The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Cutoff Finder: A Comprehensive and Straightforward Web Application Enabling Rapid Biomarker Cutoff Optimization
Open accessAbstract
Gene or protein expression data are usually represented by metric or at least ordinal variables. In order to translate a continuous variable into a clinical decision, it is necessary to determine a cutoff point and to stratify patients into two groups each requiring a different kind of treatment. Currently, there is no standard method or standard software for biomarker cutoff determination. Therefore, we developed Cutoff Finder, a bundle of optimization and visualization methods for cutoff determination that is accessible online. While one of the methods for cutoff optimization is based solely on the distribution of the marker under investigation, other methods optimize the correlation of the dichotomization with respect to an outcome or survival variable. We illustrate the functionality of Cutoff Finder by the analysis of the gene expression of estrogen receptor (ER) and progesterone receptor (PgR) in breast cancer tissues. This distribution of these important markers is analyzed and correlated with immunohistologically determined ER status and distant metastasis free survival. Cutoff Finder is expected to fill a relevant gap in the available biometric software repertoire and will enable faster optimization of new diagnostic biomarkers. The tool can be accessed at http://molpath.charite.de/cutoff.
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Cites
Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
Edgar, R. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.207 · Cited by 13,288
Györffy, B., Lanczky, A., Eklund, A. C., Denkert, C., Budczies, J., Li, Q., & Szallasi, Z. (2010) · Breast Cancer Research and Treatment · doi:10.1007/s10549-009-0674-9 · Cited by 4,169
Self-citationDangers of Using "Optimal" Cutpoints in the Evaluation of Prognostic Factors
Altman, D. G., Lausen, B., Sauerbrei, W., & Schumacher, M. (1994) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/86.11.829 · Cited by 1,143
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Lánczky, A., & Győrffy, B. (2021) · Journal of Medical Internet Research · doi:10.2196/27633 · Cited by 1,694
Self-citationComprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas
Abeshouse, A., Adebamowo, C., Adebamowo, S. N., Akbani, R., Akeredolu, T., Ally, A., Anderson, M. L., Anur, P., Appelbaum, E. L., Armenia, J., et al. (2017) · Cell · doi:10.1016/j.cell.2017.10.014 · Cited by 1,069
Tumor Mutational Burden as a Predictive Biomarker in Solid Tumors
Sha, D., Jin, Z., Budczies, J., Kluck, K., Stenzinger, A., & Sinicrope, F. A. (2020) · Cancer Discovery · doi:10.1158/2159-8290.cd-20-0522 · Cited by 859
Self-citationCapone, M., Giannarelli, D., Mallardo, D., Madonna, G., Festino, L., Grimaldi, A. M., Vanella, V., Simeone, E., Paone, M., Palmieri, G., et al. (2018) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-018-0383-1 · Cited by 497
Fumet, J.-D., Richard, C., Ledys, F., Klopfenstein, Q., Joubert, P., Routy, B., Truntzer, C., Gagné, A., Hamel, M.-A., Guimaraes, C. F., et al. (2018) · British Journal of Cancer · doi:10.1038/s41416-018-0220-9 · Cited by 176
Metadata
- Authors
- Budczies, J., Klauschen, F., Sinn, B. V., Győrffy, B., Schmitt, W. D., Darb-Esfahani, S., & Denkert, C.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2012-12-14
- Volume
- 7
- Issue
- 12
- Pages
- e51862
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W1969096316
- Cited by
- 1,224
- References
- 3
- FWCI
- 7.73
- Type
- journal article
- Language
- en
- Open access
- gold
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- Budczies, J., Klauschen, F., Sinn, B. V., Győrffy, B., Schmitt, W. D., Darb-Esfahani, S., & Denkert, C. (2012). Cutoff Finder: A Comprehensive and Straightforward Web Application Enabling Rapid Biomarker Cutoff Optimization. PLoS ONE. https://doi.org/10.1371/journal.pone.0051862
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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.
