Optimizing Initial Screening for Colorectal Cancer Detection with Adherence Behavior



    Department of Systems Engineering and Engineering Management

                       The Chinese University of Hong Kong


Date: Friday, January 6, 4:30 pm – 6:00 pm

Venue: ERB 513, The Chinese University of Hong Kong

Title:Optimizing Initial Screening for Colorectal Cancer Detection with Adherence Behavior

Speaker: Prof. Yini Gao, Singapore Management University



Two-stage screening programs are widely adopted for early colorectal cancer (CRC) detection. Individuals receiving positive outcomes in the first-stage (initial) test are recommended to undergo a second-stage test (colonoscopy) for further diagnosis. We study the initial test design—i.e., selecting cutoffs to report test outcomes—to balance the trade-off between screening effectiveness (i.e., cancer detection) and efficiency (i.e., colonoscopy costs), considering that not all individuals adhere to the guidelines to follow up with a colonoscopy after receiving positive outcomes. We integrate the Bayesian persuasion framework with information avoidance to model the problem. We show that under certain conditions, using a single cutoff in the initial test is optimal for follow-up maximization, and a continuous test (i.e., showing exact readings of the biomarker) is optimal for effectiveness maximization. We apply the framework to Singapore's CRC screening design and calibrate the model using various data sources, including a nationwide survey in Singapore. Our results suggest that compared with the current practice, increasing the cutoff to the level that maximizes expected follow-ups by cancer patients can detect 969 more CRC incidences and prevent 37,820 colonoscopies. The current practice of using lower cutoffs to achieve high sensitivity can backfire and lead to excessive unnecessary colonoscopies and low adherence. Leveraging the interpretable clustering technique, we find that using a lower cutoff for males older than 60 and females older than 70 (high-risk and high-adherence groups) and a higher cutoff for the remaining screening population (low-risk and low-adherence groups) can further improve screening effectiveness and efficiency.


Sarah Yini Gao is the Assistant Professor of Operations Management at Lee Kong Chian School of Business, Singapore Management University. Her current research interests lie in applying optimization theory and data analytics in various domains, including supply chain risk management, healthcare and humanitarian operations, and topics on innovative business models. Her research has been published in leading journals, including Management Science, Operations Research, and Marketing Science. She graduated with a Bachelor's double degree in Business Administration and Chemical Engineering from the National University of Singapore in 2012. She received her Ph.D. in Management from the Department of Decision Sciences (renamed to the Department of Analytics & Operations) at the National University of Singapore in 2017.

Everyone is welcome to attend the talk!

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Friday, January 6, 2023 - 16:30 to 18:00