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Frailty Trait Scale–Short Form: A Frailty Instrument for Clinical Practice
JAMDA xxx (2020) 1e7
JAMDA journal homepage: www.jamda.com
Original Study
Frailty Trait ScaleeShort Form: A Frailty Instrument for Clinical Practice Francisco Jose García-García MD, PhD a, b, *, Jose Antonio Carnicero PhD b, Jose Losa-Reyna PhD a, b, c, Ana Alfaro-Acha MD, PhD a, b, Carmen Castillo-Gallego MD, PhD a, b, Cristina Rosado-Artalejo MD, PhD a, b, Gonzalo Gutiérrrez-Ávila MD, PhD b, d, Leocadio Rodriguez-Mañas MD, PhD b, e a
Department of Geriatrics, Hospital Virgen del Valle, Complejo Hospitalario de Toledo, Toledo, Spain CIBER of Frailty and Healthy Aging (CIBERFES), Madrid, Spain GENUD Toledo Research Group, Universidad de Castilla La Mancha, Toledo, Spain d Epidemiologic Department, Consejería de Sanidad de Castilla la Mancha, Toledo, Spain e Geriatric Department, Hospital Universitario de Getafe, Getafe, Spain b c
a b s t r a c t Keywords: Frailty phenotype frailty assessment frailty diagnosis frailty scales risk adverse event
Objectives: To develop short versions of the Frailty Trait Scale (FTS) for use in clinical settings. Design: Prospective population-based cohort study. Setting and Participants: Data from 1634 participants from the Toledo Study for Healthy Aging. Methods: The 12-item Frailty Trait Scale (FTS) reduction was performed based on an area under the curve (AUC) analysis adjusted by age, sex, and comorbidity. Items that maximized prognostic information for adverse events were selected. Each item score was done at the same time as the reduction, identifying the score that maximized the predictive ability for adverse events. For each short version of the FTS, cutoffs that optimized the prognostic information (sensitivity and specificity) were chosen, and their predictive value was later compared with a surrogate gold standard for frailty (the Fried Phenotype). Results: Two short forms, the 5-item (FTS5) (range 0-50) and 3-item (FTS3) (range 0-30), were identified, both with AUCs for health adverse events similar to the 12-item FTS. The identified cutoffs were >25 for the FTS5 scale and >15 for the FTS3. The frailty prevalence with these cutoffs was 24% and 20% for the FTS5 and FTS3, respectively, whereas frailty according to Fried Phenotype (FP) reached 8% and prefrailty reached 41%. In general, the FTS5 showed better prognostic performance than the FP, especially with prefrail individuals, in whom the FTS5 form identified 65% of participants with an almost basal risk and 35% with a very high risk for mortality (OR: 4) and frailty (OR: 6.6-8.7), a high risk for hospitalization (OR: 1.9-2.1), and a moderate risk for disability (OR: 1.7) who could be considered frail. The FTS3 form had worse performance than the FTS5, showing 31% of false negatives between frail participants identified by FP with a high risk of adverse events. Conclusions and Implications: The FTS5 is a short scale that is easy to administer and has a similar performance to the FTS, and it can be used in clinical settings for frailty diagnosis and evolution. Ó 2019 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
The authors were supported by grants PI15/01305, CB16/10/00456 and CB16/ 10/00464 from the Instituto de Salud Carlos III (FEDER funds, Ministerio de Ciencia e Innovación, Spain), RD12/0043 from the Instituto de Salud Carlos III (Ministerio de Economía y Competitividad, Spain), PI2010/020 from FISCAM (Junta de Comunidades de Castilla La Mancha, Spain), FP7-305483-2 (“Frailomic Iniciative”) from FP7-Health-2012-Innovation (European Union). The authors declare no conflicts of interest. * Address correspondence to Francisco Jose García-García, MD, PhD, Geriatric Department, Complejo Hospitalario de Toledo, Ctra de Cobisa s/n, 45071, Toledo, Spain. E-mail address: [email protected] (F.J. García-García). https://doi.org/10.1016/j.jamda.2019.12.008 1525-8610/Ó 2019 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
Owing to its prognostic value, frailty has emerged as a priority in daily clinical practice in the care of older adults,1 influencing the management of the patient and the decision-making process.2 However, the implementation of frailty assessment in clinical scenarios is a challenge, because of several factors that are delaying its use in clinical settings1 and public health.3 One of the most relevant factors is the difficulty in diagnosing frailty. Indeed, the few studies that have assessed the usefulness of several tools to screen or diagnose frailty, in terms of their sensitivity, specificity, or predictive value, have raised disappointing results.4 This inconsistency is caused by the lack of a gold standard, because each diagnostic
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approach to frailty evaluates different aspects of a polyhedral syndrome. On the other hand, current criteria have been mostly developed and validated in epidemiologic cohorts with the main purpose of defining risks for precise adverse health outcomes such as death, disability, hospitalization, falls, etc, but not to be used in clinical settings, where the main purpose is to screen or diagnose the syndrome on individual bases and monitor the clinical evolution. In this scenario, a scale should have the following characteristics: first, a good diagnostic accuracy to properly stratify the population; second, the ability to detect small changes in the clinical progression or in the response to treatment, that is, to be sensitive to change; and third, feasibility to use in a limited clinical setting. However, frailty is not the typical syndrome with a group of symptoms that coexist and define a disease. In fact, it is a biological state that an individual reaches as a result of the decline of multiple systems, and of the interaction between physiological aging, diseases, and certain lifestyles. Actually, there are no specific biomarkers, so that individuals are classified as frail when crossing a certain, arbitrary threshold, from which the risk of adverse health events is higher. In such cases, the diagnostic accuracy is reached when the diagnostic scale includes the syndrome nuclear domains, and the sensitivity to change is reached when the impairment in each domain is captured over time. One of these scales, the Frailty Trait Scale (FTS), was