Quoc Dinh Nguyen1,2,3, Erica M Moodie3, Mark R Keezer2,4, Christina Wolfson3,5,6. 1. Division of Geriatrics, Centre hospitalier de l'Université de Montréal, Quebec, Canada. 2. Centre de recherche du Centre hospitalier de l'Université de Montréal, Quebec, Canada. 3. Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montréal, Quebec, Canada. 4. Department of Neurosciences & School of Public Health, Université de Montréal, Quebec, Canada. 5. Department of Medicine, McGill University, Montréal, Quebec, Canada. 6. Neuroepidemiology Research Unit, Research Institute of the McGill University Health Centre, Montréal, Quebec, Canada.
Abstract
BACKGROUND: Deficit accumulation frailty indices (FIs) are widely used to characterize frailty. FIs vary in number and composition of items; the impact of this variation on reliability and clinical applicability is unknown. METHOD: We simulated 12 000 studies using a set of 70 candidate deficits in 12 080 community-dwelling participants 65 years and older. For each study, we varied the number (5, 10, 15, 25, 35, 45) and composition (random selection) of items defining the FI and calculated descriptive and predictive estimates: frailty score, prevalence, frailty cutoff, mortality odds ratio, predicted probability of mortality for FI = 0.28 (prevalence threshold), and FI cutoff predicting 10% mortality over the follow-up. We summarized the estimates' medians and spreads (0.025-0.975 quantiles) by number of items and calculated intraclass correlation coefficients (ICCs). RESULTS: Medians of frailty scores were 0.11-0.12 with decreasing spreads from 0.04-0.24 to 0.10-0.14 for 5-item and 45-item FIs. The median cutoffs identifying 15% as frail was 0.19-0.20 and stable; the spreads decreased with more items. However, medians and spreads for the prevalence of frailty (median: 11%-3%), mortality odds ratio (median: 1.24-2.19), predicted probability of mortality (median: 8%-17%), and FI cutoff predicting 10% mortality (median: 0.38-0.20) varied markedly. ICC increased from 0.19 (5-item FIs) to 0.84 (45-item FIs). CONCLUSIONS: Variability in the number and composition of items of individual FIs strongly influences their reliability. Estimates using FIs may not be sufficiently stable for generalizing results or direct application. We propose avenues to improve the development, reporting, and interpretation of FIs.
BACKGROUND: Deficit accumulation frailty indices (FIs) are widely used to characterize frailty. FIs vary in number and composition of items; the impact of this variation on reliability and clinical applicability is unknown. METHOD: We simulated 12 000 studies using a set of 70 candidate deficits in 12 080 community-dwelling participants 65 years and older. For each study, we varied the number (5, 10, 15, 25, 35, 45) and composition (random selection) of items defining the FI and calculated descriptive and predictive estimates: frailty score, prevalence, frailty cutoff, mortality odds ratio, predicted probability of mortality for FI = 0.28 (prevalence threshold), and FI cutoff predicting 10% mortality over the follow-up. We summarized the estimates' medians and spreads (0.025-0.975 quantiles) by number of items and calculated intraclass correlation coefficients (ICCs). RESULTS: Medians of frailty scores were 0.11-0.12 with decreasing spreads from 0.04-0.24 to 0.10-0.14 for 5-item and 45-item FIs. The median cutoffs identifying 15% as frail was 0.19-0.20 and stable; the spreads decreased with more items. However, medians and spreads for the prevalence of frailty (median: 11%-3%), mortality odds ratio (median: 1.24-2.19), predicted probability of mortality (median: 8%-17%), and FI cutoff predicting 10% mortality (median: 0.38-0.20) varied markedly. ICC increased from 0.19 (5-item FIs) to 0.84 (45-item FIs). CONCLUSIONS: Variability in the number and composition of items of individual FIs strongly influences their reliability. Estimates using FIs may not be sufficiently stable for generalizing results or direct application. We propose avenues to improve the development, reporting, and interpretation of FIs.
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