Statistical Methods for Estimating the Cumulative Risk of Screening Mammography Outcomes

Item does not contain fulltextBACKGROUND: This study illustrates alternative statistical methods for estimating cumulative risk of screening mammography outcomes in longitudinal studies. METHODS: Data from the US Breast Cancer Surveillance Consortium (BCSC) and the Nijmegen Breast Cancer Screening Program in the Netherlands were used to compare four statistical approaches to estimating cumulative risk. We estimated cumulative risk of false-positive recall and screen-detected cancer after 10 screening rounds using data from 242,835 women ages 40 to 74 years screened at the BCSC facilities in 1993-2012 and from 17,297 women ages 50 to 74 years screened in Nijmegen in 1990-2012. RESULTS: In the BCSC cohort, a censoring bias model estimated bounds of 53.8% to 59.3% for false-positive recall and 2.4% to 7.6% for screen-detected cancer, assuming 10% increased or decreased risk among women screened for one additional round. In the Nijmegen cohort, false-positive recall appeared to be associated with subsequent discontinuation of screening leading to overestimation of risk of a false-positive recall based on adjusted discrete-time survival models. Bounds estimated by the censoring bias model were 11.0% to 19.9% for false-positive recall and 4.2% to 9.7% for screen-detected cancer. CONCLUSION: Choice of statistical methodology can substantially affect cumulative risk estimates. The censoring bias model is appropriate under a variety of censoring mechanisms and provides bounds for cumulative risk estimates under varying degrees of dependent censoring. IMPACT: This article illustrates statistical methods for estimating cumulative risks of cancer screening outcomes, which will be increasingly important as screening test recommendations proliferate. Cancer Epidemiol Biomarkers Prev; 25(3); 513-20. (c)2015 AACR