The Future of the Education of Clinical Trial Statisticians: What Changes are Needed and How do We Implement Them?

1. The Future of the Education of Clinical Trial Statisticians: What Changes are Needed and How do We Implement Them? Karl E. Peace, Ph.D. GCCDCS, SRS & Professor of Biostatistics The Jiann-Ping Hsu College of Public Health 徐建萍公共卫生学院 PO BOX 8015 Georgia Southern University Statesboro, Georgia 30460 912-478-7905 phone, 912-478-5811 fax kepeace@georgiasouthern.edu, peacekarl@cs.com Graybill Conference VII June 12, 2008

2. Abstract: Recommendations the speaker has made over the last 25 years regarding the relative importance of design, analysis and interpretation of clinical trials and The education of Clinical Trial Statisticians are discussed. J-P Hsu College of Public Health

3. Question 1:How should the training of clinical trial statisticians be modified to increase emphasis on design, monitoring, consulting, and interpretation? • CTM course: emphasis is on critical thinking and understanding concepts. More emphasis is placed on the design and conduct of clinical trials more so than their analyses. Several case studies are presented and then critiqued reflecting sequentially: - Developing a clear understanding of the objective, - Identification of required data or endpoints, - Translation of the objective into statistical questions (testing or estimation: including symbolism), - Identification of the experimental design, - Determining sample size requirements and bases for their computation, - Identification of statistical methods, - Detailing how the trial was conducted (including monitoring and data management), - Reviewing and interpreting the results. J-P Hsu College of Public Health

4. Question 1 (continued): • CTM course: In addition, - Each case study is reviewed to identify and classify methods or procedures: minimize bias, IC, design, diagnostic, treatment, safety of patients, data management, statistical, etc. and further what methods apply pre, during and post study. - The responsibilities of the statistician Pre, during and post study are identified and explained. • CTM course, Other Features: - Students learn how to write a Statistical Analysis Section for a clinical trial protocol. - Students have to write a protocol as part of final exam. J-P Hsu College of Public Health

5. Question 1 (continued): Statistical Analysis Section .1 Study Objectives as Statistical Questions .2 Endpoints .3 Statistical Methods .4 Statistical Monitoring Procedures .5 Statistical Design Considerations .6 Subset Analyses References J-P Hsu College of Public Health

6. Question 1 (continued): • CTM Final Exam Question: Following are data sets from a clinical trial in essential hypertension: Dummy Data 1 and Dummy Data 2.  The first column represents observation number, the second represents treatment group assignment.  The remaining columns, in order, represent supine diastolic blood pressure (SDBP, mmHG) at the baseline (Visit 1, at which assignment to treatment occurs) visit, and follow-up visits 2, 3, 4 and 5.  The data sets are identical, except that data set 2 contains some missing values (the '.' ). • A. Write a simple, reasonable, protocol for a clinical trial that could have produced these data.  Make sure you include inclusion & exclusion criteria, reflecting age at least 18 years, either sex, any race or ethnicity, and any weight, and that the protocol is multi-center (with two centers).  • B. After you have done this, you will need to add additional data columns to include age, sex, race or ethnicity, and weight, and supply data values for these.  Now add a column for center to reflect that the protocol is multi-center (2 centers): the first 10 patients in each treatment group come from center #1, and the last 10 patients in each treatment group come from Center #2. Also add a column for patient number (starting with 1101 for the first patient data row for center 1 and treatment A, then 1102, etc. until the last patient receiving treatment A in center 1, and starting with 1201 for the first patient data for center 2 receiving treatment A, etc.). J-P Hsu College of Public Health

7. CTM Final Exam Question (continued): • C. Then write a SAS program to analyze each data set (ignoring center). 1. Provide estimates of mean treatment differences, Standard errors of the differences, p-values for the differences, and 95% confidence intervals for the differences by visit, and averaged across visits. 2. Interpret these results. 3. Turn in your SAS program and Output. • D. Then write a SAS program to analyze each data set (including center). 1. Provide estimates of mean treatment differences, Standard errors of the differences, p-values for the differences, and 95% confidence intervals for the differences by visit, and averaged across visits. 2. Interpret these results. 3. Test whether the data are poolable across centers. 4. Turn in your SAS program and Output. • E. Please provide assumptions underlying your analysis methodology, including for Dummy Data 2, how you handled missing data. J-P Hsu College of Public Health

