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The performance of prediction models can be assessed using a variety of methods and metrics. Traditional measures for binary and survival outcomes include the Brier score to indicate overall model performance, the concordance (or c) statistic for discriminative ability (or area under the receiver operating characteristic [ROC] curve), and goodness-of-fit(More)
PURPOSE An increasing serum prostate-specific antigen (PSA) level is the initial sign of recurrent prostate cancer among patients treated with radical prostatectomy. Salvage radiation therapy (SRT) may eradicate locally recurrent cancer, but studies to distinguish local from systemic recurrence lack adequate sensitivity and specificity. We developed a(More)
PURPOSE Few published studies have analyzed risk factors for sarcoma-specific death. We developed and internally validated a nomogram that combines the factors to predict the probability of 12-year sarcoma-specific death using a database of 2,136 prospectively followed adult patients treated at a single institution. PATIENTS AND METHODS Nomogram predictor(More)
PURPOSE Laparoscopic partial nephrectomy is an increasingly performed, minimally invasive alternative to open partial nephrectomy. We compared early postoperative outcomes in 1,800 patients undergoing open partial nephrectomy by experienced surgeons with the initial experience with laparoscopic partial nephrectomy in patients with a single renal tumor 7 cm(More)
PURPOSE We analyzed the long-term progression-free probability after radical retropubic prostatectomy in a consecutive series of patients with localized prostate cancer. MATERIALS AND METHODS From 1983 to 1998, 1,000 patients (median age 62.9 years, range 37.7 to 81.4) with clinical stage T1 to T2 prostate cancer were treated with radical retropubic(More)
PURPOSE Although models exist that place patients into discrete groups at various risks for disease recurrence after surgery for prostate cancer, we know of no published work that combines pathologic factors to predict an individual's probability of disease recurrence. Because clinical stage and biopsy Gleason grade only approximate pathologic stage and(More)
PURPOSE To develop and validate a model that can be used to predict the overall survival probability among metastatic hormone-refractory prostate cancer patients (HRPC). PATIENTS AND METHODS Data from six Cancer and Leukemia Group B protocols that enrolled 1,101 patients with metastatic hormone-refractory adenocarcinoma of the prostate during the study(More)
PURPOSE Long-term prostate cancer specific mortality after radical prostatectomy is poorly defined in the era of widespread screening. An understanding of the treated natural history of screen detected cancers and the pathological risk factors for prostate cancer specific mortality are needed for treatment decision making. MATERIALS AND METHODS Using Fine(More)
PURPOSE Screening with serum prostate specific antigen testing leads to the detection of many prostate cancers early in their natural history. Statistical models have been proposed to predict indolent cancer. We validated and updated model predictions for a screening setting. MATERIALS AND METHODS We selected 247 patients with clinical stage T1C or T2A(More)
OBJECTIVES Nomograms and artificial neural networks (ANNs) represent alternative methodologic approaches to predict the probability of prostate cancer on initial biopsy. We hypothesized that, in a head-to-head comparison, one of the approaches might demonstrate better accuracy and performance characteristics than the other. METHODS A previously published(More)