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- W2029889523 abstract "Prediction models constitute one of the most common categories of research papers in urology. Indeed, a review of literature published in July 2007 found >100 different prediction tools for prostate cancer (PCa) alone [1]. Even within the very narrow research area of Lughezzani et al’s paper [2] on outcomes after radical prostatectomy, models have been published to predict recurrence based on preoperative [3] and postoperative [4] data; recurrence at 2 yr [5]; recurrence at 5 yr incorporating transforming growth factor-b1 [6]; recurrence at 5 yr including surgeon experience in the model [7]; the trifecta of continence, potency, and freedom from recurrence [8]; PCa-specific death at 10 yr [9]; and so on and so forth. PCa prediction modeling has become so complex that a ‘‘meta-literature’’ has developed around choosing appropriate prediction tools [10,11]. My guess is that few of the published prediction models are much good, and even if they were, we wouldn’t know it." @default.
- W2029889523 created "2016-06-24" @default.
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- W2029889523 date "2010-04-01" @default.
- W2029889523 modified "2023-09-23" @default.
- W2029889523 title "Prediction Models in Urology: Are They Any Good, and How Would We Know Anyway?" @default.
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- W2029889523 doi "https://doi.org/10.1016/j.eururo.2009.12.026" @default.
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