Literature DB >> 32314782

Invited Commentary: Opportunities That Come With Studying the Co-Occurrence of Multiple Outcomes.

Sebastien Haneuse, Deborah Schrag, Daniel Nevo.   

Abstract

In almost all clinical settings, patients are at risk for multiple potential events and, in consultation with health-care providers, must weigh the potential benefits and harms across these events when making decisions. As researchers seek to build an evidence base to inform these decisions, they must contend with a choice as to how they will handle the different events. One approach, arguably the standard approach in the literature, is to consider the events individually by conducting analyses and publishing results for each one at a time. Doing so, however, fails to acknowledge or exploit the inherent multivariate nature of the data, represents a lost opportunity, and results in an evidence base that is not aligned with how clinical decision-making is actually performed. The article by Prentice et al. (Am J Epidemiol. 2020;189(9):972-981) in this issue of the Journal moves beyond this standard by illustrating recently developed methods that directly take advantage of information on the co-occurrence of multiple events. Moreover, their article highlights the role of modern methods in deriving additional information and insight from studies of multiple clinical outcomes by making full use of multivariate data, with the goal being to complement, not replace, existing methods.
© The Author(s) 2020. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  decision-making; multivariate data analysis; semicompeting risks; time-to-event data

Mesh:

Year:  2020        PMID: 32314782      PMCID: PMC7443758          DOI: 10.1093/aje/kwaa031

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


  5 in total

1.  Ambient Fine Particulate Matter and Preterm Birth in California: Identification of Critical Exposure Windows.

Authors:  Paige Sheridan; Sindana Ilango; Tim A Bruckner; Qiong Wang; Rupa Basu; Tarik Benmarhnia
Journal:  Am J Epidemiol       Date:  2019-09-01       Impact factor: 4.897

2.  Cancer screening in elderly patients: a framework for individualized decision making.

Authors:  L C Walter; K E Covinsky
Journal:  JAMA       Date:  2001-06-06       Impact factor: 56.272

Review 3.  Clinical strategies for breast cancer screening: weighing and using the evidence.

Authors:  R Harris; L Leininger
Journal:  Ann Intern Med       Date:  1995-04-01       Impact factor: 25.391

4.  Semi-Competing Risks Data Analysis: Accounting for Death as a Competing Risk When the Outcome of Interest Is Nonterminal.

Authors:  Sebastien Haneuse; Kyu Ha Lee
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2016-04-12

5.  Beyond Composite Endpoints Analysis: Semicompeting Risks as an Underutilized Framework for Cancer Research.

Authors:  Ina Jazić; Deborah Schrag; Daniel J Sargent; Sebastien Haneuse
Journal:  J Natl Cancer Inst       Date:  2016-07-05       Impact factor: 13.506

  5 in total

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