A simple and accurate model for prediction of cancer-specific mortality in patients treated with surgery for primary penile squamous cell carcinoma.

TY - JOUR

T1 - A simple and accurate model for prediction of cancer-specific mortality in patients treated with surgery for primary penile squamous cell carcinoma.

AU - Zini, Laurent

AU - Cloutier, Vincent

AU - Isbarn, Hendrik

AU - Perrotte, Paul

AU - Capitanio, Umberto

AU - Jeldres, Claudio

AU - Shariat, Shahrokh F

AU - Saad, Fred

AU - Arjane, Philippe

AU - Duclos, Alain

AU - Lattouf, Jean-Baptiste

AU - Montorsi, Francesco

AU - Karakiewicz, Pierre I

PY - 2009

Y1 - 2009

N2 - PURPOSE: Cancer-specific mortality (CSM) of patients with primary penile squamous cell carcinoma (PPSCC) may be quite variable. Recently, a nomogram was developed to provide standardized and individualized mortality predictions. Unfortunately, it relies on a large number (n = 8) of specific variables that are unavailable in routine clinical practice. We attempted to develop a simpler prediction rule with at least equal accuracy in predicting CSM after surgical removal of PPSCC. EXPERIMENTAL DESIGN: The predictive rule was developed on a cohort of 856 patients identified in the 1988 to 2004 Surveillance, Epidemiology and End Results (SEER) database. The predictors consisted of age, race, SEER stage (localized versus regional versus metastatic), tumor grade, type of surgery (excisional biopsy, partial penectomy, and radical penectomy), and of lymph node status (pN0 versus pN1-3 versus pNx). A look-up table based on Cox regression model-derived coefficients was used for prediction of 5-year CSM. The predictive rule accuracy was tested using the Harrell's modification of the area under the receiver operating characteristics curve. RESULTS: SEER stage and histologic grade achieved independent predictor status and qualified for inclusion in the model. The model achieved 73.8% accuracy for prediction of CSM at 5 years after surgery. Both predictors achieved independent predictor status in competing risk regression models addressing CSM, where other cause mortality was controlled for. CONCLUSION: Despite equivalent accuracy, our predictive rule predicting 5-year CSM in patients with PPSCC is substantially less complex (2 versus 8 variables) than the previously published model.

AB - PURPOSE: Cancer-specific mortality (CSM) of patients with primary penile squamous cell carcinoma (PPSCC) may be quite variable. Recently, a nomogram was developed to provide standardized and individualized mortality predictions. Unfortunately, it relies on a large number (n = 8) of specific variables that are unavailable in routine clinical practice. We attempted to develop a simpler prediction rule with at least equal accuracy in predicting CSM after surgical removal of PPSCC. EXPERIMENTAL DESIGN: The predictive rule was developed on a cohort of 856 patients identified in the 1988 to 2004 Surveillance, Epidemiology and End Results (SEER) database. The predictors consisted of age, race, SEER stage (localized versus regional versus metastatic), tumor grade, type of surgery (excisional biopsy, partial penectomy, and radical penectomy), and of lymph node status (pN0 versus pN1-3 versus pNx). A look-up table based on Cox regression model-derived coefficients was used for prediction of 5-year CSM. The predictive rule accuracy was tested using the Harrell's modification of the area under the receiver operating characteristics curve. RESULTS: SEER stage and histologic grade achieved independent predictor status and qualified for inclusion in the model. The model achieved 73.8% accuracy for prediction of CSM at 5 years after surgery. Both predictors achieved independent predictor status in competing risk regression models addressing CSM, where other cause mortality was controlled for. CONCLUSION: Despite equivalent accuracy, our predictive rule predicting 5-year CSM in patients with PPSCC is substantially less complex (2 versus 8 variables) than the previously published model.

M3 - SCORING: Zeitschriftenaufsatz

VL - 15

SP - 1013

EP - 1018

JO - CLIN CANCER RES

JF - CLIN CANCER RES

SN - 1078-0432

IS - 3

M1 - 3

ER -