporting of Adverse Drug Reactions (ADRs) and Serious ADRs

The NOVELTY study is a disease registry. Although information about past and current drug

history will be collected, the focus of the study is not on the medicinal products.

Moreover, the current study is observational and therefore the clinical practice and patient

pathways should be as close as possible with routine practice. All investigators are encouraged

to report any observed ADR or serious ADR according to local regulatory requirements and, if

the investigator considers it appropriate, to AZ (in case of ADRs of an AZ-product) or the

corresponding marketing authorization holder of the drug.

However, the sponsor will include in the documentation provided to the physician a reminder

of the importance of spontaneous ADR reporting.

Individual Case Safety Reports (ICSRs) related to AZ�s medicinal products in the context of

the present study will be treated as per the company�s Standard Operational Procedure and

included in the appropriate section of the Periodic Benefit-Risk Evaluation Reports (PBRER).

6.4 Study Governance and Committees

A rigorous governance structure including an AZ Executive Committee with project

oversight, a Project Team with overall scientific responsibility, and an Operational Study

Team responsible for delivering the study will be set up. The study will be conducted in close

collaboration with internal AZ and external qualified individuals with relevant experience and


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expertise. A Scientific Committee will be set up to support and oversee the study and will be

governed by a Charter, detailing responsibilities and processes. Other teams and committees

will be set up as needed (e.g. sample management, publications, etc.).

6.5 Communication Plan

6.5.1 Publication Plan

In alignment with AZ policies, AZ will prepare a Study Report within 12 months after

completion of the 3rd

year of follow-up for the LPI (study completion). All reporting will be

consistent with the STrengthening the Reporting of OBservational studies in Epidemiology

(STROBE) Initiative checklist for cohort studies (STROBE 2012).37

Reports will be prepared

for each of the major analysis steps specified in the protocol. The final report will encompass

all planned analyses, including a description of the complete study population, as described

above and in the corresponding SAPs.

The final results of the core study will be disseminated through submission of manuscripts for

publication and guided by the Uniform Requirements for Manuscripts Submitted to

Biomedical Journals: Writing and Editing for Biomedical Publication of the International

Committee of Medical Journal Editors (ICMJE).38

Publication of data subsets from individual

institutions participating in multicentre studies should not precede the primary manuscript(s)

on the same topic(s). Selected interim and final results may also be disseminated through

publication or presentation at scientific meetings with support as relevant from the study

Scientific and Executive Committees.

6.5.2 Compliance with Study Registration and Results Posting Requirements

AZ is committed to providing full and transparent disclosure of, and open access to, the

findings of all AZ sponsored studies and information on ongoing studies sponsored by

AstraZeneca.

AZ or the delegated CRO must register all qualifying studies prior to enrolment of the first

patient, referred to as the First Patient In date. Studies are registered on ClinicalTrials.gov

(sponsored by the National Institute of Health) and other country-specific or regional websites

as required by law, with study information set forth on AZ internal templates. In addition to

publicly registering studies on ClinicalTrials.gov and other country specific or regional

websites, basic study information is also posted on AstraZenecaClinicalTrials.com.

Once a study is initially registered, any changes related to study status or protocol

amendments must be updated to ensure accurate reporting of all required information. By law

(FDA Amendment Act 2007), any changes in a study�s overall recruitment status must be

updated on ClinicalTrials.gov no later than 30 days after the change in status. All other

changes to posted information must be updated at least quarterly.

Results for qualifying studies must be disclosed within six months of study completion,

whether the study completed according to the study protocol or was discontinued earlier.


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Results are disclosed on ClinicalTrials.gov, AstraZenecaClinicalTrials.com and on other

public websites in a format and to timelines as required by law and should be submitted by AZ

as the Sponsor.

6.5.3 Compliance with Financial Disclosure Requirements

Financial compensation will be provided to cover all study procedures under the responsibility

of the Investigator. This compensation rate will be determined according to recommended fair

market value for the corresponding study activities.

Financial disclosure of this compensation will fulfil applicable local laws, codes and

regulations.

6.5.4 Changes to the Protocol

Changes to the protocol will be documented in written protocol amendments. Major (i.e.

substantial, significant) amendments will be approved by the relevant regulatory authorities

and will usually require submission or notification to the relevant IRB/IEC for approval or

favourable opinion, if applicable. In such cases, the amendment will be implemented at the

site only after approval or favourable opinion has been obtained.

