A pharmacoepidemiological study of the multi-level determinants, predictors, and clinical outcomes...

IM - ORIGINAL

A pharmacoepidemiological study of the multi-level determinants,predictors, and clinical outcomes of biosimilar epoetin alfafor renal anaemia in haemodialysis patients: backgroundand methodology of the MONITOR-CKD5 study

Loreto Gesualdo • Gerard London • Matthew Turner • Christopher Lee • Karen MacDonald •

David Goldsmith • Adrian Covic • Philippe Zaoui • Christian Combe • Johannes Mann •

Frank Dellanna • Michael Muenzberg • Ivo Abraham

Received: 25 January 2011 / Accepted: 29 April 2011 / Published online: 18 May 2011

� SIMI 2011

Abstract Prior longitudinal observational studies have

examined the practice patterns and outcomes of anaemia

management, including the use of erythropoiesis-stimulating

agents (ESAs). Several dimensions of effectiveness remain

unaddressed; especially considering the revised ESA label

(target Hb levels between 10 and 12 g/dL), the recently

published TREAT study, and the European approval of the

first ESA biosimilar (HX575). Anecdotal evidence suggests

that patient outcomes are influenced by physician-related

variables and whether anaemia management is congruent

with practice guidelines, but this has not been studied sys-

tematically. MONITOR-CKD5 is an international, pro-

spective, observational, pharmacoepidemiological study

evaluating the multi-level factors and outcomes of treatment

with HX575 for renal anaemia in haemodialysis patients.

Driven by a novel, integrated, multi-focal framework for

post-approval observational studies, it examines determi-

nants of response at both the patient and the physician level;Trial Registration:clinicaltrials.gov NCT01121237

L. Gesualdo

Department of Nephrology, Universita degli Studi di Bari, Bari,

Italy

e-mail: [email protected]

G. London

Department of Nephrology and Hemodialysis, Centre Hospitalier

F. H. Manhes, Fleury-Merogis, France


M. Turner � M. Muenzberg

Sandoz Biopharmaceuticals, Holzkirchen, Germany


M. Muenzberg


C. Lee � K. MacDonald � I. Abraham (&)

Matrix45, 620 Frays Ridge Road, Earlysville, VA 22936, USA


C. Lee


K. MacDonald


C. Lee � I. Abraham

Center for Health Outcomes and Pharmaco-economic Research,

College of Pharmacy, The University of Arizona, Tucson, AZ,

USA

D. Goldsmith

King’s Health Partners, Guy’s and St Thomas’ NHS Foundation

Hospital, London, UK


A. Covic

Dialysis and Transplantation Center, G. I. Popa University

Hospital of Medicine and Pharmacy, Iasi, Romania


P. Zaoui

Centre Hospitalier Universitaire de Grenoble and Universite de

Grenoble, Grenoble, France


C. Combe

Department of Nephrology and INSERM U889, Centre

Hospitalier de Bordeaux and Universite de Bordeaux 2–Victor

Segalen, Bordeaux, France


J. Mann

Schwabing Klinikum and Friedrich Alexander Universitat

Erlangen-Nurnburg, Munich, Germany


F. Dellanna

Dialysezentrum, Duesseldorf, Germany


123

Intern Emerg Med (2013) 8:389–399

DOI 10.1007/s11739-011-0622-7

integrates an advocated statistical methodology here to fore

used mainly in the social and behavioural sciences; assesses

factors potentially predictive of a poor treatment response;

and evaluates the extent to which treatment is congruent with

evidence-based guidelines, good practice evidence, and the

revised ESA label. This pan-European study will recruit at

least 1,000 patients from a minimum of 75 centres, and follow

them for up to 24 months following initiation of anaemia

management with biosimilar epoetin alfa. MONITOR-CKD5

will not only study the core issues addressed by prior obser-

vational studies but also aims to take knowledge discovery a

step further by assessing outcomes across varying cohorts of

patients, and examining the impact of evidence-based practice

on clinical outcomes, differentiating, in the process, between

physician-level and patient-level determinants.

