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Home  >  Medical Research Archives  >  Issue 149  > Comparative Review of Frailty Models and a description of the European-wide FRAILOMIC Initiative
Published in the Medical Research Archives
Jun 2018 Issue

Comparative Review of Frailty Models and a description of the European-wide FRAILOMIC Initiative

Published on Jun 15, 2018

DOI 

Abstract

 

Background

Frailty in aging populations is associated with increasing evidence of ill health, functional loss, increasing dependency and premature death. The FRAILOMIC Initiative was designed to define, predict and prevent frailty by means of identifying omic markers associated with the diagnosis, risk, and prognosis of frailty. The project hopes to build the foundations for a consensus towards a single operative, clinical definition of frailty to guide the development of ready-to-use kits measuring biomarkers to facilitate frailty risk prediction and improve diagnostic accuracy of frailty in clinical practice.

Aims

We review current models of frailty, describe the design of the FRAILOMIC study, and discuss the advent of the concept of intrinsic capacity as influencing the science of frailty and how this can be clinically interpreted.

Methods

Two main frailty models (Fried Phenotype model; Cumulative Deficit Model) are described and evaluated by detailed literature review. A description of the exploratory phase of the FRAILOMIC initiative is given which resulted in the identification of 13 omic markers related to frailty: these are currently being validated in a validation phase. We then discuss how combining the characteristics of frailty with omic-based biomarkers will enable the development of predictive, diagnostic and prognostic models.

Conclusions

Relating biomarkers associated with frailty to a continuous measure of intrinsic capacity will help in identifying and monitoring at-risk populations. The FRAILOMIC Initiative will provide key insights into the prevention, early detection, and treatment of frailty to reduce the impact of disability in our aging populations.

Author info

Alan Sinclair

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