Minor (non-substantial) protocol amendments, including administrative changes, will be filed

at each participating site and will be submitted to the relevant IRB/IEC or regulatory

authorities where required by pertinent regulations. Any amendment that could have an impact

on the patient�s agreement to participate in the study requires the patient�s informed consent

prior to continued participation in the study.

Amendments and updates to the protocol will be documented in Section �Amendment

History�.


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7. LIST OF REFERENCES

1 Global strategy for the diagnosis, management and prevention of COPD, Global Initiative for Chronic

Obstructive Lung Disease (GOLD) 2015. Available from: www.goldcopd.org. 2 Global Initiative for Asthma (GINA). Global strategy for asthma management and prevention 2015. Available

from: www.ginasthma.org. 3 Global Initiative for Asthma. Diagnosis of asthma, COPD, and asthma-COPD overlap syndrome (ACOS).

2015. Available from: www.ginasthma.org. 4 Hardin M,, Silverman EK, Barr RG, Hansel NN, Schroeder JD, Make BJ et al. The clinical features of the

overlap between COPD and asthma. Respir Res. 2011 Sep 27;12:127. doi: 10.1186/1465-9921-12-127. 5 Blanchette CM, Gutierrez B, Ory C, Chang E, Akazawa M. Economic burden in direct costs of concomitant

chronic obstructive pulmonary disease and asthma in a Medicare Advantage population. J Manag Care Pharm.

2008 Mar;14(2):176-85. 6 Zeki AA, Schivo M, Chan A, Albertson TE, Louie S. The asthma-COPD overlap syndrome: a common clinical

problem in the elderly. J Allergy (Cairo). 2011;2011:861926. doi: 10.1155/2011/861926. 7 Soler-Cataluna JJ, Cosio B, Izquierdo JL, Lopez-Campos JL, Marin JM, Aguero R et al. Consensus document

on the overlap phenotype COPD-asthma in COPD. Arch Bronconeumol. 2012 Sep;48(9):331-7. 8 Bateman ED, Reddel HK, van Zyl-Smit RN, Agusti A. The asthma-COPD overlap syndrome: towards a revised

taxonomy of chronic airways diseases? Lancet Respir Med. 2015 Sep;3(9):719-28. 9 Postma DS, Rabe KF. The Asthma-COPD Overlap Syndrome. N Engl J Med. 2015 Sep 24;373(13):1241-9.

10 Papaiwannou A, Zarogoulidis P, Porpodis K, Spyratos D, Kioumis I, Pitsiou G, et al. Asthma-chronic

obstructive pulmonary disease overlap syndrome (ACOS): current literature review. J Thorac Dis. 2014 Mar;6

Suppl 1:S146-51. doi:10.3978/j.issn.2072-1439.2014.03.04. 11

Papaiwannou A, Zarogoulidis P, Porpodis K, Spyratos D, Kioumis I, Pitsiou G, et al. Asthma-chronic

obstructive pulmonary disease overlap syndrome (ACOS): current literature review. J Thorac Dis. 2014 Mar;6

Suppl 1:S146-51. doi:10.3978/j.issn.2072-1439.2014.03.04. 12

Han, MK, Agusti, A, Calverley, PM, Celli, BR, Criner, G, Curtis JL et al. Chronic obstructive pulmonary

disease phenotypes: the future of COPD. Am J Respir Crit Care Med. 2010 Sep 1;182(5):598-604. doi:

10.1164/rccm.200912-1843CC. 13

Marsh, SE, Travers, J, Weatherall, M, Williams, MV, Aldington, S, Shirtcliffe, PM et al. Proportional

classifications of COPD phenotypes. Thorax. 2008 Sep;63(9):761-7. doi: 10.1136/thx.2007.089193. 14

Celli, BR. Roger S. Mitchell lecture. Chronic obstructive pulmonary disease phenotypes and their clinical

relevance. Proc Am Thorac Soc. 2006 Aug;3(6):461-5. 15

Miravitlles M, Soler-CatalunCatalun JJ, Calle, M, Molina J, Almagro P, Quintano JA et al. (2013) A new

approach to grading and treating COPD based on clinical phenotypes: summary of the Spanish COPD guidelines

