Literature DB >> 34390790

Controversy and Debate : Questionable utility of the relative risk in clinical research: Paper 4 :Odds Ratios are far from "portable" - A call to use realistic models for effect variation in meta-analysis.

Mengli Xiao1, Haitao Chu2, Stephen R Cole3, Yong Chen4, Richard F MacLehose5, David B Richardson4, Sander Greenland6.   

Abstract

OBJECTIVE: Recently Doi et al. argued that risk ratios should be replaced with odds ratios in clinical research. We disagreed, and empirically documented the lack of portability of odds ratios, while Doi et al. defended their position. In this response we highlight important errors in their position. STUDY DESIGN AND
SETTING: We counter Doi et al.'s arguments by further examining the correlations of odds ratios, and risk ratios, with baseline risks in 20,198 meta-analyses from the Cochrane Database of Systematic Reviews.
RESULTS: Doi et al.'s claim that odds ratios are portable is invalid because 1) their reasoning is circular: they assume a model under which the odds ratio is constant and show that under such a model the odds ratio is portable; 2) the method they advocate to convert odds ratios to risk ratios is biased; 3) their empirical example is readily-refuted by counter-examples of meta-analyses in which the risk ratio is portable but the odds ratio isn't; and 4) they fail to consider the causal determinants of meta-analytic inclusion criteria: Doi et al. mistakenly claim that variation in odds ratios with different baseline risks in meta-analyses is due to collider bias. Empirical comparison between the correlations of odds ratios, and risk ratios, with baseline risks show that the portability of odds ratios and risk ratios varies across settings.
CONCLUSION: The suggestion to replace risk ratios with odds ratios is based on circular reasoning and a confusion of mathematical and empirical results. It is especially misleading for meta-analyses and clinical guidance. Neither the odds ratio nor the risk ratio is universally portable. To address this lack of portability, we reinforce our suggestion to report variation in effect measures conditioning on modifying factors such as baseline risk; understanding such variation is essential to patient-centered practice.
Copyright © 2021 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Baseline risk; Clinical guidance; Cochrane Database of Systematic Reviews; Correlation; Meta-analysis; Odds ratio; Risk ratio

Mesh:

Year:  2021        PMID: 34390790      PMCID: PMC8831641          DOI: 10.1016/j.jclinepi.2021.08.002

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  41 in total

1.  Standardized binomial models for risk or prevalence ratios and differences.

Authors:  David B Richardson; Alan C Kinlaw; Richard F MacLehose; Stephen R Cole
Journal:  Int J Epidemiol       Date:  2015-07-30       Impact factor: 7.196

Review 2.  Statistical foundations for model-based adjustments.

Authors:  Sander Greenland; Neil Pearce
Journal:  Annu Rev Public Health       Date:  2015-03-18       Impact factor: 21.981

3.  Scientists rise up against statistical significance.

Authors:  Valentin Amrhein; Sander Greenland; Blake McShane
Journal:  Nature       Date:  2019-03       Impact factor: 49.962

4.  Statistics corner: A guide to appropriate use of correlation coefficient in medical research.

Authors:  M M Mukaka
Journal:  Malawi Med J       Date:  2012-09       Impact factor: 0.875

5.  Re: "Estimating the relative risk in cohort studies and clinical trials of common outcomes".

Authors:  I Karp
Journal:  Am J Epidemiol       Date:  2014-02-19       Impact factor: 4.897

6.  Constructing inverse probability weights for marginal structural models.

Authors:  Stephen R Cole; Miguel A Hernán
Journal:  Am J Epidemiol       Date:  2008-08-05       Impact factor: 4.897

7.  The Authors Respond.

Authors:  Charles Poole; Ian Shrier; Peng Ding; Tyler VanderWeele
Journal:  Epidemiology       Date:  2016-05       Impact factor: 4.822

8.  Re: Is the Risk Difference Really a More Heterogeneous Measure?

Authors:  Amand F Schmidt; Frank Dudbridge; Rolf H H Groenwold
Journal:  Epidemiology       Date:  2016-05       Impact factor: 4.822

9.  The Odds Ratio is "portable" across baseline risk but not the Relative Risk: Time to do away with the log link in binomial regression.

Authors:  Suhail A Doi; Luis Furuya-Kanamori; Chang Xu; Tawanda Chivese; Lifeng Lin; Omran A H Musa; George Hindy; Lukman Thalib; Frank E Harrell
Journal:  J Clin Epidemiol       Date:  2021-08-08       Impact factor: 6.437

Review 10.  Basic problems in interaction assessment.

Authors:  S Greenland
Journal:  Environ Health Perspect       Date:  1993-12       Impact factor: 9.031

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  2 in total

1.  Methodical considerations on adjusting for Charlson Comorbidity Index in epidemiological studies.

Authors:  Sören Möller; Mette Bliddal; Katrine Hass Rubin
Journal:  Eur J Epidemiol       Date:  2021-09-04       Impact factor: 8.082

2.  Systematic review and meta-analysis on laparoscopic cystectomy in bladder cancer: reply letter.

Authors:  Jialiang Zhu; Ziwen Lu; Wanbo Chen; Mang Ke; Xianguo Cai
Journal:  Transl Androl Urol       Date:  2022-05
  2 in total

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