Frailty indices based on self-report, blood-based biomarkers and examination-based data in the Canadian Longitudinal Study on Aging

Unleashing frailty from laboratory into real world: A critical step toward frailty-guided clinical care of older adults

Understanding patients' degree of frailty is crucial for tailoring clinical care for older adults based on their physiologic reserve and health needs ("frailty-guided clinical care"). Two prerequisites for frailty-guided clinical care are: (1) access to frailty information at the point of care and (2) evidence to inform decisions based on frailty information. Recent advancements include web-based frailty assessment tools and their electronic health records integration for time-efficient, standardized assessments in clinical practice. Additionally, database frailty scores from administrative claims and electronic health records data enable scalable assessments and evaluation of the effectiveness and safety of medical interventions across different frailty levels using real-world data. Given limited evidence from clinical trials, real-world database studies can complement trial results and help treatment decisions for individuals with frailty. This article, based on the Thomas and Catherine Yoshikawa Award lecture I gave at the American Geriatrics Society Annual Meeting in Long Beach, California, on May 5, 2023, outlines our group's contributions: (1) developing and integrating a frailty index calculator (Senior Health Calculator) into the electronic health records at an academic medical center; (2) developing a claims-based frailty index for Medicare claims; (3) applying this index to evaluate the effect of medical interventions for patients with and without frailty; and (4) efforts to disseminate frailty assessment tools through the launch of the eFrailty website and the forthcoming addition of the claims-based frailty index to the Centers for Medicare and Medicaid Services Chronic Conditions Data Warehouse. This article concludes with future directions for frailty-guided clinical care.

Gut microbial features and circulating metabolomic signatures of frailty in older adults

Frailty, a multidimensional indicator of suboptimal aging, reflects cumulative declines across multiple physiological systems. Although age-related changes have been reported in gut microbiota, their role in healthy aging remains unclear. In this study, we calculated frailty index (FI) from 33 health-related items to reflect the overall health status of 1,821 older adults (62-96 years, 55% female) and conducted multi-omics analysis using gut metagenomic sequencing data and plasma metabolomic data. We identified 18 microbial species and 17 metabolites shifted along with frailty severity, with stronger links observed in females. The associations of nine species, including various Clostridium species and Faecalibacterium prausnitzii, with FI were reproducible in two external populations. Plasma glycerol levels, white blood cell count and kidney function partially mediated these associations. A composite microbial score derived from FI significantly predicted 2-year mortality (adjusted hazard ratio across extreme quartiles, 2.86; 95% confidence interval, 1.38-5.93), highlighting the potential of microbiota-based strategies for risk stratification in older adults.

Relationship between frailty and executive function by age and sex in the Canadian Longitudinal Study on Aging

Frailty reflects age-related damage to multiple physiological systems. Executive dysfunction is often a presenting symptom of diseases characterized by cognitive impairment. A decline in cardiovascular health is associated with worse executive function. We tested the hypothesis that higher frailty would be associated with executive dysfunction and that cardiovascular health would mediate this relationship. Middle- and older-aged adults at baseline (n = 29,591 [51% female]) and 3-year follow-up (n = 25,488 [49% females]) from the Canadian Longitudinal Study on Aging (comprehensive cohort) were included. Frailty was determined at baseline from a 61-item index, a cumulative cardiovascular health score was calculated from 30 variables at baseline, and participants completed a word-color Stroop task as an assessment of executive function. Multiple linear regressions and mediation analyses of cardiovascular health were conducted between frailty, Stroop interference-condition reaction time, and cardiovascular health in groups stratified by both age and sex (middle-aged males [MM], middle-aged females [MF], older-aged males [OM], older-aged females [OF]). Frailty (MM, 0.15 ± 0.05; MF, 0.16 ± 0.06; OM, 0.21 ± 0.06; OF, 0.23 ± 0.06) was negatively associated with cardiovascular health (MM, 0.12 ± 0.08; MF, 0.11 ± 0.07; OM, 0.20 ± 0.10; OF, 0.18 ± 0.09; β > 0.037, p < 0.001), as well as the Stroop reaction time at 3-year follow-up (MM, 23.7 ± 7.9; MF, 23.1 ± 7.3; OM, 32.9 ± 13.1; OF, 30.9 ± 12.0; β > 2.57, p < 0.001) across all groups when adjusted for covariates. Cardiovascular health was a partial (~ 10%) mediator between frailty and reaction time, aside from MFs. In conclusion, higher frailty levels are associated with executive dysfunction, which was partially mediated by cardiovascular health. Strategies to improve frailty and better cardiovascular health may be useful for combatting the age-related decline in executive function.

