Association between prostate-specific antigen change over time and prostate cancer recurrence risk: A joint model.

Joint modeling Prostate cancer recurrence Prostate specific antigen (PSA)

Journal

Caspian journal of internal medicine
ISSN: 2008-6164
Titre abrégé: Caspian J Intern Med
Pays: Iran
ID NLM: 101523876

Informations de publication

Date de publication:
May 2020
Historique:
entrez: 3 9 2020
pubmed: 3 9 2020
medline: 3 9 2020
Statut: ppublish

Résumé

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. 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. 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). 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.

Sections du résumé

BACKGROUND 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 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 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 CONCLUSIONS
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.

Identifiants

pubmed: 32874441
doi: 10.22088/cjim.11.3.324
pmc: PMC7442453
doi:

Types de publication

Journal Article

Langues

eng

Pagination

324-328

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Auteurs

Reza Ali Mohammadpour (R)

Department of Biostatistics, Faculty of Health, Health Sciences Research Center, Mazandaran University of Medical Sciences, Sari, Iran.

Ahad Alizadeh (A)

Student Research Committee, Faculty of Health, Mazandaran University of Medical Sciences, Sari, Iran.

Mohammad-Reza Barzegar (MR)

Cancer Institute of Tehran, Tehran University of Medical Sciences, Tehran, Iran.

Abazar Akbarzadeh Pasha (A)

Department of Urology, Babol University of Medical Sciences, Babol, Iran.

Classifications MeSH