Keywords Biosimilar � Erythropoietin � Haemodialysis �Pharmacoepidemiology � Renal anaemia

Abbreviations

ANOVA Analysis of variance

CKD Chronic kidney disease

CKD5 Chronic kidney disease stage 5

CRF Case report form

DOPPS Dialysis Outcomes and Practice Patterns

Study

eCRF Electronic case report form

ESA Erythropoiesis-stimulating agent

ESAM European Survey on Anaemia Management

GFR Glomerular filtration rate

Hb Haemoglobin

HR Hazard ratio

MANOVA Multivariate analysis of variance

RCT Randomized controlled trial

RRT Renal replacement therapy

v2 Chi-squared

Introduction

Normochromic normocytic anaemia develops in approxi-

mately two-thirds of patients with chronic kidney disease

(CKD), and in almost all patients with Stage 5 chronic

kidney disease (CKD5) requiring renal replacement ther-

apy (RRT) [1]. Referred to also as renal anaemia, the

predominant cause is inadequate erythropoiesis: failure of

the kidneys to produce endogenous erythropoietin to

stimulate the bone marrow to produce erythrocytes [2].

Renal anaemia is an amenable condition when properly

identified and treated.

CKD5 is defined as having a glomerular filtration rate

(GFR) \ 15 mL/min/1.73 m2 or the requirement of RRT

[3]. Renal anaemia is problematic in this population

because of the higher and graded risk and degree of

anaemia with a lower GFR [4], and the elevated risk of

morbidity, hospitalization, and mortality if not treated

effectively [5, 6]. Evidence-based guidelines such as

K/DOQI and the European Best Practice Guidelines[7–9]

advocate an anaemia work-up for CKD patients with a

haemoglobin (Hb) concentration below the age- and gen-

der-adjusted population mean minus two standard deviations

(i.e., Hb \ 11.5 g/dL in adult women, Hb \ 13.5 g/dL in

adult men, and Hb \ 12.0 g/dL in adult men age[70); and for

managing moderate anaemia with erythropoiesis-stimulating

agents (ESAs) to maintain a target Hb level of 11–12 g/dL

without exceeding 13 g/dL [7–9].

Despite these guidelines and about 20 years of clinical

experience with ESAs in renal anaemia (including the first

biosimilar), large observational studies such as ESAM and

DOPPS indicate that target Hb levels are often unrealized

[10–13]; with other aspects of the care of CKD5 patients

often not being in concordance with guidelines [10, 12, 14–

17]. This suggests that in addition to patient-level charac-

teristics [18, 19], ‘‘real-world’’ practice patterns of the

treating clinician, including selection of target Hb levels,

ESA dosing and frequency, and general CKD guideline

concordance, have an impact upon Hb outcomes in CKD5

patients [15, 16]. Specifically, it has not been studied how

physician-level variables contribute to CKD5 patients

remaining at risk for poor Hb control, morbidity, hospi-

talization and mortality despite ‘‘treatment.’’ Multi-level

modelling (considering both patient- and provider-level

characteristics) is a robust, advocated method for the

evaluation of treatment effectiveness in clinical nephrol-

ogy research [20], and helps fill important gaps in

explaining variability in Hb outcomes in CKD5 patients

[19, 21, 22].

Though the recently published TREAT study [23] was

focused on non-dialysed Type 2 diabetes patients with

moderate to severe CKD (and not on haemodialysis

patients), this study comparing protocol driven ESA ther-

apy with darbepoetin alfa to placebo, underscores the

importance of mapping current treatment practice in

varying cohorts of patients. The study’s findings have

produced commentaries from the negative [24] to the more

balanced [25]. Two common themes are, first, the extent to

which the same Hb target might apply across the board to

all potential recipients of ESAs—old versus young,

comorbidity-complicated versus uncomplicated, diabetic

versus not—given that the risk–benefit calculations might

diverge between these different patient groups. Second, is

the role of adequate and timely management of absolute

and functional iron deficiencies, and the integration of iron

management and ESA therapy. The issues must be

addressed through observational studies of real-world

390 Intern Emerg Med (2013) 8:389–399

123

practice to better understand how variability in treatment

practice translates into variability in patient outcomes.

The adoption of evidence-based guidelines in medicine

has been called mixed and disappointing [26]. The extent

to which anaemia management in haemodialysis patients is

congruent with guidelines has not been studied. Further,

Port and colleagues used DOPPS data to show how six

modifiable haemodialysis parameters are associated with

reductions in mortality: dialysis dose, phosphate control,

anaemia, serum albumin (as a marker for nutrition), inter-

dialytic weight gain, and the use of catheters for vascular

access. It merits investigation of whether, on the whole,

adequate haemodialysis care translates into better patient

outcomes [15].

In addition to these scientific issues, the recent approval

of the first biosimilar recombinant human erythropoietin

(HX575, marketed as Binocrit� and Epoetin Alfa Hexal�)

[27–30] brings with it the need for observational studies to

examine how this agent is used in daily practice, and the

clinical outcomes achieved.

