Several prediction models have been developed to estimate the outcomes of prostate biopsies. Most of these tools were designed for use with Western populations and have not been validated across different ethnic group...Several prediction models have been developed to estimate the outcomes of prostate biopsies. Most of these tools were designed for use with Western populations and have not been validated across different ethnic groups. Therefore, we evaluated the predictive value of the Prostate Cancer Prevention Trial （PCPT） and the European Randomized Study of Screening for Prostate Cancer （ERSPC） risk calculators in a Chinese cohort. Clinicopathological information was obtained from 495 Chinese men who had undergone extended prostate biopsies between January 2009 and March 2011. The estimated probabilities of prostate cancer and high-grade disease （Gleason 〉6） were calculated using the PCPT and ERSPC risk calculators. Overall measures, discrimination, calibration and clinical usefulness were assessed for the model evaluation. Of these patients, 28.7% were diagnosed with prostate cancer and 19.4% had high-grade disease. Compared to the PCPT model and the prostate-specific antigen （PSA） threshold of 4 ng m1-1, the ERSPC risk calculator exhibited better discriminative ability for predicting positive biopsies and high-grade disease （the area under the curve was 0.831 and 0.852, respectively, P〈O.01 for both）. Decision curve analysis also suggested the favourable clinical utility of the ERSPC calculator in the validation dataset. Both prediction models demonstrated miscalibration： the risk of prostate cancer and high-grade disease was overestimated by approximately 20% for a wide range of predicted probabilities. In conclusion, the ERSPC risk calculator outperformed both the PCPT model and the PSA threshold of 4 ng ml- z in predicting prostate cancer and high-grade disease in Chinese patients. However, the prediction tools derived from Western men significantly overestimated the probability of prostate cancer and high-grade disease compared to the outcomes of biopsies in a Chinese cohort.展开更多
The performances of the Prostate Cancer Prevention Trial （PCPT） risk calculator and other risk calculators for prostate cancer （PCa） prediction in Chinese populations were poorly understood. We performed this stud...The performances of the Prostate Cancer Prevention Trial （PCPT） risk calculator and other risk calculators for prostate cancer （PCa） prediction in Chinese populations were poorly understood. We performed this study to build risk calculators （Huashan risk calculators） based on Chinese population and validated the performance of prostate-specific antigen （PSA）, PCPT risk calculator, and Huashan risk calculators in a validation cohort. We built Huashan risk calculators based on data from 1059 men who underwent initial prostate biopsy from January 2006 to December 2010 in a training cohort. Then, we validated the performance of PSA, PCPT risk calculator, and Huashan risk calculators in an observational validation study from January 2011 to December 2014. All necessary clinical information were collected before the biopsy. The results showed that Huashan risk calculators 1 and 2 outperformed the PCPT risk calculator for predicting PCa in both entire training cohort and stratified population （with PSA from 2.0 ng ml^-1 to 20.0 ng ml^-1）. In the validation study, Huashan risk calculator 1 still outperformed the PCPT risk calculator in the entire validation cohort （0.849 vs 0.779 in area under the receiver operating characteristic curve [AUC]） and stratified population. A considerable reduction of unnecessary biopsies （approximately 30%） was also observed when the Huashan risk calculators were used. Thus, we believe that the Huashan risk calculators （especially Huashan risk calculator 1） may have added value for predicting PCa in Chinese population. However, these results still needed further evaluation in larger populations.展开更多
Millions of men each year are faced with a clinical suspicion of prostate cancer （PCa） but the prostate biopsy fails to detect the disease. For the urologists, how to select the appropriate candidate for repeat biop...Millions of men each year are faced with a clinical suspicion of prostate cancer （PCa） but the prostate biopsy fails to detect the disease. For the urologists, how to select the appropriate candidate for repeat biopsy is a significant clinical dilemma. Traditional risk-stratification tools in this setting such as prostate-specific antigen （PSA） related markers and histopathology findings have met with limited correlation with cancer diagnosis or with significant disease. Thus, an individualized approach using predictive models such as an online risk calculator （RC） or updated biomarkers is more suitable in counseling men about their risk of harboring clinically significant prostate cancer, This review will focus on the available risk-stratification tools in the population of men with prior negative biopsies and persistent suspicion of PCa. The underlying methodology and platforms of the available tools are reviewed to better understand the development and validation of these models. The index patient is then assessed with different RCs to determine the range of heterogeneity among various RCs. This should allow the urologists to better incorporate these various risk-stratification tools into their clinical practice and improve patient counseling.展开更多
文摘Several prediction models have been developed to estimate the outcomes of prostate biopsies. Most of these tools were designed for use with Western populations and have not been validated across different ethnic groups. Therefore, we evaluated the predictive value of the Prostate Cancer Prevention Trial （PCPT） and the European Randomized Study of Screening for Prostate Cancer （ERSPC） risk calculators in a Chinese cohort. Clinicopathological information was obtained from 495 Chinese men who had undergone extended prostate biopsies between January 2009 and March 2011. The estimated probabilities of prostate cancer and high-grade disease （Gleason 〉6） were calculated using the PCPT and ERSPC risk calculators. Overall measures, discrimination, calibration and clinical usefulness were assessed for the model evaluation. Of these patients, 28.7% were diagnosed with prostate cancer and 19.4% had high-grade disease. Compared to the PCPT model and the prostate-specific antigen （PSA） threshold of 4 ng m1-1, the ERSPC risk calculator exhibited better discriminative ability for predicting positive biopsies and high-grade disease （the area under the curve was 0.831 and 0.852, respectively, P〈O.01 for both）. Decision curve analysis also suggested the favourable clinical utility of the ERSPC calculator in the validation dataset. Both prediction models demonstrated miscalibration： the risk of prostate cancer and high-grade disease was overestimated by approximately 20% for a wide range of predicted probabilities. In conclusion, the ERSPC risk calculator outperformed both the PCPT model and the PSA threshold of 4 ng ml- z in predicting prostate cancer and high-grade disease in Chinese patients. However, the prediction tools derived from Western men significantly overestimated the probability of prostate cancer and high-grade disease compared to the outcomes of biopsies in a Chinese cohort.
文摘The performances of the Prostate Cancer Prevention Trial （PCPT） risk calculator and other risk calculators for prostate cancer （PCa） prediction in Chinese populations were poorly understood. We performed this study to build risk calculators （Huashan risk calculators） based on Chinese population and validated the performance of prostate-specific antigen （PSA）, PCPT risk calculator, and Huashan risk calculators in a validation cohort. We built Huashan risk calculators based on data from 1059 men who underwent initial prostate biopsy from January 2006 to December 2010 in a training cohort. Then, we validated the performance of PSA, PCPT risk calculator, and Huashan risk calculators in an observational validation study from January 2011 to December 2014. All necessary clinical information were collected before the biopsy. The results showed that Huashan risk calculators 1 and 2 outperformed the PCPT risk calculator for predicting PCa in both entire training cohort and stratified population （with PSA from 2.0 ng ml^-1 to 20.0 ng ml^-1）. In the validation study, Huashan risk calculator 1 still outperformed the PCPT risk calculator in the entire validation cohort （0.849 vs 0.779 in area under the receiver operating characteristic curve [AUC]） and stratified population. A considerable reduction of unnecessary biopsies （approximately 30%） was also observed when the Huashan risk calculators were used. Thus, we believe that the Huashan risk calculators （especially Huashan risk calculator 1） may have added value for predicting PCa in Chinese population. However, these results still needed further evaluation in larger populations.
文摘Millions of men each year are faced with a clinical suspicion of prostate cancer （PCa） but the prostate biopsy fails to detect the disease. For the urologists, how to select the appropriate candidate for repeat biopsy is a significant clinical dilemma. Traditional risk-stratification tools in this setting such as prostate-specific antigen （PSA） related markers and histopathology findings have met with limited correlation with cancer diagnosis or with significant disease. Thus, an individualized approach using predictive models such as an online risk calculator （RC） or updated biomarkers is more suitable in counseling men about their risk of harboring clinically significant prostate cancer, This review will focus on the available risk-stratification tools in the population of men with prior negative biopsies and persistent suspicion of PCa. The underlying methodology and platforms of the available tools are reviewed to better understand the development and validation of these models. The index patient is then assessed with different RCs to determine the range of heterogeneity among various RCs. This should allow the urologists to better incorporate these various risk-stratification tools into their clinical practice and improve patient counseling.
