title: A comparison of models for predicting sperm retrieval before microdissection testicular sperm extraction in men with nonobstructive azoospermia.
abstract: OBJECTIVE
  We developed an artificial neural network and nomogram using readily available clinical features to model the chance of identifying sperm with microdissection testicular sperm extraction by readily available preoperative clinical parameters for men with nonobstructive azoospermia.
  
  
  METHODS
  We reviewed the records of 1,026 men who underwent microdissection testicular sperm extraction. Patient age, follicle-stimulating hormone level, testicular volume, history of cryptorchidism, Klinefelter syndrome and presence of varicocele were included in the models. For the artificial neural network the data set was divided randomly into a training set (75%) and a test set (25%) with n1/n2 cross validation used to evaluate model accuracy, and then modeled with a neural computational system. In addition, a nomogram with calibration plots was developed to predict sperm retrieval with microdissection testicular sperm extraction. We compared these models to logistic regression.
  
  
  RESULTS
  The ROC area for the neural computational system in the test set was 0.641. The neural network correctly predicted the outcome in 152 of the 256 test set patients (59.4%). The nomogram AUC was 0.59 and adequately calibrated. Multivariable logistic regression demonstrated patient age, history of Klinefelter syndrome and cryptorchidism to be significant predictors of sperm retrieval (p <0.05). However, follicle-stimulating hormone and testicular volume were not significant by internal validation.
  
  
  CONCLUSIONS
  We modeled a combination of well described preoperative clinical parameters to predict sperm retrieval using a neural computational system and nomogram with acceptable predictive values. The generalizability of these findings requires external validation.
authors.affiliation: Departments of Urology, New York-Presbyterian Hospital, Weill Cornell Medical College, New York, New York 10065, USA.
authors.forename: Ranjith
authors.initials: R
authors.lastname: Ramasamy
authors.forename: Wendy O
authors.initials: WO
authors.lastname: Padilla
authors.forename: E Charles
authors.initials: EC
authors.lastname: Osterberg
authors.forename: Abhishek
authors.initials: A
authors.lastname: Srivastava
authors.forename: Jennifer E
authors.initials: JE
authors.lastname: Reifsnyder
authors.forename: Craig
authors.initials: C
authors.lastname: Niederberger
authors.forename: Peter N
authors.initials: PN
authors.lastname: Schlegel
mesh_terms: D053713:Azoospermia; D005544:Forecasting; D006801:Humans; D008297:Male; D042282:Microdissection; D016571:Neural Networks, Computer; D049451:Nomograms; D053625:Sperm Retrieval / Q000706:statistics & numerical data*; D013737:Testis