Literature DB >> 29239842

Relative rates not relative risks: addressing a widespread misinterpretation of hazard ratios.

Rinku Sutradhar1, Peter C Austin2.   

Abstract

The use of the Cox proportional hazards model is ubiquitous in modern medical research. Despite the widespread implementation of this model, the terminology and interpretation that is used to describe the estimate hazard ratio (HR) has become loose and, unfortunately, often incorrect. Although some journals offer guidelines that advise against reporting HRs as relative risks, these guidelines are frequently overlooked. Perhaps due to a lack of understanding, authors continue to interpret the resultant HR as a relative risk-such an interpretation is inappropriate and can be misleading. The HR should be described as a relative rate, not as a relative risk. This article demonstrates that although the direction of the HR can be used to explain the direction of the relative risk, the magnitude of the HR alone cannot be used to explain the magnitude of the relative risk. This article clarifies the relationship between HRs and relative risks in a way that may be better suited for the applied clinical researcher. We also provide a convenient table illustrating the magnitude of relative risk under various values of the HR; the table demonstrates that for a given constant HR, the magnitude of the relative risk can vary substantially. As a take-home message, authors should refrain from using the magnitude of the HR to describe the magnitude of the relative risk. Authors should be strongly encouraged to ascribe accurate interpretations to the statistics derived from fitted Cox proportional hazards regression models.
Copyright © 2017 Elsevier Inc. All rights reserved.

Keywords:  Cox proportional hazards regression model; Hazard ratio; Instantaneous rate; Relative rate; Relative risk

Mesh:

Year:  2017        PMID: 29239842     DOI: 10.1016/j.annepidem.2017.10.014

Source DB:  PubMed          Journal:  Ann Epidemiol        ISSN: 1047-2797            Impact factor:   3.797


  13 in total

1.  Periodic screening for breast and cervical cancer in women with diabetes: a population-based cohort study.

Authors:  Dominika Bhatia; Rinku Sutradhar; Peter C Austin; Vasily Giannakeas; Liisa Jaakkimainen; Lawrence F Paszat; Lorraine L Lipscombe
Journal:  Cancer Causes Control       Date:  2021-11-20       Impact factor: 2.506

2.  Implementation of an Alternative Method for Assessing Competing Risks: Restricted Mean Time Lost.

Authors:  Hongji Wu; Hao Yuan; Zijing Yang; Yawen Hou; Zheng Chen
Journal:  Am J Epidemiol       Date:  2022-01-01       Impact factor: 5.363

3.  Risk of type 2 diabetes mellitus in women with prior hypertensive disorders of pregnancy: a systematic review and meta-analysis.

Authors:  Grace Zhao; Dominika Bhatia; Flora Jung; Lorraine Lipscombe
Journal:  Diabetologia       Date:  2021-01-07       Impact factor: 10.122

4.  Donor Lung Sequence Number and Survival after Lung Transplantation in the United States.

Authors:  Michael O Harhay; Raphaël Porcher; Gabriel Thabut; Michael J Crowther; Thomas DiSanto; Samantha Rubin; Zachary Penfil; Zhou Bing; Jason D Christie; Joshua M Diamond; Edward Cantu
Journal:  Ann Am Thorac Soc       Date:  2019-03

5.  The use of restricted mean time lost under competing risks data.

Authors:  Jingjing Lyu; Yawen Hou; Zheng Chen
Journal:  BMC Med Res Methodol       Date:  2020-07-25       Impact factor: 4.615

6.  ASO Authors Reflections: Patient Age and Survival After Surgery for Esophageal Cancer.

Authors:  Giola Santoni; Jesper Lagergren; Matteo Bottai
Journal:  Ann Surg Oncol       Date:  2020-05-29       Impact factor: 5.344

7.  Cancer risk in individuals with intellectual disability in Sweden: A population-based cohort study.

Authors:  Qianwei Liu; Hans-Olov Adami; Abraham Reichenberg; Alexander Kolevzon; Fang Fang; Sven Sandin
Journal:  PLoS Med       Date:  2021-10-21       Impact factor: 11.069

8.  The authors reply to: "Antihypertensives and skin cancer" and "Association between thiazide diuretics and skin cancer: still nebulous".

Authors:  Aaron M Drucker; An-Wen Chan
Journal:  CMAJ       Date:  2021-06-21       Impact factor: 8.262

9.  A review of the use of time-varying covariates in the Fine-Gray subdistribution hazard competing risk regression model.

Authors:  Peter C Austin; Aurélien Latouche; Jason P Fine
Journal:  Stat Med       Date:  2019-10-29       Impact factor: 2.373

10.  Patient Age and Survival After Surgery for Esophageal Cancer.

Authors:  Jesper Lagergren; Matteo Bottai; Giola Santoni
Journal:  Ann Surg Oncol       Date:  2020-05-28       Impact factor: 5.344

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.