臨試驗與€‹Œ–醫療研究Clinical Trials and Personalized...

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臨床試驗與個人化醫療研究 Clinical Trials and

Personalized Medicine Research

陳 珍 信

中央研究院統計科學研究所

台灣大學公共衛生學院流行病學與預防醫學研究所

2015.9.9

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Historical Development of Clinical Trials • The 1st controlled trial in history (James Lind, 1747)

– Treatment of scurvy (壞血病): Lemons and oranges were the most effective treatment out of six alternatives.

• The 1st randomized controlled trial (RCT) in history (pharmacists of Nuremberg, Germany, 1835) – Experiment to tell whether a homeopathic “remedy”

(ordinary salt in a homeopathic C30-dilution of distilled snow water) could be distinguished from a placebo (distilled snow water)

• The first modern RCT in medicine (Austin Bradford Hill, 1948) – The newly discovered antibiotic streptomycin (鏈黴素)

was effective against pulmonary tuberculosis (肺結核病 ).

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Sir Austin Bradford Hill (1897-1991)

The Pioneer of Randomized Control Trials presented fundamental concepts in the early 1950’s: ★ Concurrent controls ★ Random allocation ★ Definition of eligible patients ★ Definition of treatment schedule ★ Objective evaluation ★ Statistical analysis

Streptomycin in Treatment of Pulmonary Tuberculosis (MRC, 1948, British Med. J.) ★ The first properly randomized controlled trial ? Why to randomize??

Doll, R. & Hill, A. B. (1950). Smoking and Carcinoma of the Lung, British Med. J.

Clinical Trials

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Contributions to the Ascendance of RCTs • One of the discoverers, Selman A. Waksman, of

streptomycin won the Nobel Prize in 1952. • Tuberculosis, one of the greatest scourges of the

19th and early 20th centuries, suddenly became a manageable disease.

• RCTs came into great demand, as the success of “wonder drugs” (特效藥) like penicillin and vancomycin made the development of new pharmaceuticals into a highly lucrative business.

• The Food, Drug, and Cosmetic Act, passed in 1938, required drug manufacturers to provide evidence of safety to the Food and Drug Administration (FDA).

• The RCT was one of the greatest inventions in medical history.

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Contemporary Clinical Trials is an international peer reviewed journal that publishes manuscripts pertaining to all aspects of clinical trials, including, but not limited to, design, conduct, analysis, regulation and ethics. Manuscripts submitted should appeal to a readership drawn from disciplines including medicine, biostatistics, epidemiology, computer science, management science, behavioural science, pharmaceutical science, and bioethics.

Contemporary Clinical Trials (2005 - ) (formerly, Controlled Clinical Trials, 1995-2004)

Clinical Trials: Interdisciplinary Research

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Clinical Trials (2004 - ) Journal of the Society for Clinical Trials

Applied Clinical Trials (1992 - ) Peer-Reviewed Guide To Global Clinical Trials Management

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CONSORT (Consolidated Standards of Reporting Trials)

http://www.consort-statement.org/

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Clinical Study

• A clinical study involves research using human volunteers (also called participants) that is intended to add to medical knowledge.

• There are two main types of clinical studies: – clinical trials (also called interventional studies),

and – observational studies. (Source: ClinicalTrials.gov )

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5 Phases of the Clinical Trial Defined by FDA • Phase 0: Exploratory study involving very limited human exposure to the drug,

with no therapeutic or diagnostic goals (for example, screening studies, microdose studies)

• Phase 1: Studies that are usually conducted with healthy volunteers and that emphasize safety. The goal is to find out what the drug's most frequent and serious adverse events are and, often, how the drug is metabolized and excreted.

• Phase 2: Studies that gather preliminary data on effectiveness (whether the drug works in people who have a certain disease or condition). For example, participants receiving the drug may be compared with similar participants receiving a different treatment, usually an inactive substance (called a placebo) or a different drug. Safety continues to be evaluated, and short-term adverse events are studied.

• Phase 3: Studies that gather more information about safety and effectiveness by studying different populations and different dosages and by using the drug in combination with other drugs.

