The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Strategies for developing Ki67 as a useful biomarker in breast cancer
Open accessAbstract
Increased proliferation is a hallmark of malignant tumors. The proliferation marker Ki67 has been investigated as a breast cancer biomarker, but despite 32 years of research the best cutpoints and the best methods for determination are still under debate. This review is based on an overview on the efforts to standardize Ki67 and to optimize its performance that was presented at the St. Gallen oncology conference 2015. The clinical validity of Ki67 as a prognostic marker as well as a predictive marker (in the neoadjuvant setting) has been shown in several meta-analyses. Depending on cohort characteristics, molecular subtype and clinical setting, Ki67 is a prognostic marker, a predictive marker, or both. Many different cutpoints for Ki67 have been reported, but it is has not been possible to determine an evidence-based "optimal" cutpoint. This supports the view that Ki67 is continuous marker, reflecting the continuous variation of the proliferation rate in different tumors. We should probably stop looking for an "optimal" cutpoint for Ki67 because it simply does not exist. It is evident from the results of several ring trials that intermediate levels of Ki67 are particularly difficult for standardization. Due to the low analytical validity in the intermediate range as well as intratumoral heterogeneity, the clinical utility of intermediate Ki67 levels is limited. Clinical decisions should not be based on small differences in the intermediate range and additional molecular tests might be necessary for tumors with intermediate Ki67 levels. For the two groups of tumors with a very low or a very high Ki67 a clinical interpretation could be straightforward. Despite these limitations, the assessment of proliferation is a central parameter for tumor characterization and an important element of the pathological assessment.
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
Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK)
McShane, L. M., Altman, D. G., Sauerbrei, W., Taube, S. E., Gion, M., & Clark, G. M. (2005) · JNCI: Journal of the National Cancer Institute · doi:10.1093/jnci/dji237 · Cited by 2,162
Cited by
Duffy, M. J., Harbeck, N., Nap, M., Molina, R., Nicolini, A., Senkus, E., & Cardoso, F. (2017) · European Journal of Cancer · doi:10.1016/j.ejca.2017.01.017 · Cited by 522
Ki-67 as a Prognostic Biomarker in Invasive Breast Cancer
Davey, M. G., Hynes, S. O., Kerin, M. J., Miller, N., & Lowery, A. J. (2021) · Cancers · doi:10.3390/cancers13174455 · Cited by 298
Chen, S., Wang, C., Meng, Y., Li, P., Pan, Y., He, M., & Ni, X. (2024) · International Journal of Nanomedicine · doi:10.2147/ijn.s441418 · Cited by 7
Metadata
- Authors
- Denkert, C., Budczies, J., von Minckwitz, G., Wienert, S., Loibl, S., & Klauschen, F.
- Venue
- The Breast
- Publisher
- Elsevier BV
- Published
- 2015-11
- Volume
- 24
- Pages
- S67-S72
- ISSN
- 0960-9776 (ISSN-L)
- OpenAlex
- W1581976178
- Cited by
- 177
- References
- 1
- FWCI
- 5.59
- Type
- journal article
- Language
- en
- Open access
- hybrid
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: Strategies for developing Ki67 as a useful biomarker in breast cancer. https://app.cochat.ai/papers/10.1016/j.breast.2015.07.017
- The paper
- Denkert, C., Budczies, J., von Minckwitz, G., Wienert, S., Loibl, S., & Klauschen, F. (2015). Strategies for developing Ki67 as a useful biomarker in breast cancer. The Breast. https://doi.org/10.1016/j.breast.2015.07.017
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.