The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
BRCAPRO Validation, Sensitivity of Genetic Testing of BRCA1/BRCA2, and Prevalence of Other Breast Cancer Susceptibility Genes
Open accessAbstract
PURPOSE: To compare genetic test results for deleterious mutations of BRCA1 and BRCA2 with estimated probabilities of carrying such mutations; to assess sensitivity of genetic testing; and to assess the relevance of other susceptibility genes in familial breast and ovarian cancer. PATIENTS AND METHODS: Data analyzed were from six high-risk genetic counseling clinics and concern individuals from families for which at least one member was tested for mutations at BRCA1 and BRCA2. Predictions of genetic predisposition to breast and ovarian cancer for 301 individuals were made using BRCAPRO, a statistical model and software using Mendelian genetics and Bayesian updating. Model predictions were compared with the results of genetic testing. RESULTS: Among the test individuals, 126 were Ashkenazi Jewish, three were male subjects, 243 had breast cancer, 49 had ovarian cancer, 34 were unaffected, and 139 tested positive for BRCA1 mutations and 29 for BRCA2 mutations. BRCAPRO performed well: for the 150 probands with the smallest BRCAPRO carrier probabilities (average, 29.0%), the proportion testing positive was 32.7%; for the 151 probands with the largest carrier probabilities (average, 95.2%), 78.8% tested positive. Genetic testing sensitivity was estimated to be at least 85%, with false-negatives including mutations of susceptibility genes heretofore unknown. CONCLUSION: BRCAPRO is an accurate counseling tool for determining the probability of carrying mutations of BRCA1 and BRCA2. Genetic testing for BRCA1 and BRCA2 is highly sensitive, missing an estimated 15% of mutations. In the populations studied, breast cancer susceptibility genes other than BRCA1 and BRCA2 either do not exist, are rare, or are associated with low disease penetrance.
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
Cites
Gail, M. H., Brinton, L. A., Byar, D. P., Corle, D. K., Green, S. B., Schairer, C., & Mulvihill, J. J. (1989) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/81.24.1879 · Cited by 3,334
Cited by
Smith, R. A., Andrews, K. S., Brooks, D., Fedewa, S. A., Manassaram‐Baptiste, D., Saslow, D., Brawley, O. W., & Wender, R. C. (2017) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21392 · Cited by 719
Hennessy, B. T., Coleman, R. L., & Markman, M. (2009) · The Lancet · doi:10.1016/s0140-6736(09)61338-6 · Cited by 640
Smith, R. A., Manassaram‐Baptiste, D., Brooks, D., Doroshenk, M., Fedewa, S., Saslow, D., Brawley, O. W., & Wender, R. (2015) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21261 · Cited by 451
Smith, R. A., Brooks, D., Cokkinides, V., Saslow, D., & Brawley, O. W. (2013) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21174 · Cited by 422
Clinical Decision Support Systems for Improving Diagnostic Accuracy and Achieving Precision Medicine
Castaneda, C., Nalley, K., Mannion, C., Bhattacharyya, P., Blake, P., Pecora, A., Goy, A., & Suh, K. S. (2015) · Journal of Clinical Bioinformatics · doi:10.1186/s13336-015-0019-3 · Cited by 408
Metadata
- Authors
- Berry, D. A., Iversen, E. S., Gudbjartsson, D. F., Hiller, E. H., Garber, J. E., Peshkin, B. N., Lerman, C., Watson, P., Lynch, H. T., Hilsenbeck, S. G., Rubinstein, W. S., Hughes, K. S., & Parmigiani, G.
- Venue
- Journal of Clinical Oncology
- Published
- 2002-06-01
- Volume
- 20
- Issue
- 11
- Pages
- 2701-2712
- ISSN
- 0732-183X (ISSN-L)
- 1527-7755
- OpenAlex
- W2143730928
- Cited by
- 505
- References
- 1
- FWCI
- 11.51
- Type
- journal article
- Language
- en
- Open access
- green
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: BRCAPRO Validation, Sensitivity of Genetic Testing of BRCA1/BRCA2, and Prevalence of Other Breast Cancer Susceptibility Genes. https://app.cochat.ai/papers/10.1200/jco.2002.05.121
- The paper
- Berry, D. A., Iversen, E. S., Gudbjartsson, D. F., Hiller, E. H., Garber, J. E., Peshkin, B. N., Lerman, C., Watson, P., Lynch, H. T., Hilsenbeck, S. G., Rubinstein, W. S., Hughes, K. S., & Parmigiani, G. (2002). BRCAPRO Validation, Sensitivity of Genetic Testing of BRCA1/BRCA2, and Prevalence of Other Breast Cancer Susceptibility Genes. Journal of Clinical Oncology. https://doi.org/10.1200/jco.2002.05.121
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.