Cited by 5Statistical Methods in Clinical TrialsStatistical Methods in EpidemiologyMeta-analysis and systematic reviews

The DOI matches its Crossref record.

Misleading use of risk ratios

Open access

Overview

Integrity signals

Registry

Crossref · 10.1016/s0140-6736(05)61024-0

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • A 50% risk ratio for a drug tested in 100 people that reduces two deaths to one death is the same as the risk ratio for a drug tested in 1000 people that reduces two deaths to one death.

    “The authors pointed out that a 50% risk ratio for a drug tested in 100 people that reduces two deaths to one death (0.01 / 0.02 = 0.5) is the same as the risk ratio for a drug tested in a larger group of 1000 people that reduces two deaths to one death (0.001 / 0.002 = 0.5).”
  • Relative risk does not measure risk at all, because risk has dimensions, while a risk ratio has no dimensions.

    “Relative risk does not measure ‘risk’ at all, because risk has dimensions, such as observed deaths per 100 or 1000 people. However, a risk ratio has no dimensions because they cancel in calculating the ratio”
  • The change from two deaths per 100 people to one death per 100 people is a 1% decreased risk, and the change from two deaths per 1000 people to one death per 1000 people is a 0.1% decreased risk, ten times smaller.

    “Using absolute measures, the authors showed that “the change from two deaths per 100 people to one death per 100 people is a 1% decreased risk,” (ARR: 0.02 – 0.01 = 0.01 * 100 = 1%). “And the change from two deaths per 1000 people to one death per 1000 people is a 0.1% decreased risk,” (ARR: 0.002 – 0.001 = 0.001 * 100 = 0.1%), which is ten times smaller in magnitude than the decreased risk per 10”

Citations

Cites

No references could be resolved yet.

Research works printed but not linked: 3

  1. Jackson, 2005, Treating Individuals 5: Treatment with drugs to lower blood pressure and blood cholesterol based on an individual's absolute cardiovascular risk, Lancet, 365, 434, 10.1016/S0140-6736(05)70240-3 · DOI
  2. Chlebowski, 2003, Influence of estrogen plus progestin on breast cancer and mammography in healthy postmenopausal women: the Women's Health Initiative randomized trial, JAMA, 289, 3243, 10.1001/jama.289.24.3243 · DOI
  3. Gann, 2003, Combined hormone replacement therapy and breast cancer: a single-edged sword, JAMA, 289, 3303, 10.1001/jama.289.24.3304 · DOI

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Metadata

Authors
Stadel, B. V., Colman, E., & Sahlroot, T.
Affiliations
United States Food and Drug Administration (US)
Corresponding author
Stadel, Bruce V
Venue
The Lancet
Publisher
Elsevier BV
Published
2005-04
Volume
365
Issue
9467
Pages
1306-1307
ISSN
  • 0099-5355 (ISSN-L)
  • 0140-6736
OpenAlex
W2018541377
Cited by
5
References
0
Citations by year
2024: 1 · 2022: 2
Type
journal article
Language
en
Open access
Locations
  • The Lancet (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Keywords
relative risk, relative risk reduction, number needed to treat, absolute risk, risk communication, Women's Health Initiative, breast cancer screening
MeSH terms
Humans, Risk, Odds Ratio, Drug-Related Side Effects and Adverse Reactions

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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