1 A Bayesian Non-Inferiority Approach to Evaluation of Bridging Studies Chin-Fu Hsiao, Jen-Pei Liu Division of Biostatistics and Bioinformatics National.

Slides:



Advertisements
Similar presentations
OPC Koustenis, Breiter. General Comments Surrogate for Control Group Benchmark for Minimally Acceptable Values Not a Control Group Driven by Historical.
Advertisements

Tests of Hypotheses Based on a Single Sample
Robert T. O’Neill, Ph.D. Director, Office of Biostatistics CDER, FDA
Development of Evaluation and Consultation on Bridging Studies: Thailand Experiences Suchart Chongprasert, Ph.D. Investigational New Drug Subdivision Food.
Study Objectives and Questions for Observational Comparative Effectiveness Research Prepared for: Agency for Healthcare Research and Quality (AHRQ)
The ICH E5 Guidance: An Update on Experiences with its Implementation The ICH E5 Guidance: An Update on Experiences with its Implementation Robert T. O’Neill,
A Flexible Two Stage Design in Active Control Non-inferiority Trials Gang Chen, Yong-Cheng Wang, and George Chi † Division of Biometrics I, CDER, FDA Qing.
Designing Experiments: Sample Size and Statistical Power Larry Leamy Department of Biology University of North Carolina at Charlotte Charlotte, NC
CR-1 ATACAND ® (candesartan cilexetil) Cardiovascular and Renal Drugs Advisory Committee Bethesda, Maryland July 18, 2002 C.
LSU-HSC School of Public Health Biostatistics 1 Statistical Core Didactic Introduction to Biostatistics Donald E. Mercante, PhD.
COURSE: JUST 3900 INTRODUCTORY STATISTICS FOR CRIMINAL JUSTICE Instructor: Dr. John J. Kerbs, Associate Professor Joint Ph.D. in Social Work and Sociology.
Role of Pharmacoeconomics in a Developing country context Gavin Steel for Anban Pillay Cluster Manager: Health Economics National Department of Health.
Optimal Drug Development Programs and Efficient Licensing and Reimbursement Regimens Neil Hawkins Karl Claxton CENTRE FOR HEALTH ECONOMICS.
ODAC May 3, Subgroup Analyses in Clinical Trials Stephen L George, PhD Department of Biostatistics and Bioinformatics Duke University Medical Center.
Estimation and Reporting of Heterogeneity of Treatment Effects in Observational Comparative Effectiveness Research Prepared for: Agency for Healthcare.
EPIDEMIOLOGY AND BIOSTATISTICS DEPT Esimating Population Value with Hypothesis Testing.
The ICH E5 Question and Answer Document Status and Content Robert T. O’Neill, Ph.D. Director, Office of Biostatistics, CDER, FDA Presented at the 4th Kitasato-Harvard.
8-3 Testing a Claim about a Proportion
PY 427 Statistics 1Fall 2006 Kin Ching Kong, Ph.D Lecture 5 Chicago School of Professional Psychology.
Clinical Trials of Traditional Herbal Medicines In India Y.K.Gupta Professor & Head, Department of Pharmacology, All India Institute of Medical Sciences,
Overview of Statistical Hypothesis Testing: The z-Test
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved Chapter 8 Hypothesis Testing 8-1 Review and Preview 8-2 Basics of Hypothesis.
1 Dr. Jerrell T. Stracener EMIS 7370 STAT 5340 Probability and Statistics for Scientists and Engineers Department of Engineering Management, Information.
Hypothesis Testing II The Two-Sample Case.
Tests of significance & hypothesis testing Dr. Omar Al Jadaan Assistant Professor – Computer Science & Mathematics.
The paired sample experiment The paired t test. Frequently one is interested in comparing the effects of two treatments (drugs, etc…) on a response variable.
Understanding the Concept of Equivalence and Non-Inferiority Trials CM Gibson, 2000.
1 An Overview of Bridging Evaluations in Taiwan Chin-Fu Hsiao 1, Mey Wang 2, Herng-Der Chen 2, Yu-Yi Hsu 1 and Jen-pei Liu 3 1 Division of Biostatistics.
