Association of longitudinal repeated measurements of frailty index with mortality: Cohort study among community-dwelling older adults

Li, Xiangwei; Schöttker, Ben; Holleczek, Bernd; Brugger, Hermann

doi:10.1016/j.eclinm.2022.101630

Cited by 11 publications

(5 citation statements)

References 35 publications

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“…Our result that the continuous FI also predicts cancer deaths, albeit less so than CVD or mortality from other causes, differ from the results of two Swedish cohort studies [ 15 , 16 ] which did not find an association, but are in line with more recent work based on other cohort studies from China [ 17 ], Germany [ 18 ], and Canada [ 19 ] as well as with studies which provide evidence that frailty predicts mortality among cancer patients [ 33 ] and cancer survivors [ 34 ]. The nature of the association between frailty and cancer again remains ambiguous: both are strongly age-related and share a number of risk factors (e.g.…”

Section: Discussionsupporting

confidence: 62%

“…Third and finally, frailty was assessed only at baseline, although the frailty level of the survey participants likely increased during the 8 years of follow-up. Previous studies suggest that FI increases are relevant for mortality prediction [ 10 – 12 ] and that using only single-time-point assessments results in an ever-decreasing predictive capacity of the FI [ 18 ]. In other words, risk stratification based on the FI would be more accurate and potentially useful if repeated assessments were available, for example, if frailty screening were conducted regularly during annual medical check-ups.…”

Section: Discussionmentioning

confidence: 99%

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Frailty predicts all-cause and cause-specific mortality among older adults in Austria: 8-year mortality follow-up of the Austrian Health Interview Survey (ATHIS 2014)

Stolz,

Schultz,

Schüssler

et al. 2024

BMC Geriatr

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Background The frailty index (FI) is an established predictor of all-cause mortality among older adults, but less is known with regard to cause-specific mortality, and whether the predictive power of the FI varies between men and women and by socio-economic position. Methods We assessed all-cause and cause-specific mortality during 8 years of follow-up (median = 7 years) among the population-representative sample of older adults (65 + , n = 2,561) from the European Health Interview Survey in Austria (ATHIS 2014). A FI at baseline was constructed from 41 health deficits. Official cause of death information from Statistics Austria was linked with the survey data by the Austrian Micro Data Center (AMDC). Next to all-cause mortality, we differentiated between mortality from cardiovascular diseases (CVD), cancer, and other causes. Cox proportional hazard models adjusted for socio-demographic variables and causes of death as competing risks were used to assess mortality prediction. Results Among the participants, 43.5% were robust (FI < 0.10), 37.7% pre-frail (FI = 0.10–0.21), and 18.7% were frail (FI > 0.21). 405 (15.8%) participants died during follow-up. Among the deceased, 148 (36.5%) died from CVD, 127 (31.4%) died from cancer, and 130 (32.1%) died from other causes of death. The FI predicted all-cause (hazard ratio, HR = 1.33 per 0.1 FI and HR = 2.4 for frail compared to robust older adults) and cause-specific mortality risk (HRCVD = 1.25/2.46, HRcancer = 1.19/1.47, HRother = 1.49/3.59). Area under the curve (AUC) values were acceptable for CVD mortality (0.78) and other causes of death (0.74), and poor for cancer mortality (0.64). Conclusions The FI predicts all-cause and cause-specific mortality (CVD, other causes) well, which points to its relevance as a potential screening tool for risk stratification among community-dwelling older adults.

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Section: Discussionsupporting

confidence: 62%

Section: Discussionmentioning

confidence: 99%

Frailty predicts all-cause and cause-specific mortality among older adults in Austria: 8-year mortality follow-up of the Austrian Health Interview Survey (ATHIS 2014)

Stolz,

Schultz,

Schüssler

et al. 2024

BMC Geriatr

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“…Cancer patients are at higher risk of frailty status, which will increase with age [8,9]. In almost every study, the associations between frailty and poor outcomes are consistent regardless of measures, with frail individuals at higher risk of chronic disease and death [22][23][24].…”

Section: Discussionmentioning

confidence: 99%

Association between frailty and the risk of all-cause and cause-specific mortality among cancer patients

Zhai

Yin

Shen

et al. 2023

Preprint

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Background Cancer patients are vulnerable to frailty. While few studies have focused on its association with the mortality risk among cancer patients, the current study aims to reveal this association. Methods In this cohort study, 4723 cancer patients were enrolled from the National Health and Nutrition Examination Surveys (NHANES, 1999–2018). Frailty status was quantified using the 53-item frailty index. Death outcomes were linked to National Death Index Mortality data (as of December 31, 2019). Cox proportional hazard models were used to estimate HR (95% CI). Results The median (IQR) of the frailty score was 0.190 (0.132, 0.277). During the median follow-up of 6.7 years, 1775 all-cause deaths (including 581 cancer deaths and 385 cardiac deaths) were documented. Compared to the lowest tertile of frailty score, the adjusted HRs (95% CIs) for the highest tertile were 2.698 (2.224, 3.272) in all-cause mortality (P trend < 0.001), 2.145 (1.547, 2.973) in cancer mortality (P trend < 0.001), and 3.735 (2.231, 6.251) in cardiac mortality (P trend < 0.001). Moreover, a positive dose-response association between frailty score and mortality risk was determined. Per-unit increment of frailty score (natural logarithm transformed) was found to increase all-cause mortality by 159% (P < 0.001), cancer mortality by 103% (P < 0.001), and cardiac mortality by 256% (P < 0.001). The consistent result was shown when stratifying by age, gender, race, body mass index, and type of cancer. Conclusion This study suggested that the frailty index was positively associated with all-cause mortality and cause-specific mortality (including cancer and cardiac) among cancer patients.

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“…However, converging metrics suggest there is an underlying relationship that ties those concepts together over time. Whether periodical measuring of functional capacity by itself is enough to identify potentially frail individuals is subject to future research [ 41 ].…”

Section: Discussionmentioning

confidence: 99%

Correlation of frailty assessment metrics in one-year follow-up of aged care residents: a sub-study of a randomised controlled trial

et al. 2023

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Introduction Frailty is increasingly recognised as a dynamic syndrome, with multiple causes, dimensions and consequences. There is little understanding of how those frailty assessment metrics interact over time. The aim of this study was to describe the longitudinal correlation between five frailty metrics, namely multimorbidity, muscular strength, mood alterations, cognitive capacity, and functional capacity in a cohort study of aged care (nursing home) residents. Methods 248 aged care residents with Frailty Index at baseline of < 0.4 and no dementia were followed for 12 months. A multimorbidity score and an activity of daily living limitation score were created using individual items of the Frailty Index. Muscular strength was measured by grip strength. Cognitive capacity was measured using the Montreal Cognitive Assessment (MoCA) test. Mood alterations were measured using the anxiety/depression screening question from EQ-5D. We analysed the inter-individual correlation at baseline, association between baseline and future change, and within-individual correlation at baseline, 6 and 12 months. Results Population analysis shows that metrics were not associated at baseline. All of the studied metrics at baseline were associated with change in 12 months, with the exception of anxiety/depression scores. Pairwise within-individual correlation was strong between MoCA and grip strength (0.13, p = 0.02) and activity of daily living (− 0.48, p < 0.001), and between activities of daily living and multimorbidity index (0.28, p < 0.001). No within-individual correlation was found between anxiety depression score and other metrics. Conclusion The results suggest an interdependence between comorbidities, physical capacity, cognition and activities of daily living in aged care residents. Comprehensive measurement of frailty-related metrics may provide improved understanding of frailty progression at later life stages.

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Association of longitudinal repeated measurements of frailty index with mortality: Cohort study among community-dwelling older adults

Cited by 11 publications

References 35 publications

Frailty predicts all-cause and cause-specific mortality among older adults in Austria: 8-year mortality follow-up of the Austrian Health Interview Survey (ATHIS 2014)

Frailty predicts all-cause and cause-specific mortality among older adults in Austria: 8-year mortality follow-up of the Austrian Health Interview Survey (ATHIS 2014)

Association between frailty and the risk of all-cause and cause-specific mortality among cancer patients

Correlation of frailty assessment metrics in one-year follow-up of aged care residents: a sub-study of a randomised controlled trial

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