Nermarie Velazquez1, Benjamin Press2, Audrey Renson3, James S Wysock1, Samir Taneja1, William C Huang1, Marc A Bjurlin4. 1. Department of Urology, NYU Langone Health, New York, NY. 2. School of Medicine, Rutgers New Jersey Medical School, Newark, NJ. 3. Department of Clinical Research, NYU Langone Hospital-Brooklyn, Brooklyn, NY; Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, The City University of New York, New York, NY. 4. Department of Urology, NYU Langone Hospital-Brooklyn, Brooklyn, NY. Electronic address: Marc.Bjurlin@nyumc.org.
Abstract
INTRODUCTION: Penectomy for PC is useful in staging, disease prognosis, and treatment. Limited studies have evaluated its surgical complications. We sought to assess these complications and determine predictive models to create a novel risk score for penectomy complications. PATIENTS AND METHODS: A retrospective review of patients undergoing PC surgical management from the 2005-2016 American College of Surgeons National Surgical Quality Improvement Program was performed. Data were queried for partial and total penectomy among those with PC. To develop predictive models of complications, we fit LASSO logistic, random forest, and stepwise logistic models to training data using cross-validation, demographic, comorbidity, laboratory, and wound characteristics as candidate predictors. Each model was evaluated on the test data using receiver operating characteristic curves. A novel risk score was created by rounding coefficients from the LASSO logistic model. RESULTS: A total of 304 cases met the inclusion criteria. Overall incidence of penectomy complications was 19.7%, where urinary tract infection (3.0%), superficial surgical site infection (3.0%), and bleeding requiring transfusion (3.9%) were most common. LASSO logistic, random forest, and stepwise logistic models for predicting complications had area under the curve (AUC) [95% confidence interval] values of 0.66 [0.52-0.81], 0.73 [0.63-0.83], and 0.59 [0.45-0.74], respectively. Eleven variables were included in the risk score. The LASSO model-derived risk score had moderately good performance (area under the curve [95% confidence interval] 0.74 [0.66-0.82]). Using a cutoff point of 6, the score attains sensitivity 0.58, specificity 0.74, and kappa 0.26. CONCLUSION: PC management through penectomy is associated with appreciable complications rates. Predictive models of penectomy complications performed moderately well. Our novel prognostic risk score may allow for improved preoperative counseling and risk stratification of men undergoing surgical management of PC.
INTRODUCTION: Penectomy for PC is useful in staging, disease prognosis, and treatment. Limited studies have evaluated its surgical complications. We sought to assess these complications and determine predictive models to create a novel risk score for penectomy complications. PATIENTS AND METHODS: A retrospective review of patients undergoing PC surgical management from the 2005-2016 American College of Surgeons National Surgical Quality Improvement Program was performed. Data were queried for partial and total penectomy among those with PC. To develop predictive models of complications, we fit LASSO logistic, random forest, and stepwise logistic models to training data using cross-validation, demographic, comorbidity, laboratory, and wound characteristics as candidate predictors. Each model was evaluated on the test data using receiver operating characteristic curves. A novel risk score was created by rounding coefficients from the LASSO logistic model. RESULTS: A total of 304 cases met the inclusion criteria. Overall incidence of penectomy complications was 19.7%, where urinary tract infection (3.0%), superficial surgical site infection (3.0%), and bleeding requiring transfusion (3.9%) were most common. LASSO logistic, random forest, and stepwise logistic models for predicting complications had area under the curve (AUC) [95% confidence interval] values of 0.66 [0.52-0.81], 0.73 [0.63-0.83], and 0.59 [0.45-0.74], respectively. Eleven variables were included in the risk score. The LASSO model-derived risk score had moderately good performance (area under the curve [95% confidence interval] 0.74 [0.66-0.82]). Using a cutoff point of 6, the score attains sensitivity 0.58, specificity 0.74, and kappa 0.26. CONCLUSION: PC management through penectomy is associated with appreciable complications rates. Predictive models of penectomy complications performed moderately well. Our novel prognostic risk score may allow for improved preoperative counseling and risk stratification of men undergoing surgical management of PC.
Authors: Paula Dhiman; Jie Ma; Constanza L Andaur Navarro; Benjamin Speich; Garrett Bullock; Johanna A A Damen; Lotty Hooft; Shona Kirtley; Richard D Riley; Ben Van Calster; Karel G M Moons; Gary S Collins Journal: BMC Med Res Methodol Date: 2022-04-08 Impact factor: 4.615
Authors: Paula Dhiman; Jie Ma; Constanza L Andaur Navarro; Benjamin Speich; Garrett Bullock; Johanna A A Damen; Lotty Hooft; Shona Kirtley; Richard D Riley; Ben Van Calster; Karel G M Moons; Gary S Collins Journal: Diagn Progn Res Date: 2022-07-07
Authors: Demis N Lipe; Phillip B Mann; Rodrick Babakhanlou; Maria T Cruz Carreras; A Guido Hita; Monica K Wattana Journal: Emerg Med Int Date: 2021-07-27 Impact factor: 1.112