(GesEPOC). Prim Care Respir J. 2013 Mar;22(1):117-21. 16

Wenzel SE. Complex phenotypes in asthma: current definitions. Pulm Pharmacol Ther. 2013 Dec;26(6):710-5. 17

Darveaux J, Busse WW. Biologics in Asthma�The Next Step Toward Personalized Treatment. Allergy Clin

Immunol Pract. 2015 Mar-Apr;3(2):152-60; quiz 161. 18

Travers J, Marsh S, Caldwell B, Williams M, Aldington S, Weatherall M et al. External validity of randomized

controlled trials in COPD. Respir Med. 2007 Jun;101(6):1313-20. 19

Travers J, Marsh S, Williams M, Weatherall M, Caldwell B, Shirtcliffe P et al. External validity of randomised

controlled trials in asthma: to whom do the results of the trials apply? Thorax. 2007 Mar;62(3):219-23. 20

Wheelock CE, Goss VM, Balgoma D, Nicholas B, Brandsma J, Skipp PJ, et alc R; U-BIOPRED Study Group.

Application of 'omics technologies to biomarker discovery in inflammatory lung diseases. Eur Respir J.

2013;42(3):802-25. 21

Agusti A, Calverley PM, Celli B, Coxson HO, Edwards LD, Lomas DA, et al. Characterisation of COPD

heterogeneity in the ECLIPSE cohort. Respir Res 2010;11:122. 22

Couper D, LaVange LM, Han M, Barr RG, Bleecker E, Hoffman EA, et al; SPIROMICS Research Group.

Design of the Subpopulations and Intermediate Outcomes in COPD Study (SPIROMICS). Thorax.

2014;69(5):491-4.


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23

Regan EA, Hokanson JE, Murphy JR, Make B, Lynch DA, Beaty TH, et al. Genetic epidemiology of COPD

(COPDGene) study design. COPD. 2010;7(1):32-43. 24

Bush A, Kleinert K, Pavord ID. The asthmas in 2015 and beyond: a Lancet Commission. Lancet. 2015 Apr

4;385(9975):1273-5. doi: 10.1016/S0140-6736(15)60654-7. 25

Woodruff PG, Augusti A, Roche N, Singh D, Martinez FJ. Current concepts in targeting chronic obstructive

pulmonary disease pharmacotherapy: making progress towards personalised management. Lancet. 2015 May

2;385(9979):1789-98. doi: 10.1016/S0140-6736(15)60693-6. 26

Quanjer PH, Stanojevic S, Cole TJ, Baur X, L Hall GL, Culver B, et al. Multi ethnic reference values for

spirometry for the 3-95 year age range: the global lung function 2012 equations. Eur Respir J. 2012

Dec;40(6):1324-43. 27

Moore WC, Hastie AT, Li X, Li H, Busse WW, Jarjour NN, et al; National Heart, Lung, and Blood Institute's

Severe Asthma Research Program. Sputum neutrophil counts are associated with more severe asthma phenotypes

using cluster analysis. J Allergy Clin Immunol. 2014;133(6):1557-63.e5. 28

Luisetti M, Ma S, Iadarola P, Stone PJ, Viglio S, Casado B, et al. Desmosine as a biomarker of elastin

degradation in COPD: current status and future directions. Eur Respir J;2008;32:1146�1157. 29

Wenzel S. Mechanisms of severe asthma. Clin Exp Allergy. 2003;33(12):1622-8. 30

Mann BS, Chung KF. Blood neutrophil activation markers in severe asthma: lack of inhibition by prednisolone

therapy. Respir Res. 2006 Apr 6;7:59. 31

Uddin M, Nong G, Ward J, Seumois G, Prince LR, Wilson SJ, et al. Prosurvival activity for airway neutrophils

in severe asthma. Thorax 2010;65(8):684-9. 32

Sampson AP, Cowburn AS, Sladek K, Adamek L, Nizankowska E, Szczeklik A, et al. Profound

overexpression of leukotriene C4 synthase in bronchial biopsies from aspirin-intolerant asthmatic patients. Int