recently validated.5 Its approach is based on the premise that the pathway to frailty is a continuous, unstable, and reversible process similar to a biological trait that is reached over time and that could be defined as the “trait of frailty.” The scale measures the load of frailty across the frailty trait including 7 dimensions. Since its publication, the scale has shown good ability to stratify the risk for adverse events in the general population of individuals aged 65 years5 and in diabetics,6 as well as good sensitivity to stratify cognitive performance7,8 or sedentary lifestyle.9,10 However, it is a time-consuming scale, making it difficult to be widely used in clinical settings. The aim of our study is, starting from the full FTS developed in the Toledo Study for Healthy Aging (TSHA),5 to build a short, objective, and valuable instrument that can be used to assess frailty in clinical settings in daily practice. Methods Design We used data from the TSHA obtained in the first (2006-2009) and second waves (2011-2013). This is a population-based, prospective, cohort study created to evaluate the characteristics and consequences of frailty in individuals aged 65 years living in the province of Toledo (Spain), which is described elsewhere.11 Basically, the study is carried out in different phases: first, there was an interview in the participant’s home and, second, a nurse carried out a physical battery task and obtained blood and urine samples. Participants A total of 1972 individuals participated in both phases, and 1755 participants, 985 women and 770 men, completed all of the physical performance tests and were included in the analysis. The study obtained approval from the local ethics committee, and the participants signed a written informed consent. Frailty Measures Three frailty measurements were used in the Frailty Trait ScaleeShort Form (FTSSF) validation process. Because there is no gold standard to measure frailty, we used the Fried criteria12 as a reference,
because it is a successful phenotype that has become a surrogate standard in frailty. The Frailty Index was also used13 as a frailty outcome, because it is a phenotype with a substantially different approach to the measurement of frailty compared with Fried criteria and FTS. Finally, we used the FTS as the phenotype of interest for this project. The description and process of creation of the 3 constructs of frailty are described elsewhere.5 In brief, the FTS evaluates 7 domains (energy balance and nutrition, activity, nervous system, vascular system, weakness, endurance, and slowness). These domains become operational through 12 items (Table 1). Each item score represents a biological trait and ranges from 0 (the best) to 4 or 5 (the worst). The final score is obtained by adding the scores from each of the items and dividing it by the maximum score possible. The measurement was standardized to obtain a range between 0 and 100. Those participants with a score of 50 or higher were considered frail. The FTS short forms (5- and 3-item) were constructed with the items that better optimized its predictive ability. Likewise, to keep a range for the scale that would give a high evaluative capacity, we set a range from 0 to 10 for each item (Tables 1 and 2). The Frailty Index of TSHA5 was built following the methodology proposed by Searle et al,13 by developing a scale of 40 items with scores of 0 and 1. To be considered frail, the 90th centile was used so that the prevalence of frailty in both constructs (ie, Fried criteria and Frailty index) could be balanced. At last, as a standard measurement of frailty, the Fried criteria was chosen using the methodology accepted internationally and cutoffs adopted for our population.12 Fried criteria include weakness, low energy, slowness, low physical activity, and weight loss. Each factor was given a point, so participants with a score of 0 were considered robust, 1 or 2 points were prefrail, and 3 to 5 points were frail. Outcomes Mortality We obtained the date of death from the National Death Index (Ministry of Health, Consumer Affairs, and Social Welfare), hospital registry, and phone contact during the study follow-up. Hospitalization We obtained hospitalization data from the Toledo Hospital Complex, which is the study population’s referral hospital. Incident disability We evaluated the incident disability for basic activities of daily living using the Katz index14 in 2 ways: (1) new disability, which includes those participants who have developed new disability for basic activities of daily living between the first and second waves of the study; and (2) functional decline from their basic activities of daily living baseline, expressed by a worsening in 1 or more points of the Katz index. Incident frailty Development of new frailty was measured according to the Fried criteria and the Frailty Index, using cutoffs described before. Statistical Analysis The item reduction and scoring were done in 1 phase, with an algorithm that maximizes the AUC sum of the logistic models for each outcome. The models were adjusted for age, sex, and comorbidity (Charlson index),15 and the score for the variable that is created during the process of reduction until that moment. In each step, the item was scored such that, for an item with a standardized scoring algorithm (Romberg progressive), its score was rescaled so that the score ranged from 0 to 10. For the rest, an optimization algorithm identified a basal risk level and step size obtaining 10 equally spaced points above and/
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Table 1 Domain and Item Composition in FTS Forms Domain
Item
Criteria FTS-12
FTS-5
FTS-3
Energetic balance or nutrition
Body mass index Weight loss (4.5 kg) Abdominal obesity (waist perimeter) Albumin serum levels (mg/dL) PASE (total score) Verbal fluency (no. of animals in 60 s) Progressive Romberg test Brachial ankle index Grip strength (kg)* Knee extension strength (kg) Chair test (times standing up in 30 s) Walking speed (usual pace in 3 m)y
x x x x x (quintiles) x x x x (quintiles) x x x (quintiles)
x (new scoring)
x (new scoring)
x (new scoring)
x (new scoring)
x
x
Activity Nervous system Vascular system Strength Endurance Gait speed
x (new scoring)
x (new scoring)
PASE, Physical Activity Scale for the Elderly. *Jamar dynamometer. y Rolling start.
