title: Nomograms for prediction of outcome with or without adjuvant radiation therapy for patients with endometrial cancer: a pooled analysis of PORTEC-1 and PORTEC-2 trials.
abstract: BACKGROUND
  Postoperative radiation therapy for stage I endometrial cancer improves locoregional control but is without survival benefit. To facilitate treatment decision support for individual patients, accurate statistical models to predict locoregional relapse (LRR), distant relapse (DR), overall survival (OS), and disease-free survival (DFS) are required.
  
  
  METHODS
  Clinical trial data from the randomized Post Operative Radiation Therapy for Endometrial Cancer (PORTEC-1; N=714 patients) and PORTEC-2 (N=427 patients) trials and registered group (grade 3 and deep invasion, n=99) were pooled for analysis (N=1240). For most patients (86%) pathology review data were available; otherwise original pathology data were used. Trial variables which were clinically relevant and eligible according to data constraints were age, stage, given treatment (pelvic external beam radiation therapy (EBRT), vaginal brachytherapy (VBT), or no adjuvant treatment, FIGO histological grade, depth of invasion, and lymph-vascular invasion (LVSI). Multivariate analyses were based on Cox proportional hazards regression model. Predictors were selected based on a backward elimination scheme. Model results were expressed by the c-index (0.5-1.0; random to perfect prediction). Two validation sets (n=244 and 291 patients) were used.
  
  
  RESULTS
  Accuracy of the developed models was good, with training accuracies between 0.71 and 0.78. The nomograms validated well for DR (0.73), DFS (0.69), and OS (0.70), but validation was only fair for LRR (0.59). Ranking of variables as to their predictive power showed that age, tumor grade, and LVSI were highly predictive for all outcomes, and given treatment for LRR and DFS. The nomograms were able to significantly distinguish low- from high-probability patients for these outcomes.
  
  
  CONCLUSIONS
  The nomograms are internally validated and able to accurately predict long-term outcome for endometrial cancer patients with observation, pelvic EBRT, or VBT after surgery. These models facilitate decision support in daily clinical practice and can be used for patient counseling and shared decision making, selecting patients who benefit most from adjuvant treatment, and generating new hypotheses.
authors: Department of Clinical Oncology, Leiden University Medical Center, Leiden, The Netherlands. Electronic address: c.l.creutzberg@lumc.nl.
authors: Carien L
authors: CL
authors: Creutzberg
authors: Department of Radiation Oncology, MAASTRO, GROW, University Medical Centre Maastricht, Maastricht, The Netherlands.
authors: Ruud G P M
authors: RG
authors: van Stiphout
authors: Department of Clinical Oncology, Leiden University Medical Center, Leiden, The Netherlands.
authors: Remi A
authors: RA
authors: Nout
authors: Department of Radiation Oncology, MAASTRO, GROW, University Medical Centre Maastricht, Maastricht, The Netherlands.
authors: Ludy C H W
authors: LC
authors: Lutgens
authors: Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.
authors: Ina M
authors: IM
authors: Jürgenliemk-Schulz
authors: Department of Radiotherapy, Medisch Spectrum Twente, Enschede, The Netherlands.
authors: Jan J
authors: JJ
authors: Jobsen
authors: Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands.
authors: Vincent T H B M
authors: VT
authors: Smit
authors: Department of Radiation Oncology, MAASTRO, GROW, University Medical Centre Maastricht, Maastricht, The Netherlands.
authors: Philippe
authors: P
authors: Lambin
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001918:Brachytherapy; D018572:Disease-Free Survival; D016889:Endometrial Neoplasms / Q000473:pathology / Q000532:radiotherapy*; D005260:Female; D006801:Humans; D007044:Hysterectomy; D008875:Middle Aged; D015999:Multivariate Analysis; D009364:Neoplasm Recurrence, Local; D009367:Neoplasm Staging; D049451:Nomograms; D016016:Proportional Hazards Models; D018714:Radiotherapy, Adjuvant / Q000379:methods