Evaluation of breast cancer mammography screening policies considering adherence behavior

Operational research techniques applied throughout cancer care services: a review

“…The majority of breast cancer screening papers either compare mammogram screening strategies (Brailsford, Harper, & Sykes, 2012;Madadi, Zhang, & Henderson, 2015;Tejada et al, 2014) or optimise the decision of whether to mammogram or not each year (Ayer, Alagoz, & Stout, 2012;O'Mahony et al, 2015;Ayer, Alagoz, Stout, & Burnside, 2016;Wang & Zhang, 2017). Of these, Madadi et al (2015) consider an especially large set of screening strategies.…”

“…Contrastingly, O'Mahony et al (2015) purposely built a relatively simple mathematical model, validated its results against a more complex simulation and found that their model was detailed enough to demonstrate that different risk levels have different optimal screening intervals. The performance measures assessed by the models are diverse and include mortality measures (Arrospide et al, 2015;Brailsford et al, 2012;Madadi et al, 2015;Tejada et al, 2014;Wang & Zhang, 2017), quality-adjusted life year measures Ayer, 2015;Ayer et al, 2016;Madadi et al, 2015;Tejada et al, 2014) …”

“…Of these, Madadi et al (2015) consider an especially large set of screening strategies. There has been a shift in focus away from the fixed-interval policies that are common in practice, to consideration of dynamic screening intervals Brailsford et al, 2012;Tejada et al, 2014;Madadi et al, 2015;O'Mahony et al, 2015;Ayer et al, 2016;Wang & Zhang, 2017). These dynamic intervals may vary based on changing risk, age and adherence to screening guidelines.…”

“…These dynamic intervals may vary based on changing risk, age and adherence to screening guidelines. Adherence is modelled in a range of ways from detailed psychological models of behaviour (Brailsford et al, 2012), to changing physician belief about which patients are regular or irregular screeners (Ayer et al, 2016), and to uncertain adherence probabilities based on age and screening interval (Madadi et al, 2015). Arrospide et al (2015), on the other hand, aim to evaluate how well a particular screening strategy is likely to perform in the long run based on short term real-world results.…”

“…If more accurate screening tests are introduced in future, the ongoing appropriateness of the screening interval can be judged by this model. Both simulation (Arrospide et al, 2015;Brailsford et al, 2012;Tejada et al, 2014Tejada et al, , 2015 and analytical Ayer, 2015;Ayer et al, 2016;Madadi et al, 2015;O'Mahony et al, 2015;Wang & Zhang, 2017) techniques are used to model breast cancer progression and the screening process, as in earlier papers. There are some very sophisticated models combining multiple approaches, for example Tejada et al (2014; combine system dynamics with detailed discrete event simulations.…”