• Jeroen J van den Broek, Nicolien T van Ravesteyn, Jeanne S Mandelblatt, Hui Huang, Mehmet Ali Ergun, Elizabeth S Burnside, Cong Xu, Yisheng Li, Oguzhan Alagoz, Sandra J Lee, Natasha K Stout, Juhee Song, Amy Trentham-Dietz, Sylvia K Plevritis, Sue M Moss, and Harry J de Koning.
• Department of Public Health, Erasmus Medical Center, Rotterdam, the Netherlands.
• Med Decis Making. 2018 Apr 1; 38 (1_suppl): 140S-150S.

BackgroundThe UK Age trial compared annual mammography screening of women ages 40 to 49 years with no screening and found a statistically significant breast cancer mortality reduction at the 10-year follow-up but not at the 17-year follow-up. The objective of this study was to compare the observed Age trial results with the Cancer Intervention and Surveillance Modeling Network (CISNET) breast cancer model predicted results.MethodsFive established CISNET breast cancer models used data on population demographics, screening attendance, and mammography performance from the Age trial together with extant natural history parameters to project breast cancer incidence and mortality in the control and intervention arm of the trial.ResultsThe models closely reproduced the effect of annual screening from ages 40 to 49 years on breast cancer incidence. Restricted to breast cancer deaths originating from cancers diagnosed during the intervention phase, the models estimated an average 15% (range across models, 13% to 17%) breast cancer mortality reduction at the 10-year follow-up compared with 25% (95% CI, 3% to 42%) observed in the trial. At the 17-year follow-up, the models predicted 13% (range, 10% to 17%) reduction in breast cancer mortality compared with the non-significant 12% (95% CI, -4% to 26%) in the trial.ConclusionsThe models underestimated the effect of screening on breast cancer mortality at the 10-year follow-up. Overall, the models captured the observed long-term effect of screening from age 40 to 49 years on breast cancer incidence and mortality in the UK Age trial, suggesting that the model structures, input parameters, and assumptions about breast cancer natural history are reasonable for estimating the impact of screening on mortality in this age group.

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