or under the basal risk according to linear increasing or decreasing risk (gait speed, handgrip, physical activity), or U-shaped risk [body mass index (BMI)]. In each step, using the scoring method described previously for each item, the FTSSF score was computed with all the included items and the candidate item, and the AUC was estimated for the full models. The step size that maximized the sum of the AUC was selected as the best way to introduce it within the FTSSF score. The candidate item that maximized the AUC sum was included in the FTSSF. The optimal cutoffs for each FTSSF were identified for evaluating their prognostic performance with the AUC for each outcome (death, hospitalization, disability, and frailty) using a regression logistic model. Those cutoffs that best optimized the diagnostic classification were selected. In the second phase, the prognostic performance of each short form was compared with the Fried Phenotype using Cox multivariate regression models (outcome time dependent) and logistic models (dichotomous dependent variable). All the analyses were done with R, version 3.3.2 for Windows,16 and statistical significance was set at P < .05. Results A total of 1735 participants met the inclusion criteria, but 101 were lost to follow-up, so 1634 were included in the analysis (721 men and 913 women). The participants’ mean age was 74.7 years. They were followed for an average of 5.59 years for mortality, 3.27 years for hospitalization, and 4.98 years for frailty and disability. The incidence
rates for mortality, hospitalization, disability, and frailty were 16.77%, 21.05%, 25.25%, and 9.06%, respectively. In general, higher comorbidity, worse physical performance, and higher adverse event rates could be observed in participants who are frail according to the scales used for evaluation.
Item Reduction, Scoring, and Cutoff Selection The items that best optimized the prediction ability were the BMI, progressive Romberg, physical activity measured with the Physical Activity Scale for the Elderly (PASE), usual walking speed, and hand grip strength. Two scales of 5 and 3 items, respectively, were built. The scoring criteria for the 5 best items are included in Table 2. In Table 3, the areas under the curves (AUCs) from the basal model (age, sex, and Charlson index) and the added models from the 5 items that were selected are shown. The complete 5-item model (range 0-50) was the one with the highest AUC in each health event, and in the aggregate of possibilities regarding the Fried Phenotype (FP) and Frailty Index (FI) models. It also had a better diagnostic performance than the 12-item FTS, but the differences were not statistically significant. To avoid some of the problems in standardizing the performance task (gait speed and hand grip), a 3-item model including only BMI, physical activity, and progressive Romberg (range 0-30) was selected. In Table 4, the sensitivity and specificity for the Short Forms (FTS5 and FTS3, respectively) are shown. The cutoffs that maximized the prognostic information were >25 for FTS5 and >15 for FTS3.
Table 2 FTS Short Forms Scoring Table Score
0 1 2 3 4 5 6 7 8 9 10
BMI, kg/m2
23.01-26.99 27-28.99 29-30.99 31-32.99 33-34.99 35-36.99 37-38.99 39-40.99 41-42.99 43-44.99 45
PASE
21.01-23 19.01-21 17.01-19 15.01-17 13.01-15y 11.01-13y NA NA NA NA
>194 174.61-194 155.21-174.6 135.81-155.2 116.41-135.8 97.01-116.4 77.61-97 58.21-77.6 38.81-58.2 19.41-38.8 0-19.4
Gait Speed, s*
<2.45 2.45-2.99 3.00-3.54 3.55-4.09 4.10-4.64 4.65-5.19 5.20-5.74 5.75-6.29 6.30-6.84 6.85-7.39 7.4
Grip Strength, kg
Score
Women
Men
>22 19.81-22 17.61-19.8 15.41-17.6 13.21-15.4 11.01-13.2 8.81-11.0 6.61-8.8 4.41-6.6 2.21-4.4 0-2.2
>29 26.11-29 23.21-26.1 20.31-23.2 17.41-20.3 14.51-17.4 11.61-14.5 8.71-11.6 5.81-8.7 2.91-5.8 0-2.9
0 2.5 5 7.5 10
Progressive Romberg Position
Seconds
Tandem Tandem Tandem Semitandem Semitandem Side by side Side by side
10 3.01-9.99 3 10 <10 10 <10
PASE, Physical Activity Scale for the Elderly. FTS5 includes all the items of the table (range 0-50), and frail participants are those with FTS5 scores >25. FTS3 includes BMI, PASE, and Romberg test (range 0-30), and frail participants are those with FTS3 scores >15. *Gait speed refers to time in accomplish 3-metres at usual pace. y Model estimation.
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Table 3 Area Under the Curve for Different Outcomes According to Frailty Models Model
Death
Hospitalization
Incident Disability
Incident Frailty (FP)
Incident Frailty (FI)
Sum of Probabilities
Basic B BþP FTS3: BþPþBMI BþPþBMIþG FTS5: BþPþBMIþGþGS Fried Phenotype FTS12 Frailty Index
0.7803 0.7964 0.8062 0.8070 0.8124 0.8130 0.8002 0.8122 0.8094
0.6133 0.6383 0.6410 0.6415 0.6445 0.6509 0.6223 0.6378 0.6352
0.7001 0.7138 0.7185 0.7300 0.7353 0.7332 0.7065 0.7317 0.7261
0.7511 0.7852 0.8012 0.8102 0.8205 0.8175 0.7779 0.8171 0.8195
0.7712 0.8111 0.8354 0.8332 0.8498 0.8504 0.8145 0.8431 0.8380
3.6160 3.7449 3.8023 3.8220 3.8626 3.8650 3.7214 3.8419 3.8282
B, balance; G, grip strength; GS, gait speed; P, Physical Activity Scale for the Elderly. Basic model: age, sex, Charlson Index.
