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Optimization of biomarkers-based classification scores as progression-free survival predictors: an intuitive graphical representation
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 v...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Future Science Ltd
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6234460/ https://www.ncbi.nlm.nih.gov/pubmed/30450233 http://dx.doi.org/10.4155/fsoa-2018-0020 |
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author | Manciu, Marian Hosseini, Sorour Di Desidero, Teresa Allegrini, Giacomo Falcone, Alfredo Bocci, Guido Kirken, Robert A Francia, Giulio |
author_facet | Manciu, Marian Hosseini, Sorour Di Desidero, Teresa Allegrini, Giacomo Falcone, Alfredo Bocci, Guido Kirken, Robert A Francia, Giulio |
author_sort | Manciu, Marian |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6234460 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Future Science Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-62344602018-11-16 Optimization of biomarkers-based classification scores as progression-free survival predictors: an intuitive graphical representation Manciu, Marian Hosseini, Sorour Di Desidero, Teresa Allegrini, Giacomo Falcone, Alfredo Bocci, Guido Kirken, Robert A Francia, Giulio Future Sci OA Research Article 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. Future Science Ltd 2018-11-01 /pmc/articles/PMC6234460/ /pubmed/30450233 http://dx.doi.org/10.4155/fsoa-2018-0020 Text en © 2018 Marian Manciu et al. This work is licensed under a Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/) |
spellingShingle | Research Article Manciu, Marian Hosseini, Sorour Di Desidero, Teresa Allegrini, Giacomo Falcone, Alfredo Bocci, Guido Kirken, Robert A Francia, Giulio Optimization of biomarkers-based classification scores as progression-free survival predictors: an intuitive graphical representation |
title | Optimization of biomarkers-based classification scores as progression-free survival predictors: an intuitive graphical representation |
title_full | Optimization of biomarkers-based classification scores as progression-free survival predictors: an intuitive graphical representation |
title_fullStr | Optimization of biomarkers-based classification scores as progression-free survival predictors: an intuitive graphical representation |
title_full_unstemmed | Optimization of biomarkers-based classification scores as progression-free survival predictors: an intuitive graphical representation |
title_short | Optimization of biomarkers-based classification scores as progression-free survival predictors: an intuitive graphical representation |
title_sort | optimization of biomarkers-based classification scores as progression-free survival predictors: an intuitive graphical representation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6234460/ https://www.ncbi.nlm.nih.gov/pubmed/30450233 http://dx.doi.org/10.4155/fsoa-2018-0020 |
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