Cost-effectiveness analysis of artificial intelligence (AI) for response prediction of neoadjuvant radio(chemo)therapy in locally advanced rectal cancer (LARC) in the Netherlands.

ABSTRACT:

Background

Given the potential of artificial intelligence (AI) and the increasing importance of understanding AI's economic impact, this study aims to provide insights into the potential cost-effectiveness of an AI tool in the response prediction to neoadjuvant chemoradiotherapy (nCRT) of Stage II-III LARC patients in comparison to usual care (UC).

Methods

This study included a state-transition Markov model from a Dutch societal perspective. Quality-adjusted life years (QALY) and costs were simulated over a 10-year horizon. Sensitivity analyses and a threshold analysis were performed. Results were presented as incremental cost-effectiveness ratios.

Results

With incremental cost savings of -€2,530,000 per QALY gained per 1000 patients, the AI is dominant in the base-ca

SUBMITTER: Maas L 

PROVIDER: S-EPMC12829733 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature