ABE results from SAS and WinNolin are not matched [Regulatives / Guidelines]
Hi, Please help on the issue.
when I compared the ABE (Proc Mixed) output between SAS (FDA Draft Guidance on Progesterone, SAS code) and WinNonlin, they are not matched. For the given dataset (see code and dataset below)
SAS
ratio/ unscabe_lower/ unscabe_upper
135.096 / 115.546 / 157.954
WinNolin BE tool:
Ratio_%Ref_/ CI_90_Lower/ CI_90_Upper
Ln(Cmax)/ 74.0214/ 63.3096 /86.54555
Phoenix FDA RSABE Full Replicate template v1.4:
Dependent/ Ratio_%Ref_/ CI_90_Lower/ CI_90_Upper/
Data/ 74.021385/ 63.3096/ 86.54555/
However, if I change “TRT 1 -1” to “TRT -1 1” in “ESTIMATE 'T vs. R' TRT 1 -1 /CL ALPHA=0.1 in below SAS code ” I got them matched.
ratio/ unscabe_lower/ unscabe_upper
74.021385/ 63.3096/ 86.54555
I am wondering.
1. If anyone have same issue?
2. if we should change ESTIMATE 'T vs. R' to “TRT -1 1” since discussion in this Forum and FDA SAS code indicate we should use “TRT 1 -1” not “TRT -1 1”
3. If not how to deal this issue to make it consistent for results from two side?
Thanks
David
data Pk;
input subj per seq$ trt$ Cmax;
datalines;
1 1 RRT R 8592.1516
1 2 RRT R 9991.7692
1 3 RRT T 7877.606
2 1 TRR T 18119.532
2 2 TRR R 13082.5504
2 3 TRR R 20443.9168
3 1 RTR R 9964.4028
3 2 RTR T 7849.2956
3 3 RTR R 9930.2392
4 1 RRT R 11545.9044
4 2 RRT R 9931.7044
4 3 RRT T 4738.6024
5 1 RTR R 24863.772
5 2 RTR T 18131.4312
5 3 RTR R 18598.8372
6 1 RTR R 18767.834
6 2 RTR T 9631.2328
6 3 RTR R 13983.2816
7 1 TRR T 12357.3376
7 2 TRR R 12691.0256
7 3 TRR R 18033.464
8 1 RRT R 12490.2528
8 2 RRT R 29039.6884
8 3 RRT T 7453.3548
9 1 TRR T 13225.8472
9 2 TRR R 16836.392
9 3 TRR R 18455.9432
10 1 TRR T 7004.77
10 2 TRR R 16164.5532
10 3 TRR R 14568.2016
11 1 TRR T 24770.8476
11 2 TRR R 18791.1712
11 3 TRR R 20901.2328
12 1 RTR R 13570.0112
12 2 RTR T 13299.33
12 3 RTR R 14449.334
13 1 RRT R 16827.2456
13 2 RRT R 18581.1544
13 3 RRT T 13971.156
14 1 RRT R 10933.23
14 2 RRT R 15124.9448
14 3 RRT T 7768.3136
15 1 RTR R 10889.7196
15 2 RTR T 6809.4608
15 3 RTR R 10329.3052
16 1 RRT R 16119.3252
16 2 RRT R 20508.9744
16 3 RRT T 21888.374
;
run;
data pk;
set pk;
lauct=log(Cmax) ;
run;
PROC MIXED
data=pk;
CLASS SEQ SUBJ PER TRT;
MODEL LAUCT = SEQ PER TRT/ DDFM=SATTERTH;
RANDOM TRT/TYPE=FA0(2) SUB=SUBJ G;
REPEATED/GRP=TRT SUB=SUBJ;
ESTIMATE 'T vs. R' TRT 1 -1 /CL ALPHA=0.1;
ods output Estimates=unsc1;
title1 'unscaled BE 90% CI - guidance version';
title2 'AUCt';
run;
data unsc1;
set unsc1;
ratio=exp(estimate)*100;
unscabe_lower=exp(lower)*100;
unscabe_upper=exp(upper)*100;
run;
when I compared the ABE (Proc Mixed) output between SAS (FDA Draft Guidance on Progesterone, SAS code) and WinNonlin, they are not matched. For the given dataset (see code and dataset below)
SAS
ratio/ unscabe_lower/ unscabe_upper
135.096 / 115.546 / 157.954
WinNolin BE tool:
Ratio_%Ref_/ CI_90_Lower/ CI_90_Upper
Ln(Cmax)/ 74.0214/ 63.3096 /86.54555
Phoenix FDA RSABE Full Replicate template v1.4:
Dependent/ Ratio_%Ref_/ CI_90_Lower/ CI_90_Upper/
Data/ 74.021385/ 63.3096/ 86.54555/
However, if I change “TRT 1 -1” to “TRT -1 1” in “ESTIMATE 'T vs. R' TRT 1 -1 /CL ALPHA=0.1 in below SAS code ” I got them matched.
