1] Department of Pathophysiology, Prostate Diseases Prevention and Treatment Research Centre, Norman Bethune College of Medicine, Jilin University, Changchun 130021, China  Laboratory of Transplantation and Immunology, Xuzhou Medical College, Xuzhou 221000, China.
The PSA screening for 25 years in America is the biggest cohort study in a field of public health.27 We should realize not only the significance of the early diagnosis and treatment of PCa, but also the dramatic decrease in PCaMR from 2002 to 2008. The data from the IARC were especially noteworthy.Moreover, the patients with highly aggressive PCa, who account for more than 30% of all PCa patients, could only be diagnosed earlier by PSA screening. The patients would thus gain the opportunity for earlier treatment and would have a prolonged, higher quality life-span. However, the complications of interventional treatments, including biopsy,radical prostatectomy and/or radiation therapy,will become more avoidable in the near future.According to the supporting evidence for the decrease in PCa mortality in PSA screening, we strongly hope that the USPSTF changes the 'D' recommendation for PSA screening.
[Show abstract][Hide abstract] ABSTRACT: Many computer models for predicting the risk of prostate cancer have been developed including for prediction of biochemical recurrence (BCR). However, models for individual BCR free probability at individual time-points after a BCR free period are rare. Follow-up data from 1656 patients who underwent laparoscopic radical prostatectomy (LRP) were used to develop an artificial neural network (ANN) to predict BCR and to compare it with a logistic regression (LR) model using clinical and pathologic parameters, prostate-specific antigen (PSA), margin status (R0/1), pathological stage (pT), and Gleason Score (GS). For individual BCR prediction at any given time after operation, additional ANN, and LR models were calculated every 6 months for up to 7.5 years of follow-up. The areas under the receiver operating characteristic (ROC) curve (AUC) for the ANN (0.754) and LR models (0.755) calculated immediately following LRP, were larger than that for GS (AUC: 0.715; P = 0.0015 and 0.001), pT or PSA (AUC: 0.619; P always <0.0001) alone. The GS predicted the BCR better than PSA (P = 0.0001), but there was no difference between the ANN and LR models (P = 0.39). Our ANN and LR models predicted individual BCR risk from radical prostatectomy for up to 10 years postoperative. ANN and LR models equally and significantly improved the prediction of BCR compared with PSA and GS alone. When the GS and ANN output values are combined, a more accurate BCR prediction is possible, especially in high-risk patients with GS ≥7.
Asian Journal of Andrology 07/2014; 16(6). DOI:10.4103/1008-682X.129940 · 2.60 Impact Factor
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