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Mohamed Alosh, Ph.D. Kathleen Fritsch, Ph.D.
Shiowjen Lee, Ph.D. DBIII, OB, CDER, FDA
Efficacy Evaluation in Acne Clinical Trials
2
An Outline
1. Re-visit choice of primary endpoints
(statistical viewpoint)
2. Statistical analysis methods and datatransformations
3. Repeated measurements vs. final assessment
4. Effect of baseline severity
5. Final Comments
3
1. Primary Endpoints in Acne Trials
(Statistical Viewpoint)
Inflammatory, non-inflammatory, and Total Lesion Counts can be analyzed as final lesion counts change from baseline percent change
Investigator Global Evaluation (IGE)
4
Analysis of Change Scores
Pros Easy to interpret &
analyze
Attempts to remove influence of baseline counts
Cons Baseline may still have
influence since change is negatively correlated with final counts
Change and percent change scores may have highly skewed distributions (violates parametric tests)
5
Figure 1. Mean Lesion Counts by Type over Time(Drug X, Study 1)
0
20
40
60
80
100
0 4 8 12Week
Mea
n l
esio
n c
ou
nt
Tot. (act)Tot. (veh.)N-Inf (act.)N-Inf. (veh.)Inf. (act.)Inf. (veh.)
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Figure 2. Mean Lesion Counts by Type over Time(Drug Y, Study 2)
0
20
40
60
80
100
0 1 2 3 4 5 6Cycle
Mea
n le
sion
cou
nt
Tot. (act.)Tot. (pbo.)N-Inf. (act.)N-Inf. (pbo.)Inf. (act.)Inf. (pbo.)
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Figure 3. Inflammatory Counts at Week 12 vs. Baseline Count (Drug X, Vehicle Arm)
Vehicle Arm - Drug X
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40
50
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70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Infl. Count at Baseline
Infl
. C
ou
nt
at W
eek
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0 - 100% Reduction
0 - 100% Increase
>100% Increase
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Figure 4. Inflammatory Counts at Week 12 vs. Baseline Count (Drug X, Active Arm)
Active Arm - Drug X
0
20
40
60
80
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120
0 20 40 60 80 100 120
Infl. Count at Baseline
Infl
. C
ou
nt
at W
eek
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0 - 100% Reduction
0 - 100% Increase
>100% Increase
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Figure 5. Mean % Change in Infl. Lesions over Time (Drug X, Study 1)
-60
-40
-20
0
20
40
60
80
100
0 4 8 12
Week
mea
n %
ch
ang
e
Act. (mean)Veh. (mean)
+/- sd (Act.)+/- sd (Veh.)
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0
50
100
150
200
250
0 4 8 12Week
Mea
n le
sion
cou
nt
Subj.1 (veh.)Subj.2 (veh.)Subj.3 (veh.)Subj.4 (veh.)Subj.5 (act.)Subj.6 (act.)Subj.7 (act.)Subj.8 (act.)
Figure 6. Subject’s Total Lesion Count over Time -- Center A (Drug X, Study 1)
11
2. Statistical Analysis Issues(a) Analysis units
original transformed data (ranks, log, etc.)
(Pros & Cons)
(b) Analysis methods for final study endpoint Simple comparisons ANOVA (treatment, center, interaction) ANCOVA (include baseline count as covariate)
(Comparison of results presented in Tables 1a-c & Tables 2a-c)
12
3. Repeated Measures vs. Final Assessment
Repeated measures may increase power for detecting treatment effect
Must select number of timepoints to be included in repeated measurements model
Repeated Measures Models:
MANOVA, GLM, MIXED (Comparison of results presented in Tables 1a-c &
Tables 2a-c))
13
Table 1a: Treatment effect p-values for various statistical methods (Drug X, Study 1)
COUNTS Infl. Lesions Non-Inf. Les. Total Lesions
Data Ranks Data Ranks Data Ranks
Week 12 0.130 0.044 0.002 <0.001 0.002 <0.001
Week 8 0.308 0.222 0.003 0.002 0.005 <0.001
Week 4 0.834 0.917 0.270 0.418 0.325 0.293
ANCOVA 0.062 0.013 <0.001 <0.001 <0.001 <0.001
MANOVA 0.306 0.069 <0.001 <0.001 <0.001 <0.001
GLM (R) 0.316 0.219 0.010 0.006 0.013 0.003ANCOVA (R) 0.155 0.075 <0.001 <0.001 <0.001 <0.001
Mean Count (18.4, 20.6)* (37.4, 46.7)* (55.8, 67.2)*
*(active, vehicle) (R) = Repeated Measures
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Table 1b: Treatment effect p-values for various statistical methods (Drug X, Study 1)
CHANGE Infl. Lesions Non-Inf. Les. Total Lesions
Data Ranks Data Ranks Data Ranks
Week 12 0.031 0.040 <0.001 <0.001 <0.001 <0.001
Week 8 0.116 0.132 <0.001 0.001 <0.001 <0.001
Week 4 0.429 0.789 0.020 0.021 0.027 0.030
ANCOVA 0.035 0.050 <0.001 <0.001 <0.001 <0.001
MANOVA 0.176 0.158 <0.001 <0.001 <0.001 <0.001
GLM (R) 0.081 0.134 <0.001 <0.001 <0.001 <0.001ANCOVA (R) 0.091 0.143 <0.001 <0.001 <0.001 <0.001
Mean Chnge (9.2, 6.4)* (26.0, 15.5)* (35.1, 21.9)*
*(active, vehicle) (R) = Repeated Measures
15
Table 1c: Treatment effect p-values for various statistical methods (Drug X, Study 1)
% CHANGE Infl. Lesions Non-Inf. Les. Total Lesions
Data Ranks Data Ranks Data Ranks
Week 12 0.012 0.008 <0.001 <0.001 <0.001 <0.001
Week 8 0.201 0.108 <0.001 0.001 <0.001 <0.001
Week 4 0.498 0.712 0.050 0.037 0.023 0.034
ANCOVA 0.015 0.009 <0.001 <0.001 <0.001 <0.001
MANOVA 0.067 0.046 <0.001 <0.001 <0.001 <0.001
GLM (R) 0.079 0.061 <0.001 <0.001 <0.001 <0.001ANCOVA (R) 0.061 0.053 <0.001 <0.001 <0.001 <0.001
Mean % Ch. (32.1, 21.4)* (41.1, 24.8)* (38.8, 24.8)*
*(active, vehicle) (R) = Repeated Measures
16
Comments on Results for Drug Xresults for total are similar to non-infl.
