Literature DB >> 17146982

Detecting qualitative interactions in clinical trials: an extension of range test.

Jianjun Li1, Ivan S F Chan.   

Abstract

To help interpret a treatment effect in clinical trials, investigators usually examine whether the observed treatment effect is the same in various subsets of patients. The qualitative interaction, which means that the treatment is beneficial in some subsets and harmful in others, is of major importance. In this paper, a new statistical test is developed for detecting such interactions. The new test is an extension of the well-known range test, but utilizes all observed treatment differences rather than only the maximum and the minimum values. Extensive simulations indicate that the proposed extended range test generally outperforms the range test and is even better than the likelihood ratio test in the sense that the extended range test is much more powerful than the likelihood test when one treatment is superior to the other in most subsets and yet does not lose much power otherwise. It is also illustrated through a real clinical trial example that the extended range test detects the qualitative interaction while the range test and likelihood ratio test do not.

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Year:  2006        PMID: 17146982     DOI: 10.1080/10543400600801588

Source DB:  PubMed          Journal:  J Biopharm Stat        ISSN: 1054-3406            Impact factor:   1.051


  8 in total

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Review 4.  Considerations when assessing heterogeneity of treatment effect in patient-centered outcomes research.

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Review 5.  Subgroup analyses in confirmatory clinical trials: time to be specific about their purposes.

Authors:  Julien Tanniou; Ingeborg van der Tweel; Steven Teerenstra; Kit C B Roes
Journal:  BMC Med Res Methodol       Date:  2016-02-18       Impact factor: 4.615

6.  Selecting Optimal Subgroups for Treatment Using Many Covariates.

Authors:  Tyler J VanderWeele; Alex R Luedtke; Mark J van der Laan; Ronald C Kessler
Journal:  Epidemiology       Date:  2019-05       Impact factor: 4.822

7.  The Interaction Continuum.

Authors:  Tyler J VanderWeele
Journal:  Epidemiology       Date:  2019-09       Impact factor: 4.822

8.  Statistical Analysis Plan for Stage 1 EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care) Study.

Authors:  Eva Petkova; R Todd Ogden; Thaddeus Tarpey; Adam Ciarleglio; Bei Jiang; Zhe Su; Thomas Carmody; Philip Adams; Helena C Kraemer; Bruce D Grannemann; Maria A Oquendo; Ramin Parsey; Myrna Weissman; Patrick J McGrath; Maurizio Fava; Madhukar H Trivedi
Journal:  Contemp Clin Trials Commun       Date:  2017-02-24
  8 in total

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