A last factor concerns the recent changes in the Euro-

pean label for ESAs, which set target Hb levels in the

10–12 g/dL range. Whether daily practice is congruent

with this revised label has not been evaluated.

Framework for observational effectiveness studies

Randomized controlled trials (RCT) are the indicated

method for determining the efficacy of pharmacological

agents. However, by necessity RCTs are constrained in

terms of patients and clinicians included, and treatments

must be limited to the agent under investigation so as to be

able to draw unconfounded efficacy inferences. Observa-

tional studies are needed to examine the effectiveness of

drugs previously documented to be efficacious: how a

treatment works under ordinary and variable conditions,

prescribed by licensed clinicians with varying degrees of

expertise, and practicing across the spectrum of healthcare

settings, to treat a heterogeneity of eligible patients. Most

observational studies focus narrowly on evaluating a

treatment’s effectiveness under ‘‘real-world’’ conditions,

leaving key questions unanswered. The question of

‘‘whether the treatment works?’’, while critical, does not

address the equally important questions of ‘‘when does the

treatment work, and when not?’’, ‘‘in whom does the

treatment work, and in whom not?’’, ‘‘why does the treat-

ment work in some patients but not in others?’’, ‘‘why does

the treatment work with some clinicians but not with oth-

ers?’’, and ‘‘why is the treatment tolerated by some patients

but not by others?’’ To answer these questions, the

MONITOR-CKD5 study has adopted an integrated

framework for observational effectiveness studies, used

now in several studies, that has become a de facto quality

model to assure clinical relevance, scientific value, and

technical merit (see Fig. 1).

Aims

Within the framework (Fig. 1), the study’s primary aim is

to describe the haemodialysis patient population with renal

anaemia being treated with marketed Binocrit� or Epoetin

Alfa Hexal� (HX575) per their prescribing physician’s best

clinical judgment; assess treatment patterns involving this

agent, (including the extent to which these are congruent

with the approved label and clinical practice guidelines);

evaluate Hb level and Hb variability outcomes; and

examine time to and determinants of any hospitalizations,

thrombo-embolic/vascular events, and mortality. Second-

arily, this study aims to identify patient cohorts who are

vulnerable to poor treatment response, and to understand

the differences between those patients who do and those

who do not respond to treatment with HX575.

Fig. 1 Framework for observational effectiveness studies

Intern Emerg Med (2013) 8:389–399 391

123

Objectives and research questions

The study’s objectives and associated research questions,

as derived from the framework (Fig. 1), are as follows:

Primary objectives

• Case-finding and patient description

• Objective 1 To describe the patients requiring

haemodialysis who, in their treating physician’s

best clinical judgment, are receiving HX575 for the

treatment of renal anaemia in terms of demograph-

ics, clinical status, medical history, concomitant

comorbid conditions, current status of disease, and

prior and concomitant medications.

• Treatment patterns

• Objective 2 To describe HX575 treatment patterns

for renal anaemia over up to 24 months of

treatment.

• Congruence of treatment with labels and guidelines

• Objective 3 To determine the extent to which the

management of renal anaemia in haemodialysis

patients is in congruence with prevailing best

practice guidelines and approved label in terms of

target Hb levels, treatment initiation, and treatment

modification; and whether this is associated with

better treatment outcomes.

• Objective 4 To determine the extent to which the

overall management of patients with CKD5 is in

congruence with Port et al.’s [15] evidence regard-

ing modifiable risk factors for poor patient out-

comes; and whether this is associated with better

treatment outcomes.

• Description of observed outcomes

• Objective 5 To describe Hb outcomes observed over

up to 24 months of treatment with HX575 for renal

anaemia in patients with CKD5.

• Objective 6 To describe the distribution of safety

outcomes and estimate the time-to-event for first

overnight hospitalization, for thrombo-embolic/vas-

cular events, and for all-cause mortality over up to

24 months of treatment with HX575.

• Multi-level determinants of outcomes

• Objective 7 To examine the multi-level determi-

nants (patient and physician/centre) and Hb and

safety outcomes of treatment with HX575 to better

understand the variability in Hb and safety out-

comes achieved.

Secondary objectives

• Cohort identification and differentiation

• Objective 8 To identify different latent clusters of

patients with CKD5 receiving HX575 for the

treatment of renal anaemia using statistical data-

mining techniques to profile patients based on

medical history, concomitant comorbid conditions,

and current clinical status.

• Non-responder analyses

• Objective 9 To model patient- and physician/centre-

level variables between patients who respond, and

those who do not respond to treatment with HX575.

