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Quantifying the value of biomarkers for predicting mortality.

Noreen Goldman1, Dana A Glei2

  • 1Office of Population Research, Woodrow Wilson School of Public and International Affair, Princeton University, Princeton, NJ.

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PubMed
Summary

Biomarkers, especially inflammatory markers like interleukin-6, significantly improve prediction of all-cause mortality beyond self-reports. Three discrimination measures consistently showed this prognostic value in older Taiwanese adults.

Keywords:
Biological markersDiscriminationInflammationMortalityPrognosisTaiwan

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Area of Science:

  • Gerontology
  • Biomarker Research
  • Epidemiology

Background:

  • Assessing the prognostic value of biomarkers is crucial for predicting mortality.
  • Self-reported measures have limitations in predicting health outcomes.
  • Biomarkers may offer incremental predictive value beyond subjective assessments.

Purpose of the Study:

  • To evaluate the incremental value of biomarkers for predicting all-cause mortality.
  • To compare three discrimination measures: area under the receiver-operating characteristic curve (AUC), continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI).
  • To determine if these measures yield consistent conclusions regarding biomarker utility.

Main Methods:

  • Utilized longitudinal data from a nationally representative sample of 639 older Taiwanese adults (aged 54+ in 2000).
  • Data collected in 2000 and 2006, with mortality follow-up through 2011.
  • Estimated age-specific mortality using a Gompertz hazard model.

Main Results:

  • All three discrimination measures consistently supported the inclusion of biomarkers, particularly inflammatory markers, in mortality prediction.
  • Interleukin-6 emerged as the strongest predictor across all measures.
  • Other inflammatory markers and homocysteine also demonstrated significant prognostic value.

Conclusions:

  • Findings across discrimination measures were largely consistent, supporting biomarker utility in predicting mortality.
  • Researchers are advised to use multiple discrimination measures to confirm results due to varying levels of detail.
  • Biomarkers, especially inflammatory ones, enhance prognostic accuracy beyond self-reported data.