DOI . ORG {
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We began analyzing https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0051862, but it redirected us to https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0051862. The analysis below is for the second page.
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Description:
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.
Title[redir]:
No title found...
Description:
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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Doi.org utilizes WORDPRESS.
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🌍 Impressive Traffic: 500k - 1M visitors per month
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Keywords {🔍}
cutoff, expression, data, survival, optimization, article, view, cancer, google, scholar, point, methods, plots, gene, determination, pgr, breast, optimal, method, based, receptor, analysis, finder, variable, correlation, status, biomarker, determined, plos, image, patients, test, outcome, prognostic, points, gse, web, clinical, distance, application, distribution, user, set, cutoffs, significance, results, software, estrogen, sensitivity, specificity,
Topics {✒️}
cookies plos plos scientific publications complex situations global scale formalin-fixed paraffin-embedded tissue medicine applications open-access article distributed distance metastasis-free und distance metastasis-free survival node-negative breast cancer original author outcome-based cut-point optimization survival-data-based cutoff determination breast cancer tissue assessing treatment-covariate interactions advanced breast cancer newly identified biomarkers gene expression based distribution-based cutoff optimization breast cancer tissues breast cancer treated overview plots give web application calls biometric software repertoire commercial software jmp arbitrary web browser breast cancer prognosis assess treatment-covariate interactions gene expression omnibus gene-expression signature plots include information tissue-based diagnostics larger deviation epithelial ovarian cancer ncbi gene expression tissue biomarkers gene expression data result web page gene expression values software x-tile save selected preferences esr1 gene expression pgr gene expression tab-separated table hybridization based methods enable faster optimization breast cancer [23] breast cancer
Questions {❓}
- Hilsenbeck SG, Clark GM, McGuire WL (1992) Why do so many prognostic factors fail to pan out?
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