• Phase 4: Studies occurring after FDA has approved a drug for marketing. These including postmarket requirement and commitment studies that are required of or agreed to by the sponsor. These studies gather additional information about a drug's safety, efficacy, or optimal use.

10 (Source: ClinicalTrials.gov)

Topic Headings of a Typical Study Protocol

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Friedman, Furberg & DeMets (2010) Fundamentals of Clinical Trials, 4th Ed.

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Multi-Site Trial Multi-Nation Trial

Study Sponsors: Industry or Government

• Manufacturer-Sponsored Trials (Manufacturer-Initiated Trials)

– Guidelines for Researchers Involved in Manufacturer-Sponsored Trials (American Academy of Emergency Medicine)

– http://www.aaem.org/em-resources/position-statements/education-and-research/researcher-guidelines

• Investigator-Initiated Trials (Investigator-Sponsored Trials)

– Guidelines for Investigator Initiated Multi-Site Clinical Trials (NIH, USA) – http://grants.nih.gov/grants/guide/pa-files/PAR-10-096.html

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Published in 2014

seven case studies of past “success stories” in statistics

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Statistical Design

• Randomization – Bias reduction

• Stratification – Efficiency improvement

• Sample Size Determination – Error rates control

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The Role of Randomization • In the Idealized Scientific Investigation

– All experimental units are alike – The treatment is exactly reproducible from occasion to

occasion • In Clinical Studies

– Patients cannot be exactly alike – Treatment cannot be exactly reproduced on every

occasion • The use of a chance mechanism to assign the

patients to treatments by giving each patient the same opportunity of receiving any of the treatments under study.

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Advantages of Randomization • It protects against conscious bias, e.g. physician

/patient selection bias. • It protects against unconscious bias, e.g. unknown

prognostic factors. • It makes treatment groups “alike on the average” with

respect to prognostic factors, non-treatment-related-factors affecting the “drop-out” rate and the censoring mechanism.

• It establishes the validity of most of the statistical methods for data analysis.

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Patients’ Imbalance Using Simple Randomization

• Pr(Difference in Tx #s or more extreme) > 0.05 Total # of Patients Difference in Tx #s

10 2:8 20 6:14 50 18:32 100 40:60 200 86:114 500 228:272 1000 469:531

Stratified Analysis

Hu, et al. (1993). A Randomized Controlled Trial on the Treatment for Acute Partial Ischemic Stroke with Acupuncture. Neuroepidemiology, 12, 106-113.

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Berkson’s Fallacy • Taller school kids tend to get higher scores on math.

(Confounded by age) • Think about “conditional Probability”! • Handsome guys tend to be not nice.

Nice

Mean

Ugly Handsome

No way

Acceptable

https://en.wikipedia.org/wiki/Berkson%27s_paradox

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Stratification • Confounding of treatment and risk factors

– A false-positive conclusion is arrived if there are large imbalances in the treatment assignment over some prognostic factors.

– The observed treatment difference is simply a measure of the heterogeneity between the treatment groups.

• Interaction of treatment and risk factors – Real differences between treatments can be

observed if there exist interactions of treatment and risk factors.

Confounding of treatment and risk factors

Response No Response Total A 37 ( 74% ) 13 50 B 13 ( 26% ) 37 50

Table 1. Response by Treatment

Table 2. Response by Treatment (i) Biomarker X present Response No Response Total

A 36 ( 90 % ) 4 40B 9 ( 90 % ) 1 10

Table 2. Response by Treatment (ii) Biomarker X absent Response No Response Total A 1 ( 10 % ) 9 10 B 4 ( 10 % ) 36 40

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Interaction of treatment and risk factors

Response No Response Total C 30 ( 60% ) 20 50 D 30 ( 60% ) 20 50

Table 3. Response by Treatment

Table 4. Response by Treatment (i) Biomarker X present Response No Response Total C 27 ( 90 % ) 3 30 D 18 ( 60 % ) 12 30

Response No Response Total

C 3 ( 15 % ) 17 20 D 12 ( 60 % ) 8 20

Table 4. Response by Treatment (ii) Biomarker X absent

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The treatment difference between sildenafil and placebo was assumed to be 0.75 and the common variance was assumed to be 2.3. Using these assumptions, a sample size of 86 patients per treatment group would be required to achieve a power of 90% at the significance level of 0.05.

Sildenafil for Treatment of Erectile Dysfunction in Men With Diabetes: A Randomized Controlled Trial, by M.S. Rendell et al. (1999, JAMA)

Sample Size Determination

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Sample Size Determination

The sample sizein each group

The power to detectP(T) = 0.7 vs. P(C) = 0.4

15 0.4052 0.9098 0.99

To test the null hypothesis H: P(T) = P(C) vs. the alternative hypothesis A: P(T) > P(C) at significance level 0.05

Statistical Exercise

1. To compare the response proportions in a two-arm clinical trial, equal randomization of the same sample sizes for both arms has been conventionally used in the trial design. Can you think of any statistical rationale behind this design consideration?

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Survival data (Survival endpoint) CLINICAL TRIALS MEDICAL FOLLOW-UP STUDIES

Censoring: Incomplete Observations

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Can survival data be analyzed in this way? Prologue Review: Incorrect Analysis of UGDP Mortality Data a. Mortality rates of cardiovascular causes

in the clinics using TOLB:

Group No. of

Subjects % Dead

Tolbutamide 204 12.7% Placebo 205 4.9%

b. UGDP analysis used chi-square test based on the 2 × 2 table

Death Other Tolbutamide 26 178 204 Placebo 10 195 205 36 373 409

and obtained a 2-sided P-value = 0.008.

c. Improper definition of the endpoint for variable length of follow-up entailed criticisms.

University Group Diabetes Program (UGDP). 1970. Diabetes 19 (Suppl 2):747-830. Schwartz, TB and Meinert, CL. 2004. The UGDP Controversy: thirty-four years of contentious ambiguity laid to rest. Perspectives in Biology and Medicine 47:564-574.

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Medical Follow-Up and Censored Data

• Important Features – Staggered Entry:

Patients enter the study at different times over the recruitment period.

– Censored Data: Patient observations may be incomplete during the follow-up.

• Possible Causes of (Right) Censoring – Loss to follow-up – Withdrawal from the

study – Termination of the

study – Death from competing

risks

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Month Alive at Beginning Died Censored (1) (2) (3)

[0, 9) 5 0 0 [9, 15) 5 1 1 [15, 26) 3 1 1 [26, ∞) 1 1 0

Proportion Dying

Proportion Surviving

Cumulative Proportion Surviving

(4) = (2) / (1) (5) = 1. - (4) 0. 1. 1.

0.20 0.80 0.80 0.33 0.67 0.54

1. 0. 0.

∏=

j

ii

1

)5(

Example : 9 13+ 15 20+ 26

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The Kaplan-Meier (1958) Estimator

A Properties of Kaplan-Meier Estimator

( )

ˆ( ) (1 )i

i

Y t i

dS tn≤

= −∏

Redistribution-to-the-Right Algorithm

Reference : Efron (1967, Proc. 5th Berkeley Symp., IV)

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Survival Analysis: Cited Reference Index (Google as of 2015-09-09)

• Kaplan, E.L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53: 457-481. – Citing Articles: 45802

• Cox, D.R. (1972). Regression Models and Life-tables

(with Discussion). Journal of the Royal Statistical Society Series B 34: 187-220. – Citing Articles: 39608

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Time to an Event

• Event of Death Survival Time • Event of Relapse Remission Duration • Event of a Disease/Disorder Age of Onset

Survival Time Analysis Event History Analysis

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Cure or Non-susceptibility • Implicit assumption in survival analysis: All the study subjects are eventually susceptible to the event. • In clinical trials: - Long-term disease-free survival - Cured-fraction In epidemiological studies: - Non-susceptibility > may not carry disease genes > may have not been exposed to detrimental environments

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Cure: Consecutive Real Examples

Some Issues • The RCT was one of the greatest inventions in

medical history. • If there is any problem with the RCT, it has

been too successful, to the point of becoming a straitjacket.

• “The only problem was that people didn’t want to tinker with it.” (Don Berry of MD Anderson Cancer Center)

• “Collective Ethics” versus “Individual Ethics”

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New Challenges to Traditional RCTs

1. The AIDS epidemic of the 1980s RCTs came under fire for being too slow and too

insensitive to patients’ needs. Led to certain reforms such as easier access to

experimental drugs and the use of “surrogate endpoints” (such as improved T-cell counts) as evidence of effectiveness.

Innovations: • These surrogates themselves had to be investigated statistically. • Interim analysis was used while the study is still in progress. • Early termination of studies in which the treatment has either an

extremely positive or an extremely negative effect.

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New Challenges to Traditional RCTs

2. Personalized medicine Cancer is not one disease, but has many subtypes,

each potentially requiring a different treatment. Genomics enables doctors to distinguish different

types of patients, as well. New approaches:

• Adaptive designs enable researchers to zero in on effective treatments for smaller populations.

• SMART design (SMART stands for Sequential Multiple Assignment Randomized Trial.)

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Personalized Medicine • It’s far more important to

know what person the disease has than what disease the person has.

– Hippocrates

• Several terms, including – “precision medicine,” – “stratified medicine,” – “targeted medicine,” and – “pharmacogenomics,”

are sometimes used interchangeably with “personalized medicine.”

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Defining Personalized Medicine • “Precision medicine” is perhaps most

synonymous to “personalized medicine” and has been defined by the National Academy of Sciences as “the use of genomic, epigenomic, exposure and other data to define individual patterns of disease, potentially leading to better individual treatment.”

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Describing Personalized Medicine (1/2) • “The use of new methods of molecular

analysis to better manage a patient’s disease or predisposition to disease.”

– Personalized Medicine Coalition

• “Providing the right treatment to the right patient, at the right dose at the right time.”

– European Union

• “The tailoring of medical treatment to the individual characteristics of each patient.”

– President’s Council of Advisors on Science and Technology

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Describing Personalized Medicine (2/2)

• “Health care that is informed by each person’s unique clinical, genetic, and environmental information.”

– American Medical Association

• “A form of medicine that uses information about a person’s genes, proteins, and environment to prevent, diagnose, and treat disease.”

– National Cancer Institute, NIH

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The trial-and-error or one-dose-fits-all approach versus personalized medicine

43 (Source: Xie & Frueh, 2005, Personalized Medicine)

Percentage of patients for whom drugs are ineffective

44 (Source: Spear, Heath-Chiozzi & Huff, 2001,TRENDS in Molecular Medicine)

• Knowledge about associations between genomic factors and disease has rapidly accumulated. (Source: Raskin, A. Casdin, E. 2011. The Dawn of Molecular Medicine: The Transformation of Medicine and Its Consequences for Investors. New York, NY: Alliance Bernstein.)

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Pharmacogenomic biomarker information contained in labeling of more than 100 approved drugs

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Reference Books: Predictive Medicine

New approaches 1. Adaptive designs Unlike traditional RCT, the experimenters are

allowed to see data while the experiment is in progress.

Experimental conduct can change as the trial progresses, which are determined by a well-documented protocol. • Stopping a trial if a treatment proves to be extremely

successful or unsuccessful. • The probability of new patients being enrolled can be

increased if a treatment is seen to be more successful. • The decisions can be made by a computer program with

instructions on how to modify the trial.

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New approaches 2. SMART design A solution to the dynamic treatment allocation. In

some chronic illnesses or behavioral disorders, a clinical intervention takes place over a longer period and involve several steps.

More than one decision point and several options at each. At each decision point, the patients are re-randomized.

Treatment options may be restricted depending on intermediate outcome.

Have been conducted or are in progress for treatments of autism, ADHD, drug and alcohol abuse, and depression

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Molecularly Targeted Clinical Trial

• Example: FDA approved Herceptin for treating metastatic HER2 positive breast cancer

• About one quarter of patients with breast cancer is HER2-positive (Her2= human epidermal growth factor receptpr2). HER2-positive breast cancers tend to be more aggressive than HER2-negative breast cancers.

• Herceptin is called a targeted immune therapy because it targets breast cancers that make too much of the HER2/neu gene or HER2 protein.

http://www.herceptin.com/index.jsp

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Targeted Clinical Trials: Herceptin • Both in vitro and in vivo, Herceptin was tested against

breast cancer cells with over-expressed HER2. • As a monotherapy, Herceptin was found to inhibit the

tumor growth. • When used in combination with other chemoagents, such

as paclitaxel, it provided additive effects. • Phase I studies demonstrated that the safety profile of

Herceptin was tolerable. • Phase II trials showed that the objective response of

Herceptinwas about 15% in the patients with metastatic breast cancer, after failure of the previous chemotherapy.

• Several large-scale randomized phase III trials were conducted in patients with metastatic breast cancer with over-expressed HER2 protein to confirm the effectiveness and safety of Herceptin (Slamon et al., 2001).

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Herceptin Trial with Control = paclitaxel after doxorubicin and cyclophosphamide (NSABP B-31 & NCCTG N9831)

(Romond, et al., 2005, NEJM) The medianfollow-up was 2.0 years.

4-Year Follow-Up of Trastuzumab Plus Adjuvant Chemotherapy for Operable HER2-Positive Breast Cancer: Joint Analysis of Data From NCCTG N9831 & NSABP B-31

The median follow-up was 3.9 years.

(Perez, et al., 2011, J Clin Oncol)

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Improved Survival with Vemurafenib in Melanoma with BRAF Mutation (Chapman et al., 2011, NEJM)

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Adaptive Design • As indicated in the Critical Path Opportunities

Report, biomarker development and streamlining clinical trials are the two most important areas for improving medical product development.

• The streamlining clinical trials call for advancing innovative trial designs such as adaptive designs to improve innovation in clinical development.

• An adaptive design is a clinical study design that uses accumulating data to decide on how to modify aspects of the study as it continues, without undermining the validity and integrity of the trial.

Types of Adaptation in Clinical Trials • The designs encompass selection of various patient groups or dosing

regimens of drugs based on some marker(s) or clinical endpoint(s). • An adaptive design allows modifications of various features such as

sample size and treatment assignments in a clinical study based on the analysis of interim data.

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Chow & Chang (2012) Adaptive Design Methods in Clinical Trials.

Some Issues in Adaptive Designs • Different prevalence and allele frequencies of

biomarkers • Various response rate corresponding to each

combination of biomarkers • Subgroup analysis related to the stopping of a

trial on the decision of interim analyses. • Re-estimation of the sample size after the

planned interim analyses. • Number of looks at the data sufficient for interim

analyses

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I-SPY 2: the 1st Large-Scale Adaptive Trial (1/3)

60 (Berry, DA, 2012, Nature Reviews – Clinical Oncology)

Some subtypes have very low prevalence and so are of limited marketing interest for sponsors.

I-SPY 2: the 1st Large-Scale Adaptive Trial (2/3)

• In the I-SPY 2, Don Berry and Laura Esserman simultaneously studied the effectiveness of 5 breast cancer drugs made by different sponsoring manufacturers on 10 subpopulations of cancer patients.

• Three experimental drugs remained in the trial before 2011.

61 (Berry, DA, 2012, Nature Reviews – Clinical Oncology)

I-SPY 2: the 1st Large-Scale Adaptive Trial (3/3)

• In the Phase II setting of neoadjuvant chemotherapy, the primary end point is pathologic complete response (pCR) at the time of surgery, which occurs about 5 months after the initiation of chemotherapy.

• By the end of 2013, they had identified two drugs with a high probability of success in a Phase III study.

• Veliparib was effective against triple-negative breast cancer; the other, called Neratinib, showed promise against HER2-positive, estrogen-negative, and progesterone-negative cancers. 62

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Repeated Use of Significance Tests Risk of False Positive

Number of repeated tests at the 5% level

Overall significance level for comparing 2 treatments

1 0.05 2 0.08 3 0.11 4 0.13 5 0.14 10 0.19 20 0.25 50 0.32 100 0.37 1000 0.53 ∞ 1.0

Data Monitoring Committees • The DMC takes periodic interim looks at the accumulating data. • The DMC should have membership

• with independent and multidisciplinary representation, • limited to individual free of apparent significant conflicts of interest.

