title: Impact of statistical learning methods on the predictive power of multivariate normal tissue complication probability models.
abstract: OBJECTIVE
  To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models.
  
  
  METHODS
  In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods.
  
  
  RESULTS
  It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method.
  
  
  CONCLUSIONS
  The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.
authors.affiliation: Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. c.j.xu@umcg.nl
authors.forename: Cheng-Jian
authors.initials: CJ
authors.lastname: Xu
authors.forename: Arjen
authors.initials: A
authors.lastname: van der Schaaf
authors.forename: Cornelis
authors.initials: C
authors.lastname: Schilstra
authors.forename: Johannes A
authors.initials: JA
authors.lastname: Langendijk
authors.forename: Aart A
authors.initials: AA
authors.lastname: van't Veld
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001499:Bayes Theorem; D015986:Confounding Factors, Epidemiologic; D005260:Female; D006258:Head and Neck Neoplasms / Q000532:radiotherapy*; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D058958:Organs at Risk / Q000528:radiation effects*; D011337:Probability Learning; D020266:Radiotherapy, Conformal / Q000379:methods; D014987:Xerostomia / Q000209:etiology*