title: PREDICT Plus: development and validation of a prognostic model for early breast cancer that includes HER2.
abstract: BACKGROUND
  Predict (www.predict.nhs.uk) is an online, breast cancer prognostication and treatment benefit tool. The aim of this study was to incorporate the prognostic effect of HER2 status in a new version (Predict+), and to compare its performance with the original Predict and Adjuvant!.
  
  
  METHODS
  The prognostic effect of HER2 status was based on an analysis of data from 10 179 breast cancer patients from 14 studies in the Breast Cancer Association Consortium. The hazard ratio estimates were incorporated into Predict. The validation study was based on 1653 patients with early-stage invasive breast cancer identified from the British Columbia Breast Cancer Outcomes Unit. Predicted overall survival (OS) and breast cancer-specific survival (BCSS) for Predict+, Predict and Adjuvant! were compared with observed outcomes.
  
  
  RESULTS
  All three models performed well for both OS and BCSS. Both Predict models provided better BCSS estimates than Adjuvant!. In the subset of patients with HER2-positive tumours, Predict+ performed substantially better than the other two models for both OS and BCSS.
  
  
  CONCLUSIONS
  Predict+ is the first clinical breast cancer prognostication tool that includes tumour HER2 status. Use of the model might lead to more accurate absolute treatment benefit predictions for individual patients.
authors: Cambridge Breast Unit, Addenbrookes Hospital, Cambridge, UK.
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mesh_terms: D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000188:drug therapy* / Q000201:enzymology*; D015331:Cohort Studies; D005260:Female; D006801:Humans; D008875:Middle Aged; D015233:Models, Statistical; D011379:Prognosis; D016016:Proportional Hazards Models; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000096:biosynthesis*; D015203:Reproducibility of Results; D055815:Young Adult
chemical_list: D018719:Erb-b2 Receptor Tyrosine Kinases