Magnetic Resonance Elastography (MRE) -Based Prediction Model for Hepatic Decompensation in MASLD

Age:

Years

Albumin:

g/dL

MRE:

kPa

Platelet Count:

x1000/μL

AST:

U/L

3-Year Risk of Hepatic Decompensation:

5-Year Risk of Hepatic Decompensation:

Study Design

Retrospective cohort study with data from six centers from the United States, Europe and Asia:

The University of California San Diego
Mayo Clinic Rochester
Cedars Sinai
Musashino Red Cross Hospital
Yokohama City University
Ankara University School of Medicine

Follow-up time started at the time of the MRE. Participants were followed until development of hepatic decompensation, HCC, death, or the last clinical encounter. Follow-up assessment was performed by a retrospective chart review.

Patient characteristics, including demographic, laboratory, imaging and outcome data are reported as median (interquartile range [IQR]) for continuous variables and N (%) for categorical variables. For the primary outcome, the cohort was randomly split in 1:1 ratio into training and validation sets.

Inclusion and Exclusion Criteria

Inclusion

Adults age ≥ 18 years with MASLD and liver stiffness (LS) measurement by MRE who were assessed for hepatic decompensation, HCC, and death.
MASLD was defined as hepatic steatosis on imaging or a historical liver biopsy in the absence of significant alcohol consumption.

Exclusion

Previous history of hepatic decompensation or HCC before enrollment or within 3 months of enrollment, follow-up duration of < 3 months, and incomplete critical laboratory data (Figure 1).

Population Data - Medians

1254 Participants

Training Cohort (n=627)

Age: 61 Years
BMI: 29.1 kg/m²
MRE: 3.5 kPa
Average Follow-up: 3 Years

Validation Cohort

Age: 60 Years
BMI: 28.8 kg/m²
MRE: 3.4 kPa
Average Follow-up: 4 Years

68 (5.4%) met the composite primary outcome of hepatic decompensation including varices needing treatment, ascites, or hepatic encephalopathy.

Analysis & Results

In univariable analysis in the training set, age, DM, ln (MRE), square (albumin), ln (AST), and platelet count were significantly associated with hepatic decompensation
In multivariable analysis in the training set, age, ln (MRE), square (albumin), ln (AST), and platelet count met the statistical threshold for inclusion in the multivariable model (p<.10)

Multivariable Model:

S₀(t) at 3 Years	S₀(t) at 5 Years	Mean Score	Individual Score
0.9681	0.9490	0.059	=0.024(Age) + 0.949ln(MRE) - 0.122(Albumin)² + 0.734ln(AST) - 0.016(Platelets)

Final Risk Estimation Calculated as: 1 - S₀(t)^{e^{(Individual Score - Mean Score)}}

The equation derived in the validation cohort was evaluated in quartiles and stratified the risk of hepatic decompensation in the validation cohort (p<.0001) (Figure 2).

In Context With Published Literature

Fibrosis stage on liver biopsy has been adopted as a surrogate marker for future liver-related outcomes in clinical trials
Recently, studies have demonstrated the direct association of non-invasive tests (NITs) such as FIB-4 index (33, 34), liver stiffness on vibration-controlled transient elastography (35), and MRE (25, 27, 36, 37) on liver-related events.
Here, we evaluated a candidate set of variables and then formed a multivariable model for hepatic decompensation that retained excellent diagnostic accuracy in a multi-ethnic validation cohort.
Importantly, the score differentiated the risk of hepatic decompensation in patients with and without cACLD, despite the low risk (1%) for decompensation in the subset of patients without cACLD.

Strengths and Limitations

Strengths

Large sample size of > 1,200 patients
High number of incident hepatic decompensation events (n=68, 5.4%) allowed for adequate power to assess multivariable models in a training and validation cohort

Limitations

First, MRE was only assessed at a single time point in this study. This score was developed to assess prognosis at a single time point and future studies will be required to assess the dynamics of changes in this score over time and its impact on a patients risk of hepatic decompensation
Second, primarily because MRE has become available in the clinical practice more recently compared to other NITs, e.g. VCTE or other blood-based markers, our study has a relatively short median follow-up duration.
Last, since all patients in the present study belonged to retrospective cohorts at academic medical centers, a subset of clinical events may not have been captured.

Future prospective studies evaluating this MRE-based model with systematic assessment of hepatic decompensation are recommended