Abstract
We sought to develop a predictive model to preoperatively identify patients with hepatocellular carcinoma (HCC) at risk of undergoing futile upfront liver resection (LR). Patients undergoing curative-intent LR for HCC were identified from a large multi-institutional database. Futile LR was defined by death or disease recurrence within six months postoperatively. Backward logistic regression was performed to identify factors associated with futility. Additionally, binary criteria were established for surgical candidacy, aiming to keep the likelihood of futility below 20%. Among 1633 patients with HCC, 264 (16.2%) underwent futile upfront LR. Tumor burden score (TBS) (coefficient: 0.083, 95%CI: 0.067-0.099), alpha-fetoprotein (AFP) (coefficient: 0.254, 95%CI: 0.195-0.310), and albumin-bilirubin (ALBI) grade 2/3 (coefficient: 0.566, 95%CI: 0.420-0.718) were independently associated with an increased risk of futile LR. The model demonstrated strong discrimination and calibration in both derivation and validation cohorts. Low, intermediate, and high-risk groups were determined based on the risk model, each with an escalating likelihood of futility, worse histological features, and worse survival outcomes. Six distinct conditions based on AFP-adjusted-to-TBS criteria were established, all with a futility likelihood of less than 20%. Patients fulfilling these criteria had significantly better long-term recurrence-free and overall survival. The futility risk model was made available online for wide clinical applicability: (https://altaf-pawlik-hcc-futilityofsurgery-calculator.streamlit.app/). A preoperative risk model and AFP-adjusted-to-TBS criteria were developed and validated to predict the likelihood of futile LR among patients with HCC. This pragmatic clinical tool may assist clinicians in preoperative decision-making, helping them avoid futile surgery unlikely to offer long-term benefits.
Published Version
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