• The purpose of DMCs is to protect • the safety of trial participants

unacceptable toxicity levels to adjust or abandon treatment • the credibility of the study

unacceptably slow accrual rate high ineligibility rate protocol violations unexpectedly high dropout rate to clarify or change the study protocol

• the validity of the study results • Recommendations for trial termination will be made due to

• favorable benefit-to-risk assessment • unfavorable benefit-to-risk assessment • inability to answer trial questions

• The practice of interim reviews motivated the development of some useful statistical procedures, including group sequential methods and conditional power, in the late 1970’s and 1980’s.

Ellenberg, Fleming & DeMets (2003, Wiley)

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Boundaries in Group Sequential Design with the Alpha-Spending Function

(Lan & DeMets, 1983, Biometrika)

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1.96 (fixed-sample test boundary)

[ ] Date

# deaths 56 77 126 177 247 318

Group Sequential Testing in Beta-Blocker Heart Attack Trial (DeMets, et al. 1984, Controlled Clinical Trials)

In the 6 meetings of Policy and Data Monitoring Board (PDMB), the observed number of deaths were (56, 77, 126, 177, 247, 318). The trial was terminated on recommendation of the PDMB 9 months before the scheduled closing date. The propranolol group, at the time of the decision (the 6th meeting), had a 26% lower mortality (z=2.82).

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(fixed-sample test boundary)

Molecularly Targeted Therapies • In 1998 Trastuzumab (trade name: Herceptin)

was approved for patients with metastatic breast cancer whose tumors over-express the HER2 protein.

• On 2011/08/17 Vemurafenib (trade name: Zelboraf) and a companion diagnostic test were approved for patients with BRAF mutation-positive metastatic melanoma.

• On 2011/08/26 crizotinib (trade name: Xalkori) and a companion diagnostic kit was approved for patients with non-small cell lung cancer (NSCLC) with the abnormal ALK gene. 67

Biomarkers (Biological measurements used to inform treatment selection)

• Prognostic Markers – Provide pretreatment information about long-

term outcome for patients who either are untreated or receive standard treatment.

– Often reflect a combination of intrinsic disease factors and sensitivity to standard therapy.

• Predictive Markers – Identify patients who are likely or unlikely be

benefit from a specific treatment. 68

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Drug-Diagnostic Co-Development (FDA, 2005, Concept Paper)

• How to prospectively co-develop a drug or biological therapy (drugs) and device test in a scientifically robust and efficient way.

• Co-development refers to products that raise development issues that affect both the drug therapy and the diagnostic test, regardless of their regulatory status as a combination product or as a noncombination product.

• Pharmacogenomics is defined here as the use of a pharmacogenomic or pharmacogenetic test (see glossary for definitions) to be used in conjunction with drug therapy.

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Measures of Diagnostic Test Efficacy

• Sensitivity • Specificity • Positive predicted value • Negative predicted value • Accuracy

: Negative test response: Positive test resp onse, RR −+

: iseased patient, : ormal subject D ND D −+

Pr ( | )R D+ +

Pr ( | )R D− −

Pr ( | )D R+ +

Pr ( | )D R− −

Pr ( ) Pr ( | ) Pr ( ) Pr ( | )D R D D R D+ + + − − −⋅ + ⋅

)(D Pr +=Prevalence

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Designs for Targeted Clinical Trials

Cosmatos and Chow (2009)

(Enrichment design)

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Two-dimensional hierarchical clustering of 203 lung tumors and normal lung samples was performed with 3,312 transcript sequences. Normal lung (NL) Pulmonary carcinoids (COID) Small-cell lung cancer (SCLC) Squamous cell lung carcinomas(SQ) Adenocarcinomas from the lung Adenocarcinomas as colon metastases

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Pathway Analysis : The IGF-1 Receptor & Longevity

To increase lifespan in a wide range of organisms is through the restriction of caloric intake. http://www.biocarta.com/pathfiles/m_longevityPathway.asp

您知道什麼是「大數據」?

• 打電話到速食店訂餐 「先生,請問您的手機號碼是?」 …..

