Risk prediction models for biochemical recurrence after radical prostatectomy using prostate-specific antigen and Gleason score
| Autor: | Xin-Hai Hu, Henning Cammann, Hellmuth-A Meyer, Klaus Jung, Hong-Biao Lu, Natalia Leva, Ahmed Magheli, Carsten Stephan, Jonas Busch |
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| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: | |
| Zdroj: | Asian Journal of Andrology, Vol 16, Iss 6, Pp 897-901 (2014) |
| Druh dokumentu: | article |
| ISSN: | 1008-682X 1745-7262 |
| DOI: | 10.4103/1008-682X.129940 |
| Popis: | 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 |
| Databáze: | Directory of Open Access Journals |
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