RE: Truncated Emax

________________________________ From: Martin Bergstrand [mailto:[email protected]] Sent: Tuesday, December 20, 2011 08:27 To: 'Francois Gaudreault'; [email protected] Cc: 'Waqas Sadiq'; Elassaiss - Schaap, J. (Jeroen) Subject: RE: [NMusers] Truncated Emax Dear François, I do not agree with Jeroen that less than ~1/3 of total data censored is a guarantee for that these observations can be ignored without substantial bias. I think this is highly dependent on the nature of the model (system), the limit of quantification in relationship to Emax etc. To make a statement on what percentage of censored data (out of the total) that will result in negligible bias is never a good idea since it might be that only a small portion of the total data speaks to a specific parameter. If a substantial amount of that small portion of data is censored it can have important implications while it is still just a minor percentage that is missing out of the total. But importantly you do not need to take anyone's word for this since you can test it you self with simulation based diagnostics and/or simulation and re-estimation with the applied censoring. The way that I would go about this issue is that I would take into account also the censored observations. The below code is just a slight alteration of the M3 method suggested by S. Beal for the handling of observations below the limit o detection (BQL)[1]. More detail on how this is best implemented in NONMEM is given in a paper by Anh et.al [2]. Me and others have also several times discussed how to best diagnose models in the presence of censored observations (see NMusers archive). ;;; --------------------------------------------------------- $ERROR W = THETA(.) ; Residual error model (in this example simple additive) ULOQ = 10 ; Upper limit of detection (10mA) IPRED = PT ; Individual prediction of perception threshold according to your desired model DUM = (IPRED-ULOQ)/SIG CUMD = PHI(DUM) ; Flag variable CENS in dataset. CENS=1 => observation >ULOQ IF(CENS.EQ.0) THEN ; <ULOQ F_FLAG = 0 Y = IPRED+SIG*ERR(1) ENDIF IF(ALQ.EQ.1) THEN ; >ULOQ F_FLAG = 1 Y = CUMD ENDIF ;;; --------------------------------------------------------- Obs. When applying this code the SIGMA variance is fixed to 1 ($SIGMA 1 FIX) and the Lapalcian estimation option needs to be utilized (or possibly SAEM etc.) [2]. This type of coding have previously been successfully applied by my colleague Waqas Sadiq. A manuscript on this project is currently in preparation and might be referenced once published (look out). [1] Beal SL. Ways to fit a PK model with some data below the quantification limit. J Pharmacokinet Pharmacodyn. 2001 Oct;28(5):481-504. [2] Ahn JE, Karlsson MO, Dunne A, Ludden TM. Likelihood based approaches to handling data below the quantification limit using NONMEM VI. J Pharmacokinet Pharmacodyn. 2008 Aug 7. Kind regards, Martin Bergstrand, PhD Pharmacometrics Research Group Dept of Pharmaceutical Biosciences Uppsala University, Sweden [email protected]<mailto:[email protected]> Visiting scientist: Mahidol-Oxford Tropical Medicine Research Unit, Bangkok, Thailand Phone: +66 8 9796 7611 From: [email protected] [mailto:[email protected]] On Behalf Of Elassaiss - Schaap, J. (Jeroen) Sent: Tuesday, December 20, 2011 4:12 AM To: Francois Gaudreault; [email protected] Subject: RE: [NMusers] Truncated Emax Hi Francois, For pain measurements it is not uncommon to analyze data with a upper limit of quantitation. You can follow the literature on BQL, only reversing from a lower limit to an upper limIt. In my experience just deleting censored data works fine, certainly as a first attempt, as long as censoring stays below ~1/3 of total data. Best regards, Jeroen J. Elassaiss-Schaap Scientist PK/PD MSD PO Box 20, 5340 BH Oss, Netherlands Phone: + 31 412 66 9320 Fax: + 31 412 66 2506 e-mail: [email protected]<mailto:[email protected]> ________________________________ From: [email protected]<mailto:[email protected]> [mailto:[email protected]] On Behalf Of Francois Gaudreault Sent: Monday, December 19, 2011 21:40 To: [email protected]<mailto:[email protected]> Subject: [NMusers] Truncated Emax Dear NM users I am currently developing a PK PD model for local anesthetics using a sequential approach with ADVAN6. The PD model is a sigmoid Emax with an effect compartment (Ce). The intensity and duration of nerve blockade are monitored throughout the perioperative period in patients using a quantitative pharmacodynamic endpoint, i.e, the current perception threshold (CPT) REF: Can. J. Anesth, 57 (S1) 2010). Briefly, CPT is evaluated before and after the administration of the local anesthectic. Data are normalized by baseline using the following equation : (observed-baseline) / (max-baseline) *100 (%) Here is the problem. The device only goes to a maximum of 10 mA. In some patients, the real Emax is much higher. Any ideas on how handle a truncated Emax ? Thanks in advance -- François Gaudreault, Ph.D. Candidate Pharmacométrie / Pharmacometrics Charger de cours / Lecturer Faculté de pharmacie / Faculty of Pharmacy Université de Montréal Notice: This e-mail message, together with any attachments, contains information of Merck & Co., Inc. (One Merck Drive, Whitehouse Station, New Jersey, USA 08889), and/or its affiliates Direct contact information for affiliates is available at http://www.merck.com/contact/contacts.html) that may be confidential, proprietary copyrighted and/or legally privileged. It is intended solely for the use of the individual or entity named on this message. 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