8. Question 2:How should the education of clinical trial statisticians include development of communication skills (oral and written)? • Approach that has worked: - I help each class select a research project; - with my help, they do the research and write a manuscript style report, and develop PPTs for presentation at three research symposia (PKP, COGS, JPHCOPH). - Every member contributes. - Provides experience in: planning, research methodology, consulting, group interaction, and written and oral communication. J-P Hsu College of Public Health

9. Question 3: The power of computing and resampling – based methods has in some cases replaced use of large sample statistical theory. How can we identify an appropriate balance of applied and methodological statistical skills? • Unsure as to the proper balance: - Some mix is needed (including Bayesian - go to resampling-based methods any time no validated method exists and/or when methodological assumptions are violated? J-P Hsu College of Public Health

10. Question 4:How should the education of clinical trial statisticians include more medical and biological training? • Not sure, but a mix is needed. - Georgia Southern University has no Medical School and JPHCOPH has no formal affiliation with one. - JPHCOPH is young and we are exploring collaborations with proximal medical schools. We do have collaborations with SWGCC, SEGACA, GCC, GACORE, and some health departments and local hospitals for student practicum experience. - In the classes I teach (CTM and SIDRD), I provide key information about the substantive aspects of the application (plus draw from students who have MD) J-P Hsu College of Public Health

11. Concluding Remarks: • “Analysis and Interpretation are important, but I believe the greater contribution by the statistician is at the design stage. Even helping to define the question the experiment is to answer is an important contribution.” • “…The curriculum should de-emphasize methods and ‘how to’ and place greater emphasis on ‘why.’ The non-statistical community will also derive greater benefit from courses which stress sound experimental design concepts and principles and the importance of scientific rigor than from all the methods courses. There should also be courses on understanding the structure of data, and better ways to descriptively profile and display data.” • [Peace, KE: “Some Thoughts on the Biopharmaceutical Section and Statistics” ASA Sesquicentennial Meeting, 1989] J-P Hsu College of Public Health

12. Concluding Remarks: • “We are confronted with many opportunities for consultation in areas where we are ill prepared substantively. In the future we must find the time to gain sufficient substantive knowledge about the application so that we interact with the client in a meaningful way – and keep the client coming back. Now I know that many statisticians have acquired needed substantive knowledge. I say it in this way to signal that greater emphasis in the future should be placed on gaining such knowledge prior to the consultation – even formally in statistical degree programs.” • [Peace, KE: “Some Thoughts on the Biopharmaceutical Section and Statistics” ASA Sesquicentennial Meeting, 1989] J-P Hsu College of Public Health

13. The Jiann-Ping Hsu College of Public Health 徐建萍公共卫生学院 Thank You. J-P Hsu College of Public Health

14. The Jiann-Ping Hsu College of Public Health 徐建萍公共卫生学院 Summary of Biostatistical Training/ Mentoring Activities in the PI • Biostatistical Aspects of Clinical Development Programs • Focus was asking and answering questions • Writing the protocol • No tolerance for the PARC method of research • Biostatistical Aspects of Basic Research Programs • WHY? To improve communication primarily • Eventually reciprocated from Clinical Development and some of the substantive areas. • Result: substantive area scientists learned more about statistics, experimental design, the importance of framing the question, etc., and the statisticians learned more about the substantive areas – at least their vocabulary improved; so that communication and consultation improved • As Chair of the PMA Training Committee of the Biostatistics Subsection made both programs available to the PMA and taught them at several Pharmaceutical companies; Later they were co-taught by statisticians from across the industry in DC and perhaps under PERI. J-P Hsu College of Public Health

15. The Jiann-Ping Hsu College of Public Health 徐建萍公共卫生学院 • Biostatistical Aspects of Clinical Development Programs • Quality clinical development programs require careful attention to planning, execution, summarization and reporting. Even planning a single clinical trial requires attention to these issues (which reflect generally an exercise of writing a quality protocol): • Asking and answering Questions • Defining the Question (including endpoints) • Variability of Data • Subject / Patient definition and selection • Treatment (or intervention) definition and assignment • Standard Clinical Protocol Template • Answering the question • Multi-center trials • Safety / Informed Consent • Management Structure and Procedures (including monitoring) J-P Hsu College of Public Health