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Physical Inactivity, Metabolic Syndrome and Prostate Cancer Diagnosis: Development of a Predicting Nomogram
Insufficient physical activity (PA) may be a shared risk factor for the development of both metabolic syndrome (MetS) and prostate cancer (PCa). To investigate this correlation and to develop a nomogram able to predict tumor diagnosis. Between 2016 and 2018, a consecutive series of men who underwent...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9860889/ https://www.ncbi.nlm.nih.gov/pubmed/36677036 http://dx.doi.org/10.3390/metabo13010111 |
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author | De Nunzio, Cosimo Brassetti, Aldo Cancrini, Fabiana Prata, Francesco Cindolo, Luca Sountoulides, Petros Toutziaris, Chrysovalantis Gacci, Mauro Lombardo, Riccardo Cicione, Antonio Tema, Giorgia Schips, Luigi Simone, Giuseppe Serni, Sergio Tubaro, Andrea |
author_facet | De Nunzio, Cosimo Brassetti, Aldo Cancrini, Fabiana Prata, Francesco Cindolo, Luca Sountoulides, Petros Toutziaris, Chrysovalantis Gacci, Mauro Lombardo, Riccardo Cicione, Antonio Tema, Giorgia Schips, Luigi Simone, Giuseppe Serni, Sergio Tubaro, Andrea |
author_sort | De Nunzio, Cosimo |
collection | PubMed |
description | Insufficient physical activity (PA) may be a shared risk factor for the development of both metabolic syndrome (MetS) and prostate cancer (PCa). To investigate this correlation and to develop a nomogram able to predict tumor diagnosis. Between 2016 and 2018, a consecutive series of men who underwent prostate biopsy at three institutions were prospectively enrolled. PA was self-assessed by patients through the Physical Activity Scale for the Elderly (PASE) questionnaire; MetS was assessed according to Adult Treatment Panel III criteria. A logistic regression analyses was used to identify predictors of PCa diagnosis and high-grade disease (defined as International Society of Uro-Pathology grade >2 tumors). A nomogram was then computed to estimate the risk of tumor diagnosis. A total of 291 patients were enrolled; 17.5% of them (n = 51) presented with MetS. PCa was diagnosed in 110 (38%) patients overall while 51 presented high-grade disease. At multivariable analysis, age (OR 1.04; 95%CI: 1.00–1.08; p = 0.048), prostate volume (PV) (OR 0.98; 95%CI: 0.79–0.99; p = 0.004), suspicious digital rectal examination (OR 2.35; 95%CI: 1.11–4.98; p = 0.02), total PSA value (OR 1.12; 95%CI: 1.05–1.2; p < 0.001), and PASE score (OR 0.99; 95%CI: 0.98–0.99; p = 0.01) were independent predictors of tumor diagnosis. The latter two also predicted high-grade PCa. MetS was not associated with PCa diagnosis and aggressiveness. The novel nomogram displayed fair discrimination for PCa diagnosis (AUC = 0.76), adequate calibration (p > 0.05) and provided a net benefit in the range of probabilities between 20% and 90%. reduced PA was associated with an increased risk of PCa diagnosis and high-grade disease. Our nomogram could improve the selection of patients scheduled for prostate biopsy at increased risk of PCa. |
format | Online Article Text |
id | pubmed-9860889 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98608892023-01-22 Physical Inactivity, Metabolic Syndrome and Prostate Cancer Diagnosis: Development of a Predicting Nomogram De Nunzio, Cosimo Brassetti, Aldo Cancrini, Fabiana Prata, Francesco Cindolo, Luca Sountoulides, Petros Toutziaris, Chrysovalantis Gacci, Mauro Lombardo, Riccardo Cicione, Antonio Tema, Giorgia Schips, Luigi Simone, Giuseppe Serni, Sergio Tubaro, Andrea Metabolites Article Insufficient physical activity (PA) may be a shared risk factor for the development of both metabolic syndrome (MetS) and prostate cancer (PCa). To investigate this correlation and to develop a nomogram able to predict tumor diagnosis. Between 2016 and 2018, a consecutive series of men who underwent prostate biopsy at three institutions were prospectively enrolled. PA was self-assessed by patients through the Physical Activity Scale for the Elderly (PASE) questionnaire; MetS was assessed according to Adult Treatment Panel III criteria. A logistic regression analyses was used to identify predictors of PCa diagnosis and high-grade disease (defined as International Society of Uro-Pathology grade >2 tumors). A nomogram was then computed to estimate the risk of tumor diagnosis. A total of 291 patients were enrolled; 17.5% of them (n = 51) presented with MetS. PCa was diagnosed in 110 (38%) patients overall while 51 presented high-grade disease. At multivariable analysis, age (OR 1.04; 95%CI: 1.00–1.08; p = 0.048), prostate volume (PV) (OR 0.98; 95%CI: 0.79–0.99; p = 0.004), suspicious digital rectal examination (OR 2.35; 95%CI: 1.11–4.98; p = 0.02), total PSA value (OR 1.12; 95%CI: 1.05–1.2; p < 0.001), and PASE score (OR 0.99; 95%CI: 0.98–0.99; p = 0.01) were independent predictors of tumor diagnosis. The latter two also predicted high-grade PCa. MetS was not associated with PCa diagnosis and aggressiveness. The novel nomogram displayed fair discrimination for PCa diagnosis (AUC = 0.76), adequate calibration (p > 0.05) and provided a net benefit in the range of probabilities between 20% and 90%. reduced PA was associated with an increased risk of PCa diagnosis and high-grade disease. Our nomogram could improve the selection of patients scheduled for prostate biopsy at increased risk of PCa. MDPI 2023-01-09 /pmc/articles/PMC9860889/ /pubmed/36677036 http://dx.doi.org/10.3390/metabo13010111 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article De Nunzio, Cosimo Brassetti, Aldo Cancrini, Fabiana Prata, Francesco Cindolo, Luca Sountoulides, Petros Toutziaris, Chrysovalantis Gacci, Mauro Lombardo, Riccardo Cicione, Antonio Tema, Giorgia Schips, Luigi Simone, Giuseppe Serni, Sergio Tubaro, Andrea Physical Inactivity, Metabolic Syndrome and Prostate Cancer Diagnosis: Development of a Predicting Nomogram |
title | Physical Inactivity, Metabolic Syndrome and Prostate Cancer Diagnosis: Development of a Predicting Nomogram |
title_full | Physical Inactivity, Metabolic Syndrome and Prostate Cancer Diagnosis: Development of a Predicting Nomogram |
title_fullStr | Physical Inactivity, Metabolic Syndrome and Prostate Cancer Diagnosis: Development of a Predicting Nomogram |
title_full_unstemmed | Physical Inactivity, Metabolic Syndrome and Prostate Cancer Diagnosis: Development of a Predicting Nomogram |
title_short | Physical Inactivity, Metabolic Syndrome and Prostate Cancer Diagnosis: Development of a Predicting Nomogram |
title_sort | physical inactivity, metabolic syndrome and prostate cancer diagnosis: development of a predicting nomogram |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9860889/ https://www.ncbi.nlm.nih.gov/pubmed/36677036 http://dx.doi.org/10.3390/metabo13010111 |
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