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Association between prostate-specific antigen change over time and prostate cancer recurrence risk: A joint model
BACKGROUND: Prostate specific antigen (PSA) is an important biomarker to monitor patients after treated with radiation therapy (RT). The aim of this study is to evaluate the relationship between the PSA data and prostate cancer recurrence using the joint modeling. METHODS: This historical cohort stu...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Babol University of Medical Sciences
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442453/ https://www.ncbi.nlm.nih.gov/pubmed/32874441 http://dx.doi.org/10.22088/cjim.11.3.324 |
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author | Ali Mohammadpour, Reza Alizadeh, Ahad Barzegar, Mohammad-Reza Akbarzadeh Pasha, Abazar |
author_facet | Ali Mohammadpour, Reza Alizadeh, Ahad Barzegar, Mohammad-Reza Akbarzadeh Pasha, Abazar |
author_sort | Ali Mohammadpour, Reza |
collection | PubMed |
description | BACKGROUND: Prostate specific antigen (PSA) is an important biomarker to monitor patients after treated with radiation therapy (RT). The aim of this study is to evaluate the relationship between the PSA data and prostate cancer recurrence using the joint modeling. METHODS: This historical cohort study was performed on 422 prostate cancer patients. Inclusion criteria included: patients with localized prostate cancer referring to Cancer Institute in Tehran (Iran) from 2007 to 2012, and under radiation therapy. Joint model has two components or sub-models. We showed the results by parameter estimating the longitudinal sub-model and survival sub-model. EM algorithm, Newton-Gauss and Gauss-Hermit law were used for final model parameters. R software version 3.2 was used for statistical analysis. RESULTS: In this study, considering the inclusion and exclusion criteria, out of 422 patients, the data on 314 cases were selected for analysis and the main result of joint model was obtained. PSA directly and significantly was associated with recurrence risk, therefore increasing 2.6 ml/lit PSA (one unit in transformed PSA) increases 39% recurrence risk (95% CI for RR: 1.09-1.77). Also, slope of PSA trend has significant association with prostate cancer recurrence risk (95% CI for RR: 1.05-1.41). CONCLUSION: This study showed a significant relationship between PSA, and its slope with the recurrence risk by joint model, with regard to the pathological, demographic and clinical features in the Iranian population. |
format | Online Article Text |
id | pubmed-7442453 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Babol University of Medical Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-74424532020-08-31 Association between prostate-specific antigen change over time and prostate cancer recurrence risk: A joint model Ali Mohammadpour, Reza Alizadeh, Ahad Barzegar, Mohammad-Reza Akbarzadeh Pasha, Abazar Caspian J Intern Med Original Article BACKGROUND: Prostate specific antigen (PSA) is an important biomarker to monitor patients after treated with radiation therapy (RT). The aim of this study is to evaluate the relationship between the PSA data and prostate cancer recurrence using the joint modeling. METHODS: This historical cohort study was performed on 422 prostate cancer patients. Inclusion criteria included: patients with localized prostate cancer referring to Cancer Institute in Tehran (Iran) from 2007 to 2012, and under radiation therapy. Joint model has two components or sub-models. We showed the results by parameter estimating the longitudinal sub-model and survival sub-model. EM algorithm, Newton-Gauss and Gauss-Hermit law were used for final model parameters. R software version 3.2 was used for statistical analysis. RESULTS: In this study, considering the inclusion and exclusion criteria, out of 422 patients, the data on 314 cases were selected for analysis and the main result of joint model was obtained. PSA directly and significantly was associated with recurrence risk, therefore increasing 2.6 ml/lit PSA (one unit in transformed PSA) increases 39% recurrence risk (95% CI for RR: 1.09-1.77). Also, slope of PSA trend has significant association with prostate cancer recurrence risk (95% CI for RR: 1.05-1.41). CONCLUSION: This study showed a significant relationship between PSA, and its slope with the recurrence risk by joint model, with regard to the pathological, demographic and clinical features in the Iranian population. Babol University of Medical Sciences 2020-05 /pmc/articles/PMC7442453/ /pubmed/32874441 http://dx.doi.org/10.22088/cjim.11.3.324 Text en This is an Open Access article distributed under the terms of the Creative Commons Attribution License, (http://creativecommons.org/licenses/by/3.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Ali Mohammadpour, Reza Alizadeh, Ahad Barzegar, Mohammad-Reza Akbarzadeh Pasha, Abazar Association between prostate-specific antigen change over time and prostate cancer recurrence risk: A joint model |
title | Association between prostate-specific antigen change over time and prostate cancer recurrence risk: A joint model |
title_full | Association between prostate-specific antigen change over time and prostate cancer recurrence risk: A joint model |
title_fullStr | Association between prostate-specific antigen change over time and prostate cancer recurrence risk: A joint model |
title_full_unstemmed | Association between prostate-specific antigen change over time and prostate cancer recurrence risk: A joint model |
title_short | Association between prostate-specific antigen change over time and prostate cancer recurrence risk: A joint model |
title_sort | association between prostate-specific antigen change over time and prostate cancer recurrence risk: a joint model |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442453/ https://www.ncbi.nlm.nih.gov/pubmed/32874441 http://dx.doi.org/10.22088/cjim.11.3.324 |
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