ratio/ unscabe_lower/ unscabe_upper
74.021385/ 63.3096/ 86.54555
I am wondering.
1. If anyone have same issue?
2. if we should change ESTIMATE 'T vs. R' to “TRT -1 1” since discussion in this Forum and FDA SAS code indicate we should use “TRT 1 -1” not “TRT -1 1”
3. If not how to deal this issue to make it consistent for results from two side?
Thanks
David
data Pk;
input subj per seq$ trt$ Cmax;
datalines;
1 1 RRT R 8592.1516
1 2 RRT R 9991.7692
1 3 RRT T 7877.606
2 1 TRR T 18119.532
2 2 TRR R 13082.5504
2 3 TRR R 20443.9168
3 1 RTR R 9964.4028
3 2 RTR T 7849.2956
3 3 RTR R 9930.2392
4 1 RRT R 11545.9044
4 2 RRT R 9931.7044
4 3 RRT T 4738.6024
5 1 RTR R 24863.772
5 2 RTR T 18131.4312
5 3 RTR R 18598.8372
6 1 RTR R 18767.834
6 2 RTR T 9631.2328
6 3 RTR R 13983.2816
7 1 TRR T 12357.3376
7 2 TRR R 12691.0256
7 3 TRR R 18033.464
8 1 RRT R 12490.2528
8 2 RRT R 29039.6884
8 3 RRT T 7453.3548
9 1 TRR T 13225.8472
9 2 TRR R 16836.392
9 3 TRR R 18455.9432
10 1 TRR T 7004.77
10 2 TRR R 16164.5532
10 3 TRR R 14568.2016
11 1 TRR T 24770.8476
11 2 TRR R 18791.1712
11 3 TRR R 20901.2328
12 1 RTR R 13570.0112
12 2 RTR T 13299.33
12 3 RTR R 14449.334
13 1 RRT R 16827.2456
13 2 RRT R 18581.1544
13 3 RRT T 13971.156
14 1 RRT R 10933.23
14 2 RRT R 15124.9448
14 3 RRT T 7768.3136
15 1 RTR R 10889.7196
15 2 RTR T 6809.4608
15 3 RTR R 10329.3052
16 1 RRT R 16119.3252
16 2 RRT R 20508.9744
16 3 RRT T 21888.374
;
run;
data pk;
set pk;
lauct=log(Cmax) ;
run;
PROC MIXED
data=pk;
CLASS SEQ SUBJ PER TRT;
MODEL LAUCT = SEQ PER TRT/ DDFM=SATTERTH;
RANDOM TRT/TYPE=FA0(2) SUB=SUBJ G;
REPEATED/GRP=TRT SUB=SUBJ;
ESTIMATE 'T vs. R' TRT 1 -1 /CL ALPHA=0.1;
ods output Estimates=unsc1;
title1 'unscaled BE 90% CI - guidance version';
title2 'AUCt';
run;
data unsc1;
set unsc1;
ratio=exp(estimate)*100;
unscabe_lower=exp(lower)*100;
unscabe_upper=exp(upper)*100;
run;
Complete thread:
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- Variable names, lexical order? Helmut 2023-04-21 15:45