Literature DB >> 21490044

Remarks on antagonism.

Tyler J VanderWeele1, Mirjam J Knol.   

Abstract

Different forms of antagonism are classified in terms of response types and are related to the sufficient-cause framework. These forms of antagonism include "synergy under recoding of an exposure," "synergism under recoding of the outcome," and so-called "competing response types," with synergism itself conceived of as causal co-action within the sufficient-cause framework. In this paper, the authors show that subadditivity necessarily implies at least one of these 3 forms of antagonism. Empirical conditions for specific forms of antagonism are given for settings in which monotonicity assumptions are and are not considered plausible. The implications of subadditivity and superadditivity for causal co-action for either an outcome or its absence are characterized under various assumptions about monotonicity. A simple computational procedure is described for assessing whether any specific form of causal co-action can be detected for either an outcome or its absence for both cohort and case-control data. The results in this paper are illustrated by application to examples drawn from the existing literature on gene-gene and gene-environment interactions.

Mesh:

Year:  2011        PMID: 21490044      PMCID: PMC3121324          DOI: 10.1093/aje/kwr009

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  27 in total

1.  Sufficient cause interactions and statistical interactions.

Authors:  Tyler J VanderWeele
Journal:  Epidemiology       Date:  2009-01       Impact factor: 4.822

2.  Estimation of the relative excess risk due to interaction and associated confidence bounds.

Authors:  David B Richardson; Jay S Kaufman
Journal:  Am J Epidemiol       Date:  2009-02-11       Impact factor: 4.897

3.  The estimation of synergy or antagonism.

Authors:  K J Rothman
Journal:  Am J Epidemiol       Date:  1976-05       Impact factor: 4.897

4.  Marginal structural models for sufficient cause interactions.

Authors:  Tyler J Vanderweele; Stijn Vansteelandt; James M Robins
Journal:  Am J Epidemiol       Date:  2010-01-11       Impact factor: 4.897

5.  Epistatic interactions.

Authors:  Tyler J VanderWeele
Journal:  Stat Appl Genet Mol Biol       Date:  2010-01-06

6.  Sufficient cause interactions for categorical and ordinal exposures with three levels.

Authors:  Tyler J Vanderweele
Journal:  Biometrika       Date:  2010-06-01       Impact factor: 2.445

7.  Invariants and noninvariants in the concept of interdependent effects.

Authors:  S Greenland; C Poole
Journal:  Scand J Work Environ Health       Date:  1988-04       Impact factor: 5.024

Review 8.  Tests for interaction in epidemiologic studies: a review and a study of power.

Authors:  S Greenland
Journal:  Stat Med       Date:  1983 Apr-Jun       Impact factor: 2.373

9.  Causal interactions in the proportional hazards model.

Authors:  Tyler J VanderWeele
Journal:  Epidemiology       Date:  2011-09       Impact factor: 4.822

Review 10.  Epistasis--the essential role of gene interactions in the structure and evolution of genetic systems.

Authors:  Patrick C Phillips
Journal:  Nat Rev Genet       Date:  2008-11       Impact factor: 53.242

View more
  16 in total

1.  A mapping between interactions and interference: implications for vaccine trials.

Authors:  Tyler J VanderWeele; Jan P Vandenbroucke; Eric J Tchetgen Tchetgen; James M Robins
Journal:  Epidemiology       Date:  2012-03       Impact factor: 4.822

2.  Inference for additive interaction under exposure misclassification.

Authors:  Tyler J Vanderweele
Journal:  Biometrika       Date:  2012-04-02       Impact factor: 2.445

3.  Invited Commentary: The Continuing Need for the Sufficient Cause Model Today.

Authors:  Tyler J VanderWeele
Journal:  Am J Epidemiol       Date:  2017-06-01       Impact factor: 4.897

4.  Invited commentary: assessing mechanistic interaction between coinfecting pathogens for diarrheal disease.

Authors:  Tyler J Vanderweele
Journal:  Am J Epidemiol       Date:  2012-07-25       Impact factor: 4.897

5.  Sufficient Cause Representation of the Four-way Decomposition for Mediation and Interaction.

Authors:  Tyler J VanderWeele; Ian Shrier
Journal:  Epidemiology       Date:  2016-09       Impact factor: 4.822

6.  Assessing causal mechanistic interactions: a peril ratio index of synergy based on multiplicativity.

Authors:  Wen-Chung Lee
Journal:  PLoS One       Date:  2013-06-24       Impact factor: 3.240

7.  Testing for mechanistic interactions in long-term follow-up studies.

Authors:  Jui-Hsiang Lin; Wen-Chung Lee
Journal:  PLoS One       Date:  2015-03-26       Impact factor: 3.240

8.  Estimation of a common effect parameter from follow-up data when there is no mechanistic interaction.

Authors:  Wen-Chung Lee
Journal:  PLoS One       Date:  2014-01-20       Impact factor: 3.240

9.  Complementary Log Regression for Sufficient-Cause Modeling of Epidemiologic Data.

Authors:  Jui-Hsiang Lin; Wen-Chung Lee
Journal:  Sci Rep       Date:  2016-12-13       Impact factor: 4.379

10.  Sharp bounds on sufficient-cause interactions under the assumption of no redundancy.

Authors:  Wen-Chung Lee
Journal:  BMC Med Res Methodol       Date:  2017-04-21       Impact factor: 4.615

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.