Prognostic Performance of the FTS Short Forms Table 5 shows the OR adjusted for each model for every health event. The prognostic performance for each short form was contrasted with a well-established frailty phenotype, and every participant was classified in terms of frailty according to the FTS5 and FTS3 in each of the frailty stratum, taking into account the Fried criteria (robust, prefrail, and frail). The frailty prevalence, according to the FTS and its short forms (FTS5 and FTS3), reached 28%, 24%, and 20%, respectively, whereas frailty according to the FP reached 8% and prefrailty, 41% (Table 5). In the different forms of the FTS, frail participants had a high risk for mortality (OR: 2.6-3.6) and disability (OR: 1.89-2.1), a very high risk for frailty (OR: 4.5-6.3, except FTS3, OR: 2.6-2.8), and a low to moderate risk for hospitalization (OR: 1.37-1.8). On the other hand, frail individuals in the Fried Phenotype comprised a very high-risk group for mortality (OR: 4.6), disability (OR: 4.0), and frailty (OR: 6.5), and had no relevant risk for hospitalization, whereas prefrail individuals were identified as participants with a high risk for mortality (OR: 2.1) and frailty (OR: 2.7-3.1), a mild risk for hospitalization (OR: 1.4), and no significant relevant risk for disability (OR: 1.2). Table 5 shows the FTS short forms’ (FTS5, FTS3) prognostic performance in each of the Fried Phenotype strata. The FTS5 discriminated 4.6% of robust according to FP with high risk for disability (OR: 2.3) and frailty (ORFried: 3.9). On the contrary, in those frail participants according to FP, the FTS5 identified 8.7% with low risk in every outcome. The behavior in prefrail FP participants is even more interesting, with the FTS5 stratifying them in 2 big groups. The first group (FPprefrail-FTS5 frail) was composed of 35% of the participants with a very high risk for mortality (OR: 4.0) and frailty (OR: 6.6-8.7), a high risk for hospitalization (OR: 2.1), and a moderate risk for disability (OR: 1.7). The second group comprised 65% (FPprefrail-FTS5 nonfrail) of the participants, with a basal risk for hospitalization and disability, a mild or basal risk for mortality (OR: 1.5; NS), and a high risk for frailty according to the Frailty Index (ORFI: 2.1) and nonexistent or mild according to FP (ORFP: 1.6; NS). Finally, the FTS3 had a similar behavior as the FTS5, but its ability to discriminate participants with high or low risk in each of the Fried Phenotype strata was much lower. In fact, it classified as nonfrail 31% of the participants identified as frail according to FP, although they present a high risk for mortality (OR: 2.3), a high or very high risk for disability (OR: 2.8-4), and a very high risk for frailty (ORFI: 4.0). Discussion The aim of this study was to simplify the FTS for its use in screening and monitor frailty in a clinical setting. To do so, the FTS, which is a scale that shares the Fried and Walston’s approach12 to evaluate frailty, was simplified and reduced, and it proved to be very useful in identifying individuals at risk for health adverse events6e12 in a
population research setting. Two FTS Short forms were identified, and the best prognostic performance was obtained with the 5-item scale (FTS5) that evaluates core aspects of frailty, such as BMI, energy expenditure, and the state of the neuromuscular interface (balance, gait speed, and hand grip). The FTS5 performance is less demanding for frailty than Fried Phenotype but more inclusive, identifying 24% of participants with high risk for mortality, hospitalization, disability, and progression to frailty (according to other phenotypes), and is susceptible to intervention, therefore, helping medical practitioners and health providers in decision making. The 3 forms of FTS showed similar prognostic performance, just like Frailty Index and Fried Phenotype, so all of them can be used in clinical settings. However, choosing which one to use will depend on the time available to run them, the presence or not of the instrument for measurement, and the sensitivity to change, among others factors. Interestingly, although the FTS-12 and FI incorporate biological (albumin, vascular state evaluation, etc), functional, and clinical variables, they did not have higher AUC in comparison with the short versions (FTS5 and FTS3) and Fried Phenotype. So, some of those items may be redundant. We know that in clinical practice it is important to classify patients according to their risk for adverse health events with the lowest cost possible. However, among all the studied scales, this is only achieved with the short forms of the FTS (mainly the FTS5) and the Fried Phenotype. In our opinion, the FTS5 presents a better profile for its use because the (1) FTS5 provides an opportunity for tracking trajectories inside each category (frail or nonfrail) and between categories, supporting the fact that frailty is not a “categorical” issue but a continuous, discrete one; (2) FTS5 has a range from 0 to 25 that evaluates the