Publication Type
Journal Article
Version
publishedVersion
Publication Date
12-2024
Abstract
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.
Keywords
Cancer Screening, Cutoff Selection, Adherence, Bayesian Persuasion, Information Avoidance
Discipline
Operations and Supply Chain Management | Public Health
Research Areas
Operations Management
Publication
Management Science
ISSN
0025-1909
Identifier
10.1287/mnsc.2023.01319
Publisher
Institute for Operations Research and Management Sciences
Citation
GAO, Sarah Yini; HE, Yan; ZHANG, Ruijie; ZHENG, Zhichao; LAM, Shao Wei Lam; and TAN, Emile.
Optimizing initial screening for colorectal cancer detection with adherence behavior. (2024). Management Science.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/7681
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1287/mnsc.2023.01319
