Skimming the Median and the Problem of Exaggerated Survival Gains

This Viewpoint describes a phenomenon termed skimming the median and discusses 3 examples to emphasize why an entire dataset should be considered to reach precise conclusions.

Authors

Tito Fojo (ORCID: https://orcid.org/0000-0002-8083-2688)
Susan E. Bates (ORCID: https://orcid.org/0000-0001-6708-0330)

Institutions

James J. Peters VA Medical Center (US)
Columbia University (US)

Publication Details

Journal: JAMA Oncology
Published: 2025-05-22
DOI: https://doi.org/10.1001/jamaoncol.2025.0035
Citations: 7
Primary Topic: Machine Learning in Healthcare
Type: article
Field-Weighted Citation Impact: 17.37

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article

Skimming the Median and the Problem of Exaggerated Survival Gains

Tito Fojo, Susan E. Bates

May 22, 2025

7 citations

JAMA Oncology

Machine Learning in Healthcare

17.37

article

Skimming the Median and the Problem of Exaggerated Survival Gains

Tito Fojo, Susan E. Bates

May 22, 2025article en

7 citations

Abstract

This Viewpoint describes a phenomenon termed skimming the median and discusses 3 examples to emphasize why an entire dataset should be considered to reach precise conclusions.

JAMA OncologyVol. 11(7)

James J. Peters VA Medical Center (US), Columbia University (US)

Openalex Percentile: Top 1%

Machine Learning in Healthcare

17.37

DOI Source OpenAlex

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