135 / 2024-04-21 20:08:20

Optimizing Initial Screening for Colorectal Cancer Detection with Adherence Behavior

Cancer screening; cutoff selection; adherence; Bayesian persuasion; information avoidance

Background: Two-stage screening programs are widely adopted for early colorectal cancer (CRC) detection, where individuals receiving positive outcomes in the first-stage (initial) test are recommended to undergo a second-stage test (colonoscopy) for further diagnosis.

Methods: We study the initial test design—the selection of cutoffs for reporting test outcomes—to balance the trade-off between screening effectiveness (i.e., CRC and polyp detection) and efficiency (i.e., colonoscopy costs), incorporating the fact that not all individuals follow up with a colonoscopy after receiving positive outcomes. We integrate the Bayesian persuasion framework with information avoidance to model this problem and apply it to Singapore’s CRC screening program design. We calibrate the model using various sources of data, including a nationwide survey with 3,920 responses in Singapore.

Results: We show that under certain conditions, using a single cutoff is optimal for maximizing follow-up, while showing exact biomarker readings is optimal for maximizing effectiveness. Our results suggest that, compared to the current practice, raising the cutoff to our recommended level of 39 μg/g can detect 20.83% more CRC and polyp incidences, reduce 26.98% colonoscopies, and lower the lifetime risk of CRC by 11.03%. This could reduce public healthcare expenditure by S$19.93 million and individual spending by S$11.96 million on average in screening costs.

Conclusions: Choosing appropriate cutoffs for the initial test can significantly improve the screening effectiveness while efficiently managing colonoscopy demands. The current practice of using lower cutoffs to achieve high sensitivity can result in an excessive number of unnecessary colonoscopies and low adherence rates.