Manciu M, Hosseini S, Di Desidero T, Allegrini G, Falcone A, Bocci G, Kirken RA, Francia G. Optimization of biomarkers-based classification scores as progression-free survival predictors: an intuitive graphical representation.
Future Sci OA 2018;
4:FSO346. [PMID:
30450233 PMCID:
PMC6234460 DOI:
10.4155/fsoa-2018-0020]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2018] [Accepted: 08/17/2018] [Indexed: 02/04/2023] Open
Abstract
Aim
To construct classification scores based on a combination of cancer patient plasma biomarker levels, for predicting progression-free survival.
Methods
The approach is based on the optimization of the biomarker cut-off values, which maximize the statistical differences between the groups with values lower or larger than the cut-offs, respectively. An intuitive visualization of the quality of the classification score is also proposed.
Results
Even if there are only weak correlations between individual biomarker levels and progression-free survival, scores based on suitably chosen combination of three biomarkers have classification power comparable with the Response Evaluation Criteria in Solid Tumors criteria classification of response to treatments in solid tumors.
Conclusion
Our approach has the potential to improve the selection of the patients who will benefit from a given anticancer treatment.
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