「陳先生您好,您是住在xxx?家裡電話號碼是ooo?」 ???

「陳先生,因我們馬上連線到公司的客服系統,上面有您的資料。」 !!!

– 「我要一份招牌漢堡與大份薯條…..」

「請問您 是否要改吃我們的少油、少鹽的素食漢堡?再把薯條換成沙拉?因為根據您上週去健康檢查的紀錄顯示,血壓和膽固醇都偏高。」

~ 商業週刊第1438期(2015.6.4)康育萍撰「大數據的新生意經」

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「大數據」的新生意經

• 你心裡還想著「羊毛出在羊身上嗎?」如果是這樣,那你就落伍了! – 你一定要懂羊毛出在狗身上,由豬買單

• Google、臉書、阿里巴巴等大企業告訴你,「免費」才是最好的生意。

• 驅動這個改變的,正是大數據。 • 當能源、教育、醫療…..都變零元,你該如何把握機會從中淘金?

• 馬雲說:數據時代是去服務好別人,讓別人更爽。 ~ 商業週刊第1438期(2015.6.4)康育萍撰「大數據的新生意經」 ~

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生技月暖身 3大概念股聚焦 • 生技月重頭大戲生技展,7月下旬火熱登場,預期今年參觀人數

將首度突破10萬大關的人氣指數,加上今年論壇聚焦的精準醫療、疫苗、長照等話題,都將帶動生技月概念股出頭天

• 另外,最受矚目的是22日登場的「BioBusiness Asia Conference(BBA亞洲生技商機高峰論壇)」 ,今年聚焦「精準醫療」發展趨勢。

• 生物產業發展協會名譽理事李鍾熙表示,精準醫療目標在追求用更準確的診斷來配對更好藥物,找出最經濟有效的個人化醫療。但因為族群有不同基因型態,所以「精準醫療」是具有地區性特色和需求的產業,亦是台灣生技產業可發展的利基。

• 初步統計,目前國內已有不少廠商搶攻精準醫學商機,除了大江、行動基因和賽亞投入基因檢測外,世基是搭配癲癇藥物、創源鎖定新生兒篩檢,另外,康聯、合富、基亞等公司都投入診斷試劑的開發。

2015年07月12日 /工商時報─財經要聞

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2014//6/10: 生技股市值王─基亞(3176)所研發的肝癌新藥PI-88臨床試驗結果即將出爐, 基亞董事長張世忠昨天 表示,預期7月底、8月初公布期中分析 結果, 是成是敗屆時一翻兩瞪眼. 7/24: 基亞肝癌新藥「解盲」27日開牌!董事長張世忠今天表示, 過關把握超過 5成. 8/27: 據傳證期局正制訂「基亞條款 Part II」… 基亞從 23 元掛牌一直漲到最高 486 元,兩年多來漲幅超過 20 倍! 9/04: 股價自 7 /28 起連續 19 個交易日跳空跌停, 跌幅達 74 %, 市值蒸發 450 億元.

來源:台股觀測站 http://2330.tw/Stock_Chart.aspx?id=3176

7/28 收盤價 437.5

8/21 收盤價 113

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Precision Medicine

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Envisioning Health Care in 2030

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• Prof. Susan Murphy’s 2015 Wald Lecture I: Sequential Decision-Making and Personalized Treatment: The future is now! II: Offline Data Analysis Methods and Learning Algorithms for Constructing Mobile Treatment Policies III: Continual, Online Learning in Sequential Decision-Making

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• Professor Michael Kosorok’s Medallion Lecture: – Recent Developments in Machine Learning for

Personalized Medicine

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Target for Precision or Accuracy?

85

“All scientific work is incomplete - whether it be observational or experimental. All scientific work is liable to be upset or modified by advancing knowledge. That does not confer upon us a freedom to ignore the knowledge we already have, or to postpone the action that it appears to demand at a given time.”

Sir Austin Bradford Hill (1965)

Proceeding of the Royal Society of Medicine

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87

Life Course

Genetic Counseling

Prevention

Screening

Diagnosis

Treatment Mortality

88

徵 才

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