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Cutoff Finder: A Comprehensive and Straightforward Web Application Enabling Rapid Biomarker Cutoff Optimization

Author

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  • Jan Budczies
  • Frederick Klauschen
  • Bruno V Sinn
  • Balázs Győrffy
  • Wolfgang D Schmitt
  • Silvia Darb-Esfahani
  • Carsten Denkert

Abstract

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.

Suggested Citation

  • Jan Budczies & Frederick Klauschen & Bruno V Sinn & Balázs Győrffy & Wolfgang D Schmitt & Silvia Darb-Esfahani & Carsten Denkert, 2012. "Cutoff Finder: A Comprehensive and Straightforward Web Application Enabling Rapid Biomarker Cutoff Optimization," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-7, December.
    • Handle: RePEc:plo:pone00:0051862
    DOI: 10.1371/journal.pone.0051862
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    Cited by:

    1. Eike Steidl & Ulrich Pilatus & Elke Hattingen & Joachim P Steinbach & Friedhelm Zanella & Michael W Ronellenfitsch & Oliver Bähr, 2016. "Myoinositol as a Biomarker in Recurrent Glioblastoma Treated with Bevacizumab: A 1H-Magnetic Resonance Spectroscopy Study," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-15, December.
    2. B Rey deCastro, 2019. "Cumulative ROC curves for discriminating three or more ordinal outcomes with cutpoints on a shared continuous measurement scale," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-16, August.
    3. Claudia Bühnemann & Simon Li & Haiyue Yu & Harriet Branford White & Karl L Schäfer & Antonio Llombart-Bosch & Isidro Machado & Piero Picci & Pancras C W Hogendoorn & Nicholas A Athanasou & J Alison No, 2014. "Quantification of the Heterogeneity of Prognostic Cellular Biomarkers in Ewing Sarcoma Using Automated Image and Random Survival Forest Analysis," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-14, September.
    4. Jin Sheng & Yun-Peng Yang & Yu-Xiang Ma & Tao Qin & Zhi-Huang Hu & Shao-Dong Hong & Ting Zhou & Yan Huang & Hong-Yun Zhao & Li Zhang, 2016. "Low Prognostic Nutritional Index Correlates with Worse Survival in Patients with Advanced NSCLC following EGFR-TKIs," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-12, January.
    5. Özge Özgüç & Ludmilla de Plater & Varun Kapoor & Anna Francesca Tortorelli & Andrew G Clark & Jean-Léon Maître, 2022. "Cortical softening elicits zygotic contractility during mouse preimplantation development," PLOS Biology, Public Library of Science, vol. 20(3), pages 1-23, March.
    6. Elisa I. Rivas & Jenniffer Linares & Melissa Zwick & Andrea Gómez-Llonin & Marc Guiu & Anna Labernadie & Jordi Badia-Ramentol & Anna Lladó & Lídia Bardia & Iván Pérez-Núñez & Carolina Martínez-Ciarpag, 2022. "Targeted immunotherapy against distinct cancer-associated fibroblasts overcomes treatment resistance in refractory HER2+ breast tumors," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    7. Hyungjin Kim & Chang Min Park & Bhumsuk Keam & Sang Joon Park & Miso Kim & Tae Min Kim & Dong-Wan Kim & Dae Seog Heo & Jin Mo Goo, 2017. "The prognostic value of CT radiomic features for patients with pulmonary adenocarcinoma treated with EGFR tyrosine kinase inhibitors," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-13, November.

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