Arch Allergy Immunol. 1997;113(1-3):355-7. 33

Burgel PR, Paillasseur JL, Roche N. Identification of clinical phenotypes using cluster analyses in COPD

patients with multiple comorbidities. Biomed Res Int. 2014;2014:420134. doi: 10.1155/2014/420134. 34

Haldar P(1), Pavord ID, Shaw DE, Berry MA, Thomas M, Brightling CE, Wardlaw AJ,

Green RH. Cluster analysis and clinical asthma phenotypes. Am J Respir Crit Care Med. 2008 Aug

1;178(3):218-24. 35

Miller MR, Crapo R, Hankinson J, Brusasco V, Burgos F, Casaburi R, et al. General considerations for lung

function Testing. Eur Respir J. 2005;26(1):153-61 36

Pellegrino R, Viegi G, Brusasco V, Crapo RO, Burgos F, Casaburi R, et al. Interpretative strategies for lung

function tests. Eur Respir J. 2005;26:948-968. 37

STROBE Group [Internet]. STROBE Statement: STrengthening the Reporting of OBservational studies in

Epidemiology. March 30, 2008. Available at: http://www.strobe-statement.org/News%20Archive.html. 38

International Committee of Medical Journal Editors (ICMJE). Uniform Requirements for Manuscripts

Submitted to Biomedical Journals (current official version available at www.ICMJE.org).


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8. APPENDICES

8.1 List of countries and targeted number of patients

Country participation to this protocol is flexible, but core anticipated countries to be included

and respective number of patients to be recruited are given in Table 4.

Table 4 - Estimated number of patients to be recruited from each core anticipated participating country

Country

Number of

Patients with

an asthma

diagnosis*

Number of

mild

Number of

moderate

Number of

severe

Australia 600 200 200 200

Canada 600 200 200 200

China (Mainland) 1,000 300 350 350

France 600 200 200 200

Germany 600 200 200 200

Italy 600 200 200 200

Japan 600 200 200 200

Nordics (Denmark,

Norway and Sweden) 600 200 200 200

South Korea 300 100 100 100

Spain 600 200 200 200

UK 600 200 200 200

US 1,000 300 300 400

Total 7,700 2,500 2,550 2,650


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Country

Number of

Patients with a

COPD

diagnosis*

Number of

mild

Number of

moderate

Number of

severe/very

severe

Australia 600 200 200 200

Canada 600 200 200 200

China (Mainland) 600 200 200 200

France 600 200 200 200

Germany 600 200 200 200

Italy 600 200 200 200

Japan 600 200 200 200

Nordics (Denmark,

Norway and Sweden) 600 200 200 200

South Korea 300 100 100 100

Spain 600 200 200 200

UK 600 200 200 200

US* 800 200 200 400

Total 7,100 2,300 2,300 2,500

*Diagnosis or primarily suspected diagnosis of asthma/COPD


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8.2 Specific procedures for Laboratory Tests

At baseline and each annual data collection point, the site personnel will collect optional

biologic samples to be analysed immediately at a central laboratory (haematological variables)

or stored in a central biospecimen repository (biobank) for later analysis. The haematological

parameters may be reported back to the site investigators, but analyses performed on the

biobanked samples will not be reported to the sites. In the substudies, biospecimen samples

may also be taken on a more frequent basis in sub-populations e.g. during exacerbation of

disease.

Handling, storage and destruction of biospecimen samples

The samples will be used up or disposed of after analyses or retained for further use as

described below. Refer to the Laboratory Manual for detailed sample processing, handling,

shipment and storage information.

Biospecimen samples for future research will be retained at a Biobank on behalf of AZ for a

maximum of 15 years following the finalisation of the Clinical Study Report. The results from

future analyses will not be reported in a formal Study Report but separately in addenda,

internal reports or external publications such as abstracts at scientific meetings and peer-

reviewed scientific articles.

Genomic samples

· The patient�s consent to participate in the genomic research components of the study is

optional;

· A blood sample for genetic research will be obtained from the patients at the baseline

visit. Although genotype is a stable parameter, early sample collection is preferred to

avoid introducing bias through excluding patients who may withdraw later in the

study. If for any reason the sample is not drawn at the baseline visit or otherwise lost,

it may be taken at any visit until the last study visit. Only one sample should be

collected and stored per patient for genetics during the study;

· Samples will be collected, labelled, stored and shipped as detailed in the Laboratory

Manual;

· The samples will be used to investigate whether patients with asthma and COPD have

an increased frequency of certain genotypes that predispose them to disease

pathogenesis and poor disease control and clinical progression. Similarly, candidate

gene analysis in genetic association studies will enable us to find disease-susceptibility

genes.


