A single blood test may be able to detect your risk of dying within five to 10 years.
That's according to new research published this week in the journal Nature Communications, for which scientists in the Netherlands examined blood sample data on 44,168 Europeans ages 18 to 109 from 12 cohorts. More than 5,500 participants died during follow-up studies.
» RELATED: Too much sleep linked to early death, disease risk
When looking through the data, lead researcher Eline Slagboom and her team identified 14 biomarkers in the blood independently associated with “all-cause mortality.”
This set of biomarkers, which are “involved in various processes, such as lipoprotein and fatty acid metabolism, glycolysis, fluid balance, and inflammation,” ultimately help determine one’s score (or risk) of dying within five to 10 years.
“Such a score,” study authors wrote, “could potentially be used in clinical practice to guide treatment strategies, for example when deciding whether an elderly person is too fragile for an invasive operation.”
» RELATED: Study: Sugary drinks linked to higher risk of early death, especially for women
But how well can those 14 biomarkers actually predict risk of death?
To find out, the scientists also compared their data with a 1997 cohort in Finland. According to data on more than 7,600 Finnish individuals (1,213 of whom had died during follow-up), the 14 biomarkers initially examined predicted patient deaths within five to 10 years with approximately 83% accuracy, according to the study. This suggests the biomarkers “clearly improve risk prediction of five and 10-year mortality as compared to conventional risk factors across all ages,” study authors wrote. Conventional risk factors, such as systolic blood pressure and total cholesterol, typically have a mortality prediction accuracy of 78% to 79%.
Still, further research is certainly needed before a blood test based on the 14 biomarkers is used in clinical settings. Because the data used in the study comes from a variety of cohorts, future efforts should focus on creating a biomarker score based on individual-level data.
About the Author
