Literature DB >> 2006355

On estimating efficacy from clinical trials.

A Sommer1, S L Zeger.   

Abstract

We define 'biologic efficacy' as the effect of treatment for all persons who receive the therapeutic agent to which they were assigned. It measures the biologic action of treatment among compliant persons. In a randomized trial with one treatment and one placebo control, one can theoretically estimate efficacy by comparing persons who complete the treatment regimen with controls who similarly complete the control regimen. In practice, however, we make this comparison with reservation because a control protocol often presents a different challenge for compliance than does the treatment, so that the compliant subgroups are not comparable. Standard practice employs intent-to-treat comparisons in which one compares those randomized to treatment and control without reference to whether they actually received the treatment. Intent-to-treat comparisons estimate the 'programmatic effectiveness' of a treatment rather than its biologic efficacy. This paper introduces and derives the statistical properties of an alternative estimator of biologic efficacy that avoids the potential selection bias inherent in a comparison of compliant subgroups. The method applies to randomized trials with a dichotomous outcome measure, whether or not a placebo is given to the control group. The idea is to compare the compliers in the treatment group to an inferred control subgroup chosen to eliminate selection bias. The methodology was motivated by and is illustrated in the analysis of a randomized community trial of the impact of vitamin A supplementation on children's mortality.

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Year:  1991        PMID: 2006355     DOI: 10.1002/sim.4780100110

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  54 in total

Review 1.  What is meant by intention to treat analysis? Survey of published randomised controlled trials.

Authors:  S Hollis; F Campbell
Journal:  BMJ       Date:  1999-09-11

2.  Principal stratification in causal inference.

Authors:  Constantine E Frangakis; Donald B Rubin
Journal:  Biometrics       Date:  2002-03       Impact factor: 2.571

Review 3.  Is intent-to-treat analysis always (ever) enough?

Authors:  Lewis B Sheiner
Journal:  Br J Clin Pharmacol       Date:  2002-08       Impact factor: 4.335

Review 4.  Optimising the economic efficiency of drug studies.

Authors:  M E Kitler
Journal:  Pharmacoeconomics       Date:  1992-11       Impact factor: 4.981

5.  Semiparametric transformation models for causal inference in time to event studies with all-or-nothing compliance.

Authors:  Wen Yu; Kani Chen; Michael E Sobel; Zhiliang Ying
Journal:  J R Stat Soc Series B Stat Methodol       Date:  2015-03-01       Impact factor: 4.488

Review 6.  Post-randomisation exclusions: the intention to treat principle and excluding patients from analysis.

Authors:  Dean Fergusson; Shawn D Aaron; Gordon Guyatt; Paul Hébert
Journal:  BMJ       Date:  2002-09-21

7.  Nonparametric inference for assessing treatment efficacy in randomized clinical trials with a time-to-event outcome and all-or-none compliance.

Authors:  Robert M Elashoff; Gang Li; Ying Zhou
Journal:  Biometrika       Date:  2012-03-20       Impact factor: 2.445

8.  Adverse events after mass azithromycin treatments for trachoma in Ethiopia.

Authors:  Berhan Ayele; Teshome Gebre; Jenafir I House; Zhaoxia Zhou; Charles E McCulloch; Travis C Porco; Bruce D Gaynor; Paul M Emerson; Thomas M Lietman; Jeremy D Keenan
Journal:  Am J Trop Med Hyg       Date:  2011-08       Impact factor: 2.345

9.  Latent subgroup analysis of a randomized clinical trial through a semiparametric accelerated failure time mixture model.

Authors:  L Altstein; G Li
Journal:  Biometrics       Date:  2013-02-05       Impact factor: 2.571

Review 10.  Adaptive designs for randomized trials in public health.

Authors:  C Hendricks Brown; Thomas R Ten Have; Booil Jo; Getachew Dagne; Peter A Wyman; Bengt Muthén; Robert D Gibbons
Journal:  Annu Rev Public Health       Date:  2009       Impact factor: 21.981

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