The OR is "portable" but not the RR: Time to do away with the log link in binomial regression

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Author(s)
Doi, Suhail A
Furuya-Kanamori, Luis
Xu, Chang
Chivese, Tawanda
Lin, Lifeng
Musa, Omran AH
Hindy, George
Thalib, Lukman
Harrell, Frank E
Griffith University Author(s)
Year published
2021
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OBJECTIVES: In a recent paper we suggest that the relative risk (RR) be replaced with the odds ratio (OR) as the effect measure of choice in clinical epidemiology. In response, Chu and colleagues raise several points that argue for the status quo. In this paper, we respond to their response. STUDY DESIGNS AND SETTINGS: We use the same examples given by Chu and colleagues to recompute estimates of effect and demonstrate the problem with the RR. RESULTS: We reaffirm the following findings: a) the OR and RR measure different things and their numerical difference is only important if misinterpreted b) this potential misinterpretation ...
View more >OBJECTIVES: In a recent paper we suggest that the relative risk (RR) be replaced with the odds ratio (OR) as the effect measure of choice in clinical epidemiology. In response, Chu and colleagues raise several points that argue for the status quo. In this paper, we respond to their response. STUDY DESIGNS AND SETTINGS: We use the same examples given by Chu and colleagues to recompute estimates of effect and demonstrate the problem with the RR. RESULTS: We reaffirm the following findings: a) the OR and RR measure different things and their numerical difference is only important if misinterpreted b) this potential misinterpretation is a trivial issue compared to the lack of portability of the RR c) the same examples reaffirm non-portability of the RR and demonstrate how misleading the results might be in contrast to the OR, which is independent of the baseline risk d) the concept of collapsibility for the OR should be expected in the presence of a non-confounding risk factor and is not a bias e) the log link in regression models that generate RRs as well as the use of RRs in meta-analysis is shown to be problematic using the same examples. CONCLUSIONS: The OR should replace the RR in clinical research and meta-analyses though there should be conversion of the end product into ratios or differences of risk, solely for interpretation. To this end we provide a Stata module (logittorisk) for this purpose.
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View more >OBJECTIVES: In a recent paper we suggest that the relative risk (RR) be replaced with the odds ratio (OR) as the effect measure of choice in clinical epidemiology. In response, Chu and colleagues raise several points that argue for the status quo. In this paper, we respond to their response. STUDY DESIGNS AND SETTINGS: We use the same examples given by Chu and colleagues to recompute estimates of effect and demonstrate the problem with the RR. RESULTS: We reaffirm the following findings: a) the OR and RR measure different things and their numerical difference is only important if misinterpreted b) this potential misinterpretation is a trivial issue compared to the lack of portability of the RR c) the same examples reaffirm non-portability of the RR and demonstrate how misleading the results might be in contrast to the OR, which is independent of the baseline risk d) the concept of collapsibility for the OR should be expected in the presence of a non-confounding risk factor and is not a bias e) the log link in regression models that generate RRs as well as the use of RRs in meta-analysis is shown to be problematic using the same examples. CONCLUSIONS: The OR should replace the RR in clinical research and meta-analyses though there should be conversion of the end product into ratios or differences of risk, solely for interpretation. To this end we provide a Stata module (logittorisk) for this purpose.
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Journal Title
Journal of Clinical Epidemiology
Copyright Statement
© 2021 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
Note
This publication has been entered as an advanced online version in Griffith Research Online.
Subject
Mathematical sciences
Biostatistics
Health sciences
baseline risk
clinical trial, meta-analysis
odds ratio
relative risk