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Storage, re-use and destruction of genomic samples

The processes adopted for the coding and storage of samples for genetic analysis are

important to maintain patient confidentiality. Samples will be stored for a maximum of 15

years from the date of the finalisation of the Clinical Study Report, after which they will be

destroyed. DNA is a finite resource that may be used up during analyses. The results of any

further analyses will be reported either in the Clinical Study Report itself or as an addendum,

or separately in a scientific report or publication.

For all samples irrespective of the type of coding used, the DNA will be extracted from the

blood sample. The DNA sample will be assigned a unique number replacing the information

on the sample tube. Thereafter, the DNA sample will be identifiable by the unique DNA

number only. The DNA number is used to identify the sample and corresponding data at the

AZ genetics laboratories, or at the designated contract laboratory. No personal details

identifying the individual will be available to any person (AZ employee or contract laboratory

staff working with the DNA).

The samples and data for genetic analysis in this study will be single coded. The link between

the patient enrolment code and the DNA number will be maintained and stored in a secure

environment, with restricted access. The link will be used to identify the relevant DNA

samples for analysis, facilitate linking of genotypic results with clinical data, allow regulatory

audit, and to trace samples for destruction in the case of withdrawal of consent when the

patient has requested disposal/destruction of collected samples not yet analysed.

Any genotype data generated in this study will be stored in an appropriate secure system

within AZ and/or third party contracted to work with AZ to analyse samples. The results from

this genetic research may be reported in the Clinical Study Report for the main study, or in

separate reports as appropriate. Some or all of the clinical datasets from the main study may

be merged with the genetic data in a suitable secure environment separate from the clinical

database.

Labelling and shipment of biohazard samples

The Principal Investigator will ensure that samples are labelled and shipped in accordance

with the Laboratory Manual and the Biological Substance, Category B Regulations (materials

containing or suspected to contain infectious substances that do not meet Category A criteria

(see International Airline Transportation Association IATA 6.2 Guidance Document, Section

8.3).

Any samples identified as Infectious Category A materials will not be shipped and no further

samples will be taken from the patient unless agreed with AZ and appropriate labelling,

shipment and containment provisions are approved.

Chain of custody of biospecimen samples

A full chain of custody will be maintained for all samples throughout their lifecycle.


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The Principal Investigator at each centre will keep full traceability of collected biospecimen

samples from the patients whilst in storage at the centre until shipment and will retain sample

receipt documentation.

The sample receiver will keep full traceability of the samples whilst in storage and during use

until used or disposed or until further shipment and keeps documentation of receipt of arrival.

AZ or its designee will keep oversight of the entire life cycle through internal procedures,

monitoring of study sites and auditing of external laboratory providers.

Samples retained for further use will be registered in the AZ (or its designee) Biobank system

during the entire life cycle.

Withdrawal of informed consent for donated biospecimen samples

If a patient withdraws consent to the use of donated biospecimen samples, the samples will be

disposed of/destroyed, if not already analysed and documented.

As collection of the biospecimen samples is a voluntary part of the study, the patient may

continue in the study.

The Principal Investigator:

· Will ensure patients� withdrawal of informed consent is notified immediately to AZ;

· Will ensure that biospecimen samples from that patient, if stored at the study site, are

immediately identified, disposed of/destroyed and the action documented;

· Will ensure that the laboratory(ies) holding the samples is/are informed about the

withdrawn consent immediately and that samples are disposed of/destroyed and the

action documented and returned to the study site.

AZ will ensure that the central laboratory(ies) holding the samples is/are informed about the

withdrawn consent immediately and that samples are disposed of/destroyed and the action

documented returned to the study site.

If samples are already analysed, AZ are not obliged to destroy the results of this research.

Data management and statistical analysis

Data associated with biospecimen samples will be transferred to laboratories internal or

external to AstraZeneca along with those samples, to maintain identifiability and traceability.


