Defining safe thresholds for risk-adapted surveillance after liver transplantation for hepatocellular carcinoma

Recurrence of hepatocellular carcinoma (HCC) after liver transplantation (LT) is a major concern, but it is unclear whether existing models can safely "rule out" patients from intensive imaging strategies.

We retrospectively studied 493 LT recipients transplanted for HCC (2002-2023). Competing-risk Fine-Gray regression with bootstrap stability selection was used to derive an illustrative score and compared with established models. Rule-out performance was evaluated by 5-year cumulative incidence. Decision curve analysis (DCA) and surveillance simulations quantified trade-offs between CT scans saved and recurrences missed under reduced protocols.

Our model identified total tumor diameter, microvascular invasion, satellite nodules, and log(AFP) as stable predictors. DCA showed all models outperformed uniform surveillance only when 5-year recurrence exceeded 4%, with 7.5% as the upper acceptable threshold. Within this range, low-risk groups across models had 5-year recurrence risks of 2.5-5.7%. Reduced-intensity strategies could save 160-856 CTs per 100 patients while missing ≤1 recurrence with semiannual or annual two-year protocols. Cost-benefit analysis supported 4-7.5% as the optimal threshold. False negatives were uncommon (n = 13), with only two patients misclassified by all models.

Widely used models can identify patients suitable for reduced surveillance, though none delineated a true "no-screening" group.