Early detection of Prostate Cancer with Prostate Specific Antigen > 4 ng/ml : A Multivariate Logistic Regression

Background: Early detection of prostate cancer is a possible means of decreasing the mortality and increasing the quality of life.   Objective : To determine whether the prostate specific antigen (PSA), abnormal DRE, family history, age, and prostate volume could increase the specificity and sen...

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Main Authors: Prahara Yuri, Sungsang Rochadi
Format: Article
Language:English
Published: IKATAN AHLI UROLOGI INDONESIA 2015-04-01
Series:Jurnal Urologi Indonesia
Online Access:http://juri.urologi.or.id/juri/article/view/90
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author Prahara Yuri
Sungsang Rochadi
author_facet Prahara Yuri
Sungsang Rochadi
author_sort Prahara Yuri
collection DOAJ
description Background: Early detection of prostate cancer is a possible means of decreasing the mortality and increasing the quality of life.   Objective : To determine whether the prostate specific antigen (PSA), abnormal DRE, family history, age, and prostate volume could increase the specificity and sensitivity of screening for prostate cancer.   Methods : We included 92 patients with PSA > 4 ng/ml between January and December 2011 in Sardjito Hospital. Patients received prostate biopsy due to having abnormal serum prostate specific antigen (PSA) level. The relationship between the possibility of prostate cancer and the following variables were evaluated including: age; PSA level, prostate volume, DRE finding and family history. By using chi-square analysis, multiple logistic regression and receiver operating characteristic (ROC) curve were drawn based on the predictive scoring equation to predict the possibility of prostate cancer. All analyses were performed with SPSS, version 18.0.   Results: We analyzed 92 patients with PSA > 4 ng/ml. It showed the relationship between the possibility of prostate cancer and the following variables, including : age (p < 0.001), PSA level (p < 0,001), DRE finding (p < 0.001) family history (p < 0,001) except prostate volume (p = 0.398). Using a predictive equation, P = 1/(1-e-X), where X= -3,821 +1.846 (if DRE positive) + 2,488 ( if family history positive ) + 1.718 ( when PSA > 10 ) + 1.414 ( when age > 68), followed by receiver-operating characteristic curve analysis, it showed the sensitivity 90,4% and specificity 85 % in predicting the possibility of prostate cancer.   Conclusion:  Age,  DRE  finding,  PSA  and  family  history  are  factors  associated prostate cancer. They can be used as independent predictor to predict prostate cancer.   Key words: Logistic regression, early detection,prostate cancer
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spelling doaj.art-1e98706d02874b30853371faad224f4b2022-12-22T00:04:16ZengIKATAN AHLI UROLOGI INDONESIAJurnal Urologi Indonesia0853-442X2355-14022015-04-0122110.32421/juri.v22i1.9090Early detection of Prostate Cancer with Prostate Specific Antigen > 4 ng/ml : A Multivariate Logistic RegressionPrahara Yuri0Sungsang Rochadi1Department of Urology, Faculty of Medicine/Indonesia University, Cipto Mangunkusumo General Hospital, Jakarta.Staff Division of Urology/Department of Surgery, Faculty of Medicine/Gajah Mada University, Sardjito General Hospital, Yogyakarta.Background: Early detection of prostate cancer is a possible means of decreasing the mortality and increasing the quality of life.   Objective : To determine whether the prostate specific antigen (PSA), abnormal DRE, family history, age, and prostate volume could increase the specificity and sensitivity of screening for prostate cancer.   Methods : We included 92 patients with PSA > 4 ng/ml between January and December 2011 in Sardjito Hospital. Patients received prostate biopsy due to having abnormal serum prostate specific antigen (PSA) level. The relationship between the possibility of prostate cancer and the following variables were evaluated including: age; PSA level, prostate volume, DRE finding and family history. By using chi-square analysis, multiple logistic regression and receiver operating characteristic (ROC) curve were drawn based on the predictive scoring equation to predict the possibility of prostate cancer. All analyses were performed with SPSS, version 18.0.   Results: We analyzed 92 patients with PSA > 4 ng/ml. It showed the relationship between the possibility of prostate cancer and the following variables, including : age (p < 0.001), PSA level (p < 0,001), DRE finding (p < 0.001) family history (p < 0,001) except prostate volume (p = 0.398). Using a predictive equation, P = 1/(1-e-X), where X= -3,821 +1.846 (if DRE positive) + 2,488 ( if family history positive ) + 1.718 ( when PSA > 10 ) + 1.414 ( when age > 68), followed by receiver-operating characteristic curve analysis, it showed the sensitivity 90,4% and specificity 85 % in predicting the possibility of prostate cancer.   Conclusion:  Age,  DRE  finding,  PSA  and  family  history  are  factors  associated prostate cancer. They can be used as independent predictor to predict prostate cancer.   Key words: Logistic regression, early detection,prostate cancerhttp://juri.urologi.or.id/juri/article/view/90
spellingShingle Prahara Yuri
Sungsang Rochadi
Early detection of Prostate Cancer with Prostate Specific Antigen > 4 ng/ml : A Multivariate Logistic Regression
Jurnal Urologi Indonesia
title Early detection of Prostate Cancer with Prostate Specific Antigen > 4 ng/ml : A Multivariate Logistic Regression
title_full Early detection of Prostate Cancer with Prostate Specific Antigen > 4 ng/ml : A Multivariate Logistic Regression
title_fullStr Early detection of Prostate Cancer with Prostate Specific Antigen > 4 ng/ml : A Multivariate Logistic Regression
title_full_unstemmed Early detection of Prostate Cancer with Prostate Specific Antigen > 4 ng/ml : A Multivariate Logistic Regression
title_short Early detection of Prostate Cancer with Prostate Specific Antigen > 4 ng/ml : A Multivariate Logistic Regression
title_sort early detection of prostate cancer with prostate specific antigen 4 ng ml a multivariate logistic regression
url http://juri.urologi.or.id/juri/article/view/90
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AT sungsangrochadi earlydetectionofprostatecancerwithprostatespecificantigen4ngmlamultivariatelogisticregression