Dynamic LSM changes predict liver events in advanced chronic liver diseaseTracking liver stiffness changes predicts liver-related events in chronic disease

This systematic review and meta-analysis evaluated the association between dynamic changes in liver stiffness measurement (LSM) via vibration-controlled transient elastography and the risk of liver-related events (LREs) in patients with and without compensated advanced chronic liver disease (cACLD). The analysis included 24,557 patients from observational studies, with a median follow-up of 52.8 months. The primary outcome was the occurrence of LREs, defined as hepatic decompensation, hepatocellular carcinoma, or liver-related death.

In patients with cACLD, those who showed LSM progression (increase in LSM over time) had a higher risk of LREs compared to non-progressors, with a relative risk (RR) of 1.64 (95% CI 0.56-4.81). However, this result was not statistically significant. The absolute event rates were 17.9% in progressors versus 6.5% in non-progressors. In contrast, among patients without cACLD (no-cACLD), LSM progression was associated with a significantly increased risk of LREs (RR 6.02, 95% CI 4.22-8.59), with absolute rates of 5.7% versus 0.4%.

Importantly, LSM regression (decrease in LSM) in cACLD patients was associated with a significantly reduced risk of LREs compared to non-regressors (RR 0.18, 95% CI 0.13-0.25). Absolute event rates were 2.2% in regressors versus 9% in non-regressors. This finding suggests that improvements in liver stiffness may translate into clinical benefit.

Safety and tolerability data were not reported in this meta-analysis, as the included studies focused on LSM changes and outcomes rather than adverse events. No information on funding or conflicts of interest was provided.

Compared to prior landmark studies, this meta-analysis aggregates data from multiple observational cohorts, reinforcing the prognostic value of serial LSM measurements. Previous research has established baseline LSM as a predictor of outcomes; this study extends that by showing that changes over time add predictive value.

Key methodological limitations include the observational nature of the included studies, which precludes causal inference. The association between LSM changes and LRE risk may be confounded by factors such as treatment effects or disease progression. Additionally, the result for cACLD progressors was not statistically significant, possibly due to heterogeneity or insufficient power. The authors note that prospective longitudinal studies are needed to evaluate whether LSM changes are linked to improved patient outcomes.

For clinical practice, these findings highlight the potential utility of serial LSM measurements for monitoring disease progression and regression in chronic liver disease. LSM regression may serve as a surrogate endpoint in clinical trials. However, clinicians should interpret LSM changes in the context of other clinical and laboratory parameters, and recognize that the evidence is based on observational data.

Unanswered questions include the optimal frequency of LSM monitoring, the impact of specific treatments on LSM trajectories, and whether LSM-guided management improves hard outcomes. Prospective studies are needed to confirm these associations and establish causality.