The DOI matches its Crossref record.
Screening for Breast Cancer
Abstract
There is very good evidence that screening for breast cancer reduces mortality in women older than 50 years and suggestive but inconsistent evidence that screening is effective in reducing long-term mortality in women younger than 50 years. The probability that an average-risk woman will be diagnosed with breast cancer in the coming 10 years is about 130 in 10,000 for a 40-year-old woman, 230 in 10,000 for a 55-year-old woman, and 280 in 10,000 for a 65-year-old woman. The chance of dying from breast cancer diagnosed in the coming 10 years is about 90 in 10,000, 123 in 10,000, and 120 in 10,000 for women age 40, 55, and 65, respectively. Mathematical models based on data from controlled trials of screening programs indicate that screening annually for 10 years with breast physical examination will decrease the probability of death from breast cancer by about 25 in 10,000 for women in the three age groups and increase life expectancy by about 20 days. Adding annual mammography will decrease the probability of death from breast cancer an additional 25 in 10,000 and increase life expectancy an additional 20 days. The actual reductions in mortality observed in controlled trials are slightly lower. If women are screened annually for 10 years with breast physical examination and mammography, the chance for a false-positive result over the 10-year period is approximately 2500 in 10,000. On the population level, if 25% of women age 40 to 75 are screened annually with both examinations, deaths from breast cancer would be decreased by about 4000 in the year 2000. Net annual costs would be approximately $1.3 billion. Recommending a screening strategy requires weighing the benefits against the risks and costs.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Assessing cost-effectiveness in healthcare: history of the $50,000 per QALY threshold
Grosse, S. D. (2008) · Expert Review of Pharmacoeconomics & Outcomes Research · doi:10.1586/14737167.8.2.165 · Cited by 637
Sarasin, F. P., Giostra, E., & Hadengue, A. (1996) · The American Journal of Medicine · doi:10.1016/s0002-9343(96)00197-0 · Cited by 368
Cost-effectiveness of radiofrequency ablation for supraventricular tachycardia
Cheng, C. H. F., Sanders, G. D., Hlatky, M. A., Heidenreich, P., McDonald, K. M., Lee, B. K., Larson, M. S., & Owens, D. K. (2000) · Annals of Internal Medicine · doi:10.7326/0003-4819-133-11-200012050-00010 · Cited by 87
Metadata
- Authors
- Eddy, D. M.
- Venue
- Annals of Internal Medicine
- Publisher
- American College of Physicians
- Published
- 1989-09-01
- Volume
- 111
- Issue
- 5
- Pages
- 389-399
- ISSN
- 0003-4819 (ISSN-L)
- 1539-3704
- OpenAlex
- W2121879722
- Cited by
- 307
- References
- 0
- FWCI
- 11.52
- Type
- journal article
- Language
- en
- Open access
- closed
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Screening for Breast Cancer. https://app.cochat.ai/papers/10.7326/0003-4819-111-5-389
- The paper
- Eddy, D. M. (1989). Screening for Breast Cancer. Annals of Internal Medicine. https://doi.org/10.7326/0003-4819-111-5-389
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.