(strong corr., highly signif.)no general pattern for ranks vs. original datafor infl. lesions, % change has smaller
p-values than counts or change for change and % change, ANCOVA has
similar results to Week 12 analysisp-values for rep. meas. in general are larger
than final study endpoint analysis (prev. weeks not signif.)
17
Table 2a: Treatment effect p-values for various statistical methods (Drug Y, Study 2)
COUNTS Infl. Lesions Non-Inf. Les. Total Lesions
Data Ranks Data Ranks Data Ranks
Cycle 6 0.020 0.018 0.294 0.071 0.161 0.022
Cycle 5 0.031 0.024 0.636 0.231 0.327 0.072
Cycle 4 0.160 0.375 0.803 0.099 0.561 0.098
ANCOVA 0.014 0.032 0.044 0.017 0.015 <0.001
MANOVA 0.065 0.058 0.479 0.154 0.354 0.021
GLM (R) 0.020 0.031 0.415 0.120 0.211 0.023ANCOVA (R) 0.015 0.016 0.072 0.030 0.021 0.001
Mean Count (13.7, 16.2)* (43.6, 49.2)* (57.3, 65.3)*
*(active, vehicle) (R) = Repeated Measures
18
Table 2b: Treatment effect p-values for various statistical methods (Drug Y, Study 2)
CHANGE Infl. Lesions Non-Inf. Les. Total Lesions
Data Ranks Data Ranks Data Ranks
Cycle 6 0.060 0.036 0.027 0.001 0.010 <0.001
Cycle 5 0.016 0.007 0.204 0.024 0.063 0.002
Cycle 4 0.117 0.124 0.240 0.014 0.118 0.001
ANCOVA 0.014 0.023 0.044 <0.001 0.015 <0.001
MANOVA 0.097 0.046 0.087 0.018 0.035 0.003
GLM (R) 0.037 0.017 0.043 0.008 0.013 0.001ANCOVA (R) 0.015 0.009 0.072 0.003 0.021 <0.001
Mean Chnge (8.1, 3.7)* (6.6, -2.4)* (14.7, 3.3)*
*(active, vehicle) (R) = Repeated Measures
19
Table 2c: Treatment effect p-values for various statistical methods (Drug Y, Study 2)
% CHANGE Infl. Lesions Non-Inf. Les. Total Lesions
Data Ranks Data Ranks Data Ranks
Cycle 6 0.097 0.017 0.021 0.005 0.002 <0.001
Cycle 5 0.078 0.010 0.078 0.020 0.010 0.004
Cycle 4 0.249 0.188 0.039 0.012 0.021 0.004
ANCOVA 0.096 0.016 0.037 0.004 0.004 <0.001
MANOVA 0.203 0.030 0.071 0.016 0.010 <0.001
GLM (R) 0.076 0.009 0.035 0.005 0.003 <0.001ANCOVA (R) 0.074 0.008 0.061 0.005 0.005 <0.001
Mean % Ch. (31.0, 22.0)* (13.2, -5.2)* (22.6, 8.5)**(active, vehicle) (R) = Repeated Measures
20
Comments on Results for Drug Y
results for total & non-infl. are similar, as for X (but here less signif.)
