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5 August, 2014

Introduction: Challenges in Analyzing and Interpreting Multiple (Censored) Outcomes in Chronic Disease Trials Dianne M. Finkelstein, Ph.D., MGH, Harvard University, Boston, MA, USA. 5 August, 2014. Multiple Outcomes In Clinical Trials.

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5 August, 2014

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  1. Introduction: Challenges in Analyzing and Interpreting Multiple (Censored) Outcomes in Chronic Disease Trials Dianne M. Finkelstein, Ph.D., MGH, Harvard University, Boston, MA, USA 5 August, 2014

  2. Multiple Outcomes In Clinical Trials • Trials often have several outcomes that are monitored for treatment benefit • Survival is primary in a life-threatening disease but may take too long to show benefit • Other measures of disease progression can be more rapidly sensitive in a trial • How should these be handled in the design, analysis, and report of the trial results?

  3. Examples of Multiple Outcomes • Breast cancer clinical trial • Survival, recurrence (distant, local), quality of life • Commonly use progression-free survival as primary • ALS (Lou Gehrig’s Disease) • ALS functional rating scale (ALSFRS) • Survival not likely to be affected by Rx • ALSFRS commonly chosen as primary

  4. Examples of Multiple Outcomes • Heart Failure (CHARM trial) • Chronic heart failure (death, cardiovascular event), hospitalizations • Commonly use time to first of cardiac events/death • Scleroderma (interstitial lung disease) • Pulmonary function (FVC) at 12 months and death • Commonly combined FVC and death primary Disability and quality of life secondary

  5. How are multiple endpoints usually handled? • Report univariate analyses with correction for multiplicity (Bonferroni for example) • Select a primary endpoint that guides decision about the treatment • Co-primary outcomes or hierarchy

  6. Alternatively: Test Based on Data From Two or More Endpoints • “Time to first” of two or more events • Failure-time analysis • Failure is the first observed • Example: Progression-free survival in cancer • Global test on first as well as subsequent endpoints • Can compare patients pair-wise on many events • Base the test on sum of scores from one group

  7. Advantage of Tests Based on a Combined Outcome • Considering “time to first event” or “global test” • Allows simultaneous evaluation of multiple outcomes without adjustment for multiplicity • Account for effect confounding of outcome measures that are combined • Recovers information from censored or missing data • Can increase power • Co-primary endpoints would require larger N as both must have sufficient power

  8. Problems With “Time to First Outcome” Test • Treats all events equally • Lose information from subsequent or repeated events • CHF: time to death or first cardiac event loses information on recurrences • PFS loses information on death for patients with progression observed before death • Sometimes early events are less important clinically • Could lose power if treatment primarily effects progression, and survival dilutes the test

  9. A Global Test to Combine Mortality and Longitudinal Outcomes in a Clinical Trial • Joint Rank Test of Finkelstein & Schoenfeld 1999 • All patients compared pair-wise on time to death and a longitudinal outcome • If cannot compare on death (due to censoring) then compare on longitudinal outcome at the latest time point that you have data from both subjects • Assigned score of +1 (better) or -1 (worse) or 0 (can’t compare) • Test based on sum scores for each patient in treated group. Wilcoxon test applied

  10. A Global Test to Combine Mortality and Longitudinal Outcomes in a Clinical Trial (continued) • The F-SJoint Rank Test was first proposed in SIM in 1999 Finkelstein-Schoenfeld • Called Generalized Wilcoxon Test (GGW) in paper or Combined Test in literature • Other papers have re-named the test • CAFS (Combined Assessment of Function and Survival) in Berry et al. (2013) for ALS • Win Ratio (Pocock et al for cardiac trails) 2012 • Ritesh Ramchandani will discuss a generalization to this later in this session

  11. Other Global Tests:PCO’Brien Rank Sum Test (1984) • In the pooled sample, patients are ranked on each outcome • Outcome-specific ranks are summed, giving a total rank for every patient • Conduct ANOVA, t-test, or rank-sum test on total ranks • Viewed as supplement to univariate results

  12. Estimate Derived from the Global Test Pocock et al. Win Ratio • As for F-S Joint Rank test, count number of pairs where new Rx patient did better (win) or worse (loss) • Win Ratio= number of winners / number of losers • Get estimate of proportion who won from WR • Allows calculation of confidence bounds and graphical display of results