Development and testing of a lymphoma clinical trial-specific frailty index: a secondary analysis of the NCIC-CTG LY.12 clinical trial

The prevalence of frailty in clinical trials of lymphoma is unknown. We conducted a secondary analysis of the phase III LY.12 trial in which patients with relapsed aggressive non-Hodgkin lymphoma were randomized to different salvage regimens before autologous stem cell transplant. The primary objective was to construct a lymphoma clinical trials-specific frailty index (LyFI) using previously described methods. The secondary objective was to describe the association of frailty withover all and event-free survival (OS, EFS). The LyFI was constructed using 619 patients, and11% (N = 70) were classified as frail. Frailty was associated with EFS (HR 1.94, 95%CI 1.53-2.46) and OS (HR 2.01, 95%CI 1.57-2.58) in univariable analysis, but was only significant as a continuous (not binary) variable in multivariable analysis controlling for prognostic score, suggesting limitations of a FI in this trial population. Future work could validate the FI using clinical assessments and/or apply it to an older trial population.

Relation between frailty and hypertension is partially mediated by physical activity among males and females in the Canadian Longitudinal Study on Aging

Frailty reflects the heterogeneity in aging and may lead to the development of hypertension and heart disease, but the frailty-cardiovascular relationship and whether physical activity modifies this relationship in males and females are unclear. We tested whether higher frailty was positively associated with hypertension and heart disease in males and females and whether habitual movement mediated this relationship. The relationship between baseline frailty with follow-up hypertension and heart disease was investigated using the Canadian Longitudinal Study on Aging at 3-year follow-up data (males: n = 13,095; females: n = 13,601). Frailty at baseline was determined via a 73-item deficit-based index, activity at follow-up was determined via the Physical Activity Scale for the Elderly, and cardiovascular function was self-reported. Higher baseline frailty level was associated with a greater likelihood of hypertension and heart disease at follow-up, with covariate-adjusted odds ratios of 1.08-1.09 (all, P < 0.001) for a 0.01 increase in frailty index score. Among males and females, sitting time and strenuous physical activity were independently associated with hypertension, with these activity behaviors being partial mediators (except male-sitting time) for the frailty-hypertension relationship (explained 5-10% of relationship). The strength of this relationship was stronger among females. Only light-moderate activity partially mediated the relationship (∼6%) between frailty and heart disease in females, but no activity measure was a mediator for males. Higher frailty levels were associated with a greater incidence of hypertension and heart disease, and strategies that target increases in physical activity and reducing sitting may partially uncouple this relationship with hypertension, particularly among females.NEW & NOTEWORTHY Longitudinally, our study demonstrates that higher baseline frailty levels are associated with an increased risk of hypertension and heart disease in a large sample of Canadian males and females. Movement partially mediated this relationship, particularly among females.

Prognostic accuracy of 70 individual frailty biomarkers in predicting mortality in the Canadian Longitudinal Study on Aging

The frailty index (FI) uses a deficit accumulation approach to derive a single, comprehensive, and replicable indicator of age-related health status. Yet, many researchers continue to seek a single "frailty biomarker" to facilitate clinical screening. We investigated the prognostic accuracy of 70 individual biomarkers in predicting mortality, comparing each with a composite FI. A total of 29,341 individuals from the comprehensive cohort of the Canadian Longitudinal Study on Aging were included (mean, 59.4 ± 9.9 years; 50.3% female). Twenty-three blood-based biomarkers and 47 test-based biomarkers (e.g., physical, cardiac, cardiology) were examined. Two composite FIs were derived: FI-Blood and FI-Examination. Mortality status was ascertained using provincial vital statistics linkages and contact with next of kin. Areas under the curve were calculated to compare prognostic accuracy across models (i.e., age, sex, biomarker, FI) in predicting mortality. Compared to an age-sex only model, the addition of individual biomarkers demonstrated improved model fit for 24/70 biomarkers (11 blood, 13 test-based). Inclusion of FI-Blood or FI-Examination improved mortality prediction when compared to any of the 70 biomarker-age-sex models. Individual addition of seven biomarkers (walking speed, chair rise, time up and go, pulse, red blood cell distribution width, C-reactive protein, white blood cells) demonstrated an improved fit when added to the age-sex-FI model. FI scores had better mortality risk prediction than any biomarker. Although seven biomarkers demonstrated improved prognostic accuracy when considered alongside an FI score, all biomarkers had worse prognostic accuracy on their own. Rather than a single biomarker test, implementation of routine FI assessment in clinical settings may provide a more accurate and reliable screening tool to identify those at increased risk of adverse outcomes.

Development and validation of a frailty index for use in the osteoarthritis initiative

BACKGROUND

The Osteoarthritis Initiative (OAI) evaluates the development and progression of osteoarthritis. Frailty captures the heterogeneity in aging. Use of this resource-intensive dataset to answer aging-related research questions could be enhanced by a frailty measure.

OBJECTIVE

To: (i) develop a deficit accumulation frailty index (FI) for the OAI; (ii) examine its relationship with age and compare between sexes, (iii) validate the FI versus all-cause mortality and (iv) compare this association with mortality with a modified frailty phenotype.

DESIGN

OAI cohort study.

SETTING

North America.

SUBJECTS

An FI was determined for 4,755/4,796 and 4,149/4,796 who had a valid FI and frailty phenotype.

METHODS

Fifty-nine-variables were screened for inclusion. Multivariate Cox regression evaluated the impact of FI or phenotype on all-cause mortality at follow-up (up to 146 months), controlling for age and sex.

RESULTS

Thirty-one items were included. FI scores (0.16 ± 0.09) were higher in older adults and among females (both, P < 0.001). By follow-up, 264 people had died (6.4%). Older age, being male, and greater FI were associated with a higher risk of all-cause mortality (all, P < 0.001). The model including FI was a better fit than the model including the phenotype (AIC: 4,167 vs. 4,178) and was a better predictor of all-cause mortality than the phenotype with an area under receiver operating characteristic curve: 0.652 vs. 0.581.

CONCLUSION

We developed an FI using the OAI and validated it in relation to all-cause mortality. The FI may be used to study aging on clinical, functional and structural aspects of osteoarthritis included in the OAI.

Comparison of three frailty measures for predicting hospitalization and mortality in the Canadian Longitudinal Study on Aging

BACKGROUND

Few studies have compared different measures of frailty for predicting adverse outcomes. It remains unknown which frailty measurement approach best predicts healthcare utilization such as hospitalization and mortality.

AIMS

This study aims to compare three approaches to measuring frailty-grip strength, frailty phenotype, and frailty index-in predicting hospitalization and mortality among middle-aged and older Canadians.

METHODS

We analyzed baseline and the first 3-year follow-up data for 30,097 participants aged 45 to 85 years from the comprehensive cohort of the Canadian Longitudinal Study on Aging (CLSA). Using separate logistic regression models adjusted for multimorbidity, age and biological sex, we predicted participants' risks for overnight hospitalization in the past 12 months and mortality, at the first 3-year follow-up, using each of the three frailty measurements at baseline. Model discrimination was assessed using Harrell's c-statistic and calibration assessed using calibration plots.

RESULTS

The predictive performance of all three measures of frailty were roughly similar when predicting overnight hospitalization and mortality risk among CLSA participants. Model discrimination measured using c-statistics ranged from 0.67 to 0.69 for hospitalization and 0.79 to 0.80 for mortality. All measures of frailty yielded strong model calibration.

DISCUSSION AND CONCLUSION

All three measures of frailty had similar predictive performance. Discrimination was modest for predicting hospitalization and superior in predicting mortality. This likely reflects the objective nature of mortality as an outcome and the challenges in reducing the complex concept of healthcare utilization to a single variable such as any overnight hospitalization.

Long-term Impact of a 10-Year Intensive Lifestyle Intervention on a Deficit Accumulation Frailty Index: Action for Health in Diabetes Trial

BACKGROUND

Multidomain lifestyle interventions may slow aging as captured by deficit accumulation frailty indices; however, it is unknown whether benefits extend beyond intervention delivery.

METHODS

We developed a deficit accumulation frailty index (FI-E) to span the 10 years that the Action for Health in Diabetes (Look AHEAD) randomized controlled clinical trial delivered interventions (a multidomain lifestyle intervention focused on caloric restriction, increased physical activity, and diet compared to a control condition) and to extend across an additional 8 years post-delivery. The study cohort included 5 145 individuals, aged 45-76 years at enrollment, who had type 2 diabetes and either obesity or overweight.

RESULTS

Overall, FI-E scores were relatively lower among lifestyle participants throughout follow-up, averaging 0.0130 [95% confidence interval: 0.0104, 0.0156] (p < .001) less across the 18 years. During Years 1-8, the mean relative difference between control and lifestyle participants' FI-E scores was 0.0139 [0.0115, 0.0163], approximately 10% of the baseline level. During Years 9-18, this average difference was 0.0107 [0.0066, 0.0148]. Benefits were comparable for individuals grouped by baseline age and body mass index and sex but were not evident for those entering the trial with a history of cardiovascular disease.

CONCLUSIONS

Multidomain lifestyle intervention may slow biological aging long term, as captured by an FI-E. Clinical Trials Registration Number: NCT00017953.

On the comparability of frailty scores under the accumulation of deficits approach

BACKGROUND

While the cumulative deficit model is arguably the most popular instrument for population-level frailty screening, several questions remain unanswered regarding the comparability of the resulting scores across subpopulations.

METHODS

Based on data from the five waves of the Mexican Health and Aging Study (MHAS) we draw upon the alignment method to test for measurement invariance of frailty scores as per the accumulation of deficits approach.

