Quantifying independent risk factors for failing to rescreen in a breast cancer screening program in Flanders, Belgium.

BACKGROUND: Mammographic screening may reduce breast cancer mortality by about 20%, provided participation is high and women screen regularly. We quantified independent risk factors for failing to rescreen and built a model to predict how rescreening rates change if these risk factors would be modified. METHODS: Multivariate analysis was used to analyze data from a prospective study which included a self-administered questionnaire and rescreening status 30months after a t0 mammogram, using a random sample of women 50-67years (Belgium 2010-2013). RESULTS: A false positive result at the most recent past mammogram (Odds Ratio=5.0, 95% Confidence Interval 3.6-6.8), an interval until new invitation greater than 25months (Odds Ratio=4.8 for >29months, 95% Confidence Interval 2.9-8.1), waiting times in the mammography unit >1h (Odds Ratio=2.1, 95% Confidence Interval 1.2-3.7) and difficulties in reaching the unit (Odds Ratio=2.5, 95% Confidence Interval 1.4-4.4) were the strongest independent predictors for failing to rescreen. The area under the curve of the receiver operating characteristic analysis was 0.705 for the model development stage and 0.717 for the validation stage and goodness-of-fit was good. CONCLUSIONS: Maintaining an invitation cycle of maximum 25months, limiting waiting time in the mammography unit and lowering the number of false positives could increase breast cancer screening compliance.