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The challenges of evaluating dose response in flexible-dose trials using marginal structural models.
MedLine Citation:
PMID:  23060290     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Assessing dose response from flexible-dose clinical trials is problematic. The true dose effect may be obscured and even reversed in observed data because dose is related to both previous and subsequent outcomes. To remove selection bias, we propose marginal structural models, inverse probability of treatment-weighting (IPTW) methodology. Potential clinical outcomes are compared across dose groups using a marginal structural model (MSM) based on a weighted pooled repeated measures analysis (generalized estimating equations with robust estimates of standard errors), with dose effect represented by current dose and recent dose history, and weights estimated from the data (via logistic regression) and determined as products of (i) inverse probability of receiving dose assignments that were actually received and (ii) inverse probability of remaining on treatment by this time. In simulations, this method led to almost unbiased estimates of true dose effect under various scenarios. Results were compared with those obtained by unweighted analyses and by weighted analyses under various model specifications. The simulation showed that the IPTW MSM methodology is highly sensitive to model misspecification even when weights are known. Practitioners applying MSM should be cautious about the challenges of implementing MSM with real clinical data. Clinical trial data are used to illustrate the methodology. Copyright © 2012 John Wiley & Sons, Ltd.
Authors:
Ilya Lipkovich; Craig H Mallinckrodt; Douglas E Faries
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-10-12
Journal Detail:
Title:  Pharmaceutical statistics     Volume:  -     ISSN:  1539-1612     ISO Abbreviation:  Pharm Stat     Publication Date:  2012 Oct 
Date Detail:
Created Date:  2012-10-12     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101201192     Medline TA:  Pharm Stat     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2012 John Wiley & Sons, Ltd.
Affiliation:
Quintiles, Inc., Durham, NC 27703, NC, USA.
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