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8.3 International Airline Transportation Association (IATA) 6.2

Guidance Document

LABELLING AND SHIPMENT OF BIOHAZARD SAMPLES

International Airline Transportation Association (IATA) classifies biohazardous agents into 3

categories. For transport purposes the classification of infectious substances according to risk

groups was removed from the Dangerous Goods Regulations (DGR) in the 46th edition

(2005). Infectious substances are now classified either as Category A, Category B or Exempt.

There is no direct relationship between Risk Groups and categories A and B.

Category A Infectious Substances are infectious substances in a form that, when exposure to

it occurs, is capable of causing permanent disability, life-threatening or fatal disease in

otherwise healthy humans or animals.

Category A pathogens e.g., Ebola, Lassa fever virus:

� are to be packed and shipped in accordance with IATA Instruction 602.

Category B Infectious Substances are infectious Substances that do not meet the criteria for

inclusion in Category A. Category B pathogens are e.g., hepatitis A, B, C, D, and E viruses,

human immunodeficiency virus (HIV) types 1 and 2. They are assigned the following UN

number and proper shipping name:

� UN 3373 � Biological Substance, Category B

� are to be packed in accordance with UN3373 and IATA 650

Exempt - all other materials with minimal risk of containing pathogens

� Clinical trial samples will fall into Category B or exempt under IATA regulations

� Clinical trial samples will routinely be packed and transported at ambient temperature

in IATA 650 compliant packaging

� Biospecimen samples transported in dry ice require additional dangerous goods

specification for the dry-ice content

� IATA compliant courier and packaging materials should be used for packing and

transportation and packing should be done by an IATA certified person, as applicable

� Samples routinely transported by road or rail are subject to local regulations which

require that they are also packed and transported in a safe and appropriate way to

contain any risk of infection or contamination by using approved couriers and packaging


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/ containment materials at all times. The IATA 650 biospecimen sample containment

standards are encouraged wherever possible when road or rail transport is used.

8.4 EMR feasibility study overview

An EMR feasibility study was conducted along with the protocol development. This

feasibility is intended to optimize the study protocol and planning, in lieu of a pilot, by

conducting initial research that will achieve the following objectives:

� Determine the feasibility to implement the NOVELTY study and build a research

platform

� Assess high level cost structure and timing estimates for NOVELTY by country

� Highlight considerations for protocol development based on design options

� Recommend best option(s) by country, and identify design tradeoffs

� Identify country-specific risks, barriers and how to proactively address them

before launching NOVELTY

The scope of the feasibility study covers analysis of existing EMR data by country, research

into asthma and COPD patient pathways and research into obtaining data not available

through EMR access. The following are outcomes for the feasibility:

� Validation of routine clinical data capture (overall coverage and completeness)

and physician representativeness

� Distribution of patients by severity algorithm

� Data input for recruitment planning

� Investigator interest in the NOVELTY study and prospective data collection

� Feasibility of obtaining data not available through EMR access (e.g. biomarker

sample

For details of EMR feasibility study, please contact one of the responsible parties to

obtain full report.

Below Table 5 is the patient count and severity distribution, obtained from the feasibility

study using the EMR database selected for each country. Patients with a diagnosis of

asthma or COPD during the inclusion period spanning from 1st August 2013 to 31st July

2014 were selected, the Index date is the most recent date of asthma or COPD diagnosis

during the inclusion period and inclusion criteria refers to at least one year of history

before index date and at least one year history post index date. The severity was then

defined using algorithm of treatments for Asthma according to the GINA guideline, and a

mix of treatment and lung function FEV1 results according to the GOLD guideline for

COPD.


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Table 5: Patient count and severity distribution from EMR feasibility study

FR: France; ES: Spain, IT: Italy; DE: Germany; SE: Sweden; JP: Japan, CA: Canada; AU: Australia;

For US: total 8 networks are being accessed plus IMS US EMR, the results from intermountain healthcare system was presented here.

For China: the EMR records were manually reviewed on a small sample of identified patient due to the unique treatment options in the

Market and ensuring the accuracy, thus the results were not included here.. ACOS: Asthma COPD Overlap Syndrome

Key observations:

§ Large number of patients are available across all countries except Canada.

