- Wishart, GC;
- Bajdik, CD;
- Dicks, E;
- Provenzano, E;
- Schmidt, MK;
- Sherman, M;
- Greenberg, DC;
- Green, AR;
- Gelmon, KA;
- Kosma, V-M;
- Olson, JE;
- Beckmann, MW;
- Winqvist, R;
- Cross, SS;
- Severi, G;
- Huntsman, D;
- Pylkäs, K;
- Ellis, I;
- Nielsen, TO;
- Giles, G;
- Blomqvist, C;
- Fasching, PA;
- Couch, FJ;
- Rakha, E;
- Foulkes, WD;
- Blows, FM;
- Bégin, LR;
- van't Veer, LJ;
- Southey, M;
- Nevanlinna, H;
- Mannermaa, A;
- Cox, A;
- Cheang, M;
- Baglietto, L;
- Caldas, C;
- Garcia-Closas, M;
- Pharoah, PDP
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!. 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. 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. 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.