PREDICT is an online prognostication tool for early-stage breast cancer, which incorporates human epidermal growth factor 2 (HER2) status and stratifies absolute treatment benefits for hormone therapy, chemotherapy and trastuzumab. The present study compared historical multidisciplinary team (MDT) decisions regarding adjuvant treatment with PREDICT estimates, to determine whether certain patients are being over- or undertreated, particularly when stratified by age and oestrogen-receptor (ER) status. HER2-positive early-stage breast cancer cases over a five-year period at the Cambridge Breast Unit (Addenbrooke’s Hospital, Cambridge, UK) were retrospectively reviewed. Patients receiving neo-adjuvant therapy were excluded. Adjuvant chemotherapy/trastuzumab recommendations based on PREDICT (<3%, no benefit; 3–5%, discuss treatment; and >5%, recommend treatment) were compared with actual MDT decisions. In total, 109 eligible patients were identified. The average age at diagnosis was 59.6 years, with 21 patients older than 70 years (19%). Four patients were predicted to gain an absolute benefit of >5% from chemotherapy/ trastuzumab, but were not offered treatment (all >70 years). Amongst the 19 patients aged >70 years predicted to benefit >3%, six were not offered treatment (32%). In the patients aged <69 years, there was evidence of overtreatment with adjuvant chemotherapy/trastuzumab in 8 out of 12 cases with <3% benefit using PREDICT. For all 20 patients with ER-negative tumours, the MDT and PREDICT decisions correlated, whilst for ER-positive cases, more than half (8 out of 14) were offered treatment despite a <3% predicted benefit. PREDICT can aid decision-making in HER2-positive early-stage breast cancer by identifying older patients at risk of undertreatment with chemotherapy/trastuzumab, and by reducing the overtreatment of patients with little predicted benefit, particularly in ER-positive disease.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.