path from robust to frailty and from 26 (frail) to 50 who are extremely frail; and (3) the FTS5 identifies a cutoff above which participants (24% of the sample) have a higher risk for adverse health events and is able to classify the risk of the people with a high accuracy. In contrast, the Fried model identifies a group that is at a very high risk (ie, frail; 8%) for adverse health events and another one of intermediate risk (ie, prefrail; 41% of the sample), the latter being a heterogeneous group (Table 5). The frail phenotype in the FTS5 included 124 from the 137 classified as frail according to Fried criteria, 238 of the 677 prefrail that are considered high risk, and 37 of 797 robust of Fried with high levels of disability and frailty (Table 5). Thus, its prognostic performance compared to a standard of frailty such as the Fried Phenotype is better to stratify the risk, identifying 8% of frail and 4.5% of robust who were false positives and false negatives, respectively. Yet, the main FTS5 performance was found to be with prefrail participants, according to Fried criteria, in which it identified a big group (65%) classified as robust with a risk that is almost negligible and the remaining group (35%) with very high risk, categorized as frail. So, the FTS5 included 35% of the prefrail with a high risk and the frail with a very high risk from the Fried model in a single group. In this way, the FTS5 clarified the group of interest for a determinate intervention to 24% of the
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Table 4 Sensitivity and Specificity of FTS5 and FTS3 by Different Cutoffs Cutoff Score
FTS5 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 FTS3 10 11 12 13 14 15 16 17 18 19 20
Death
Hospitalization
Disability
Frailty (FP)
Frailty (FI)
S
SP
S
SP
S
SP
S
SP
S
SP
0.885 0.881 0.857 0.817 0.794 0.738 0.714 0.690 0.663 0.619 0.563 0.508 0.468 0.440 0.385 0.313 0.238 0.194 0.155 0.131
0.315 0.377 0.424 0.470 0.517 0.557 0.589 0.636 0.688 0.733 0.768 0.813 0.846 0.878 0.900 0.925 0.938 0.956 0.966 0.975
0.834 0.795 0.756 0.709 0.670 0.634 0.604 0.551 0.493 0.443 0.380 0.319 0.271 0.235 0.199 0.147 0.122 0.091 0.075 0.061
0.317 0.375 0.420 0.465 0.509 0.553 0.584 0.625 0.670 0.714 0.744 0.788 0.818 0.848 0.873 0.899 0.921 0.940 0.954 0.964
0.825 0.767 0.733 0.692 0.644 0.623 0.575 0.524 0.462 0.397 0.346 0.284 0.229 0.185 0.144 0.106 0.089 0.065 0.048 0.031
0.405 0.478 0.528 0.579 0.628 0.673 0.703 0.754 0.797 0.829 0.860 0.902 0.926 0.949 0.959 0.974 0.983 0.992 0.994 0.994
0.912 0.882 0.853 0.814 0.765 0.745 0.735 0.716 0.676 0.608 0.539 0.441 0.363 0.265 0.216 0.127 0.088 0.088 0.049 0.029
0.363 0.436 0.487 0.544 0.593 0.638 0.675 0.731 0.785 0.823 0.854 0.898 0.922 0.941 0.953 0.963 0.970 0.985 0.990 0.992
0.943 0.935 0.935 0.902 0.854 0.821 0.789 0.780 0.732 0.642 0.553 0.463 0.390 0.309 0.252 0.163 0.146 0.138 0.098 0.073
0.366 0.438 0.490 0.542 0.590 0.634 0.670 0.724 0.777 0.814 0.841 0.883 0.909 0.935 0.950 0.961 0.973 0.987 0.992 0.993
0.881 0.837 0.802 0.726 0.659 0.567 0.433 0.353 0.270 0.194 0.135
0.346 0.425 0.493 0.564 0.643 0.728 0.802 0.859 0.902 0.929 0.950
0.809 0.751 0.693 0.604 0.504 0.388 0.291 0.233 0.166 0.130 0.097
0.345 0.423 0.487 0.555 0.625 0.703 0.783 0.844 0.888 0.921 0.947
0.812 0.719 0.654 0.545 0.449 0.339 0.267 0.171 0.123 0.075 0.055
0.434 0.520 0.593 0.658 0.724 0.805 0.871 0.914 0.947 0.959 0.977
0.912 0.843 0.794 0.755 0.667 0.510 0.392 0.255 0.196 0.137 0.098
0.393 0.479 0.555 0.635 0.714 0.795 0.861 0.906 0.937 0.956 0.970
0.951 0.894 0.862 0.780 0.650 0.520 0.423 0.285 0.220 0.154 0.114
0.395 0.484 0.559 0.636 0.712 0.796 0.865 0.904 0.936 0.954 0.972
S, sensitivity; SP, specificity.
population compared with the 49% of frail and prefrail participants identified by the Fried Phenotype. Accordingly, the FTS5 is less demanding but more inclusive, identifying 24% of the participants who were susceptible and at a high risk for mortality, hospitalization, and disability, for intervention and thus helping with clinical decisions. This fact, along with the wide range of evaluation of this scale (050) and the short time taken to perform the test (5 minutes), makes the FTS5 a very useful measurement in multiple scenarios: (1) Clinical Environment, for diagnosis and to monitor patients across a wide range; (2) Research Environment, for its ability to classify individuals and its sensitivity to change derived from its wide range; and (3) Public Health, simplifying the amount of patients who should receive treatment to a group at a high or very high risk. Finally, because of its characteristics, FTS5 can be considered complementary to other very well-known and broadly used scales in clinical settings (eg, Clinical Frailty Scale). Likewise, it shows some advantages mainly in controlled clinical settings in which the goal is to monitor the trajectory of the frailty status in response to interventions or intercurrent diseases. The other scale (FTS3), which included 3 of the items (BMI, energy expenditure, and progressive Romberg) from the FTS5, is short but has a prognostic performance similar to the FTS5 (Table 3). However, this scale loses prognostic accuracy by excluding 2 items that are part of the core of frailty, since it classified 31% of frail participants as robust but with a high risk for adverse health events. The FTS and its short forms share with Fried and Walston’s Phenotype their approximation to the study and evaluation of frailty and includes almost all their items. Four criteria of the Fried Phenotype are included in the complete version of the FTS, sharing the same
