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

FDA Statistical Review 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 Panel Presentation FDA Statistical Review

FDA Statistical Review 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) Panel Presentation FDA Statistical Review

FDA Statistical Review 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 Panel Presentation FDA Statistical Review

Differences in Baseline Characteristics across Treatments 42 baseline covariates examined 4 lowest p-values Covariate CorCap (n = 148) Control (n = 152) p-value Female 53.4% 36.2% 0.001 Peak VO2 13.3 ml/kg/min 15.5 ml/kg/min 0.0005 DBP 68.9 mmHg 71.5 mmHg 0.053 Years since HF diagnosis 4.5 years 5.4 years 0.080 Panel Presentation FDA Statistical Review

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 Panel Presentation FDA Statistical Review

Primary Endpoint Model - Proportional Odds > Improved Same > Worsened 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 Panel Presentation FDA Statistical Review

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 Panel Presentation FDA Statistical Review

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

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 Panel Presentation FDA Statistical Review

FDA Statistical Review 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 Panel Presentation FDA Statistical Review

FDA Statistical Review 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 Panel Presentation FDA Statistical Review

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 Panel Presentation FDA Statistical Review

Selected Baseline Means by “Early” and “Later” Enrollees Early Enrollee (N = 137) Later Enrollee (N = 163) p (t-test) Site NYHA 2.93 2.85 0.12 LVEF 26.5 27.3 0.45 LVEDD 72.9 70.7 0.08 6MW (m) 333.5 347.1 0.19 VO2 13.1 13.0 0.93 LVESD 64.2 61.6 0.06 Panel Presentation FDA Statistical Review

Analysis of Primary Endpoint Imputation Method Odds Ratio 95% CI p No imputation; available data only CorCap: N = 93 Control: N = 98 (FDA Analysis) 1.57 (0.89, 2.79) 0.12 Linear regression imputation CorCap: N = 147 Control: N = 146 1.73 (1.07, 2.79) 0.02 Ordinal regression imputation 1.69 (1.06, 2.72) 0.03 Panel Presentation FDA Statistical Review

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 recommended that the sponsor consider imputation as one solution to the problem of such a large amount of missing data that appeared to be missing at random, only due to the enrollment time. Nonetheless, there are concerns about imputation in this context. Panel Presentation FDA Statistical Review

Concern about Proportional Odds Assumption FDA’s Analysis of Primary Endpoint for Different Cut-points (using available data): CorCap N = 93; Control N = 98 Cutpoint Estimated Odds Ratios Improved vs. (Same or Worsened) 2.00 (0.991, 4.036) (Improved or Same) vs. Worsened 1.45 (0.793, 2.641) Comment: Please discuss the appropriateness of the proportional odds assumption. Panel Presentation FDA Statistical Review

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 Panel Presentation FDA Statistical Review

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 Treatment N=148 Control N=152 30 Days 7 (4.7%) 1 (0.7%) 12 months 19 (12.8%) 21 (13.8%) 24 months 22 (14.9%) 24 (15.8%) Up to CCD 25 (16.9%) 25 (16.4%) As of 4/15/2005 29 (19.6%) 33 (21.7%) Panel Presentation FDA Statistical Review

Separate Analysis of Change in NYHA Component of Primary Endpoint Patients who had MCP or died do not have recorded NYHA at CCD Model Odds Ratio 95% CI p No imputation; available NYHA data only (FDA) CorCap: N=52 Control: N=45 1.61 (0.71, 3.65) 0.25 Linear regression imputation CorCap: N=107 Control: N=99 1.64 (0.87, 3.08) 0.12 + assume class IV for MCP 1.74 (1.00, 3.02) 0.049 Panel Presentation FDA Statistical Review

Analysis of MCP Contribution to Primary Endpoint CorCap Control CMH Odds Ratio (95% CI) 19/148 = 12.8% 33/152 = 22% 2.22 (1.16, 4.20) p = 0.014 Panel Presentation FDA Statistical Review

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. Panel Presentation FDA Statistical Review

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 Panel Presentation FDA Statistical Review

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. Panel Presentation FDA Statistical Review

“Major” Secondary Endpoints Difference in mean change over time (CorCap – Control) Adjusted p Site NYHA -0.04 0.98 LVEF 0.83% MLHF -4.47 0.12 LVEDV -17.9 0.032 Panel Presentation FDA Statistical Review

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. Panel Presentation FDA Statistical Review

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

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 Panel Presentation FDA Statistical Review

Within-stratum Analyses of Primary Endpoint MVR stratum X Treatment not found to be significant Model Odds Ratio 95% CI NO MVR Stratum N = 107 2.57 (1.09, 6.08) MVR Stratum N = 193 1.51 (0.84, 2.72) Panel Presentation FDA Statistical Review

Within-stratum Analyses - by component MCPs Change in core NYHA from baseline   CorCap Control CMH Odds Ratio (95% CI) No MVR N = 107 5/57 = 8.8% 12/50=24% 3.70 (1.12, 12.5) MVR N = 193 14/91=15.4% 21/102=20.6% 1.63 (0.76, 3.57) Model Odds Ratio 95% CI NO MVR Stratum N = 107 2.37 (0.72, 7.72) MVR Stratum N = 193 1.45 (0.66, 3.20) Panel Presentation FDA Statistical Review

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 Panel Presentation FDA Statistical Review

FDA Statistical Review 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 Panel Presentation FDA Statistical Review

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 Panel Presentation FDA Statistical Review