AIM: to develop a prediction risk model of prostate cancer based on Indonesia population. METHODS: we included all benign prostate hyperthrophy (BPH) and PCa patients who had prostate biopsy and prostatectomy between January 2009 and December 2013 from 5 urology centers in Indonesia. The relationship between the possibility of PCa with the following variables including: age; PSA level, prostate volume (by transabdominal ultrasound or transrectal ultrasound) and digital rectal examination (DRE) finding. We calculated a predictive scoring equation to predict the possibility of PCa using chi-square analysis, Kolmogorov-Smirnov test, multiple logistic regression and ROC curve. Then, we designed an application for predicting prostate cancer risk called Indonesian Prostate Cancer Risk Calculator (IPCRC). RESULTS: there were 784 PCa and 1173 BPH patients were used for developing the risk calculator in our study. The mean ages, PSA and prostate volume are 66.9±8.1 years old; 72.4±248.9 ng/ml and 49.6±28.2 ml, respectively. Abnormal DRE was found in 637 PCa and 56 BPH. We included age, PSA level, abnormal DRE finding (all showed significant p<0.05 in univariate model). Additionally, although not significant, we included prostate volume (p=0.157) due to its clinical importance. The corrected ROC analysis showed AUC 0.935, sensitivity of 90.1% and specificity 80% in predicting the prostate cancer in our population. CONCLUSION: we have developed the Indonesian Prostate Cancer Risk Calculator which includes age, PSA, DRE, and prostate volume as its variables. Future prospective study to validate the risk calculator is needed.
AIM: to develop a prediction risk model of prostate cancer based on Indonesia population. METHODS: we included all benign prostate hyperthrophy (BPH) and PCa patients who had prostate biopsy and prostatectomy between January 2009 and December 2013 from 5 urology centers in Indonesia. The relationship between the possibility of PCa with the following variables including: age; PSA level, prostate volume (by transabdominal ultrasound or transrectal ultrasound) and digital rectal examination (DRE) finding. We calculated a predictive scoring equation to predict the possibility of PCa using chi-square analysis, Kolmogorov-Smirnov test, multiple logistic regression and ROC curve. Then, we designed an application for predicting prostate cancer risk called Indonesian Prostate Cancer Risk Calculator (IPCRC). RESULTS: there were 784 PCa and 1173 BPH patients were used for developing the risk calculator in our study. The mean ages, PSA and prostate volume are 66.9±8.1 years old; 72.4±248.9 ng/ml and 49.6±28.2 ml, respectively. Abnormal DRE was found in 637 PCa and 56 BPH. We included age, PSA level, abnormal DRE finding (all showed significant p<0.05 in univariate model). Additionally, although not significant, we included prostate volume (p=0.157) due to its clinical importance. The corrected ROC analysis showed AUC 0.935, sensitivity of 90.1% and specificity 80% in predicting the prostate cancer in our population. CONCLUSION: we have developed the Indonesian Prostate Cancer Risk Calculator which includes age, PSA, DRE, and prostate volume as its variables. Future prospective study to validate the risk calculator is needed.
Authors: Prahara Yuri; Katsumi Shigemura; Koichi Kitagawa; Exsa Hadibrata; Muhammad Risan; Andy Zulfiqqar; Indrawarman Soeroharjo; Ahmad Z Hendri; Raden Danarto; Aya Ishii; Saya Yamasaki; Yongmin Yan; Didik S Heriyanto; Masato Fujisawa Journal: Prostate Int Date: 2020-02-10