no general pattern for ranks vs. original datafor infl. lesions, % change has larger
p-values than counts or change for change and % change, ANCOVA has
similar results to Cycle 6 analysisp-values for GLM(R)/ANCOVA(R) in
general are smaller than final study endpoint
21
4. Effect of Baseline Severity
Divide subjects into equal sized groups (e.g., quartiles) based on baseline lesion countPlots of lesion counts by baseline category
Compare efficacy results by baseline category Tables 3a-b present results for lesion counts Tables 4a-b present results for IGE
22
Figure 7. Mean Week 12 Lesion Counts by Type over Baseline Category (Drug X, Study 1)
0
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1 2 3 4
Baseline Category
Me
an
Le
sio
n C
ou
nt
Infl - Act
Infl - Veh
Non-Inf - Act
Non-Inf - Veh
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Figure 8. Mean Cycle 6 Lesion Counts by Type over Baseline Category (Drug Y, Study 2)
0
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120
1 2 3 4
Baseline Category
Me
an
Le
sio
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Infl - Act
Infl - Pbo
Non-Inf - Act
Non-Inf - Pbo
24
Table 3.a. Treatment Effect at Week 12 by Baseline Category (Drug X, Study 1)
Baseline Category1 2 3 4
Counts Act Veh Dif Act Veh Dif Act Veh Dif Act Veh DifInf. 13.3 13.2 0.1 17.0 20.0 -3.0 19.4 22.9 -3.5 23.2 26.8 -3.6Non. 18.1 23.5 -5.4 25.7 36.7 -11.0 41.3 47.0 -5.7 59.7 85.6 -25.9Total 31.4 36.7 -5.3 42.7 56.6 -13.9 60.8 69.8 -9.0 82.9 112.5 -29.5ChangeInf. 6.2 4.3 1.9 7.6 6.0 1.6 8.3 6.9 1.4 13.6 8.9 4.7Non 14.7 10.9 3.8 19.1 7.8 11.3 24.1 17.5 6.6 42.5 26.6 15.9Total 20.9 15.3 5.6 26.7 13.9 12.8 32.3 24.4 7.9 56.1 35.4 20.7% ChgInf. 30.9 24.4 6.5 28.4 18.4 10.0 32.2 17.7 14.5 35.9 26.8 9.1Non 44.0 31.2 12.8 41.3 17.0 24.3 35.8 27.2 8.6 42.6 21.9 20.7Total 40.2 29.4 10.8 38.3 19.1 19.2 35.3 26.2 9.1 40.8 23.5 17.3
25
Table 3.b. Comparison of IGE Success* Rates at Week 12 by Baseline Category (Drug X, Study 1)
*Success = None or Minimal Acne
26
Table 4.a. Treatment Effect at Cycle 6 by Baseline Category (Drug Y, Study 2)
Baseline Category1 2 3 4
Counts Act Pbo Dif Act Pbo Dif Act Pbo Dif Act Pbo DifInf. 9.6 10.2 -0.6 11.8 12.0 -0.3 14.5 17.4 -2.9 18.9 24.4 -5.5Non. 10.3 13.2 -2.9 17.7 22.5 -4.8 38.9 44.0 -5.2 110.7 112.3 -1.6Total 21.7 25.8 -4.1 33.5 35.8 -2.2 50.2 60.0 -9.8 127.6 139.5 -11.9ChangeInf. 1.9 1.5 0.4 39. 3.5 0.4 7.4 4.2 3.2 19.7 13.9 5.8Non 1.0 -1.8 2.7 4.6 -0.5 5.1 7.3 0.2 7.1 13.7 -7.1 20.8Total 5.4 0.8 4.6 9.4 7.5 1.9 19.5 11.2 8.3 25.1 -5.6 30.7% ChgInf. 14.8 12.3 2.5 25.1 21.4 3.6 33.9 19.4 14.5 49.9 36.2 13.7Non 5.4 -17.7 23.1 20.2 -6.7 26.9 14.8 3.1 11.7 11.8 0.3 11.5Total 19.2 2.8 16.4 23.0 17.7 5.3 28.3 15.5 12.7 19.5 -0.8 20.3
27
Baseline CategoryTreat.
1 2 3 4
Overall
Active 28/43
(65%)
25/51
(49%)
21/46
(46%)
15/44
(34%)
89/184
(48%)
Placebo 28/49
(57%)
17/42
(40%)
12/46
(26%)
12/47
(26%)
69/184
(38%)
Trt effect()
8% 9% 20% 8% 10%
(% success in active group – % success in placebo group)
Table 4.b. Comparison of IGE Success* Rates by Baseline Category (Drug Y, Study 2)
*Success = ‘Clear’ or ‘Almost Clear/Mild’
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Comments about efficacy results by baseline category
For the two drugs considered, no general pattern for results for lesion counts by type, their change, or percent change
Similarly, for the two drugs considered, there is also no general pattern for the IGE
For the range of lesion counts in these studies, efficacy results do not appear to vary by baseline severity
29
5. Final Comments
(a) Analysis of change from baseline, percent change, and final counts with baseline as covariate attempt to account for variability at baseline
(b) Percent change data could have extreme outliers when the baseline count is relatively small (e.g., inflammatory lesions)
30
Final Comments (cont’d)(c) Repeated measurements approach attempts
to reduce the influence of outliers (flares) by ‘averaging’ over time.
The impact of the repeated measures on the p-value depends on whether efficacy reached a plateau at previous time points.
(d) For the data sets considered, treatment efficacy did not vary by baseline severity whether one considers analysis of lesion counts or IGE