Extrahepatic Disease & Mortality in Steatotic Liver Patients – UK Biobank Study
Unveiling Disease Clusters adn Mortality Risks in Individuals wiht Fatty Liver disease
Table of Contents
Fatty liver disease (SLD), a prevalent metabolic disorder, is increasingly recognized for its multifaceted impact on health, extending beyond the liver to influence cardiovascular and oncological outcomes.Understanding distinct patient profiles within SLD is crucial for targeted interventions and improved patient management. This article delves into the identification of disease clusters among individuals with SLD and examines their associations with mortality from cardiovascular diseases (CVD), extrahepatic cancers, hepatocellular carcinoma (HCC), and liver-related diseases, stratified by sex.
Identifying Distinct Disease Clusters in SLD
latent Class Analysis (LCA) was employed to identify distinct patient clusters based on their disease profiles. The analysis revealed five distinct clusters, each characterized by a unique combination of comorbidities. These clusters provide a nuanced understanding of the heterogeneity within the SLD population.
Cluster Validation and Robustness
To ensure the reliability of the identified clusters,rigorous validation procedures were undertaken. LCA was applied to randomly selected subsets of the data (80% and 50% of the full sample). The results demonstrated remarkable consistency across these subsamples, with the optimal number of clusters remaining at five. The disease profiles and cluster assignments showed high concordance with the full-sample analysis, with over 96% of individuals remaining in the same clusters across different sample sizes.
A sensitivity analysis was conducted by excluding participants with a low posterior probability of cluster assignment (maximum posterior probability < 70%). This exclusion, affecting approximately 29.7% of males and 22.2% of females, did not significantly alter the observed associations between disease clusters and mortality outcomes, further underscoring the robustness of the clustering solution.
Associations Between Disease Clusters and Mortality Outcomes
The identified disease clusters exhibited significant associations with various mortality outcomes, with notable differences observed between males and females.
cardiovascular disease (CVD) Mortality
All five identified clusters were associated with an increased risk of mortality from CVD. The highest risks were observed in the stroke and heart clusters.In males, the stroke cluster was associated with a 130% increased mortality risk (Hazard Ratio [HR] 2.30; 95% Confidence Interval [CI] 2.04-2.58), while the heart cluster showed a 4.28-fold increase (HR 5.28; 95% CI 4.83-5.77). In females, the stroke/heart cluster demonstrated the most substantial increase in CVD mortality, with a 4.66-fold higher risk (HR 5.66; 95% CI 4.75-6.75).
Interestingly, the stroke cluster in males exhibited a lower overall mortality rate (26.9 per 1000 person-years) compared to the heart cluster (30.1 per 1000 person-years). This cluster was associated with lower CVD mortality but higher cancer mortality relative to the heart cluster, as detailed in Additional file 1 (Figure S3).
Extrahepatic Cancer Mortality
All five clusters were linked to an elevated risk of mortality from extrahepatic cancers. The highest mortality risks were observed in cancer-specific clusters in both sexes. Males in the cancer cluster faced a 77% increased risk (HR 1.77; 95% CI 1.62-1.92), while females in the corresponding cluster experienced a 74% increase (HR 1.74; 95% CI 1.53-1.98).
The disease clusters also demonstrated a general trend of positive, albeit often non-significant, associations with mortality from HCC and other liver-related diseases. These non-significant findings are likely attributable to the relatively small number of events observed in these specific clusters, as indicated in Table 3.
In females, specific clusters were associated with a significant increase in liver-related death.As an example,one cluster was linked to a 46% increase in liver-related death (HR 1.41; 95% CI 1.06-1.86).
Implications for Clinical Practice and Future Research
The identification of distinct disease clusters within the SLD population highlights the importance of personalized medicine approaches. Understanding these patient profiles can aid clinicians in stratifying risk, tailoring treatment strategies, and implementing targeted preventive measures for CVD and cancer. Further research is warranted to explore the underlying biological mechanisms driving these associations and to develop specific interventions for each cluster.The findings underscore the systemic impact of SLD and the