Latin American Liver Research Educational and Awareness Network (LALREAN), Buenos Aires, Argentina.
Hospital Universitario Austral, University, School of Medicine, Buenos Aires, Argentina.
Liver Int. 2022 Aug;42(8):1879-1890. doi: 10.1111/liv.15223. Epub 2022 Apr 2.
BACKGROUND & AIM: Liver transplantation (LT) selection models for hepatocellular carcinoma (HCC) have not been proposed to predict waitlist dropout because of tumour progression. The aim of this study was to compare the alpha-foetoprotein (AFP) model and other pre-LT models in their prediction of HCC dropout.
A multicentre cohort study was conducted in 20 Latin American transplant centres, including 994 listed patients for LT with HCC from 2012 to 2018. Longitudinal tumour characteristics, and patterns of progression were recorded at time of listing, after treatments and at last follow-up over the waitlist period. Competing risk regression models were performed, and model's discrimination was compared estimating Harrell's adapted c-statistics.
HCC dropout rate was significantly higher in patients beyond (24% [95% CI 16-28]) compared to those within Milan criteria (8% [95% IC 5%-12%]; p < .0001), with a SHR of 3.01 [95% CI 2.03-4.47]), adjusted for waiting list time and bridging therapies (c-index 0.63 [95% CI 0.57; 0.69). HCC dropout rates were higher in patients with AFP scores >2 (adjusted SHR of 3.17 [CI 2.13-4.71]), c-index of 0.71 (95% CI 0.65-0.77; p = .09 vs Milan). Similar discrimination power for HCC dropout was observed between the AFP score and the Metroticket 2.0 model. In patients within Milan, an AFP score >2 points discriminated two populations with a higher risk of HCC dropout (SHR 1.68 [95% CI 1.08-2.61]).
Pre-transplant selection models similarly predicted HCC dropout. However, the AFP model can discriminate a higher risk of dropout among patients within Milan criteria.
由于肿瘤进展，尚无用于预测肝癌（HCC）肝移植（LT）候选者脱落的 HCC 筛选模型。本研究旨在比较甲胎蛋白（AFP）模型和其他 LT 前模型在预测 HCC 脱落方面的表现。
本研究为一项多中心队列研究，纳入了 2012 年至 2018 年间拉丁美洲 20 家移植中心的 994 例 HCC 患者。在等待名单期间，记录患者 LT 时、治疗后和最后一次随访时的肿瘤纵向特征和进展模式。使用竞争风险回归模型，通过估计哈雷尔调整后的 C 统计量比较模型的判别能力。
超出米兰标准的 HCC 患者（24% [95%CI 16-28]）比符合米兰标准的 HCC 患者（8% [95%CI 5%-12%]；p<0.0001）的 HCC 脱落率显著更高，校正等待时间和桥接治疗后，调整风险比（SHR）为 3.01 [95%CI 2.03-4.47]），校正后 C 指数为 0.63 [95%CI 0.57; 0.69]）。AFP 评分>2 的患者 HCC 脱落率更高（校正 SHR 为 3.17 [95%CI 2.13-4.71]），C 指数为 0.71（95%CI 0.65-0.77；p=0.09 与米兰标准相比）。AFP 评分和 Metroticket 2.0 模型在 HCC 脱落的判别能力相似。在符合米兰标准的患者中，AFP 评分>2 分可区分 HCC 脱落风险较高的两组人群（SHR 为 1.68 [95%CI 1.08-2.61]）。
LT 前筛选模型可预测 HCC 脱落。然而，AFP 模型可在符合米兰标准的患者中预测 HCC 脱落的高风险。