Research Design. Research is based on Scientific Method Propose a hypothesis that is testable Objective observations are collected Results are analyzed.
Sample size determination Nick Barrowman, PhD Senior Statistician Clinical Research Unit, CHEO Research Institute March 29, 2010.
Statistical Decision Theory
Chapter 8 Introduction to Hypothesis Testing
Nonclinical Perspective on Initiating Phase 1 Studies for Small Molecular Weight Compounds John K. Leighton, PH.D., DABT Supervisory Pharmacologist Division.
Delivering Robust Outcomes from Multinational Clinical Trials: Principles and Strategies Andreas Sashegyi, PhD Eli Lilly and Company.
Challenges of Non-Inferiority Trial Designs R. Sridhara, Ph.D.
1 Statistical Review Dr. Shan Sun-Mitchell. 2 ENT Primary endpoint: Time to treatment failure by day 50 Placebo BDP Patients randomized Number.
One-Sample Tests of Hypothesis Chapter 10 McGraw-Hill/Irwin Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved.
What is a non-inferiority trial, and what particular challenges do such trials present? Andrew Nunn MRC Clinical Trials Unit 20th February 2012.
Analysis of Variance 1 Dr. Mohammed Alahmed Ph.D. in BioStatistics (011)
1 Chapter 9 Hypothesis Testing. 2 Chapter Outline  Developing Null and Alternative Hypothesis  Type I and Type II Errors  Population Mean: Known 
Economics 173 Business Statistics Lecture 4 Fall, 2001 Professor J. Petry
Federal Institute for Drugs and Medical Devices The BfArM is a Federal Institute within the portfolio of the Federal Ministry of Health (BMG) The use of.
Not in FPP Bayesian Statistics. The Frequentist paradigm Defines probability as a long-run frequency independent, identical trials Looks at parameters.
Slide Slide 1 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Overview.
Statistical Decision Theory Bayes’ theorem: For discrete events For probability density functions.
Bioequivalence Dr Mohammad Issa Saleh.
2006, Tianjin, China sf.ppt - Faragalli 1 Statistical Hypotheses and Methods in Clinical Trials with Active Control Non-inferiority Design Yong-Cheng.
1 Chapter 9 Bridging Studies & Multi-Regional Trials.
Hypothesis Testing Errors. Hypothesis Testing Suppose we believe the average systolic blood pressure of healthy adults is normally distributed with mean.
1 Chapter 9 Bridging Studies. 2 Outline  Introduction  Taiwan ’ s Situations  An Bayesian Approach  Discussion.
1 Chapter 9 Bridging Studies & Multi-Regional Trials.
General Regulatory Issues in the Development of Drugs Intended for Treatment of Chronic Illness Sharon Hertz, M.D. Medical Officer Division of Anesthetic,
Understanding Basic Statistics Fourth Edition By Brase and Brase Prepared by: Lynn Smith Gloucester County College Chapter Nine Hypothesis Testing.
考慮區域性差異之多區域藥物臨床試驗之評估與設計 Design and Evaluation of Multi-regional Clinical Trials With Heterogeneous Treatment Effect Across Regions Chi-Tian Chen Advisor.
Chapter 9 Hypothesis Testing Understanding Basic Statistics Fifth Edition By Brase and Brase Prepared by Jon Booze.
Remaining Challenges in Assessing Non-Inferiority Steven Snapinn DIA Statistics Community Virtual Journal Club December 16, 2014 Based on Paper with Qi.
Chapter Nine Hypothesis Testing.
Statistical Core Didactic
P-values.
Strategies to incorporate pharmacoeconomics into pharmacotherapy
Hypothesis Testing: Hypotheses
Testing a Claim About a Mean:  Known
One-Sample Tests of Hypothesis
Challenges of Bridging Studies in Biomarker Driven Clinical Trials
Elementary Statistics
Issues in Hypothesis Testing in the Context of Extrapolation
Bridging Studies - A Genomic Approach
Copyright © Cengage Learning. All rights reserved.
Introduction to Research Methods in Psychology
Assessing Similarity to Support Pediatric Extrapolation
Presentation transcript:

