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1 Clinical Trials: Understanding Biostatistics Joseph Massaro Harvard Clinical Research Institute Boston University Department of Biostatistics

Understanding Biostatistics - Clinical Trials Data Management

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Page 1: Understanding Biostatistics -  Clinical Trials Data Management

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Clinical Trials: Understanding Biostatistics

Joseph Massaro

Harvard Clinical Research Institute

Boston University Department of Biostatistics

March 21, 2008

Page 2: Understanding Biostatistics -  Clinical Trials Data Management

Outline

• Clinical trial definition and types of trials

• Phases of pharmaceutical/biotech trials

• Medical device trials

• Major stat considerations for clinical trials

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Clinical Trial Definition

“…any form of planned experiment which involves patients and is designed to elucidate the most appropriate treatment of future patients with a given medical condition.”

– Pocock, from Clinical Trials: A Practical Approach (1984)

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Types of Clinical Trials

• Clinical Trials are performed in– Pharmaceutical Products (Synthetic “Drugs”)– Biotechnology Products (products made from

human cells/tissues for example, such as vaccines, blood products)

– Devices (e.g., cardiac stents, pacemakers)

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Phases of Pharmaceutical/Biotechnology Clinical Trials

• Pre-Clinical (in vivo, in vitro)• Investigational New Drug (IND) Application • Phase I - First time in humans• Phase II - Exploratory

– Phase IIb– Phase II/III

• Phase III - Confirmatory• New Drug Application (NDA)/Product License Application (PLA)• Phase IV - Post Marketing

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Phases of Pharmaceutical/Biotechnology Clinical Trials

•FDA Center for Drug Evaluation and Research Handbook at http://www.fda.gov/cder/handbook/index.htm; click on (a) “New Drug Development and Review” “IND Review Process” click on (b) “New Drug Development and Review” “New Drug Development Process”

• FDA Center for Drug Evaluation and Research general web site at http://www.fda.gov/cder

• FDA Center for Biologics Evaluation and Research general web site at http://www.fda.gov/cber

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Phase I Pharm/Biotech Trials• First time in humans• Objectives

– Assess pharmacology/pharmacokinetics• How drug flows through body• How drug is excreted and how long (half-life)

– Assess toxicology (safety)• Adverse events, Labs, EKGs, Vital Signs, Physical Exams• Determine maximum tolderated dose (MTD)

– Performed usually in 15-20 subjects– No interest in efficacy – Descriptive Analysis

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Phase II Pharm/Biotech Trials• Performed in usually 50-200 patients

– Sample often based on time, cost considerations

• Concentrate on safety, but also look at efficacy• Often exploratory in terms of efficacy

– Find parameters on which product is efficacious?

– Find magnitude of the product’s effect on these parameters?

• Contains control group (placebo/active)

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Phase II Pharm/Biotech Trials

• Multiple doses

• Find dose with best safety profile and best efficacy profile (not always the highest dose)

• Use results to design confirmatory Phase III trials– Not necessarily required to obtain statistical

significance (“p<0.05”) in Phase II in order to move to Phase III

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Phase III Pharm/Biotech Trials

• Objective– Confirm efficacy of new drug seen in Phase II– Determine safety of new drug (especially for

uncommon “adverse events”).

• Often called “Pivotal” trials

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Phase III Pharm/Biotech Trials

• Often performed in 2 treatment groups– Study drug vs. Control

• Control may be Active or Placebo

• Some suggest both Active and Placebo control

• If Active-controlled, not necessary to show superiority, but “non-inferiority” or “equivalence”

• FDA has no official rules about control group

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Phase III Pharm/Biotech Trials

• Sample size based heavily on statistics– If treatment works in population, we want a sample

large enough to represent population– I.e., Want a high probability treatment works in

sample

• FDA usually requires 2 phase III studies, with p<0.05 for efficacy (if superiority trial)

• For “large simple trials” (e.g., CV) only one large study may suffice (with, say, p<0.01 or p<0.001).

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Phase II/III Pharm/Biotech Trials

• Phase IIb, Phase II/III Trials

– Exploratory, but less so than Phase II– State a specific analysis; if successful, consider

study as one of the Phase IIIs (“pivotal”)– If not successful, then consider as exploratory

analysis for planning Phase III

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New Drug Application (NDA)

• “The data gathered during the animal studies and human clinical trials of an Investigational New Drug (IND) become part of the NDA.” (From FDA Center for Drug Evaluation and Research Handbook at http://www.fda.gov/cder/handbook/index.htm; click on “New Drug Development and Review”, “New Drug Application (NDA) Review Process”)

• Biologic equivalent is PLA (Product License Application)

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Clinical Trials in Medical Devices

• For further information, see FDA Center for Devices and Radiological Health (CDRH) web site at http://www.fda.gov/cdrh/index.html.

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International Conference on Harmonisation

• The “International Conference on Harmonisation” (ICH), as quoted at at http://www.ich.org,– “is a unique project that brings together the regulatory

authorities of Europe, Japan and the United States and experts from the pharmaceutical industry…”

– “The purpose is to make recommendations on ways to achieve greater harmonisation in the interpretation and application of technical guidelines and requirements for product registration in order to reduce…”

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Statistical Issues in Clinical Trials

• Efficacy variables– Phase III (Confirmatory)

• 1-2 Primary efficacy variable; e.g. Respiratory Distress Syndrome (RDS) in premature infants has 2 primary endpoints

– RDS 24 hours after birth

– 28-day survival

• Show Rx effect in both endpoints (alpha=0.05 for each)

• Show Rx effect in at least 1 endpoint (alpha=0.025 for each).

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Statistical Issues in Clinical Trials

• Efficacy variables

– Phase III (Confirmatory)• Usually several secondary endpoints

– In RDS trial: Fi02, Mean Airway Pressure, All-cause mortality, Incidence of Bronchopulmonary Dysplasia

• How you “split the alpha” depends on objective of secondary endpoints (e.g. for label? just exploratory?)

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Statistical Issues in Clinical Trials

• Blindness– Double-blind – neither investigator nor patient know

treatment patient is receiving• Ideal situation

• Removes potential bias

• Still sometimes easy to ascertain the treatment patient is receiving (e.g., ALS study, lipid lowering study)

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Statistical Issues in Clinical Trials

• Blindness– Single-blind – investigator knows treatment patient

is receiving– Open-label – patient and investigator know the

treatment patient is receiving• Such trials occur in cases when comparing, say,

chemotherapy with surgery

• Have a blinded evaluation of patient outcome (someone not involved in treatment administration nor care of the patient).

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Statistical Issues in Clinical Trials

• Single-center or multi-center– Choice often depends on logistical issues

• Can you obtain enough subjects in a single-center?

• If so, can you obtain enough in an allotted amount of time

– Is a single center representative of the population as a whole?

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Treatment-by-Center Interaction• (Snapinn, 1998)

– Why multiple centers?• Increase enrollment• Increase generalizability of results to population

– Potential issue with multiple centers• Center demographics/center study conduct may affect

treatment performance• Treatment-by-center (or treatment-by-clinic) interaction:

A treatment difference that varies significantly across study centers

• FDA would like assurance such an interaction does not exist so patients across centers can be pooled into one group for analysis

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• Interpreting Interaction – The classical approach (Snapinn, 1998):

Means by treatment group and center under various scenariosNo interaction

0

1

2

3

4

Clinic 1 Clinic 2 Clinic 3

Quantitative Interaction

0

1

2

3

4

Clinic 1 Clinic 2 Clinic 3Qualitative Interaction

0

1

2

3

4

Clinic 1 Clinic 2 Clinic 3

Treat 1

Treat 2