§ Disease severity is hard to determine by treatment alone and even utilizing FEV1 (COPD)

§ Asthma disease severity often requires extraction of daily dose from the text of medication

§ Records FEV1 is not readily available in structured format

§ Among severity classified patients, for asthma approximately 32% of the patients will be

severe or very severe. For COPD, more than 50% of the patients will be severe or very severe

Disease Severity

Total

classified43,770 100% 17,084 100% 12,494 100% 12,590 100% 42,521 100% 6,322 100%

Mild (i) 7,338 17% 4,074 24% 2,360 19% 1,587 13% 8,233 19% 504 8%

Mild (ii) 9,704 22% 1,326 8% 1,163 9% 1,575 13% 6996 16% 777 12%

Moderate 11,651 27% 2,193 13% 3,169 25% 5,618 45% 22,222 52% 1,914 30%

Severe 13,740 31% 8,735 51% 5,044 40% 3,173 25% 4,882 11% 2464 39%

Very Severe 1,337 3% 756 4% 758 6% 637 5% 188 0% 663 10%

Unclassified 13,248 - 11,616 - 4,085 - 10,130 - 15,220 - 2,079 -

Total

classified38,811 100% 7,359 100% 11,673 100% 11,698 100% 43,840 100% 3,917 100%

Mild 4,500 12% 542 7% 663 6% 417 4% 6,890 16% 136 3%

Moderate 20,883 54% 2,371 32% 3,601 31% 3,073 26% 12,670 29% 833 21%

Severe 13,428 35% 4,446 60% 7,409 63% 8,208 70% 24,280 55% 2,405 61%

Very Severe1 - - - - - - - - - - 543 14%

Unclassified 3,066 - 3,622 - 1903 - 10,866 - 23,751 - 328 -

ACOS Total 3,920 100% 1,966 100% 1,063 100% 1,493 100% 12,015 100% 558 100%

UK FR ES

Asthma

COPD

IT DE SE


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9. ATTACHMENTS


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70

SIGNATURE OF NATIONAL CO-ORDINATING INVESTIGATOR

D2287R00103 Observational study of obstructive lung disease

(NOVELTY): A NOVEL observational longiTudinal studY on patients with

a diagnosis or suspected diagnosis of asthma and/or COPD to describe

patient characteristics, treatment patterns and the burden of illness over

time and to identify phenotypes and endotypes associated with differential

outcomes that may support future development of personalised treatment

strategies

<<This NIS Protocol >> <<has/have>> been subjected to an internal AstraZeneca

review>>

I agree to the terms of this Non-Interventional Study protocol. I will conduct the study

according to the procedures specified herein, and according to the local regulations.

Site No.: <<If the National Co-ordinating Investigator is not responsible

for a specific site, please delete the Site No.: This may be hand-

written onto the page at the time the signature is collected. It is

not necessary for any one investigator to sign the protocol more

than once ie, if the international co-ordinator is a Principal

Investigator at a site it is not necessary for them to sign the

investigator signature page>>

Signature:

<<Name, title, email address and telephone

number>>

Date

(Day Month Year)

This document contains confidential information, which should not be copied, referred to,

released or published without written approval from AstraZeneca. Investigators are cautioned

that the information in this protocol may be subject to change and revision.


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71

SIGNATURE OF PRINCIPAL INVESTIGATOR

D2287R00103 Observational study of obstructive lung disease

(NOVELTY): A NOVEL observational longiTudinal studY on patients with

a diagnosis or suspected diagnosis of asthma and/or COPD to describe

patient characteristics, treatment patterns and the burden of illness over

time and to identify phenotypes and endotypes associated with differential

outcomes that may support future development of personalised treatment

strategies

<<This NIS Protocol >> <<has/have>> been subjected to an internal AstraZeneca

review>>

I agree to the terms of this study protocol. I will conduct the study according to the

procedures specified herein, and according to the local regulations.

Site No.: <<This may be hand-written onto the page at the time the signature is

collected>>

Signature:

<<Name, title, email address and telephone

number>>

Date

(Day Month Year)

This document contains confidential information, which should not be copied, referred to,

released or published without written approval from AstraZeneca. Investigators are cautioned

that the information in this protocol may be subject to change and revision.

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