Literature DB >> 7924127

A new approach to the analysis of analgesic drug trials, illustrated with bromfenac data.

L B Sheiner1.   

Abstract

A clinical trial of an analgesic agent compares pain relief scores (ordered categorical responses) over time among groups of patients, each subject to a painful procedure and given various doses of active agent (including zero, i.e., placebo) on demand. Patients may elect to remedicate with an active agent if their pain relief is insufficient, so the sample of patients at any given time is biased toward those with better relief. Standard analyses usually (1) fill in the missing data but make no correction for so doing and (2) treat the ordered categorical variable as continuous. Both of these create problems in interpretation and inference, but the former is more serious than the latter. An alternative analysis has been recently proposed that deals with these problems. This article presents that method for a nonstatistical audience and illustrates its use on some data from the analgesic bromfenac.

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Year:  1994        PMID: 7924127     DOI: 10.1038/clpt.1994.142

Source DB:  PubMed          Journal:  Clin Pharmacol Ther        ISSN: 0009-9236            Impact factor:   6.875


  41 in total

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2.  Modeling and stimulation for clinical trial design involving a categorical response: a phase II case study with naratriptan.

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3.  Modelling of pain intensity and informative dropout in a dental pain model after naproxcinod, naproxen and placebo administration.

Authors:  Marcus A Björnsson; Ulrika S H Simonsson
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4.  Evaluation of type I error rates when modeling ordered categorical data in NONMEM.

Authors:  Ulrika Wählby; Katalin Matolcsi; Mats O Karlsson; E Niclas Jonsson
Journal:  J Pharmacokinet Pharmacodyn       Date:  2004-02       Impact factor: 2.745

5.  Extending the latent variable model for extra correlated longitudinal dichotomous responses.

Authors:  Matthew M Hutmacher; Jonathan L French
Journal:  J Pharmacokinet Pharmacodyn       Date:  2011-10-22       Impact factor: 2.745

6.  Implementation and evaluation of the SAEM algorithm for longitudinal ordered categorical data with an illustration in pharmacokinetics-pharmacodynamics.

Authors:  Radojka M Savic; France Mentré; Marc Lavielle
Journal:  AAPS J       Date:  2010-11-11       Impact factor: 4.009

7.  A Minimal Continuous-Time Markov Pharmacometric Model.

Authors:  Emilie Schindler; Mats O Karlsson
Journal:  AAPS J       Date:  2017-06-20       Impact factor: 4.009

8.  Estimating bias in population parameters for some models for repeated measures ordinal data using NONMEM and NLMIXED.

Authors:  Siv Jönsson; Maria C Kjellsson; Mats O Karlsson
Journal:  J Pharmacokinet Pharmacodyn       Date:  2004-08       Impact factor: 2.745

9.  The back-step method--method for obtaining unbiased population parameter estimates for ordered categorical data.

Authors:  Maria C Kjellsson; Siv Jönsson; Mats O Karlsson
Journal:  AAPS J       Date:  2004-08-11       Impact factor: 4.009

Review 10.  Non-linear mixed effects modeling - from methodology and software development to driving implementation in drug development science.

Authors:  Goonaseelan Colin Pillai; France Mentré; Jean-Louis Steimer
Journal:  J Pharmacokinet Pharmacodyn       Date:  2005-11-07       Impact factor: 2.745

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