Dear Siwei,
If you have a time-varying covariate, you may want to entertain the extended models possible/necessary for time-varying, as opposed to time-constant, covariates. See Wählby et al Models for time-varying covariates in population pharmacokinetic-pharmacodynamic analysis. Br J Clin Pharmacol. 2004 Oct;58(4):367-77. Best regards, Mats Mats Karlsson, PhD Professor of Pharmacometrics Dept of Pharmaceutical Biosciences Faculty of Pharmacy Uppsala University Box 591 75124 Uppsala Phone: +46 18 4714105 Fax + 46 18 4714003 <http://www.farmbio.uu.se/research/researchgroups/pharmacometrics/> www.farmbio.uu.se/research/researchgroups/pharmacometrics/ From: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com] On Behalf Of siwei Dai Sent: 26 August 2013 18:13 To: nmusers@globomaxnm.com Subject: Re: [NMusers] Time-varing covariate Hi, Sebastien, Bill, Nick, Leonid, Mats and Hans: Thank you all very much for the suggestions and nice discussions. I enjoyed to learn from this thread and I am very clear how this should be handled now. I believe this thread also provided a nice record for other new folks like me to learn from. Thanks a lot. Best regards, Siwei On Fri, Aug 23, 2013 at 1:10 PM, Nick Holford <n.holf...@auckland.ac.nz> wrote: Siwei, I don't know why you think this complicated. Suppose you have age (AGE) as a covariate. This must of course be a time varying covariate if it is intended to be the current age. And you might have weight (WT) or creatinine clearance (CLCR) as covariates which typically change with time. So just code the $INPUT data items and use them as you wish e.g. $INPUT ID TIME AGE WT CLCR etc ... $PK ; CL=(CLnon-renal*f(age) + CLrenal*f(renal_function)) * allometric WT CL=(THETA(1)*EXP(THETA(2)*(AGE-40)) + THETA(3)*CLCR/100)*(WT/70)**0.75 EVID=4 has nothing to do with using time varying covariates. Perhaps you could explain more clearly what your problem is and why you think it is complicated to use time varying covariates? Best wishes, Nick On 23/08/2013 6:00 p.m., siwei Dai wrote: Hi, Dear NMusers: I want to add a time-varing covariate in my model. For example, blood pressure or blood flow as covariates. But I am not sure how to do it. I see some earlier threads to discuss it but they all use complicated methods. I am wondering if there are any new way to do it in NM 7.2? I see in the user guide that EVID=4 can indicate physiological change. Is this what I should use? Thank you very much for any suggestions. Best regards, Siwei -- Nick Holford, Professor Clinical Pharmacology Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand office:+64(9)923-6730 <tel:%2B64%289%29923-6730> mobile:NZ +64(21)46 23 53 <tel:%2B64%2821%2946%2023%2053> FR +33(7)85 36 84 99 <tel:%2B33%287%2985%2036%2084%2099> email: n.holf...@auckland.ac.nz http://holford.fmhs.auckland.ac.nz/ Holford NHG. Disease progression and neuroscience. Journal of Pharmacokinetics and Pharmacodynamics. 2013;40:369-76 http://link.springer.com/article/10.1007/s10928-013-9316-2 Holford N, Heo Y-A, Anderson B. A pharmacokinetic standard for babies and adults. J Pharm Sci. 2013: http://onlinelibrary.wiley.com/doi/10.1002/jps.23574/abstract Holford N. A time to event tutorial for pharmacometricians. CPT:PSP. 2013;2: http://www.nature.com/psp/journal/v2/n5/full/psp201318a.html Holford NHG. Clinical pharmacology = disease progression + drug action. British Journal of Clinical Pharmacology. 2013: http://onlinelibrary.wiley.com/doi/10.1111/bcp.12170/abstract
