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Predicting the diagnosis of prostate cancer with a scoring system based on novel biomarkers

OBJECTIVE: To predict prostate cancer using novel biomarker ratios and create a predictive scoring system. MATERIALS AND METHODS: Data of a total of 703 patients who consulted Urology Department of Selayang Hospital between January 2013 and December 2017 and underwent prostate biopsy were screened r...

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Autores principales: Jethwani, Durvesh Lachman, Sivamoorthy, Lameena Lalitha, Toh, Charng Chee, Malek, Rohan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8808971/
https://www.ncbi.nlm.nih.gov/pubmed/35109827
http://dx.doi.org/10.1186/s12894-022-00956-2
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author Jethwani, Durvesh Lachman
Sivamoorthy, Lameena Lalitha
Toh, Charng Chee
Malek, Rohan
author_facet Jethwani, Durvesh Lachman
Sivamoorthy, Lameena Lalitha
Toh, Charng Chee
Malek, Rohan
author_sort Jethwani, Durvesh Lachman
collection PubMed
description OBJECTIVE: To predict prostate cancer using novel biomarker ratios and create a predictive scoring system. MATERIALS AND METHODS: Data of a total of 703 patients who consulted Urology Department of Selayang Hospital between January 2013 and December 2017 and underwent prostate biopsy were screened retrospectively. Prostate specific antigen (PSA) levels, prostate volumes (PV), neutrophil and lymphocyte counts, neutrophil-to-lymphocyte ratio (NLR), Prostate specific antigen density (PSAD) and histopathology were evaluated. RESULTS: Ages ranged from 43 to 89 years, divided into 2 groups as per biopsy results; positive for prostate cancer (n = 290, 41.3%) and negative for malignancy (n = 413; 58.7%). Intergroup comparative evaluations were performed. Independent variables with p < 0.001 in the univariate analysis were age, DRE, PV, NLR, PSAD. A scoring system was modelled using NLR < 0.9, PSAD > 0.4, Age > 70 and DRE. A score of 2 or more predicted prostate cancer with a Sensitivity of 83.8% and Specificity of 86.4%. CONCLUSIONS: NLR is shown to be good predictor for prostate cancer its usage in this scoring system affords more disease specificity as compared to PSA alone.
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spelling pubmed-88089712022-02-03 Predicting the diagnosis of prostate cancer with a scoring system based on novel biomarkers Jethwani, Durvesh Lachman Sivamoorthy, Lameena Lalitha Toh, Charng Chee Malek, Rohan BMC Urol Research OBJECTIVE: To predict prostate cancer using novel biomarker ratios and create a predictive scoring system. MATERIALS AND METHODS: Data of a total of 703 patients who consulted Urology Department of Selayang Hospital between January 2013 and December 2017 and underwent prostate biopsy were screened retrospectively. Prostate specific antigen (PSA) levels, prostate volumes (PV), neutrophil and lymphocyte counts, neutrophil-to-lymphocyte ratio (NLR), Prostate specific antigen density (PSAD) and histopathology were evaluated. RESULTS: Ages ranged from 43 to 89 years, divided into 2 groups as per biopsy results; positive for prostate cancer (n = 290, 41.3%) and negative for malignancy (n = 413; 58.7%). Intergroup comparative evaluations were performed. Independent variables with p < 0.001 in the univariate analysis were age, DRE, PV, NLR, PSAD. A scoring system was modelled using NLR < 0.9, PSAD > 0.4, Age > 70 and DRE. A score of 2 or more predicted prostate cancer with a Sensitivity of 83.8% and Specificity of 86.4%. CONCLUSIONS: NLR is shown to be good predictor for prostate cancer its usage in this scoring system affords more disease specificity as compared to PSA alone. BioMed Central 2022-02-02 /pmc/articles/PMC8808971/ /pubmed/35109827 http://dx.doi.org/10.1186/s12894-022-00956-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Jethwani, Durvesh Lachman
Sivamoorthy, Lameena Lalitha
Toh, Charng Chee
Malek, Rohan
Predicting the diagnosis of prostate cancer with a scoring system based on novel biomarkers
title Predicting the diagnosis of prostate cancer with a scoring system based on novel biomarkers
title_full Predicting the diagnosis of prostate cancer with a scoring system based on novel biomarkers
title_fullStr Predicting the diagnosis of prostate cancer with a scoring system based on novel biomarkers
title_full_unstemmed Predicting the diagnosis of prostate cancer with a scoring system based on novel biomarkers
title_short Predicting the diagnosis of prostate cancer with a scoring system based on novel biomarkers
title_sort predicting the diagnosis of prostate cancer with a scoring system based on novel biomarkers
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8808971/
https://www.ncbi.nlm.nih.gov/pubmed/35109827
http://dx.doi.org/10.1186/s12894-022-00956-2
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