Comparison of questionnaire-based breast cancer prediction models in the Nurses’ Health Study - Glynn, Robert J (Cancer Epidemiol Biomarkers Prev, 2019)
BACKGROUND: The Gail model and the model developed by Tyrer and Cuzick are two questionnaire–based approaches with demonstrated ability to predict development of breast cancer in a general population. METHODS: We compared calibration, discrimination and net-reclassification of these models, using data from questionnaires sent every 2 years to 76,922 participants in the Nurses’ Health Study between 1980 and 2006, with 4,384 incident invasive breast cancers identified by 2008 (median follow-up 24 years; range 1–28 years). In a random one-third sample of women, we also compared the performance of these models with predictions from the Rosner-Colditz model estimated from the remaining participants. RESULTS: Both the Gail and Tyrer-Cuzick models showed evidence of mis-calibration (Hosmer-Lemeshow P<0.001 for each) with notable (P<0.01) over-prediction in higher risk women (2-year risk above about 1%) and under-prediction in lower risk women (risk below about .25%). The Tyrer-Cuzick model had slightly higher C-statistics both overall (P<0.001) and in age-specific comparisons than the Gail model (overall C 0.63 for Tyrer-Cuzick versus 0.61 for the Gail model). Evaluation of net reclassification did not favor either model. In the one-third sample, the Rosner-Colditz model had better calibration and discrimination than the other two models. All models had C-statistics <0.60 among women age ≥70. CONCLUSION: Both the Gail and Tyrer-Cuzick models had some ability to discriminate breast cancer cases and non-cases, but have limitations in their model fit. IMPACT: Refinements may be needed to questionnaire-based approaches to predict breast cancer in older and higher risk women.