• Objective 10 To model patient- and physician/

centre-level variables between patients who had C1

overnight hospitalization, and those who were hospi-

talization-free during up to 24 months of treatment

with HX575.


centre-level variables between patients with thrombo-

embolic events, and those free from thrombo-embolic/

vascular events during up to 24 months of treatment

with HX575.


centre-level variables between patients who die, and

those who survive during treatment with HX575.

Safety, including immunogenicity, will also be monitored

throughout the study.

Methods/design

Study design

MONITOR-CKD5 is an international, prospective, obser-

vational, multi-level, pharmacoepidemiological study in

which haemodialysis patients are started on commercially

available HX575 (Binocrit� or Epoetin Alfa Hexal�) for

the treatment of renal anaemia per their prescribing

physician’s best clinical judgment. Potential centres and

physician-investigators are identified by the local affiliate of

the study sponsor (Sandoz Biopharmaceuticals, Holzkirchen,

Germany) using a Study Briefing document summarizing the

study (Fig. 2).

The multi-level design of this observational study is

warranted for both clinical and statistical reasons. Clini-

cally, it can be assumed that patients under the care of the

same physician (or, for that matter, at the same centre) are

uniquely and exclusively exposed to that physician’s

knowledge, experience, expertise, and clinical practice

patterns. At the centre level, patient care may be influenced

392 Intern Emerg Med (2013) 8:389–399

123

by clinical policies, procedures, and protocols. Statistically,

this exposure to the same physician or centre means that

these patients are treated with a certain communality that

may be different across investigators and centres partici-

pating in the study. Extending this across physician-

investigators and centres, observations on the total sample

of patients are not independent, thus violating a major

assumption for statistical testing. In multi-level (or hierarchical

linear) modelling, the effect of class (e.g., treating physician)

on patient-level outcomes are estimated before the effect

of between-patient variability is determined; yielding an

attribution of variance and identification of level-specific

predictors of patient outcomes that separates between-class

and within-patient variability.

The enrolment period is 36 months. Patients will be

evaluated monthly for up to 24 months. The total duration

of the study protocol is 60 months. The MONITOR-CKD5

study is a pan-European study to which Austria, Belgium,

France, Germany, Italy, Spain, Switzerland, Poland,

Romania, Slovenia and the United Kingdom have already

committed (and assured the required sample size). Addi-

tional countries may join as HX575 market entry expands

in the coming years.

Identification of eligible patients

Both ESA-naive patients and patients previously treated

with other ESAs will be screened for eligibility. Those

meeting the inclusion and exclusion criteria will be

informed about the study and written informed consent will

be obtained.

Patient inclusion criteria

To be included, patients should be male or female adults

(age [ 18 years), on chronic haemodialysis for any dura-

tion due to end-stage renal disease (CKD5) of original or

grafted kidneys, diagnosed with renal anaemia, and treated

with commercially available HX575 (Binocrit� or Epoetin

Alfa Hexal�) per physician’s best clinical judgment, and

under consideration of available guidance and evidence.

Female patients must be either post-menopausal for 1 year,

surgically sterile, or using effective contraceptive methods

such as barrier method with spermicide, an intra-uterine

device, or oral contraceptives. Informed consent to partic-

ipate in the study must be granted by patient or a legal

guardian.

Fig. 2 Study briefing document used for centre and physician-investigator recruitment

Intern Emerg Med (2013) 8:389–399 393

123

Patient exclusion criteria

Excluded are patients who demonstrate any of the fol-

lowing: known sensitivity to HX575 or any other ESA;

diagnosed with solid or haematological neoplasia treated

with chemotherapy; treatment with any myelosuppressant

medications; blood transfusion dependency; a history of

pure red cell aplasia; a bleeding episode in 30 days prior

to enrolment; orthopaedic surgery in 30 days prior to

enrolment; medical condition(s) that in the view of the

investigator prohibit(s) participation in the study; or

wilfully negligent non-adherence to their haemodialysis,

medication, nutrition, or other recommended treatment

regimens.

Setting

This study will be conducted in haemodialysis centres

throughout Europe. While patients are the main study

population, the multi-level design of the study also requires

a minimum number of physician-investigators. At least

1,000 patients (allowing for a 25% attrition rate) are to be

recruited by a minimum of 75 centres to achieve the

statistical power needed to meet the study objectives. To

enable the greatest possible diversity in physician-investi-

gators so as to better reflect the heterogeneity of providers,

physician criteria are limited to any person licensed to

practise medicine in his/her country of origin and practic-

ing, at least part-time, in a haemodialysis centre.

