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Novel Algorithm, FAST-3, Shows Promise as Noninvasive Classifier for Advanced Fibrosis in MASLD


The predictive algorithm uses FibroScan-captured CAP and LSM data plus 5 clinical variables to identify advanced fibrosis in persons with MASLD.

FAST-3 algorithm effective noninvasive classifier for risk of MASH fibrosis Image credit liver ©Tina Bits/stock.adobe.com
©Tina Bits/stock.adobe.com

A novel algorithm to identify patients with advanced fibrosis in metabolic dysfunction-associated steatohepatitis (MASH) demonstrated good calibration, discrimination, and performance, showing promise as an alternative to invasive assessment via hepatic biopsy.

The findings were presented at The Liver Meeting (TLM) 2023, November 10-14, in Boston, MA. TLM is the annual scientific meeting of the American Association for the Study of Liver Disease.

Diagnosis and scoring of MASH currently rely on metabolic dysfunction-associated steatotic liver disease (MASLD) activity score (NAS) and a score for fibrosis, both obtained from histologic assessment of hepatic tissue biopsy.

The study authors aimed to develop a noninvasive classifier that would yield a quantitative estimation of available laboratory measures and transient elastography (TE) parameters as a screening and diagnostic test for advanced MASH (NAS >4 and fibrosis stage >3 [F3]) in adults with MASLD.

Transient elastography parameters: controlled attenuation parameter (CAP) and liver stiffness score (LSM)

The retrospective cohort study included 258 adults with MASLD who had been evaluated with TE (FibroScan®) as well as liver biopsy.

The team developed and internally validated a predictive logistic regression-based algorithm using FibroScan-captured CAP and LSM data for all participants.

After evaluating fractional polynomial forms of the predictors, researchers built the final model with L1 penalization (LASSO) using 10-fold cross-validation to obtain the optimum penalty factor. They examined the model for calibration (calibration plot), discrimination (area under ROC curve [AUROC]), and performance (Brier score, sensitivity, specificity, positive predictive value [PPV], and negative predictive value [NPV]), and established optimal cut points for “rule-in” and “rule-out” criteria.


Named FAST-3, the predictive algorithm incorporated 5 clinical variables (sex, body mass index, aspartate aminotransferase, bilirubin, platelet count), CAP, and LSM. The quantitative classifier demonstrated good calibration (calibration plot), discrimination (AUROC: 0.77 [0.71 – 0.83]), and performance (Brier score 0.13 [0.11 – 0.16]), according to the study abstract. After evaluation of optimal rule-in/rule-out cut point criteria, the investigators reported excellent PPV and NPV (PPV: 45% and NPV: 95%).

“The potential utility for a non-invasive classifier (FAST-3) as a replacement for invasive liver biopsies to identify patients with advanced fibrosis in MASH (NAS4/F3) is enormous,” investigators concluded in the study abstract. They call for validation of their results in a future multicenter prospective cohort study, “especially with high representation from Hispanic and other at-risk minority groups.”

Source: Shah P, Leff P, Nadeem R, Kundu R, Alkhouri N. Development of a non-invasive classifier (FAST-3)to predict advanced fibrosis in MASH in lieu of liver biopsies in US adults with MASLD. Abstract presented at: The Liver Meeting 2023; November 10-14, 2023; Boston, MA. https://www.aasld.org/the-liver-meeting/development-non-invasive-classifier-fast-3-predict-advanced-fibrosis-mash-lieu

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