Tailored Prediction Model of Survival after Liver Transplantation for Hepatocellular Carcinoma.
hepatocellular carcinoma
liver transplantation
recurrence
survival
Journal
Journal of clinical medicine
ISSN: 2077-0383
Titre abrégé: J Clin Med
Pays: Switzerland
ID NLM: 101606588
Informations de publication
Date de publication:
28 Jun 2021
28 Jun 2021
Historique:
received:
26
04
2021
revised:
06
06
2021
accepted:
23
06
2021
entrez:
2
7
2021
pubmed:
3
7
2021
medline:
3
7
2021
Statut:
epublish
Résumé
This study aimed to create a tailored prediction model of hepatocellular carcinoma (HCC)-specific survival after transplantation based on pre-transplant parameters. Data collected from June 2006 to July 2018 were used as a derivation dataset and analyzed to create an HCC-specific survival prediction model by combining significant risk factors. Separate data were collected from January 2014 to June 2018 for validation. The prediction model was validated internally and externally. The data were divided into three groups based on risk scores derived from the hazard ratio. A combination of patient demographic, laboratory, radiological data, and tumor-specific characteristics that showed a good prediction of HCC-specific death at a specific time (t) were chosen. Internal and external validations with Uno's C-index were 0.79 and 0.75 (95% confidence interval (CI) 0.65-0.86), respectively. The predicted survival after liver transplantation for HCC (SALT) at a time "t" was calculated using the formula: [1 - (HCC-specific death(t'))] × 100. The 5-year HCC-specific death and recurrence rates in the low-risk group were 2% and 5%; the intermediate-risk group was 12% and 14%, and in the high-risk group were 71% and 82%. Our HCC-specific survival predictor named "SALT calculator" could provide accurate information about expected survival tailored for patients undergoing transplantation for HCC.
Identifiants
pubmed: 34203396
pii: jcm10132869
doi: 10.3390/jcm10132869
pmc: PMC8268829
pii:
doi:
Types de publication
Journal Article
Langues
eng
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