Literature DB >> 25275571

Time at risk and intention-to-treat analyses: parallels and implications for inference.

Sunni L Mumford1, Enrique F Schisterman, Stephen R Cole, Daniel Westreich, Robert W Platt.   

Abstract

Although the standard recommendation is to exclude person-time not at risk (ie, time during which the outcome could not have occurred) from the denominators of disease rates, there are scenarios where person-time not at risk should be included. In particular, we draw an analogy between including person-time not at risk and intention-to-treat (ITT) analyses of randomized trials, and excluding person-time not at risk and compliance-corrected analysis of these same trials. Excluding person-time not at risk is appropriate when addressing questions of the biologic or mechanistic effects of an exposure, whereas the ITT-type approach typically addresses questions regarding the effect of an exposure under observed compliance patterns. The choice of approach directly affects the causal question being addressed and subsequent inference, with potential implications for public health. When interested in estimating treatment effects that allow and account for potential noncompliance, or where the exposure may be associated with the time at risk, we argue that person-time not at risk should be included. In the case of time to pregnancy, although the ITT-type analysis may underestimate the biological fecundity of the population, it may also yield an answer to a question that is of more interest to couples trying to become pregnant.

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Year:  2015        PMID: 25275571      PMCID: PMC6191842          DOI: 10.1097/EDE.0000000000000188

Source DB:  PubMed          Journal:  Epidemiology        ISSN: 1044-3983            Impact factor:   4.822


  29 in total

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6.  Skin cancer as a marker of sun exposure: a case of serious immortality bias.

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Review 7.  Beyond intention to treat: what is the right question?

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8.  The hazards of hazard ratios.

Authors:  Miguel A Hernán
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9.  Inverse probability-of-censoring weights for the correction of time-varying noncompliance in the effect of randomized highly active antiretroviral therapy on incident AIDS or death.

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Journal:  Stat Med       Date:  2009-05-30       Impact factor: 2.373

10.  Statistical models for prevalent cohort data.

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Journal:  Biometrics       Date:  1993-03       Impact factor: 2.571

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  2 in total

1.  Association Between Pesticide Residue Intake From Consumption of Fruits and Vegetables and Pregnancy Outcomes Among Women Undergoing Infertility Treatment With Assisted Reproductive Technology.

Authors:  Yu-Han Chiu; Paige L Williams; Matthew W Gillman; Audrey J Gaskins; Lidia Mínguez-Alarcón; Irene Souter; Thomas L Toth; Jennifer B Ford; Russ Hauser; Jorge E Chavarro
Journal:  JAMA Intern Med       Date:  2018-01-01       Impact factor: 21.873

2.  Epidemiologic Approaches for Studying Assisted Reproductive Technologies: Design, Methods, Analysis and Interpretation.

Authors:  Carmen Messerlian; Audrey J Gaskins
Journal:  Curr Epidemiol Rep       Date:  2017-04-17
  2 in total

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