problems of external validity, especially regarding its standardization with other cultures, races, and regions, of 2 criteria: gait speed and hand grip. Thus, there are substantial differences in regard to distribution, by income, race and population extraction, that could partially explain interregional differences in a given country17 and in between countries.18,19 Therefore, estimates of frailty prevalence can vary substantially if the cutoffs are not adjusted to a given population, as it happens in Spain.20 Even though the FTS5 results of this study are valid for the Spanish population, there should be some comments regarding its strength to extrapolate the results to other populations. On the one hand, there is the inclusive construct related to the risk levels; thus, the FTS5 score covers a range that reaches all the spectrum of risk in each domain in physical activity (PASE: 194-0), gait speed (1.2-0.4 m/s) (20), BMI (complete range), and peripheral Romberg (complete range) (Table 2), minimizing the effects of different cutoffs for each population. Furthermore, special mention should be made with the hand grip behavior in our sample, with a range starting from 22 kg in women and 29 kg in men. Both points represent a threshold risk from which it increases and initiates the score, which correspond to centiles 84 and 54 in women and men, respectively. It is known that the differences in hand grip between regions are important, being higher in North Europe and North America than in Asia, Africa, or South America.21 Likewise, there are substantial interregional differences, so hand grip is stronger in North Europe than in Mediterranean populations.18 Although these data are real, when strength is assessed in respect to adverse health events the differences between populations decrease substantially. Thus, even though the German population (as an average) is much more robust than the Spanish one, the threshold from which the mortality risk is increased is similar in women
6
F.J. García-García et al. / JAMDA xxx (2020) 1e7
Table 5 OR of Relevant Outcomes According to FTS Forms, Fried Phenotype, and Fried Phenotype Status by FTS5 and FTS3 Mortality n (e) Fried Phenotype Robust 797 (54) Prefrail 677 (124) Frail 137 (59) FTS No frail 1154 (100) Frail 457 (137) FTS5 No frail 1211 (108) Frail 400 (129) FTS3 No frail 1288 (136) Frail 323 (101) Fried Phenotype status by FTS5 Robust FTS5, No frail 760 (50) FTS5, Frail 37 (4) Prefrail FTS5, No frail 439 (56) FTS5, Frail 238 (68) Frail 12 (2) FTS5, No frail FTS5, Frail 125 (57) Fried Phenotype status by FTS3 Robust FTS3, No frail 736 (48)
Hospitalization OR
n (e)
First Disability
Worsening Disability
Incident Frailty (FP)
Incident Frailty (FI)
OR
n (e)
OR
n (e)
OR
n (e)
OR
n (e)
OR
1 2.15* 4.65*
797 (134) 677 (171) 137 (39)
1 1.46y 1.4
633 (130) 420 (123) 32 (21)
1 1.22 3.97*
688 (147) 507 (158) 66 (39)
1 1.26 2.89*
626 (30) 445 (67) na
1 2.78* na
688 (30) 482 (77) 34 (12)
1 3.13* 6.52*
1 3.11*
1154 (214) 457 (130)
1 1.50y
878 (177) 207 (97)
1 2.12*
971 (206) 290 (138)
1 2.03*
874 (45) 197 (52)
1 5.17*
967 (51) 237 (68)
1 4.46*
1 3.61*
1211 (220) 400 (124)
1 1.83*
917 (193) 168 (81)
1 2.05*
1016 (225) 245 (119)
1 1.92*
915 (49) 156 (48)
1 6.34*
1008 (58) 196 (61)
1 4.46*
1 2.57*
1288 (252) 323 (92)
1 1.37z
946 (214) 139 (60)
1 1.93y
1060 (254) 201 (90)
1 1.88*
937 (70) 134 (27)
1 2.64*
1040 (80) 164 (39)
1 2.83*
1 1.34
760 (126) 37 (8)
1 1.36
609 (117) 24 (13)
1 2.63z
656 (130) 32 (17)
1 2.35z
598 (24) 28 (6)
1 3.93z
657 (25) 31 (5)
1 1.9
1.50x 4.04*
439 (93) 238 (78)
1.21 2.19*
301 (73) 119 (50)
1.13 1.74z
352 (92) 155 (66)
1.21 1.68z
317 (25) 128 (42)
1.62 8.72*
345 (33) 137 (44)
2.10y 6.64*
1.01 6.09*
12 (1) 125 (38)
0.31 1.70z
7 (3) 25 (18)
2.04 5.51*
8 (3) 58 (36)
1.59 3.49*
na na
na na
6 (0) 28 (12)
1
736 (120)
1
1
584 (25)
1
639 (23)
FTS3, Frail
61 (6)
1.31
Prefrail FTS3, No frail
509 (77)
1.85
y
FTS3, Frail
168 (47)
3.46*
Frail FTS3, No frail
43 (11)
2.36
FTS3, Frail
94 (48)
6.68*
z
594 (114)
61 (14)
1.49
509 (120)
1.41z y
1
639 (126)
11.3*
1
39 (16)
2.01x
49 (21)
2.13z
42 (5)
2.15
49 (7)
2.64z
332 (87)
1.15
393 (112)
1.24
353 (45)
2.50*
382 (52)
3.07*
92 (22)
5.40*
100 (25)
6.00*
4.01z
88 (36)
y
y
1.99
114 (46)
1.86
168 (51)
1.84
43 (12)
1.53
20 (13)
4.07y
28 (16)
2.89z
na
na
19 (5)
94 (27)
1.46
12 (8)
4.64z
38 (23)
3.38*
na
na
15 (7)
16.7*
e, number of events; na, not available. *P < .001; yP < .01; zP < .05; xP < .1.
