Literature DB >> 25364768

HETEROGENEITY IN TREATMENT EFFECT AND COMPARATIVE EFFECTIVENESS RESEARCH.

Zhehui Luo1.   

Abstract

The ultimate goal of comparative effectiveness research (CER) is to develop and disseminate evidence-based information about which interventions are most effective for which patients under what circumstances. To achieve this goal it is crucial that researchers in methodology development find appropriate methods for detecting the presence and sources of heterogeneity in treatment effect (HTE). Comparing with the typically reported average treatment effect (ATE) in randomized controlled trials and non-experimental (i.e., observational) studies, identifying and reporting HTE better reflect the nature and purposes of CER. Methodologies of CER include meta-analysis, systematic review, design of experiments that encompasses HTE, and statistical correction of various types of estimation bias, which is the focus of this review.

Entities:  

Year:  2011        PMID: 25364768      PMCID: PMC4212262     

Source DB:  PubMed          Journal:  China Health Rev        ISSN: 2325-1549


  11 in total

1.  Practical clinical trials: increasing the value of clinical research for decision making in clinical and health policy.

Authors:  Sean R Tunis; Daniel B Stryer; Carolyn M Clancy
Journal:  JAMA       Date:  2003-09-24       Impact factor: 56.272

2.  Sensitivity analyses for unmeasured confounding assuming a marginal structural model for repeated measures.

Authors:  Babette A Brumback; Miguel A Hernán; Sebastien J P A Haneuse; James M Robins
Journal:  Stat Med       Date:  2004-03-15       Impact factor: 2.373

3.  Beyond efficacy: the STAR*D trial.

Authors:  Thomas R Insel
Journal:  Am J Psychiatry       Date:  2006-01       Impact factor: 18.112

4.  Sequential causal inference: application to randomized trials of adaptive treatment strategies.

Authors:  Ree Dawson; Philip W Lavori
Journal:  Stat Med       Date:  2008-05-10       Impact factor: 2.373

5.  Demystifying optimal dynamic treatment regimes.

Authors:  Erica E M Moodie; Thomas S Richardson; David A Stephens
Journal:  Biometrics       Date:  2007-06       Impact factor: 2.571

6.  Does comparative-effectiveness research threaten personalized medicine?

Authors:  Alan M Garber; Sean R Tunis
Journal:  N Engl J Med       Date:  2009-05-07       Impact factor: 91.245

7.  A pragmatic-explanatory continuum indicator summary (PRECIS): a tool to help trial designers.

Authors:  Kevin E Thorpe; Merrick Zwarenstein; Andrew D Oxman; Shaun Treweek; Curt D Furberg; Douglas G Altman; Sean Tunis; Eduardo Bergel; Ian Harvey; David J Magid; Kalipso Chalkidou
Journal:  J Clin Epidemiol       Date:  2009-05       Impact factor: 6.437

8.  Improving health by taking it personally.

Authors:  Ralph Snyderman; Michaela A Dinan
Journal:  JAMA       Date:  2010-01-27       Impact factor: 56.272

9.  Individualization at the heart of comparative effectiveness research: the time for i-CER has come.

Authors:  Anirban Basu
Journal:  Med Decis Making       Date:  2009 Nov-Dec       Impact factor: 2.583

10.  Evidence-based medicine, heterogeneity of treatment effects, and the trouble with averages.

Authors:  Richard L Kravitz; Naihua Duan; Joel Braslow
Journal:  Milbank Q       Date:  2004       Impact factor: 4.911

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