Summary
This large observational study of 44,168 individuals identified a panel of 14 circulating metabolic biomarkers that independently predict all-cause mortality with greater accuracy than conventional clinical risk factors. The metabolomic profile achieved C-statistics of 0.837 (5-year) and 0.830 (10-year) mortality prediction, substantially outperforming conventional risk models. The findings suggest that metabolomics may offer a more efficient and non-invasive approach to mortality risk stratification, though the authors note that further investigation is needed before adoption as a clinical surrogate endpoint.
UK applicability
These findings are potentially applicable to UK clinical practice and public health, as metabolomics platforms are increasingly available in research and diagnostic settings. However, validation in UK-specific cohorts and integration with existing NHS risk prediction tools would be necessary before clinical implementation.
Key measures
C-statistic for 5-year mortality (0.837) and 10-year mortality (0.830) prediction; comparison with conventional risk factor models (C-statistic 0.772 and 0.790 respectively)
Outcomes reported
The study identified 14 circulating metabolic biomarkers independently associated with all-cause mortality using metabolomics profiling in 44,168 individuals (5,512 deaths during follow-up). Predictive accuracy was assessed for 5- and 10-year mortality risk using a model containing these biomarkers.
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