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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...

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Autores principales: Manciu, Marian, Hosseini, Sorour, Di Desidero, Teresa, Allegrini, Giacomo, Falcone, Alfredo, Bocci, Guido, Kirken, Robert A, Francia, Giulio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Future Science Ltd 2018
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.
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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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