Statistical Review of P040049 Acorn’s CorCap Cardiac Support Device

1. Statistical Review of P040049 Acorn’s CorCap Cardiac Support Device Laura Thompson, Ph.D. Mathematical Statistician CDRH/FDA FDA Statistical Review

2. Outline • Study Design • Primary Endpoint Analysis • Concerns • Separate Analyses of Components of Primary Endpoint • Analyses of Secondary Endpoints • Analyses of Primary Endpoint by MVR Strata • Summary FDA Statistical Review

3. Study Design • Two-arm, randomized 1:1 study (300 pts) • Randomization blocked by site (30 sites) and stratified by concomitant MVR surgery • Primary analysis pooled across strata (test for treatment x MVR interaction was not found to be significant) FDA Statistical Review

4. Primary Endpoint • Composite Endpoint (evaluated > 12 months) • all-cause mortality • change in core lab NYHA class assessment from baseline • major cardiac procedures indicative of worsening HF • Ordinal Scoring (1=Improved, 2=Same, 3=Worsened) • Improved = Improved NYHA class and did not die and did not receive MCP • Same = no change in NYHA from baseline, did not die and did not receive MCP • Worse = • Died, or • Received MCP for worsening HF, or • Worsened on NYHA class FDA Statistical Review

5. Differences in Baseline Characteristics across Treatments • 42 baseline covariates examined • 4 lowest p-values FDA Statistical Review

6. Explanatory Variables used in Primary Endpoint Analysis • MVR stratum • Site Size (small, medium, large) • Length of follow-up (“early”, “late” enrollee) • 3 baseline covariates • Gender • baseline peak VO2 • DBP FDA Statistical Review

7. Primary Endpoint Model - Proportional Odds Two possible binary logistic regression models: • “Success” = “Improved”; “Failure” = “same” or “worsened” • “Success” = “Improved” or “same”; “Failure” = “Worsened” • Proportional odds model fits both models simultaneously, with common treatment effect > > Improved Same Worsened FDA Statistical Review

8. Proportional Odds Property (constant difference in log odds) • Proportionality: The odds of any higher category for trt1 are times the odds for trt2 Hypothetical Illustration vs. Same or worsened vs. worsened FDA Statistical Review

9. Non-Proportional Odds (non-constant log odds) Hypothetical Illustration vs. Worsened vs. Same or Worsened Comment: Is Proportional Odds assumption appropriate for the data? FDA Statistical Review

10. Missing Data in Primary Endpoint • Assignment of NYHA class by site physician was unblinded • Core lab assignment of NYHA class was done by a blinded cardiologist • 42% of patients have baseline core lab NYHA assessments (CorCap n=61, Control n=65 available) • The sponsor has shown a low concordance between the site-assessed and core lab NYHA • 58% of baseline core lab NYHA assessments were filled-in or imputed using an imputation model FDA Statistical Review

11. Imputation Models • Observed variables used to predict missing core lab baseline NYHA • MVR stratum • Site Size (small, medium, large) • Length of follow-up (“early”, “late” enrollee) • Duration of HF • Age • Baseline 6-MW • Baseline MLHF score • Baseline SF-36 score • Ischemic/non-ischemic etiology • Gender • DBP • Baseline Peak VO2 • Baseline LVEF • Baseline Site-assessed NYHA FDA Statistical Review

12. Imputation Models • Imputation Model #1: Linear regression of baseline NYHA on observed baseline variables • Imputation Model #2: Ordinal regression of baseline NYHA on observed baseline variables • Multiple imputation techniques • 59% of CorCap and 55% of Control baseline NYHA values were imputed FDA Statistical Review

13. Assumption: Missing at Random • Missing at random: Baseline NYHA is missing due only to enrollment time (and can be predicted from observed variables) • Missing not at random: Baseline NYHA for “early” enrollees (before 7/4/2002) is distributed differently than for “later” enrollees. • In an unblinded trial, there is a concern of selection bias in choosing patients who enter the trial. • In this trial, a concern is that later enrollees may be less sick than earlier enrollees. • Nonetheless, a selection bias might affect CorCap and Control roughly equally FDA Statistical Review

14. Selected Baseline Means by “Early” and “Later” Enrollees FDA Statistical Review

15. Analysis of Primary Endpoint FDA Statistical Review

16. Concerns about Imputation • More than1/3 of patients are missing primary endpoint measurements. More than half of patients are missing baseline core lab NYHA. • Results may be sensitive to violation of “missing at random” (MAR) assumption • Comment: Discuss the reliability of analyses that used imputation. FDA Statistical Review

17. Concern about Proportional Odds Assumption FDA’s Analysis of Primary Endpoint for Different Cut-points (using available data): CorCap N = 93; Control N = 98 Comment: Please discuss the appropriateness of the proportional odds assumption. FDA Statistical Review

18. Separate Analyses of Components of Primary Endpoint • Which components contribute relatively more to the overall composite? • Familywise error rate was not controlled a priori. P-values cannot be interpreted with respect to any significance level. • A Bonferroni correction would imply a significance level of 0.05/3=0.017 FDA Statistical Review

19. Separate Analysis of Mortality Component of Primary Endpoint • Log-rank test of difference in KM survival curves p = 0.85 Cumulative Number of Deaths by Time FDA Statistical Review

20. Separate Analysis of Change in NYHA Component of Primary Endpoint • Patients who had MCP or died do not have recorded NYHA at CCD FDA Statistical Review

21. Analysis of MCP Contribution to Primary Endpoint FDA Statistical Review

22. Difficulty of Re-operation after CorCap • A referral bias could arise if physicians were reluctant to refer CorCap patients for MCP • This might have affected the relative number of patients who received MCP across treatment groups • Could a referral bias account for an observed increase in percentage improved on NYHA for the CorCap vs. control groups? • However, observed improvement on NYHA seen in CorCap vs. control was not statistically significant. FDA Statistical Review

23. Pre-specified “Major” Secondary Endpoints • LVEDV, LVEF, MLHF, site-assessed NYHA • Hochberg procedure to control familywise type I error rate at 5% • Hochberg p = 0.032 • Presented individual p-values are adjusted for multiplicity FDA Statistical Review

24. Multiple Secondary Endpoints:A Reminder • If and only if the primary endpoint is met, pre-specified multiple secondary endpoints are tested as a set at an additional overall significance level. • For any secondary endpoints for which multiple testing issues were not considered a priori, statistical significance cannot be interpreted • The chance could be too high that the randomization to treatment groups resulted in an artificial “significant” difference on a few of many secondary endpoints. FDA Statistical Review

25. “Major” Secondary Endpoints FDA Statistical Review

26. Other Secondary Endpoints • Other secondary endpoint tests were not controlled for multiple testing issues. P-values are not interpretable with respect to significance. • Comment: Please comment on the use of tests of other secondary endpoints in making statements about intended use. FDA Statistical Review

27. Relationship between Structural and Functional Endpoints • Low magnitude of correlation; low p-value does not imply high degree of concordance p = 0.003 FDA Statistical Review

28. Stratum-Specific Analyses: A Reminder • Power the study to detect a stratum X treatment interaction at a pre-specified significance level. • If interaction is significant, perform tests within each stratum. A within-stratum analysis with a significant result can claim a treatment effect. • If sample size is not large enough for interaction test, then tests within strata can be made for exploratory purposes FDA Statistical Review

29. Within-stratum Analyses of Primary Endpoint • MVR stratum X Treatment not found to be significant FDA Statistical Review

30. Within-stratum Analyses - by component • MCPs • Change in core NYHA from baseline FDA Statistical Review

31. Within-stratum Analyses of Primary Endpoint • MVR X Treatment Interaction not statistically significant (study not powered to detect) • Larger observed treatment difference was seen in the stratum with smaller sample size (NoMVR n=107; MVR n=193) • Observed difference across strata might be worth examining further FDA Statistical Review

32. Statistical Summary • Sponsor met composite primary endpoint at 0.05 significance level • Large amount of missing data may make inference uncertain • Examination of separate components of composite shows strong influence of reduction in MCPs • Difficult to determine if referral bias for MCP accounts for any of the perceived benefit of CorCap FDA Statistical Review

33. Statistical Summary (cont) • Similar number of deaths in each treatment group • Results from major secondary analyses were mixed with respect to finding a significant CorCap benefit • Measures of cardiac structure do not show an association with functional status • Treatment difference across MVR strata may not be consistent FDA Statistical Review