RESULTS

Our results show that adjusting for measurement non-invariance not only improves predictive validity of our frailty measures, but resulting scores are more consistent with what is theoretically expected from them in longitudinal research.

CONCLUSIONS

There are clear potential benefits of measurement invariance testing as a general analytical framework from which to tackle with issues of comparability in frailty research.

Efficient representations of binarized health deficit data: the frailty index and beyond

We investigated efficient representations of binarized health deficit data using the 2001-2002 National Health and Nutrition Examination Survey (NHANES). We compared the abilities of features to compress health deficit data and to predict adverse outcomes. We used principal component analysis (PCA) and several other dimensionality reduction techniques, together with several varieties of the frailty index (FI). We observed that the FI approximates the first - primary - component obtained by PCA and other compression techniques. Most adverse outcomes were well predicted using only the FI. While the FI is therefore a useful technique for compressing binary deficits into a single variable, additional dimensions were needed for high-fidelity compression of health deficit data. Moreover, some outcomes - including inflammation and metabolic dysfunction - showed high-dimensional behaviour. We generally found that clinical data were easier to compress than lab data. Our results help to explain the success of the FI as a simple dimensionality reduction technique for binary health data. We demonstrate how PCA extends the FI, providing additional health information, and allows us to explore system dimensionality and complexity. PCA is a promising tool for determining and exploring collective health features from collections of binarized biomarkers.

The frailty index based on laboratory test data as a tool to investigate the impact of frailty on health outcomes: a systematic review and meta-analysis

The frailty index (FI) quantifies frailty as deficit accumulation. It has been adapted to employ laboratory test data (FI-Lab). Our objective was to systematically review and meta-analyse the FI-Lab's ability to predict mortality. Secondary objectives were to review the FI-Lab's association with adverse health outcomes and whether FI-Lab scores differed between the sexes. A systematic literature search was carried out using six online databases to identify studies that measured the FI-Lab in humans. Hazard ratios (HRs) were combined in a meta-analysis to create a pooled risk estimate for mortality. Of the 1,201 papers identified, spanning January 2010 until 11 July 2022, 38 were included. FI-Lab scores per 0.01 unit increase predicted mortality overall (HR = 1.04; 95% confidence interval (CI) = 1.03-1.05) and for studies with a mean age of 81+ years (HR = 1.04; 95% CI = 1.03-1.05). The quality of evidence for these meta-analyses are moderate and high, respectively. Further, higher FI-Lab scores were associated with more frequent adverse health outcomes. Sex differences in FI-Lab scores varied, with no consistent indication of a sex effect. The FI-Lab is associated with mortality and with a variety of adverse health outcomes. No consistent sex differences in FI-Lab scores were observed, with several studies in disagreement. Notably, these conclusions were most relevant to older (65+ years old) individuals; further evidence in younger people is needed in both clinical and population representative studies.

Association between the frailty index and vascular brain damage: The Treviso Dementia (TREDEM) registry

PURPOSE

An association between frailty and vascular brain damage (VBD) has been described in older adults. However, most studies have identified frailty according to the phenotypic model. It is less clear whether frailty, operationalized as an accumulation of health deficits, is associated with the presence and severity of VBD. The present study was therefore undertaken to verify whether a 50-item frailty index (FI) is related to VBD in a large and relatively unselected cohort of attendees of a memory clinic.

MATERIALS AND METHODS

The TREDEM (Treviso Dementia) registry includes retrospective observational data of 1584 participants. A modified FI was calculated from 50 variables comprising diseases, disability, behavioral disorders, and blood biochemistry. The presence and severity of VBD, including leukoaraiosis, lacunes, larger infarctions and the hierarchical vascular rating scale (HVRS), were determined based on brain computerized tomography imaging. Multiple logistic regression models were built according to the stepwise method.

RESULTS

Mean age of the 1584 participants was 79.6 ± 7.5 years and 1033 (65.2 %) were females. The average number of health deficits was 11.6 ± 6.2, corresponding to an FI of 0.23 ± 0.12 (range: 0.00-0.56). Each 0.01-point increase in the FI was associated with an increased probability of leukoaraiosis (+2.3 %) and severe leukoaraiosis (+5 %), lacunas in the basal ganglia (+1.73 %), occipital lobes (+2.7 %), parietal lobes (+3 %), frontal lobes (+3.6 %), temporal lobes (+4.2 %), and thalamus (+4.4 %). Moreover, an increase of 0.01 points in the FI was associated with a 3.1 % increase in the probability of HVRS score (≥2).

CONCLUSION

An FI based on routine clinical and laboratory variables was associated with the presence, degree, and some localizations of VBD in a population of older adults with cognitive decline. This frailty assessment tool may therefore be used to identify individuals at risk of developing cerebrovascular disease and, consequently, to implement strategies for vascular risk factor control.