Hepatocellular Carcinoma in Metabolic Dysfunction-Associated Steatotic Liver Disease

Abstract

Importance: In the US, hepatocellular carcinoma (HCC) has been the most rapidly increasing cancer since 1980, and metabolic dysfunction-associated steatotic liver disease (MASLD) is expected to soon become the leading cause of HCC.

Objective: To develop a prediction model for HCC incidence in a cohort of patients with MASLD.

Design, setting, and participants: This prognostic study was conducted among patients aged at least 18 years with MASLD, identified using diagnosis of MASLD using International Classification of Diseases, Ninth Revision (ICD-9) or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) diagnosis codes; natural language processing of radiology imaging report text, which identified patients who had imaging evidence of MASLD but had not been formally diagnosed; or the Dallas Steatosis Index, a risk equation that identifies individuals likely to have MASLD with good precision. Patients were enrolled from Kaiser Permanente Northern California, an integrated health delivery system with more than 4.6 million members, with study entry between January 2009 and December 2018, and follow-up until HCC development, death, or study termination on September 30, 2021. Statistical analysis was performed during February 2023 and January 2024.

Exposure: Data were extracted from the electronic health record and included 18 routinely measured factors associated with MASLD.

Main outcome and measures: The cohort was split (70:30) into derivation and internal validation sets; extreme gradient boosting was used to model HCC incidence. HCC risk was divided into 3 categories, with the cumulative estimated probability of HCC 0.05% or less classified as low risk; 0.05% to 0.09%, medium risk; and 0.1% or greater, high risk.

Results: A total of 1 811 461 patients (median age [IQR] at baseline, 52 [41-63] years; 982 300 [54.2%] female) participated in the study. During a median (range) follow-up of 9.3 (5.8-12.4) years, 946 patients developed HCC, for an incidence rate of 0.065 per 1000 person-years. The model achieved an area under the curve of 0.899 (95% CI, 0.882-0.916) in the validation set. At the medium-risk threshold, the model had a sensitivity of 87.5%, specificity of 81.4%, and a number needed to screen of 406. At the high-risk threshold, the model had a sensitivity of 78.4%, a specificity of 90.1%, and a number needed to screen of 241.

Conclusions and relevance: This prognostic study of more than 1.8 million patients with MASLD used electronic health record data to develop a prediction model to discriminate between individuals with and without incident HCC with good precision. This model could serve as a starting point to identify patients with MASLD who may need intervention and/or HCC surveillance.

Figure 1.. Calibration Plot Showing Mean Predicted vs Observed Hepatocellular Carcinoma (HCC) Risk in the Validation Set (n = 543 577)

Figure 2.. Relative Importance of Each Variable in the Extreme Gradient Boosted Model to Predict Hepatocellular Carcinoma Risk

The variable importance measure is scaled to have a maximum value of 100%. ALT indicates alanine transaminase; AST, aspartate transaminase; BMI, body mass index; INR, international normalized ratio.

Figure 3.. Area Under the Receiver Operating Characteristic Curve in the Derivation (n = 1 267 884) and Validation (n = 543 577) Samples