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Cited by 438

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Prostate-Specific–Antigen Testing for Early Diagnosis of Prostate Cancer

Barry, Michael J.·2001·New England Journal of Medicine

Abstract

This Journal feature begins with a case vignette highlighting a common clinical problem. Evidence supporting various strategies is then presented, followed by a review of formal guidelines, when they exist. The article ends with the author's clinical recommendations.A 65-year-old man with no risk factors for prostate cancer except his age has a normal digital rectal examination. Should a prostate-specific–antigen (PSA) test be ordered?The Clinical ProblemThe introduction of PSA testing in 1987 resulted in an enormous increase in the reported incidence of prostate cancer in the United States. After peaking in 1992, the incidence fell, presumably owing to the identification of preexisting cases among men who had been tested. The rate of death from prostate cancer has risen and fallen over the same period for reasons that are unclear (Figure 1).1 Advocates of screening attribute . . .

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Crossref · 10.1056/nejm200105033441806

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Metadata

Authors
Barry, M. J.
Venue
New England Journal of Medicine
Published
2001-05-03
Volume
344
Issue
18
Pages
1373-1377
ISSN
  • 0028-4793 (ISSN-L)
  • 1533-4406
OpenAlex
W2320229303
Cited by
438
References
10
FWCI
22.34
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Prostate-Specific–Antigen Testing for Early Diagnosis of Prostate Cancer. https://app.cochat.ai/papers/10.1056/nejm200105033441806
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Barry, M. J. (2001). Prostate-Specific–Antigen Testing for Early Diagnosis of Prostate Cancer. New England Journal of Medicine. https://doi.org/10.1056/nejm200105033441806

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.