Document Detail


A causal proportional hazards estimator for the effect of treatment actually received in a randomized trial with all-or-nothing compliance.
MedLine Citation:
PMID:  12762446     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Survival data from randomized trials are most often analyzed in a proportional hazards (PH) framework that follows the intention-to-treat (ITT) principle. When not all the patients on the experimental arm actually receive the assigned treatment, the ITT-estimator mixes its effect on treatment compliers with its absence of effect on noncompliers. The structural accelerated failure time (SAFT) models of Robins and Tsiatis are designed to consistently estimate causal effects on the treated, without direct assumptions about the compliance selection mechanism. The traditional PH-model, however, has not yet led to such causal interpretation. In this article, we examine a PH-model of treatment effect on the treated subgroup. While potential treatment compliance is unobserved in the control arm, we derive an estimating equation for the Compliers PROPortional Hazards Effect of Treatment (C-PROPHET). The jackknife is used for bias correction and variance estimation. The method is applied to data from a recently finished clinical trial in cancer patients with liver metastases.
Authors:
T Loeys; E Goetghebeur
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Biometrics     Volume:  59     ISSN:  0006-341X     ISO Abbreviation:  Biometrics     Publication Date:  2003 Mar 
Date Detail:
Created Date:  2003-05-23     Completed Date:  2004-01-16     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  0370625     Medline TA:  Biometrics     Country:  United States    
Other Details:
Languages:  eng     Pagination:  100-5     Citation Subset:  IM    
Affiliation:
Clinical Biostatistics, Merck Sharp & Dohme (Europe), Clos du Lynx 5, 1200 Woluwe, Belgium. tom_loeys@merck.com
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Analysis of Variance
Bias (Epidemiology)
Causality
Computer Simulation
Data Interpretation, Statistical
Humans
Liver Neoplasms / secondary,  therapy
Patient Compliance*
Proportional Hazards Models*
Randomized Controlled Trials as Topic / methods*
Treatment Outcome

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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