(average in German women: 21 kg) and somewhat higher in men (average in German men: 32.9 kg).22 So, if needed, this problem could be overcome by adjusting the risk threshold adapted to each population if there are enough data to do so. Therefore, although we need studies to guarantee the prognostic value of FTS5, the inclusive construct of the scale minimizes the standardization issues for other populations present in the Fried and Walston Phenotype. Likewise, the wide range bases on a score that covers all, or almost all, of the path of each domain from robust to frail and ensures its sensitivity to change, which is needed to monitor patients in a clinical setting and provides a very useful measurement to assess the response to therapy. Finally, this study presents some weaknesses and strengths. The absence of interregional validation may be the main weakness for the FTS5. However, its construct, with a wide range of measurement in each dimension, minimizes any issue with external validity. On the other hand, although the FTS5 presents an optimal profile to be used in clinical practice, its performance still needs to be evaluated in this scenario. Some strengths could be highlighted: (1) the population source rules out bias in the diagnostic and prognostic accuracy parameters that are usually present in clinical samples and (2) its diagnostic performance has been tested against a wide range of outcomes (mortality, resources use, functional) and a frailty standard (Fried criteria).
Conclusions and Implications The FTS short forms, especially the FTS5, provide a frailty measurement that is valid, short, and helps identify individuals who are at high risk for frailty and is potentially useful in multiple settings (clinical, research, public health, etc). Its main advantages in comparison with the currently used tools inside the conceptual framework of the frailty phenotype can be summarized by its better classification of the risks for adverse events and the possibility of monitoring frailty trajectories. However, more interregional and validation studies are needed throughout the clinical spectrum to refine its diagnostic and prognostic value in scenarios different from community settings.
References 1. Rodriguez-Manas L, Fried LP. Frailty in the clinical scenario. Lancet 2015;385: e7ee9. 2. Dunning T, Sinclair A, Colagiuri S. New IDF guideline for managing type 2 diabetes in older people. Diabetes Res Clin Pract 2014;103:538e540. 3. Rodriguez-Artalejo F, Rodriguez-Manas L. The frailty syndrome in the public health agenda. J Epidemiol Community Health 2014;68:703e704. 4. Aguayo GA, Donneau AF, Vaillant MT, et al. Agreement between 35 published frailty scores in the general population. Am J Epidemiol 2017;186:420e434.
F.J. García-García et al. / JAMDA xxx (2020) 1e7 5. Garcia-Garcia FJ, Carcaillon L, Fernandez-Tresguerres J, et al. A new operational definition of frailty: The Frailty Trait Scale. J Am Med Dir Assoc 2014;15:371. e7-371.e13. 6. Castro-Rodriguez M, Carnicero JA, Garcia-Garcia FJ, et al. Frailty as a major factor in the increased risk of death and disability in older people with diabetes. J Am Med Dir Assoc 2016;17:949e955. 7. Rosado-Artalejo C, Carnicero JA, Losa-Reyna J, et al. Global performance of executive function is predictor of risk of frailty and disability in older adults. J Nutr Health Aging 2017;21:980e987. 8. Rosado-Artalejo C, Carnicero JA, Losa-Reyna J, et al. Cognitive performance across 3 frailty phenotypes: Toledo Study for Healthy Aging. J Appl Physiol (1985) 2017;18:785e790. 9. Del Pozo-Cruz B, Manas A, Martin-Garcia M, et al. Frailty is associated with objectively assessed sedentary behaviour patterns in older adults: Evidence from the Toledo Study for Healthy Aging (TSHA). PLoS One 2017;12:e0183911. 10. Manas A, Del Pozo-Cruz B, Guadalupe-Grau A, et al. Reallocating accelerometer-assessed sedentary time to light or moderate- to vigorousintensity physical activity reduces frailty levels in older adults: An isotemporal substitution approach in the TSHA study. J Am Med Dir Assoc 2018; 19:185.e1e185.e6. 11. Garcia-Garcia FJ, Gutierrez Avila G, Alfaro-Acha A, et al. The prevalence of frailty syndrome in an older population from Spain. The Toledo Study for Healthy Aging. J Nutr Health Aging 2011;15:852e856. 12. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: Evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56:M146eM156. 13. Searle SD, Mitnitski A, Gahbauer EA, et al. A standard procedure for creating a frailty index. BMC Geriatr 2008;8:24.
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14. Katz JN, Chang LC, Sangha O, et al. Can comorbidity be measured by questionnaire rather than medical record review? Med Care 1996;34: 73e84. 15. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis 1987;40:373e383. 16. R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2014. 17. Bandeen-Roche K, Seplaki CL, Huang J, et al. Frailty in older adults: A nationally representative profile in the United States. J Gerontol A Biol Sci Med Sci 2015; 70:1427e1434. 18. Andersen-Ranberg K, Petersen I, Frederiksen H, et al. Cross-national differences in grip strength among 50þ year-old Europeans: Results from the SHARE study. Eur J Ageing 2009;6:227e236. 19. Siriwardhana DD, Hardoon S, Rait G, et al. Prevalence of frailty and prefrailty among community-dwelling older adults in low-income and middle-income countries: A systematic review and meta-analysis. BMJ Open 2018;8: e018195. 20. Alonso Bouzon C, Carnicero JA, Turin JG, et al. The standardization of frailty phenotype criteria improves its predictive ability: The Toledo Study for Healthy Aging. J Am Med Dir Assoc 2017;18:402e408. 21. Dodds RM, Syddall HE, Cooper R, et al. Global variation in grip strength: A systematic review and meta-analysis of normative data. Age Ageing 2016;45: 209e216. 22. Steiber N. Strong or weak handgrip? Normative reference values for the German population across the life course stratified by sex, age, and body height. PLoS One 2016;11:e0163917.
