Performance of pre‐transplant criteria in prediction of hepatocellular carcinoma progression and waitlist dropout. (2nd April 2022)

• Record Type: Journal Article
• Authors: Piñero, Federico; Thompson, Marcos; Boin, Ilka; Chagas, Aline; Quiñonez, Emilio; Bermúdez, Carla; Vilatobá, Mario; Santos, Luisa; Anders, Margarita; Hoyos Duque, Sergio; Soares Lima, Agnaldo; Menendez, Josemaría; Padilla, Martín; Poniachik, Jaime; Zapata, Rodrigo; Maraschio, Martín; Chong Menéndez, Ricardo; Muñoz, Linda; Arufe, Diego; Figueroa, Rodrigo; Perales, Simone R.; Maccali, Claudia; Vergara Sandoval, Rodrigo; McCormack, Lucas; Varón, Adriana; Marciano, Sebastián; Mattera, Juan; Carrilho, Flair; Silva, Marcelo
• Is Part Of: Liver international. Volume 42:Number 8(2022)
• Page Start: 1879
• Page End: 1890
• Publication Date: 2022-04-02
• Subjects: delisting -- liver cancer -- outcomes -- radiological progression; Liver -- Periodicals; Liver -- Diseases -- Periodicals; 616.362
• DOI: 10.1111/liv.15223
• Languages: English
• ISSNs: 1478-3223

Abstract

Abstract: 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. Methods: 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. Results: 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]). Conclusions: Pre‐transplant selection models similarly predicted HCC dropout. However, the AFP model can discriminate a higher risk of dropout among patients within Milan criteria.