Informative frailty indices from binarized biomarkers.

Area of Science:

• Biogerontology
• Biomarker Discovery
• Health Outcomes Research

Background:

• Frailty indices (FIs) using continuous biomarker data predict adverse health outcomes.
• Standardizing FI creation from biomarker data is challenging due to binarization difficulties.

Purpose of the Study:

• To develop and validate a "quantile" methodology for constructing FIs from continuous biomarker data.
• To enable FI creation without requiring pre-existing medical knowledge or risk thresholds for biomarkers.

Main Methods:

• A novel "quantile" methodology was applied to biomarker data for FI construction.
• The approach was tested on the National Health and Nutrition Examination Survey (NHANES) and Canadian Study of Health and Aging (CSHA) datasets.

Main Results:

• The quantile FI approach performed comparably to, or better than, established methods.
• The proposed method demonstrated robustness against cohort effects within studies.

Conclusions:

• The quantile methodology offers a standardized and effective way to construct FIs from biomarker data.
• This approach enhances the understanding of FI robustness and challenges in cross-study comparisons.