Machine learning risk calculator predicts HCC after liver transplant
October 20, 2021|Federal Practitioner
Key clinical point: The CoxNet machine learning model was validated as a predictor of recurrence of HCC in patients who underwent liver transplant.
Major finding: The concordance score of the CoxNet-based recurrence prediction model was 0.75, which significantly outperformed the alpha-fetoprotein score (0.64; P = 0.04) and MORAL score (0.64; P = 0.03).
Study details: The data come from 739 adults with hepatocellular carcinoma who underwent liver transplants between 2000 and 2016.
,Disclosures: The study received no outside funding. The researchers had no financial conflicts to disclose.
Source: Ivanics T et al. Liver Transpl. 2021 Oct 9. doi: 10.1002/lt.26332.