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Evaluating the predictive accuracy and the clinical benefit of a nomogram aimed to predict survival in node‐positive prostate cancer patients: External validation on a multi‐institutional database
Author(s) -
Bianchi Lorenzo,
Schiavina Riccardo,
Borghesi Marco,
Bianchi Federico Mineo,
Briganti Alberto,
Carini Marco,
Terrone Carlo,
Mottrie Alex,
Gacci Mauro,
Gontero Paolo,
Imbimbo Ciro,
Marchioro Giansilvio,
Milanese Giulio,
Mirone Vincenzo,
Montorsi Francesco,
Morgia Giuseppe,
Novara Giacomo,
Porreca Angelo,
Volpe Alessandro,
Brunocilla Eugenio
Publication year - 2018
Publication title -
international journal of urology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.172
H-Index - 67
eISSN - 1442-2042
pISSN - 0919-8172
DOI - 10.1111/iju.13565
Subject(s) - nomogram , medicine , receiver operating characteristic , prostatectomy , prostate cancer , area under the curve , predictive value of tests , population , oncology , cancer , environmental health
Objectives To assess the predictive accuracy and the clinical value of a recent nomogram predicting cancer‐specific mortality‐free survival after surgery in pN 1 prostate cancer patients through an external validation. Methods We evaluated 518 prostate cancer patients treated with radical prostatectomy and pelvic lymph node dissection with evidence of nodal metastases at final pathology, at 10 tertiary centers. External validation was carried out using regression coefficients of the previously published nomogram. The performance characteristics of the model were assessed by quantifying predictive accuracy , according to the area under the curve in the receiver operating characteristic curve and model calibration. Furthermore, we systematically analyzed the specificity, sensitivity, positive predictive value and negative predictive value for each nomogram‐derived probability cut‐off. Finally, we implemented decision curve analysis, in order to quantify the nomogram's clinical value in routine practice. Results External validation showed inferior predictive accuracy as referred to in the internal validation (65.8% vs 83.3%, respectively). The discrimination ( area under the curve ) of the multivariable model was 66.7% (95% CI 60.1–73.0%) by testing with receiver operating characteristic curve analysis. The calibration plot showed an overestimation throughout the range of predicted cancer‐specific mortality‐free survival rates probabilities. However, in decision curve analysis, the nomogram's use showed a net benefit when compared with the scenarios of treating all patients or none. Conclusions In an external setting, the nomogram showed inferior predictive accuracy and suboptimal calibration characteristics as compared to that reported in the original population. However, decision curve analysis showed a clinical net benefit, suggesting a clinical implication to correctly manage pN 1 prostate cancer patients after surgery.