title: Integrated models for the prediction of late genitourinary complaints after high-dose intensity modulated radiotherapy for prostate cancer: making informed decisions.
abstract: OBJECTIVE
  To develop predictive models for late radiation-induced hematuria and nocturia allowing a patient individualized estimation of pre-treatment risk.
  
  
  METHODS
  We studied 262 PCa patients treated with curative intensity modulated radiotherapy to the intact prostate or prostate bed. A total of 372 variables were used for prediction modeling, among which 343 genetic variations. Toxicity was scored using an in-house developed toxicity scale. Predictor selection is achieved by the EMLasso procedure, a penalized logistic regression method with an EM algorithm handling missing data and crossvalidation avoiding overfit. Model performance was expressed by the area under the curve (AUC) and by sensitivity and specificity.
  
  
  RESULTS
  Variables of the model predicting late hematuria (36/262) are bladder volume receiving ⩾75 Gy, prostatic transurethral resection and four polymorphisms. (AUC = 0.80, sensitivity = 83.3%, specificity = 61.5%). The AUC drops to 0.67 when the genetic markers are left out. The model that predicts for late nocturia (29/262) contains the minimal clinical target volume (CTV) dose, the CTV volume and three polymorphisms (AUC = 0.76, sensitivity = 75.9%, specify = 67.4%). This model is a better predictor for nocturia compared to the nongenetic model (AUC of 0.60).
  
  
  CONCLUSIONS
  We were able to develop models that predict for the occurrence of late radiation-induced hematuria and nocturia, including genetic factors which might improve the prediction of late urinary toxicity.
authors.affiliation: Department of Basic Medical Sciences, Ghent University, Belgium. Electronic address: Sofie.DeLanghe@UGent.be.
authors.forename: Sofie
authors.initials: S
authors.lastname: De Langhe
authors.affiliation: Department of Radiotherapy, Ghent University Hospital, Belgium.
authors.forename: Gert
authors.initials: G
authors.lastname: De Meerleer
authors.affiliation: Department of Basic Medical Sciences, Ghent University, Belgium.
authors.forename: Kim
authors.initials: K
authors.lastname: De Ruyck
authors.affiliation: Department of Radiotherapy, Ghent University Hospital, Belgium.
authors.forename: Piet
authors.initials: P
authors.lastname: Ost
authors.affiliation: Department of Radiotherapy, Ghent University Hospital, Belgium.
authors.forename: Valérie
authors.initials: V
authors.lastname: Fonteyne
authors.affiliation: Department of Radiotherapy, Ghent University Hospital, Belgium.
authors.forename: Wilfried
authors.initials: W
authors.lastname: De Neve
authors.affiliation: Department of Basic Medical Sciences, Ghent University, Belgium.
authors.forename: Hubert
authors.initials: H
authors.lastname: Thierens
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D003657:Decision Making; D003661:Decision Support Techniques; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease; D006417:Hematuria / Q000209:etiology / Q000235:genetics; D006801:Humans; D008297:Male; D052801:Male Urogenital Diseases / Q000209:etiology* / Q000235:genetics; D008875:Middle Aged; D015233:Models, Statistical; D053158:Nocturia / Q000209:etiology / Q000235:genetics; D020641:Polymorphism, Single Nucleotide; D011471:Prostatic Neoplasms / Q000532:radiotherapy*; D011832:Radiation Injuries / Q000209:etiology* / Q000235:genetics; D050397:Radiotherapy, Intensity-Modulated / Q000009:adverse effects* / Q000379:methods; D012044:Regression Analysis
chemical_list: D005819:Genetic Markers
keywords: Genetic polymorphisms; Genitourinary toxicity; Predictive model; Prostate cancer; Radiotherapy; Translational research