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Agreement Between 35 Published Frailty Scores in the General Population.

ABSTRACT: In elderly populations, frailty is associated with higher mortality risk. Although many frailty scores (FS) have been proposed, no single score is considered the gold standard. We aimed to evaluate the agreement between a wide range of FS in the English Longitudinal Study of Ageing (ELSA). Through a literature search, we identified 35 FS that could be calculated in ELSA wave 2 (2004-2005). We examined agreement between each frailty score and the mean of 35 FS, using a modified Bland-Altman model and Cohen's kappa (?). Missing data were imputed. Data from 5,377 participants (ages ?60 years) were analyzed (44.7% men, 55.3% women). FS showed widely differing degrees of agreement with the mean of all scores and between each pair of scores. Frailty classification also showed a very wide range of agreement (Cohen's ? = 0.10-0.83). Agreement was highest among "accumulation of deficits"-type FS, while accuracy was highest for multidimensional FS. There is marked heterogeneity in the degree to which various FS estimate frailty and in the identification of particular individuals as frail. Different FS are based on different concepts of frailty, and most pairs cannot be assumed to be interchangeable. Research results based on different FS cannot be compared or pooled.

SUBMITTER: Aguayo GA

PROVIDER: S-EPMC5860330 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Agreement Between 35 Published Frailty Scores in the General Population.

Aguayo Gloria A GA Donneau Anne-Françoise AF Vaillant Michel T MT Schritz Anna A Franco Oscar H OH Stranges Saverio S Malisoux Laurent L Guillaume Michèle M Witte Daniel R DR

American journal of epidemiology 20170801 4

In elderly populations, frailty is associated with higher mortality risk. Although many frailty scores (FS) have been proposed, no single score is considered the gold standard. We aimed to evaluate the agreement between a wide range of FS in the English Longitudinal Study of Ageing (ELSA). Through a literature search, we identified 35 FS that could be calculated in ELSA wave 2 (2004-2005). We examined agreement between each frailty score and the mean of 35 FS, using a modified Bland-Altman model ...[more]

PMID: 28633404

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Project description:BACKGROUND:Frail elderly people experience elevated mortality. However, no consensus exists on the definition of frailty, and many frailty scores have been developed. The main aim of this study was to compare the association between 35 frailty scores and incident cardiovascular disease (CVD), incident cancer, and all-cause mortality. Also, we aimed to assess whether frailty scores added predictive value to basic and adjusted models for these outcomes. METHODS AND FINDINGS:Through a structured literature search, we identified 35 frailty scores that could be calculated at wave 2 of the English Longitudinal Study of Ageing (ELSA), an observational cohort study. We analysed data from 5,294 participants, 44.9% men, aged 60 years and over. We studied the association between each of the scores and the incidence of CVD, cancer, and all-cause mortality during a 7-year follow-up using Cox proportional hazard models at progressive levels of adjustment. We also examined the added predictive performance of each score on top of basic models using Harrell's C statistic. Using age of the participant as a timescale, in sex-adjusted models, hazard ratios (HRs) (95% confidence intervals) for all-cause mortality ranged from 2.4 (95% CI: 1.7-3.3) to 26.2 (95% CI: 15.4-44.5). In further adjusted models including smoking status and alcohol consumption, HR ranged from 2.3 (95% CI: 1.6-3.1) to 20.2 (95% CI: 11.8-34.5). In fully adjusted models including lifestyle and comorbidity, HR ranged from 0.9 (95% CI: 0.5-1.7) to 8.4 (95% CI: 4.9-14.4). HRs for CVD and cancer incidence in sex-adjusted models ranged from 1.2 (95% CI: 0.5-3.2) to 16.5 (95% CI: 7.8-35.0) and from 0.7 (95% CI: 0.4-1.2) to 2.4 (95% CI: 1.0-5.7), respectively. In sex- and age-adjusted models, all frailty scores showed significant added predictive performance for all-cause mortality, increasing the C statistic by up to 3%. None of the scores significantly improved basic prediction models for CVD or cancer. A source of bias could be the differences in mortality follow-up time compared to CVD/cancer, because the existence of informative censoring cannot be excluded. CONCLUSION:There is high variability in the strength of the association between frailty scores and 7-year all-cause mortality, incident CVD, and cancer. With regard to all-cause mortality, some scores give a modest improvement to the predictive ability. Our results show that certain scores clearly outperform others with regard to three important health outcomes in later life. Finally, we think that despite their limitations, the use of frailty scores to identify the elderly population at risk is still a useful measure, and the choice of a frailty score should balance feasibility with performance.

Dataset Information

Agreement Between 35 Published Frailty Scores in the General Population.

Publications

Agreement Between 35 Published Frailty Scores in the General Population.

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