Reporting only relative effect measures was potentially misleading: some good practices for improving the soundness of epidemiological results.

Observational studies Relative risk Rounding error, Odds ratio, Confidence intervals Statistical precision

Journal

Journal of clinical epidemiology
ISSN: 1878-5921
Titre abrégé: J Clin Epidemiol
Pays: United States
ID NLM: 8801383

Informations de publication

Date de publication:
09 2021
Historique:
received: 23 02 2021
revised: 08 04 2021
accepted: 15 04 2021
pubmed: 25 4 2021
medline: 11 11 2021
entrez: 24 4 2021
Statut: ppublish

Résumé

In the medical and epidemiological literature there is a growing tendency to report an excessive number of decimal digits (often three, sometimes four), especially when measures of relative occurrence are small; this can be misleading. We combined mathematical and statistical reasoning about the precision of relative risks with the meaning of the decimal part of the same measures from biological and public health perspectives. We identified a general rule for minimizing the mathematical error due to rounding of relative risks, depending on the background absolute rate, which justifies the use of one or more decimal digits for estimates close to 1. We suggest that both relative and absolute risk measures (expressed as a rates) should be reported, and two decimal digits should be used for relative risk close to 1 only if the background rate is at least 1/1,000 py. The use of more than two decimal digits is justified only when the background rate is high (ie, 1/10 py).

Identifiants

pubmed: 33894329
pii: S0895-4356(21)00122-0
doi: 10.1016/j.jclinepi.2021.04.006
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

195-199

Informations de copyright

Copyright © 2021. Published by Elsevier Inc.

Auteurs

Marco Novelli (M)

Department of Statistical Sciences "Paolo Fortunati", University of Bologna, Bologna, Italy. Electronic address: marco.novelli4@unibo.it.

Alessandro Baldi Antognini (A)

Department of Statistical Sciences "Paolo Fortunati", University of Bologna, Bologna, Italy.

Paolo Boffetta (P)

Stony Brook Cancer Center, Stony Brook University, Stony Brook, NY, USA; Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy.

John Pa Ioannidis (JP)

Stanford Prevention Research Center, Department of Medicine, Stanford University, Stanford, USA.

Giovanna Spatari (G)

Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy.

Francesco S Violante (FS)

Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy.

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