Statistical review of p040049 acorn s corcap cardiac support device
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Statistical Review of P040049 Acorn’s CorCap Cardiac Support Device. Laura Thompson, Ph.D. Mathematical Statistician CDRH/FDA. Outline. Study Design Primary Endpoint Analysis Concerns Separate Analyses of Components of Primary Endpoint Analyses of Secondary Endpoints

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Statistical review of p040049 acorn s corcap cardiac support device l.jpg

Statistical Review of P040049 Acorn’s CorCap Cardiac Support Device

Laura Thompson, Ph.D.

Mathematical Statistician

CDRH/FDA

FDA Statistical Review


Outline l.jpg
Outline Support Device

  • 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


Study design l.jpg
Study Design Support Device

  • 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


Primary endpoint l.jpg
Primary Endpoint Support Device

  • 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


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Differences in Baseline Characteristics across Treatments Support Device

  • 42 baseline covariates examined

  • 4 lowest p-values

FDA Statistical Review


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Explanatory Variables used in Primary Endpoint Analysis Support Device

  • 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


Primary endpoint model proportional odds l.jpg
Primary Endpoint Model - Proportional Odds Support Device

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


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Proportional Odds Property Support Device(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


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Non-Proportional Odds Support Device(non-constant log odds)

Hypothetical

Illustration

vs. Worsened

vs. Same or Worsened

Comment:

Is Proportional Odds assumption appropriate for the data?

FDA Statistical Review


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Missing Data in Primary Endpoint Support Device

  • 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


Slide11 l.jpg

Imputation Models Support Device

  • 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


Imputation models l.jpg
Imputation Models Support Device

  • 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


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Assumption: Support DeviceMissing 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



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Analysis of Primary Endpoint Enrollees

FDA Statistical Review


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Concerns about Imputation Enrollees

  • 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


Slide17 l.jpg

Concern about Proportional Odds Assumption Enrollees

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


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Separate Analyses of Components of Primary Endpoint Enrollees

  • 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


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Separate Analysis of Mortality Component of Primary Endpoint Enrollees

  • Log-rank test of difference in KM survival curves p = 0.85

Cumulative Number of Deaths by Time

FDA Statistical Review


Separate analysis of change in nyha component of primary endpoint l.jpg
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


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Analysis of MCP Contribution to Primary Endpoint Endpoint

FDA Statistical Review


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Difficulty of Re-operation after CorCap Endpoint

  • 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


Slide23 l.jpg

Pre-specified “Major” Secondary Endpoints Endpoint

  • 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


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Multiple Secondary Endpoints: EndpointA 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


Major secondary endpoints l.jpg
“Major” Secondary Endpoints Endpoint

FDA Statistical Review


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Other Secondary Endpoints Endpoint

  • 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


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Relationship between Structural and Functional Endpoints Endpoint

  • Low magnitude of correlation; low p-value does not imply high degree of concordance

p = 0.003

FDA Statistical Review


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Stratum-Specific Analyses: EndpointA 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


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Within-stratum Analyses of Primary Endpoint Endpoint

  • MVR stratum X Treatment not found to be significant

FDA Statistical Review


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Within-stratum Analyses - by component Endpoint

  • MCPs

  • Change in core NYHA from baseline

FDA Statistical Review


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Within-stratum Analyses of Primary Endpoint 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


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Statistical Summary Endpoint

  • 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


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Statistical Summary (cont) Endpoint

  • 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


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