Breast cancer risk assessment in 8,824 women attending a family history evaluation and screening programme

Accurate individualized breast cancer risk assessment is essential to provide risk–benefit analysis prior to initiating interventions designed to lower breast cancer risk and start surveillance. We have previously shown that a manual adaptation of Claus tables was as accurate as the Tyrer–Cuzick model and more accurate at predicting breast cancer than the Gail, Claus model and Ford models. Here we reassess the manual model with longer follow up and higher numbers of cancers. Calibration of the manual model was assessed using data from 8,824 women attending the family history evaluation and screening programme in Manchester UK, with a mean follow up of 9.71 years. After exclusion of 40 prevalent cancers, 406 incident breast cancers occurred, and 385.1 were predicted (O/E = 1.05, 95 % CI 0.95–1.16) using the manual model. Predictions were close to that of observed cancers in all risk categories and in all age groups, including women in their forties (O/E = 0.99, 95 % CI 0.83–1.16). Manual risk prediction with use of adjusted Claus tables and curves with modest adjustment for hormonal and reproductive factors was a well-calibrated approach to breast cancer risk estimation in a UK family history clinic.