post hoc pk parameter associations with clinical covariates/response

From: Meredith Goldwasser mgoldwas@gmail.com Subject: [NMusers] post hoc pk parameter associations with clinical covariates/response Date: Fri, 19 Aug 2005 15:02:03 -0400 Dear NONMEM users, I am a new NONMEM user and also new to the area of non-linear mixed effects modeling of pk data. In the clinical pk literature, I've seen predicted (post hoc) estimates of pk parameters for each subject generated from a population pk model and then used in standard association tests of covariates or models of response, e.g. using t-tests, Wilcoxon or Kruskal-Wallis tests to compare clearance between groups of subjects with or without a particular polymorphism, or using logistic regression to model toxicity on drug clearance. Is this two-step approach statistically appropriate? For instance, a standard assumption of these tests and models is independence between subjects, but it would appear that these predicted pk parameters are not independent. I've read some of the discussion of simultaneous versus sequential estimation in pk/pd analysis of Karlsson, Zhang, and others, but I'm not sure if this applies to the situation of associating pk estimates with a clinical or pharmacogenetic endpoint. Is a single endpoint like toxicity (dichotomous variable: yes or no) or survival outcome (time to event variable) considered to be PD data, as it's usually modeled in NONMEM with an Emax model? Finally, if the joint likelihood of the pk and outcome data are modeled simultaneously in the population pk model, does NONMEM provide frequentist-like inference measures, like a p-value of association between pk and the outcome variable, based on the posterior distributions? Any guidance or reference to relevant articles would be most appreciated. Meredith _______________________________________________________