1 A Bayesian Non-Inferiority Approach to Evaluation of Bridging Studies Chin-Fu Hsiao, Jen-Pei Liu Division of Biostatistics and Bioinformatics National Health Research Institites Huey-Miin Hsueh Department of Statistics National Cheng-Chi University The views expressed in this paper are professional opinions of the presenter and may not necessarily represent the position of the National Health Research Institutes, Taiwan

2 Outline Introduction Bridging Study A Bayesian Non-Inferiority Approach Discussion

3 Introduction ICH (International Conference on Harmonisation) E5 Ethnic Factors in the Acceptability of Foreign Clinical Data The purpose of this guidance is to facilitate the registration of medicines among ICH regions by recommending a framework for evaluating the impact of ethnic factors upon a medicine’s effect, i.e., its efficacy and safety at a particular dosage and dose regimen.

4 Objectives of ICH E5 To describe the characteristics of foreign clinical data that will facilitate their extrapolation to different population and support their acceptance as a basis for registration on a medicine in a new region To describe regulatory strategies that minimize duplication of clinical data and facilitate acceptance of foreign clinical data in the new region To describe the use of bridging studies, when necessary, to allow extrapolation of foreign clinical data to a new region To describe development strategies capable of characterizing ethnic factor influences on safety, efficacy, dosage, and dose regimen

5 Bridging Study A bridging study is defined as a study performed in the new region to provide pharmacodynamic or clinical data on efficacy, safety, dosage, and dose regimen in the new region that will allow extrapolation of the foreign clinical data to the population in the new region

6 Extrapolation and Similarity If the bridging study shows that dose response, safety and efficacy in the new region are similar, then the study is readily interpreted as capable of “bridging” the foreign data If a bridging study, properly executed, indicates that a different dose in the new region results in a safety and efficacy profile that is not substantially different from that derived in the original region, it will often be possible to extrapolate the foreign data to the new region, with appropriate dose adjustment, if this can be adequately justified (e.g., by pharmacokinetic and/or pharmacodynamic data).

7 Bridging Studies ICH E5 Only after the medicine is approved in the original region Performed in the new region

8 Bayesian Approach For bridging studies Small sample size No power Information on dose response, efficacy and safety of the original region can not be concurrently obtained from the local bridging studies but are available in the trials conducted in the original region Need to borrow “strength” from CCDP of the original region Information on dose response, efficacy and safety of the original region can and should be incorporated in a statistically sound manner to evaluate bridging evidence by local bridging studies.

9 Bayesian Non-Inferiority Approach Step 1: From the complete clinical data package, use the technique of meta-analysis to integrate the results from the original region to formulate the mean and variability of the prior distribution for test product and placebo Step 2: Use the data from the bridging study in the new region and prior distribution to obtain the mean and variability of the posterior distribution for the difference of test products between new and original regions Step 3: Evaluate the posterior probability that difference is greater or equal to some clinically acceptable limit Step 4: If the posterior probability is sufficiently large, say 80%, then conclude the similarity between the new and original regions.

10 Assumption and Notation Assess similarity of efficacy for comparing a test product and a placebo control Since the test product has been already approved in the original region due to its proven efficacy against placebo control, the concept of non- inferiority is referred to as the similarity between the treatment effects from both regions  P indicates the common placebo effect for both new and original regions  NT (  OT ) represents the treatment mean for the new (original) region

11 Similarity Given the data from the bridging study and prior information on (  P,  NT,  OT ) formulated from the CCDP, we claim similarity on efficacy for the new region in terms of non-inferiority concept if the posterior probability P SI = P{  NT -  OT >-δ | bridging data and prior } > 1-  for some pre-specified δ> 0 and  > 0

12 The Equivalence Limit The equivalence limit δ can be expressed as a proportion of the relative efficacy of the test product against placebo δ=f(  OT -  P ) where f is a fixed pre-specified constant and 0<f<1.

13 Example We hypothesize an example based on our experience from literature review We select four randomized studies of the effect of a test drug (versus placebo) in reducing the sitting diastolic blood pressure The results of three studies are treated as the data from the original region, while the other one study is treated as the data from the new region The alternative hypothesis of interest is that the difference of reduction from baseline in sitting diastolic blood pressure between the test drug and placebo is less than 0

14

15 Example By letting f=0.5, we obtain that P SI = We therefore conclude that the efficacy observed in the bridging study of the new region is similar to the efficacy from the original region by the concept of non- inferiority

16 Discussion From our example, it can be seen that all the results from the original region are very significant, while the results from the new region are not significant at all Even so, the Bayesian non-inferiority approach still conclude the similarity of efficacy between both regions

17 Discussion One way to resolve issue is to use weights other than sample size to combine the data from both regions Another approach is to use different prior. For the data given above and under the non- informative prior, the posterior probability of non-inferiority, P SI is