Research Square · Jul 28, 2026
The Risk Mechanism Theory Index (RMTI) as a Triage and Evidence-Grading Layer for Hepatocellular-Carcinoma Surveillance A transparent, computable model for the diagnosis-to-detection-to-management cascade, with an open calculator and a real-data demonstration
By Marolla C
Hepatocellular carcinoma (HCC) surveillance is applied uniformly to at-risk patients despite up to tenfold variation in annual incidence across cirrhosis etiologies, and fewer than 20% of eligible patients receive guideline-concordant surveillance. We adapted the Risk Mechanism Theory Index (RMTI), a governance framework from disaster-risk science, to convert HCC likelihood, exposure, liver-reserve vulnerability and surveillance resilience into a single bounded risk score, one of five urgency tiers, and an expected-loss index spanning the diagnosis–detection–management cascade. Anchoring each domain to published, externally validated incidence data and risk scores, to albumin–bilirubin grades, and to a real cohort of 29 HCC and 25 cirrhosis patients, RMTI reproduced established risk gradients (annual incidence ~ 1.0–13% across cohorts) and separated patients into distinct urgency tiers; modeling improved surveillance adequacy reduced residual risk by 30–44%. RMTI is offered as a transparent decision-support layer downstream of validated risk scores such as aMAP and THRI, not a replacement predictor — prospective validation of its discrimination and clinical benefit remains the necessary next step.