Data collection and management

Figure 3 summarizes the main procedures of the MONI-

TOR-CKD5 study. Table 1 presents the study’s timetable

and the assessments to be performed at each time point.

Being an observational study, all data will be recorded as

available. There are no mandatory treatment regimens,

assessments, and tests. Investigators enter data from source

documents into the electronic CRF (See Fig. 4 for an eCRF

screen shot). Centralized monitoring will be performed by

a contract research organization, which will also assure

query management. With the centres’ knowledge, a ran-

dom selection of 10% of patients will be identified for

complete on-site monitoring. Data will be transmitted by

the eCRF vendor to Matrix45 for assessment of data

integrity, statistical analysis, and dissemination.

Fig. 2 continued

394 Intern Emerg Med (2013) 8:389–399

123

Sample size calculations

Because of the diversity of this study’s objectives and the

associated diversity in statistical analyses, sample size

calculations were performed, as appropriate, for each of the

primary and secondary objectives. All calculations

assumed a desired power level of 0.80, alpha at 0.05 and

two-tailed tests to detect a small effect size.

These various calculations yielded divergent sample size

recommendations and the most conservative estimates

were taken as guidance. Required patient sample size

estimates ranged from 439 to 800. Taking the higher esti-

mates, a 25% margin for patient attrition was added, raising

the required sample size to a minimum of 1,000 patients to

be recruited from at least 75 centres. Each centre is asked

to enrol up to 15 patients.

Statistical analysis plan

For the descriptive (parts of certain) objectives, descriptive

statistics of frequency, central tendency, and dispersion

will be used under consideration of applicable levels of

measurement. Secondary correlational/associative analyses

may be performed if descriptive analyses suggest the

presence of associations among variables. In that case,

associative analyses will be performed under consideration

of the levels of measurement of the variables involved.

Differences in treatment by patient subgroups will be

evaluated using Fisher’s exact, v2, Student’s t, ANOVA,

Mann–Whitney U, or Kruskal–Wallis tests where

appropriate.

Hierarchical modelling will be used for Objective 3 to

determine if congruence of anaemia treatment with best

practice guidelines is associated with differences in Hb

outcomes. Likewise, it will be used to determine if con-

gruence of general treatment with the six modifiable risk

factors identified by Port et al. [15] is associated with

differences in Hb and safety outcomes (Objective 4). This

statistical method will also be applied to test the relation-

ship of patient- and physician/centre-level variables and

treatment response (Objective 7). A two-level model will

be used, consisting of two sub-models, one for each level.

Slope coefficients or odds ratios and 95% confidence

intervals will be calculated. Adjusted R2 or Nagelkerke

Fig. 3 Summary of study procedures

Intern Emerg Med (2013) 8:389–399 395

123

pseudo R2 also will be calculated where appropriate. The

intraclass correlation coefficient will be used to quantify

the variability in patient outcome attributable to within-

physician/centre variability before any patient-level deter-

minants are considered. This method will also be applied in

Cox proportional hazards modelling (calculating adjusted

hazards ratios and 95% confidence intervals) of safety

outcomes. In addition, in an exploratory fashion and data

permitting, time-dependent covariates will be assessed in

multivariate Cox proportional hazards models; evaluating

the multi-level determinants of the count of overnight

hospitalizations using hierarchical Poisson regression

modelling, calculating incident rate ratios and 95% confi-

dence intervals.

For Objective 5, a Nesselroade–Salthouse index of intra-

individual variation in Hb (‘‘Intra-Hb’’) levels will be

calculated. One-way (within-subjects) and factorial

(within-subjects and between-subjects) repeated measures

analysis of variance using the Geisser–Greenhouse

corrected F test will be used. In addition, though in an

exploratory fashion and data permitting, a time series

analysis under various scenarios of autoregressive lag will

be attempted to explore the presence of trend effects in the

data. Multiple classifications of Hb levels and variability

will be performed using descriptive statistics to be included

in predictive modelling and non-responder analyses.

Proportions, median follow-up duration, median event-

free survival times, and events per patient year will be used

to describe the safety endpoints of overnight hospitaliza-

tion, thrombo-embolic/vascular events and all-cause

mortality over the entire study period (Objective 6). The

distribution of events and event-free survival will be

described for the entire sample using Kaplan–Meier esti-

mator modelling. Mantel-Cox log-rank tests (weighing all

time points equally) or generalized Wilcoxon/Breslow tests

(weighing time points relative to the number of cases at

risk at each time point) will be used to evaluate bivariate

differences in survival distribution between identified

Table 1 Timetable and assessment schedule of the MONITOR-CKD5 Study

Visit 1 2 through up to 23 Up to 24

Month 1 2 through 23 Up to 24

Inclusion/exclusion criteria X

Informed consent/patient permission X

Demographic data X

Medical history X

Aetiology of chronic renal failure X

Haemodialysis history X

Renal anaemia history, incl. Hb values in 3 months prior to enrolment X

Prior treatments for renal anaemia, incl. data for 3 months prior to enrolment

(incl. blood transfusions, iron supplementation, ESAs)

X

Target Hb for HX575 treatment X X X

HX575 dose and frequency X X X

Comorbidities X X X

Iron supplementation X X X

Vitamin supplementation X X X

Relevant concomitant medications X X X

Height X

Dry body weight X X X

Interdialytic weight gain X X X

Blood pressure X X X

Biological parameters (Hb, iron parameters, serum albumin, C-reactive protein,

serum aluminium, phosphate and calcium)

X X X

Haemodialysis parameters (dialysis dose [Kt/V], hours of dialysis/week, blood

flow rate, membranes, vascular access)

X X X

Clinical events (infection, bleeding, thrombo-embolism, cardiovascular, surgery,

arteriovenous fistula thrombosis, neoplasia onset, renal transplantation, transfer

to peritoneal dialysis, blood transfusions, transfer to other haemodialysis centre, death)

X X X

Adherence assessment X X X

Physician’s questionnaire (demographics, knowledge of anaemia and general CKD guidelines) X

Centre characteristics, anaemia protocols, adoption of anaemia guidelines X

396 Intern Emerg Med (2013) 8:389–399

123

subgroups. Cox proportional hazards modelling will be

used to analyse the multivariate effects of identified risk

factors and other determinants on survival under the pro-

portional hazards assumption. Adjusted hazards ratios

(HRs) and 95% confidence intervals will be calculated to

test the direction and strength of the influence of individual

factors on event-risk and event-free survival. Omnibus tests

of model coefficients, -2 log likelihood and Nagelkerke

pseudo R2 will be calculated to determine variable block

and overall model fit and significance.

For Objective 8, we will apply sequentially a series

of increasingly more complex procedures: aggregation

techniques (‘‘classification and clustering methods’’),

differentiation techniques (‘‘tree-based models’’), and

associative and pattern recognition techniques (e.g.,

‘‘neural networks’’). Aggregation procedures will be done

on the sample as a whole. However, if we need to migrate

to differentiation and associative/pattern recognition pro-

cedures, we will randomly divide the sample into a training

set (for model development) and a testing set (for model

validation).

Lastly, Objective 9 through 12 will be analysed using

multiple logistic regression, Kaplan–Meier estimation, and

Cox proportional hazards modelling.

In addition to the end-of-study analyses, interim analy-

ses are planned after patients enrolled in the first 3 months

of the enrolment period and all patients enrolled by month

36 have completed 12 months of follow-up (resp. months

15 and 48); and after 12 (resp. months 27 and 64) and 24

(resp. months 39 and 76) months later for each subgroup;

using a Pocock-adjusted level of statistical significance [31,

32].

Ethical considerations

Ethics Committee approvals for this study have been

sought in accordance with the laws and regulations appli-

cable to observational studies in each of the participating

countries. No centre will be allowed to begin eligibility

screening until the necessary approvals have been obtained.

Withdrawal from study

Subjects may withdraw from the study at any time and for

whatever reason as explained in the informed consent

materials.

Discussion

The ESAM and especially the DOPPS studies have contrib-

uted significantly to the understanding of practice patterns and

outcomes of anaemia management in haemodialysis patients.

While identifying practices, outcomes, and key determinants,

Fig. 4 Example of a webpage for electronic data collection

Intern Emerg Med (2013) 8:389–399 397

123

several dimensions of effectiveness remain unaddressed.

Using a comprehensive, integrated framework, addressing the

need for effectiveness studies on biosimilar epoetin alfa, and

examining the relationship between guideline-, label- and

other evidence-congruent practice, the MONITOR-CKD5

intends to study the core issues addressed by ESAM and

DOPPS, but also to take knowledge discovery a step further by

examining the impact of evidence-based practice on clinical

outcomes—differentiating, in the process, between physician-

level and patient-level determinants. Further, the MONITOR-

CKD5 is the first pharmacoepidemiological study on anaemia

management in haemodialysis since there is a change in ESA

label and the target Hb level restriction to the 10–12 g/dL

range.

The MONITOR-CKD5 study is an international, pro-

spective, observational, pharmacoepidemiological study to

evaluate the multi-level factors and outcomes associated with

the use of HX575 in the treatment of renal anaemia in hae-

modialysis patients across varying cohorts of patients. It aims

to examine determinants of response at both the patient and the

physician level; integrates an advocated [20] statistical

methodology hereto used mainly in the social and behavioural

sciences; assesses factors potentially predictive of poor

treatment response; evaluates the extent to which treatment is

congruent with evidence-based guidelines and the revised

ESA label; while also relying on the experiences gained in

such observational studies as ESAM and DOPPS.

Acknowledgments The study is sponsored by research grants from

Sandoz Biopharmaceuticals, a Novartis company, Holzkirchen,

Germany. The authors thank Liam Smith for editorial, proofreading,

and administrative assistance. Data will be analysed independently

from the Sponsor, although the Sponsor will have the right of review

and comment.

Conflict of interest L. Gesualdo, G. London, D. Goldsmith, A.

Covic, P. Zaoui, C. Combe, J. Mann, and F. Dellanna serve as con-

sulting investigators to the MONITOR-CKD5 study. M. Turner and

M. Muenzberg are employees of Sandoz Biopharmaceuticals. C. Lee,

K. MacDonald, and I. Abraham are employees of Matrix45. By

company policy, they are prohibited from owning equity in client

organizations (except through mutual funds or other independently

administered collective investment instruments) or contracting inde-

pendently with client organizations. Matrix45 provides similar

services for other biopharmaceutical companies.

References

1. McClellan WM, Jurkovitz C, Abramson J (2005) The epidemi-

ology and control of anemia among pre-ESRD patients with

chronic kidney disease. Eur J Clin Invest 35(Suppl 3):58–65

2. Eckardt KU (2000) Pathophysiology of renal anemia. Clin

Nephrol 53(Suppl):S2–S8

3. (2002) K/DOQI clinical practice guidelines for chronic kidney

disease: evaluation, classification, and stratification. Am J Kidney

Dis 39 (Suppl 1):S1–266

4. Astor BC, Muntner P, Levin A, Eustace JA, Coresh J (2002)

Association of kidney function with anemia: the Third National

Health and Nutrition Examination Survey (1988–1994). Arch

Intern Med 162:1401–1408

5. Locatelli F, Pisoni RL, Combe C et al (2004) Anemia in

hemodialysis patients of five European countries: association

with morbidity and mortality in the Dialysis Outcomes and

Practice Patterns Study (DOPPS). Nephrol Dial Transplant

19:121–132

6. Rao M, Pereira BJ (2005) Optimal anemia management reduces

cardiovascular morbidity, mortality, and costs in chronic kidney

disease. Kidney Int 68:1432–1438

7. (2007) K/DOQI Clinical Practice Guideline and Clinical Practice

Recommendations for anemia in chronic kidney disease: 2007

update of haemoglobin target. Am J Kidney Dis 50:471–530

8. Locatelli F, Aljama P, Barany P et al (2004) Revised European

best practice guidelines for the management of anemia in patients

with chronic renal failure. Nephrol Dial Transplant 19(Suppl 2):

ii1–ii47

9. Locatelli F, Covic A, Eckardt KU, Wiecek A, Vanholder R

(2009) Anemia management in patients with chronic kidney

disease: a position statement by the Anemia Working Group of

European Renal Best Practice (ERBP). Nephrol Dial Transplant

24:348–354

10. Jacobs C, Horl WH, Macdougall IC et al (2000) European Best

Practice Guidelines 5: target haemoglobin. Nephrol Dial Trans-

plant 15(Suppl 4):15–19

11. Jacobs C, Frei D, Perkins AC (2005) Results of the European

Survey on Anemia Management 2003 (ESAM 2003): current

status of anemia management in dialysis patients, factors

affecting epoetin dosage and changes in anemia management

over the last 5 years. Nephrol Dial Transplant 20(Suppl 3):

iii3–iii24

12. Pisoni RL, Bragg-Gresham JL, Young EW et al (2004) Anemia

management and outcomes from 12 countries in the Dialysis

Outcomes and Practice Patterns Study (DOPPS). Am J Kidney

Dis 44:94–111

13. Horl WH, Vanrenterghem Y, Canaud B et al (2005) Optimal

treatment of renal anemia (OPTA): improving the efficacy and

efficiency of renal anemia therapy in hemodialysis patients

receiving intravenous epoetin. Nephrol Dial Transplant 20(Suppl

3):iii25–iii32

14. Port FK, Pisoni RL, Bommer J et al (2006) Improving outcomes

for dialysis patients in the international Dialysis Outcomes and

Practice Patterns Study. Clin J Am Soc Nephrol 1:246–255

15. Port FK, Pisoni RL, Bragg-Gresham JL et al (2004)

DOPPS estimates of patient life years attributable to modifiable

hemodialysis practices in the United States. Blood Purif

22:175–180

16. Gilbertson DT, Ebben JP, Foley RN, Weinhandl ED, Bradbury

BD, Collins AJ (2008) Hemoglobin level variability: associations

with mortality. Clin J Am Soc Nephrol 3:133–138

17. Kimata N, Akiba T, Pisoni RL et al (2005) Mineral metabolism

and hemoglobin concentration among hemodialysis patients in

the Dialysis Outcomes and Practice Patterns Study (DOPPS).

Nephrol Dial Transplant 20:927–935

18. Rayner HC, Pisoni RL, Bommer J et al (2004) Mortality and

hospitalization in hemodialysis patients in five European coun-

tries: results from the Dialysis Outcomes and Practice Patterns

Study (DOPPS). Nephrol Dial Transplant 19:108–120

19. Volkova N, Arab L (2006) Evidence-based systematic literature

review of hemoglobin/hematocrit and all-cause mortality in

dialysis patients. Am J Kidney Dis 47:24–36

20. Holden JE, Kelley K, Agarwal R (2008) Analyzing change: a

primer on multilevel models with applications to nephrology. Am

J Nephrol 28:792–801

398 Intern Emerg Med (2013) 8:389–399

123

21. Strippoli GF, Navaneethan SD, Craig JC (2006) Hemoglobin and

hematocrit targets for the anemia of chronic kidney disease.

Cochrane Database Syst Rev 4:CD003967

22. Locatelli F, Nissenson AR, Barrett BJ et al (2008) Clinical

practice guidelines for anemia in chronic kidney disease: prob-

lems and solutions. A position statement from kidney disease:

improving global outcomes (KDIGO). Kidney Int 74:1237–1240

23. Pfeffer M, Burdmann EA, Cooper DE et al (2009) A trial of

darbepoetin-alfa in type 2 diabetes and chronic kidney disease.

N Engl J Med 361:1–14

24. Singh AK (2009) Does TREAT give the boot to ESAs in the

treatment of CKD anemia. J Am Soc Nephrol 21:2–6

25. Goldsmith D, Covic A (2010) Time to reconsider evidence for

anaemia treatment (TREAT) = essential safety arguments

(ESA). Nephrol Dial Transplant 25:1734–1737

26. Timmermans S, Mauck A (2005) The promises and pitfalls of

evidence-based medicine. Health Aff 24:18–28

27. Sorgel F, Thyroff-Friesinger U, Vetter A et al (2009) Bioequiv-

alence of HX575 (IV) (recombinant human epoetin alfa) and a

comparator epoetin alfa after multiple subcutaneous administra-

tions: an open-label randomised controlled trial. BMC Clin

Pharmacol 9:10

28. Sorgel F, Thyroff-Friesinger U, Vetter A et al (2009) Bioequiv-

alence of HX575 (human recombinant epoetin alfa) and epoetin

beta after multiple subcutaneous administration. Int J Clin Phar-

macol Ther 6:391–401

29. Brockmeyer C, Seidl A (2009) Binocrit: assessment of quality,

safety, and efficacy of biopharmaceuticals. Eur J Hosp Pharm

Pract 15:34–40

30. Haag-Weber M, Vetter A, Thyroff-Friesinger U et al (2009)

Therapeutic equivalence, long-term efficacy and safety of HX575

in the treatment of anemia in chronic renal failure patients

receiving hemodialysis. Clin Nephrol 72:380–390

31. Geller NL, Pocock SJ (1987) Interim analyses in randomized

clinical trials: ramifications and guidelines for practitioners.

Biometrics 43:213–223

32. Schulz KF, Grimes DA (2005) Multiplicity in randomised trials

II: subgroup and interim analyses. Lancet 365:1657–1661

Intern Emerg Med (2013) 8:389–399 399

123

Date post:	15-Dec-2016
Category:	Documents
Upload:	matthew-turner
View:	212 times
Download:	0 times

A pharmacoepidemiological study of the multi-level determinants, predictors, and clinical outcomes...

Documents