# Presentation: 687694

## Statistical Review of P040049 Acorn’s CorCap Cardiac Support Device

- Laura Thompson, Ph.D.
- Mathematical Statistician
- CDRH/FDA

- FDA Statistical Review

- Panel Presentation

## 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

- Panel Presentation

## 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

- Panel Presentation

## 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

- Panel Presentation

## 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 |

- FDA Statistical Review

- Panel Presentation

## 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

- Panel Presentation

## 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

- Panel Presentation

## 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

- Panel Presentation

## Non-Proportional Odds (non-constant log odds)

- Hypothetical
- Illustration

- vs. Same or Worsened

- vs. Worsened

**Comment:***** ***
***Is Proportional Odds assumption appropriate for the data?***

- FDA Statistical Review

- Panel Presentation

## 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

- Panel Presentation

## 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

- Panel Presentation

## 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

- Panel Presentation

## 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

- Panel Presentation

## 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 |

- FDA Statistical Review

- Panel Presentation

## 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 |

- FDA Statistical Review

- Panel Presentation

## 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

- Panel Presentation

**Notes:**

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.

## 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.*

- FDA Statistical Review

- Panel Presentation

## 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

- Panel Presentation

## 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%) |

- FDA Statistical Review

- Panel Presentation

## 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 |
| Linear regression imputation
+ assume class IV for MCP | 1.74 | (1.00, 3.02) | 0.049 |

- FDA Statistical Review

- Panel Presentation

## 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 |

- FDA Statistical Review

- Panel Presentation

## 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

- Panel Presentation

## 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

- Panel Presentation

## 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

- Panel Presentation

## “Major” Secondary Endpoints

|  | Difference in mean change over time (CorCap – Control) | Adjusted p |
| --- | --- | --- |
| Site NYHA | -0.04 | 0.98 |
| LVEF | 0.83% | 0.98 |
| MLHF | -4.47 | 0.12 |
| LVEDV | -17.9 | 0.032 |

- FDA Statistical Review

- Panel Presentation

## 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

- Panel Presentation

## 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

- Panel Presentation

## 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

- Panel Presentation

## 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) |

- FDA Statistical Review

- Panel Presentation

## 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) |

- FDA Statistical Review

- Panel Presentation

## 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

- Panel Presentation

## 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

- Panel Presentation

## 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

- Panel Presentation