  13. Examples of published global endpoint analyses (Barry). • 1984 Non-parametric and parametric approaches to analyzing multiple endpoints; illustrated using a diabetes trial • 1999 Non-parametric evaluation of time to event (e.g. mortality) and longitudinal measure (e.g. change over time in CD4 lymphocyte count in HIV/AIDS) • 2000 Analysis of longitudinal measure and event history or survival-schizophrenia trial • 2006 Repeated measurements and event time data (shared parameter model) • 2007, 2011 Continuous measure over time (e.g. disability index in scleroderma) and time-to-event outcomes (e.g. renal crisis and death in scleroderma) • 2007 Longitudinal measurement (e.g. change in percent forced vital capacity) and time to treatment failure or death (in scleroderma-associated lung disease) • 2008 Death and another outcome such as stroke, myocardial infarction, time to re-intervention, angina, or hospitalization in cardiovascular clinical trials • 2010 Time to loss of virological response; incorporates virological failure assessments, loss to follow-up, new treatment initiation, and death HIV • 2013 Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration

  14. Suggestions in Using Global Test • Can use hierarchy to give more importance to some endpoints • Caution about including endpoints that don’t reflect Rx effect as can dilute results • Best to use in the setting that all intermediate endpoints are on the same path (to death) • Example: tumor progression is predictive of earlier death • However salvage Rx can diminish protocol Rx impact on death

  15. Suggestions on Global Analyses (continued) • Put global test analysis in the Analysis Plan • Include component-wise analysis plan • Calculate power for the global analysis

  16. Future Research is Needed • Refine the estimate associated with the test • WIN ratio is affected by the total follow-up time of the study • Graphical display of results • Depict global estimate over time • Show what outcomes dominate the score • Testing and estimation of univariate outcomes • Joint test can be significant but not univariate outcomes • Hierarchical testing

  17. Conclusions • A global test of multiple outcomes can increase power and assess multi-dimensional treatment outcomes. • Use of joint tests is gaining in popularity in many disease settings (Pharma as well as FDA) • Needs to be considered in more disease settings • New methods and approaches needed to handle the interpretation of global outcome analyses • If you propose a new test, give it a memorable name

  18. Session • Andrew Strahs: Illustration of issues that can arise with “time to first” outcome in a clinical trial • Ritesh Ramchandani: Generalization of Global test • Marc Buyse: Approach to summarizing Global test outcomes in a trial • David Schoenfeld: Discussion • SEE OUR WEBSITE FOR THE TALKS AND CONTACTS • Google “MGH Biostatistics” for hedwig.mgh.harvard.edu/

  19. References • Finkelstein, DM and Schoenfeld, DA. Combining mortality and longitudinal measures in clinical trials. Statistics in Medicine 1999;18:1341-1354. • O’Brien PC, Procedures for comparing samples with multiple endpoints, Biometrics 1984 40(4):1079087. • Berry JD, Miller R, Moore DH, Cudkowicz ME, Van Den Berg LH, Kerr DA, Dong Y, Ingersoll EW, Archibald D, “The combined assessment of function and survival (CAFS): A new endpoint for ALS clinical trials, ALS and Frontotemporal Degeneration 2013 14(3): 162-8. • Pocock SJ, Cono AA, Collier TJ, Wang, D, “The win ratio: a new approach to the analysis of composite endpoints in clinical trials based on clinical priorities, European Heart Journal 2012 33:176-82. • Sun H, Davison BAA, Cotter G, Pencina MJ, Koch GG, “Evaluating treatment efficacy by multiple end points in phase II acute heart failure clinical trials: analyzing data using a global method”, Circulation 2012: 5: 742-9.

  20. Thank you! Visit our website: hedwig.mgh.harvard.edu/biostatistics/

  21. Examples of Multiple Outcomes in ALS • Phase II Trial of two doses of dexpramipexole for ALS • Mortality alonse p=.071 ALSFRS slope p=.177 • Joint Rank test p=.046 • Simulations • If one endpoint moderate and one significant, Joint Rank test better • Moderate on each may not be enough

  22. Activity 282 on Aug 5 at 8:30am • Upload in 256 B CC • BC Healy Chair • Session 210146

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