Cost-effectiveness Analysis of Colorectal Cancer Screening Strategies Using Active Learning and Monte Carlo Simulation.

ABSTRACT:

Introduction

Detection of colorectal cancer (CRC) in the early stages through available screening tests increases the patient's survival chances. Multimodal screening policies can benefit patients by providing more diverse screening options and balancing the risks and benefits of screening tests. We investigate the cost-effectiveness of a wide variety of multimodal CRC screening policies.

Methods

We developed a Monte Carlo simulation framework to model CRC dynamics. We proposed an innovative calibration process using machine learning models to estimate age- and size-specific adenomatous polyps' progression and regression rates. The proposed approach significantly expedites the model parameter space search.

Results

Two multimodal proposed policies (i.e., 1] colonoscopy

SUBMITTER: Fouladi A 

PROVIDER: S-EPMC11325561 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature