Development and Validation of a Noninvasive Model for the Detection of High-Risk Varices in Patients with Unresectable HCC
Recommended Citation
Parikh ND, Jones P, Salgia R, Bhan I, Grinspan LT, Jou JH, Zhou K, Jalal P, Roccaro G, Rangnekar AS, Benhammou JN, Pillai A, Mehta N, Wedd J, Yang JD, Kim AK, Duarte-Rojo A, Oloruntoba OO, Tevar A, Au JS, Blain Y, Rao S, Catalano OA, Lewis S, Mendiratta-Lala M, King K, Sachdev L, Lee EW, Bruno J, Kamel I, Tolosa C, Kao K, Badawi T, Przybyszewski EM, Quirk L, Nathani P, Haydel B, Leven E, Wong N, Albertian R, Chen A, Aloor FZ, Mohamed IB, Elkheshen A, Marvil C, Issac G, Clinton JW, Woo SM, Yum J, Rieger E, Hutchison AL, Turner DA, Alsudaney M, Hernandez P, Xu Z, Khalid A, Barrick B, Wang B, Tapper EB, Hao W, and Singal AG. Development and Validation of a Noninvasive Model for the Detection of High-Risk Varices in Patients with Unresectable HCC. Clin Gastroenterol Hepatol 2024.
Document Type
Article
Publication Date
7-30-2024
Publication Title
Clinical gastroenterology and hepatology
Abstract
BACKGROUND & AIMS: Noninvasive variceal risk stratification systems have not been validated in patients with hepatocellular carcinoma (HCC), which presents logistical barriers for patients in the setting of systemic HCC therapy. We aimed to develop and validate a noninvasive algorithm for the prediction of varices in patients with unresectable HCC.
METHODS: We performed a retrospective cohort study in 21 centers in the United States including adult patients with unresectable HCC and Child-Pugh A5-B7 cirrhosis diagnosed between 2007 and 2019. We included patients who completed an esophagogastroduodonoscopy (EGD) within 12 months of index imaging but before HCC treatment. We divided the cohort into a 70:30 training set and validation set, with the goal of maximizing negative predictive value (NPV) to avoid EGD in low-risk patients.
RESULTS: We included 707 patients (median age, 64.6 years; 80.6% male; 74.0% White). Median time from HCC diagnosis to EGD was 47 (interquartile range, 114) days, with 25.0% of patients having high-risk varices. A model using clinical variables alone achieved an NPV of 86.3% in the validation cohort, whereas a model integrating clinical and imaging variables had an NPV 97.4% in validation. The clinical and imaging model would avoid EGDs in more than half of low-risk patients while misclassifying 7.7% of high-risk patients.
CONCLUSIONS: A model incorporating clinical and imaging data can accurately predict the absence of high-risk varices in patients with HCC and avoid EGD in many low-risk patients before the initiation of systemic therapy, thus expediting their care and avoiding treatment delays.
PubMed ID
39089513
ePublication
ePub ahead of print
