Setup in Phoenix/WinNonlin [Study Assessment]
❝ It is a very well known drug and many MR formulations are on the market. (You have experience with this drug).
If we are talking about the same goody: Watch out for polymorphism… Sometimes you have poor metabolizers in the study where enzymes get saturated at higher doses. In one subject I once got a slope of 1.54 for AUC and 2.16 for Cmax over a only twofold dose range! For the other subjects it got 1.05 and 1.02 with a very narrow CI.
❝ There are only two does levels to plot. The relationship is as follows:
❝
❝ LnPK=B0+B1*Ln(dose) where LnPK pertains to Cmax or AUC.
❝
❝ So we have a regression line going through the points: we evaluate the slope (B1), intercept
OK, so far.
❝ and the confidence intervals about the slope to evaluate dose proportionality.
This is beyond me. df = n – p where n is the number of data points and p the number of parameters. How can you calculate a CI with df = 0?
❝ Brian Smith in Pharm Research year 2000 has extended the approach from the original UK working party.
Yep. Smith et al. use a mixed-effects model, where subjects are a random effect. Thus we increase n. Now a CI is possible even for p = 2.
❝ It seems that you can calculate intrasubject and intersubject variance e.g. for AUC and partial AUC from this approach.
Correct.
❝ I do not follow how to do it. I use the usual intrasubject and intersubject values from Phoenix WinNonlin 6.4 and I am happy with that.
If you are happy with that, what is your question?

If you want to reproduce Smith’s results in Phoenix/WinNonlin: Start with a worksheet (columns subject, dose, Cmax, AUC, whatsoever). log-transform: dose, Cmax, … and weight=1/logCmax, … Send to LME. Map Subject as Classification, logCmax as Rgeressor, and logCmax as Dependent.
Model Specification: logCmax
Fixed Effects Confidence Level: 90%
Variance Structure / Random 1: Subject
With Smith’s Cmax-data of Table 1 I got for the slope:
0.7617 (90% CI: 0.6696, 0.8539), slightly different from the reported 0.7615 (0.679, 0.844). Why? Duno.
(jitter added to doses)
See also chapter 18.3 in Chow/Liu. Without explanation they recommend a 95% CI but a 90% CI in elaborating Smith’s approach. In general I prefer a weighted model (hence the transformation above). Fits much better.
SSQ AIC Var(Subject) Var(Res)
w = 1 0.07389 9.247 0.1120 0.01456
w = 1/logCmax 0.01548 -8.917 0.1108 0.003076
PS: Can you ask “the other worker” why he/she calculated the 98% CI?
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Helmut Schütz
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Science Quotes
Complete thread:
- Dose Proportionality and Variance AngusMcLean 2016-05-11 16:55 [Study Assessment]
- More information, please Helmut 2016-05-12 14:34
- More information, please AngusMcLean 2016-05-13 16:40
- Setup in Phoenix/WinNonlinHelmut 2016-05-14 02:26
- Setup in Phoenix/WinNonlin AngusMcLean 2016-05-14 18:54
- Setup in Phoenix/WinNonlin Helmut 2016-05-15 14:47
- Setup in Phoenix/WinNonlin AngusMcLean 2016-05-15 15:17
- Phoenix 64 Warning Helmut 2016-05-15 15:56
- Phoenix 64 Warning AngusMcLean 2016-05-15 20:11
- OT: imperial vs. metric units Helmut 2016-05-16 16:26
- Phoenix 64 Warning AngusMcLean 2016-05-15 20:11
- Setup in Phoenix/WinNonlin ElMaestro 2016-05-15 20:54
- Setup in Phoenix/WinNonlin AngusMcLean 2016-05-15 22:30
- Phoenix 64 Warning Helmut 2016-05-15 15:56
- Setup in Phoenix/WinNonlin AngusMcLean 2016-05-15 15:17
- Setup in Phoenix/WinNonlin Helmut 2016-05-15 14:47
- Setup in Phoenix/WinNonlin AngusMcLean 2016-05-16 21:00
- NCSS vs. PHX/WNL vs. SAS Helmut 2016-05-17 01:50
- NCSS vs. PHX/WNL vs. SAS - Validation? mittyri 2016-05-18 08:23
- Diagnostics ElMaestro 2016-05-18 09:20
- Diagnostics: R and Phoenix Helmut 2016-05-18 15:14
- Diagnostics: R zizou 2016-05-22 19:07
- Diagnostics: R Helmut 2016-05-23 01:22
- SASian potpourri d_labes 2016-05-24 12:02
- Compilation Helmut 2016-05-24 14:27
- REML or not d_labes 2016-05-24 16:33
- complete or not Helmut 2016-05-24 16:57
- Compilation AngusMcLean 2016-05-26 16:46
- doubts about NCSS Helmut 2016-05-26 19:13
- Doubts about NCSS zizou 2016-05-26 23:38
- doubts about NCSS Helmut 2016-05-26 19:13
- Compilation AngusMcLean 2016-05-28 00:51
- Kenward-Roger? Helmut 2016-05-28 15:59
- 90% confidence interval for R_dnm Shuanghe 2019-01-04 17:45
- 90% confidence interval for R_dnm d_labes 2019-01-05 14:01
- Visualizing lmer and limits mittyri 2019-01-06 17:00
- Visualizing lmer and limits Shuanghe 2019-01-07 11:05
- Visualizing lmer and limits d_labes 2019-01-07 15:08
- Visualizing lmer and limits mittyri 2019-01-13 23:53
- 90% confidence interval for R_dnm Shuanghe 2019-01-07 10:53
- 90% confidence interval for R_dnm d_labes 2019-01-07 15:17
- 90% confidence interval for R_dnm Shuanghe 2019-01-07 17:11
- 90% confidence interval for R_dnm d_labes 2019-01-07 18:24
- offtop: greek letters and tables mittyri 2019-01-08 00:19
- OT: greek letters and symbols Helmut 2019-02-02 16:04
- 90% confidence interval for R_dnm Shuanghe 2019-01-07 17:11
- 90% confidence interval for R_dnm d_labes 2019-01-07 15:17
- Visualizing lmer and limits mittyri 2019-01-06 17:00
- 90% confidence interval for R_dnm d_labes 2019-01-05 14:01
- REML or not d_labes 2016-05-24 16:33
- Compilation Helmut 2016-05-24 14:27
- SASian potpourri d_labes 2016-05-24 12:02
- Diagnostics: R Helmut 2016-05-23 01:22
- Diagnostics: R zizou 2016-05-22 19:07
- Diagnostics: R and Phoenix Helmut 2016-05-18 15:14
- Smith’s paper Helmut 2016-05-18 14:44
- Smith’s paper d_labes 2019-01-05 15:00
- Diagnostics ElMaestro 2016-05-18 09:20
- NCSS vs. PHX/WNL vs. SAS - Validation? mittyri 2016-05-18 08:23
- NCSS vs. PHX/WNL vs. SAS Helmut 2016-05-17 01:50
- Setup in Phoenix/WinNonlin AngusMcLean 2016-05-14 18:54
- Setup in Phoenix/WinNonlinHelmut 2016-05-14 02:26
- More information, please AngusMcLean 2016-05-13 16:40
- More information, please Helmut 2016-05-12 14:34