title: Are we able to predict survival in ER-positive HER2-negative breast cancer? A comparison of web-based models.
abstract: BACKGROUND
  Several prognostic models have been proposed and demonstrated to be predictive of survival outcomes in breast cancer. In the present article, we assessed whether three of these models are comparable at an individual level.
  
  
  METHODS
  We used a large data set (n=965) of women with hormone receptor-positive and HER2-negative early breast cancer from the public data set of the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) study. We compared the overall performance of three validated web-based models: Adjuvant!, CancerMath.net and PREDICT, and we assessed concordance of these models in 10-year survival prediction.
  
  
  RESULTS
  Discrimination performances of the three calculators to predict 10-year survival were similar for the Adjuvant! Model, 0.74 (95% CI 0.71-0.77) for the Cancermath.net model and 0.72 (95% CI 0.69-0.75) for the PREDICT model). Calibration performances, assessed graphically, were satisfactory. Predictions were concordant and stable in the subgroup, with a predicted survival higher than 90% with a median score dispersion at 0.08 (range 0.06-0.10). Dispersion, however, reached 30% for the subgroups with a predicted survival between 10 and 50%.
  
  
  CONCLUSIONS
  This study revealed that the three web-based predictors equally perform well at the population level, but exhibit a high degree of discordance in the intermediate and poor prognosis groups.
authors.affiliation: 1] Department of Surgery, Institut Curie, Paris, France [2] Department of Gynecology, Hôpital Tenon, Paris, France.
authors.forename: E
authors.initials: E
authors.lastname: Laas
authors.affiliation: 1] Department of Surgery, Institut Curie, Paris, France [2] Craigavon Area Hospital Breast Unit, Portadown BT63 5QQ, Northern Ireland.
authors.forename: P
authors.initials: P
authors.lastname: Mallon
authors.affiliation: Department of Surgery, Institut Curie, Paris, France.
authors.forename: M
authors.initials: M
authors.lastname: Delomenie
authors.affiliation: 1] Department of Informatics, EISTI Engineering School, Cergy, France [2] Department of Medicine, Bio5 Institute, University of Arizona, Tucson, AZ, USA.
authors.forename: V
authors.initials: V
authors.lastname: Gardeux
authors.affiliation: Department of medical oncology, Institut Curie, Paris, France.
authors.forename: J-Y
authors.initials: JY
authors.lastname: Pierga
authors.affiliation: Department of medical oncology, Institut Curie, Paris, France.
authors.forename: P
authors.initials: P
authors.lastname: Cottu
authors.affiliation: Department of medical oncology, Institut Curie, Paris, France.
authors.forename: F
authors.initials: F
authors.lastname: Lerebours
authors.affiliation: Department of public health, Institut Curie, Paris, France.
authors.forename: D
authors.initials: D
authors.lastname: Stevens
authors.affiliation: Department of Surgery, Institut Curie, Paris, France.
authors.forename: R
authors.initials: R
authors.lastname: Rouzier
authors.affiliation: 1] Department of Surgery, Institut Curie, Paris, France [2] Residual Tumor and Response to Treatment Team, Department of Translational Research, Institut Curie, Paris, France.
authors.forename: F
authors.initials: F
authors.lastname: Reyal
mesh_terms: D000328:Adult; D001943:Breast Neoplasms / Q000401:mortality* / Q000473:pathology*; D005260:Female; D006801:Humans; D008875:Middle Aged; D008954:Models, Biological; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000378:metabolism; D011960:Receptors, Estrogen / Q000378:metabolism; D018426:SEER Program; D016019:Survival Analysis; D064878:Web Browser
chemical_list: D018719:Erb-b2 Receptor Tyrosine Kinases; D011960:Receptors, Estrogen; C508053:ERBB2 protein, human