Prospective Multi-Institutional Study Evaluating the Performance of Prostate Cancer Risk Calculators

被引:80
作者
Nam, Robert K. [1 ]
Kattan, Michael W. [8 ]
Chin, Joseph L. [6 ]
Trachtenberg, John [2 ]
Singal, Rajiv [3 ]
Rendon, Ricardo [7 ]
Klotz, Laurence H. [1 ]
Sugar, Linda [1 ]
Sherman, Christopher [1 ]
Izawa, Jonathan [6 ]
Bell, David [7 ]
Stanimirovic, Aleksandra [1 ]
Venkateswaran, Vasundara [1 ]
Diamandis, Eleftherios P. [5 ]
Yu, Changhong [8 ]
Loblaw, D. Andrew [1 ]
Narod, Steven A. [4 ]
机构
[1] Sunnybrook Hlth Sci Ctr, Toronto, ON M4N 3M5, Canada
[2] Princess Margaret Hosp, Toronto, ON M4X 1K9, Canada
[3] Toronto E Gen & Orthoped Hosp, Toronto, ON, Canada
[4] Univ Toronto, Toronto, ON, Canada
[5] Mt Sinai Hosp, Toronto, ON M5G 1X5, Canada
[6] Univ Western Ontario, London, ON, Canada
[7] Queen Elizabeth 2 Hlth Sci Ctr, Halifax, NS, Canada
[8] Cleveland Clin, Cleveland, OH 44106 USA
关键词
DECISION CURVE ANALYSIS; PREDICTION MODELS; PREVENTION TRIAL; ANTIGEN LEVEL; MORTALITY;
D O I
10.1200/JCO.2010.32.6371
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Purpose Prostate cancer risk calculators incorporate many factors to evaluate an individual's risk for prostate cancer. We validated two common North American-based, prostate cancer risk calculators. Patients and Methods We conducted a prospective, multi-institutional study of 2,130 patients who underwent a prostate biopsy for prostate cancer detection from five centers. We evaluated the performance of the Sunnybrook nomogram-based prostate cancer risk calculator (SRC) and the Prostate Cancer Prevention Trial (PCPT)-based risk calculator (PRC) to predict the presence of any cancer and high-grade cancer. We examined discrimination, calibration, and decision curve analysis techniques to evaluate the prediction models. Results Of the 2,130 patients, 867 men (40.7%) were found to have cancer, and 1,263 (59.3%) did not have cancer. Of the patients with cancer, 403 (46.5%) had a Gleason score of 7 or more. The area under the [ concentration-time] curve (AUC) for the SRC was 0.67 (95% CI, 0.65 to 0.69); the AUC for the PRC was 0.61 (95% CI, 0.59 to 0.64). The AUC was higher for predicting aggressive disease from the SRC (0.72; 95% CI, 0.70 to 0.75) compared with that from the PRC (0.67; 95% CI, 0.64 to 0.70). Decision curve analyses showed that the SRC performed better than the PRC for risk thresholds of more than 30% for any cancer and more than 15% for aggressive cancer. Conclusion The SRC performed better than the PRC, but neither one added clinical benefit for risk thresholds of less than 30%. Further research is needed to improve the AUCs of the risk calculators, particularly for higher-grade cancer.
引用
收藏
页码:2959 / 2964
页数:6
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