Title: Development of a Frailty Index using Standard Laboratory Tests and its Utility in Predicting Adverse Health Outcomes
Funder: Dunhill Medical Trust

Abstract: Background and aims: Frailty is linked with an increased risk of a range of adverse health outcomes including mortality, falls, fractures and institutionalisation [1]. To date, clinically detectable deficits have formed the basis for our understanding of, and for classification of frailty, however, such deficits are preceded by subclinical abnormalities, reflecting underlying damage at organ, tissue, cellular and molecular levels. Some of these sub-clinical abnormalities may be captured by laboratory measurements commonly encountered in clinical practice, and detectable in older adults before clinical health deficits are apparent. Recent data suggest that combinations of these laboratory measurements (or biomarkers) may predict adverse health outcomes [2-6]. The aims of this project are to develop a frailty index (FI) consisting primarily of standard laboratory tests (lab-FI) and to examine the predictive ability of the lab-FI in relation to mortality, hospital admissions, falls, and fractures. We will also determine whether a combination of the lab-FI and existing clinically based frailty tools may improve the prediction of falls, and fractures. Methods: UK-Biobank is a population-based cohort of over 0.5 million people aged 40-69 years. At baseline, subjects completed a detailed questionnaire and had a range of physical and cognitive assessments. A blood sample was taken and a range of 30 serum biomarkers were assessed using standard methods. The UK-Biobank cohort has been linked with the Office of National Statistics and Hospital Episode Statistics allowing assessment of health outcomes including deaths, hospital admissions and fractures. A subsample of UK-Biobank subjects have also had a repeat of the baseline assessment. A lab-FI will be developed based on previous methodology for creating a frailty index [7]. The lab-FI will comprise a range of the available biomarkers within UK-Biobank and some simple physiological measures. Participants will be identified as having a deficit in a given biomarker if it is outside of the normal reference range. The lab-FI score will be calculated as the sum of deficits, divided by the total number of biomarkers considered. Logistic and Cox regression models will be used to determine the association between the lab-FI and adverse health outcomes, including mortality, hospital admissions, falls, and fractures. Area under the receiver operating characteristic curve (ROC) will also be used to compare the ability of the lab-FI, a clinically based frailty index (FI-clin) previously developed in UK-Biobank [8], and a combined lab-FI and FI-clin, to predict adverse health outcomes including falls and fractures.

Lay abstract: Frailty is a recognised feature of ageing and is linked with poor health including an increased risk of falls, fractures and admission to nursing homes. A number of researchers have developed methods which can be used to measure frailty. These methods are typically based on the number of symptoms or medical conditions that a person may have experienced ; with the more symptoms or conditions that a person has the greater will be their degree of frailty. In our project we will use a different approach to measuring frailty. We plan to look at the results of a range of common blood tests and in particular, within an individual person, how many of these common tests are abnormal. We think that those with more abnormal tests will be frailer. We think that looking at abnormal blood tests rather than symptoms or underlying medical conditions will help identify people who are becoming frail at an earlier stage than existing methods. This is because changes start to happen in the blood before health conditions and diseases develop. Also the new method may complement existing methods and a combination of the two methods may improve our ability to predict future episodes of poor health. To develop the new frailty measure we will use information which has already been collected in a study of over half a million men and women in the UK. In the study, which is known as ‘UK Biobank’, participants completed a detailed questionnaire about their health and had a physical examination performed. A blood test was also taken and from this a range of over 30 biochemical tests were assessed. Using data from the study and in particular the results of the blood tests we will develop a new frailty measure (or ‘frailty tool’) and look at how it compares with current frailty measures. We will compare it with existing frailty measures and in particular whether it is able to predict people who have subsequent poor health. We will look also at how good the new frailty tool is both on its own and in combination with existing frailty measures in identifying people who subsequently develop falls and fractures.

Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: INJURIES AND ACCIDENTS;GENERIC HEALTH RELEVANCE