The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Cathepsin D and Prognosis in Breast Cancer
Open accessAbstract
We investigated the possibility that cathepsin D, an estrogen-induced lysosomal protease, might have value as a prognostic factor in breast cancer by studying frozen tissue specimens from 397 patients. We measured the 34-kd mature form of the enzyme by Western blot assay and densitometry. Among 199 patients with node-negative disease, but not among 198 with node-positive disease, high levels of cathepsin D proved to be a significant predictor of reduced disease-free survival (median follow-up, 64 months), either as a continuous variable (log cathepsin D; P = 0.018) or as a dichotomous variable with an optimized cutoff point (P = 0.0001). Results were similar for overall survival (P = 0.009 and 0.0001, respectively). Relating the level of cathepsin D to other prognostic factors in the patients with node-negative disease, we found an association with aneuploidy but none with estrogen or progesterone receptors, tumor size, or the age of the patient. In multivariate analyses, a high level of cathepsin D was the most important independent factor in predicting shorter disease-free and overall survival in patients with node-negative disease. As compared with the risk in women with low levels of cathepsin D, the relative risk of tumor recurrence was 2.6 (95 percent confidence interval, 1.6 to 4.4) and the relative risk of death was 3.9 (95 percent confidence interval, 2.1 to 7.3) among those with high levels of cathepsin D. For disease-free survival, cathepsin D status was predictive of outcome primarily among those with aneuploid tumors; the actuarial five-year recurrence rates of aneuploid tumors were 60 percent among women with high levels of cathepsin D and 29 percent among those with low levels, as compared with 22 percent for all diploid tumors. We conclude that cathepsin D may be an independent predictor of early recurrence and death in node-negative breast cancer.
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
Nonparametric Estimation from Incomplete Observations
Kaplan, E. L., & Meier, P. (1958) · Journal of the American Statistical Association · doi:10.1080/01621459.1958.10501452 · Cited by 39,158
Measurement of protein using bicinchoninic acid
Smith, P. K., Krohn, R. I., Hermanson, G. T., Mallia, A. K., Gartner, F. H., Provenzano, M. D., Fujimoto, E. K., Goeke, N. M., Olson, B. J., & Klenk, D. C. (1985) · Analytical Biochemistry · doi:10.1016/0003-2697(85)90442-7 · Cited by 18,482
Cited by
Cancer metastasis and angiogenesis: An imbalance of positive and negative regulation
Liotta, L. A., Steeg, P. S., & Stetler-Stevenson, W. G. (1991) · Cell · doi:10.1016/0092-8674(91)90642-c · Cited by 2,720
Prognostic Factors in Breast Cancer: College of American Pathologists Consensus Statement 1999
Fitzgibbons, P. L., Page, D. L., Weaver, D., Thor, A. D., Allred, D. C., Clark, G. M., Ruby, S. G., O'Malley, F., Simpson, J. F., Connolly, J. L., et al. (2000) · Archives of Pathology & Laboratory Medicine · doi:10.5858/2000-124-0966-pfibc · Cited by 1,016
Self-citationNomi, T., Sho, M., Akahori, T., Hamada, K., Kubo, A., Kanehiro, H., Nakamura, S., Enomoto, K., Yagita, H., Azuma, M., et al. (2007) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-06-2746 · Cited by 889
Safe, S., Astroff, B., Harris, M., Zacharewski, T., Dickerson, R., Romkes, M., & Biegel, L. (1991) · Pharmacology & Toxicology · doi:10.1111/j.1600-0773.1991.tb01321.x · Cited by 287
Prognostic Factors and Treatment Decisions in Axillary-Node-Negative Breast Cancer
Desforges, J. F., McGuire, W. L., & Clark, G. M. (1992) · New England Journal of Medicine · doi:10.1056/nejm199206253262607 · Cited by 282
Self-citation
Metadata
- Authors
- Tandon, A. K., Clark, G. M., Chamness, G. C., Chirgwin, J. M., & McGuire, W. L.
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 1990-02
- Volume
- 322
- Issue
- 5
- Pages
- 297-302
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- OpenAlex
- W2326165980
- Cited by
- 456
- References
- 2
- FWCI
- 32.77
- Type
- journal article
- Language
- en
- Open access
- bronze
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: Cathepsin D and Prognosis in Breast Cancer. https://app.cochat.ai/papers/10.1056/nejm199002013220504
- The paper
- Tandon, A. K., Clark, G. M., Chamness, G. C., Chirgwin, J. M., & McGuire, W. L. (1990). Cathepsin D and Prognosis in Breast Cancer. New England Journal of Medicine. https://doi.org/10.1056/nejm199002013220504
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.