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

2. 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

3. 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

4. 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

5. 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

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
Panel Presentation
FDA Statistical Review

7. 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

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
Panel Presentation
FDA Statistical Review

9. 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

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
Panel Presentation
FDA Statistical Review

11. 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

12. 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

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
Panel Presentation
FDA Statistical Review

14. 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

15. 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

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 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

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
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

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
Panel Presentation
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
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

20. 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

21. 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

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.
Panel Presentation
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
Panel Presentation
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.
Panel Presentation
FDA Statistical Review

25. “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

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.
Panel Presentation
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
Panel Presentation
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
Panel Presentation
FDA Statistical Review

29. 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

30. 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

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
Panel Presentation
FDA Statistical Review

32. 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

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
Panel Presentation
FDA Statistical Review