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F.J. García-García et al. / JAMDA xxx (2020) 1e7
Supplementary Table 1 OR or HR of Relevant Outcomes for Older Adults According to FTS Forms and Fried Phenotype Mortality n (e) Fried phenotype Robust 797 (54) Prefrail 677 (124)
OR
Hospitalization
First Disability
Worsening Disability
Incident Frailty (FP)
Incident Frailty (FI)
n (e)
OR
n (e)
OR
n (e)
OR
n (e)
OR
n (e)
1 1.46y (1.12-1.90) 1.4 (0.89-2.21)
633 (130) 420 (123)
1 1.22 (0.90-1.66) 3.97* (1.79-8.84)
688 (147) 507 (158)
1 1.26 (0.95-1.67) 2.89* (1.65-5.06)
626 (30) 445 (67)
1 2.78* (1.74-4.44) na
688 (30) 482 (77)
1 2.15* (1.50-3.08) 4.65* (2.83-7.63)
797 (134) 677 (171)
32 (21)
66 (39)
na
34 (12)
1 3.13* (1.97-4.97) 6.52* (2.76-15.4)
Frail
137 (59)
FTS No frail Frail
1154 (100) 457 (137)
1 3.11* (2.22-4.37)
1154 (214) 457 (130)
1 1.50y (1.13-2.00)
878 (177) 207 (97)
1 2.12* (1.49-3.00)
971 (206) 290 (138)
1 2.03* (1.49-2.77)
874 (45) 197 (52)
1 5.17* (3.18-8.39)
967 (51) 237 (68)
1 4.46* (2.87-6.93)
FTS5 No frail Frail
1211 (108) 400 (129)
1 3.61* (2.54-5.12)
1211 (220) 400 (124)
1 1.83* (1.37-2.46)
917 (193) 168 (81)
1 2.05* (1.41-2.98)
1016 (225) 245 (119)
1 1.92* (1.38-2.65)
915 (49) 156 (48)
1 6.34* (3.81-10.57)
1008 (58) 196 (61)
1 4.46* (2.83-7.02)
FTS3 No frail Frail
1288 (136) 323 (101)
1 2.57* (1.84-3.58)
1288 (252) 323 (92)
1 1.37z (1.02-1.84)
946 (214) 139 (60)
1 1.93y (1.30-2.86)
1060 (254) 201 (90)
1 1.88* (1.34-2.62)
937 (70) 134 (27)
1 2.64* (1.57-4.44)
1040 (80) 164 (39)
1 2.83* (1.01-6.93)
e, number of events; na, not available. *P < .001; yP < .01; zP < .05.
137 (39)
OR
Supplementary Table 2 OR or HR of Relevant Outcomes for Older Adults According to Fried Phenotype Status by FTS5 Mortality
Robust FTS5, No frail FTS5, Frail Prefrail FTS5, No frail FTS5, Frail Frail FTS5, No frail FTS5, Frail
Hospitalization
First Disability
Worsening Disability
Incident Frailty (FP)
Incident Frailty (FI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
760 (50) 37 (4)
1 1.34 (0.42-4.24)
760 (126) 37 (8)
1 1.36 (0.59-3.12)
609 (117) 24 (13)
1 2.63*(1.08-6.42)
656 (130) 32 (17)
1 2.35* (1.08-5.11)
598 (24) 28 (6)
1 3.93* (1.29-11.9)
657 (25) 31 (5)
1
345 (33) 137 (44)
2.10z (1.21-3.66) 6.64x (3.74-11.8)
6 (0) 28 (12)
11.31x (4.53-28.2)
y
439 (56) 238 (68)
1.50 (0.98-2.28) 4.04x (2.57-6.36)
439 (93) 238 (78)
1.21 2.19x (0.89-1.64)
301 (73) 119 (50)
1.13 (0.80-1.60) 1.74* (1.11-2.74)
352 (92) 155 (66)
1.21 (0.88-1.66) 1.68*
317 (25) 128 (42)
1.62 (0.89-2.93) 8.72x (4.79-15.8)
12 (2) 125 (57)
1.01 (0.20-4.98) 6.09x (3.60-10.32)
12 (1) 12 (38)
0.31 (0.04-2.48) 1.70* (1.06-2.73)
7 (3) 25 (18)
2.04 (0.42-9.92) 5.51x (2.16-14.1)
8 (3) 58 (36)
1.59 (0.35-7.17) 3.49x (1.91-6.35)
na na
na na
1.9 (0.61-5.95)
e, number of events; na, not available. y P < .1; *P < .05; zP < .01; xP < .001.
Mortality
Fried Phenotype Status by FTS3 Robust FTS3, No frail FTS3, Frail Prefrail FTS3, No frail FTS3, Frail Frail FTS3, No frail FTS3, Frail
Hospitalization
First Disability
Worsening Disability
Incident Frailty (FP)
Incident Frailty (FI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
736 (48) 61 (6)
1 1.31 (0.51-3.34)
736 (120) 61 (14)
1 1.49 (0.78-2.82)
594 (114) 39 (16)
1 2.01* (0.98-4.12)
639 (126) 49 (21)
1 2.13y (1.13-4.03)
584 (25) 42 (5)
1 2.15 (0.72-6.38)
639 (23) 49 (7)
1
509 (77) 168 (47)
1.85z (1.24-2.76) 3.46x (2.14-5.59)
509 (120) 168 (51)
1.41y (1.06-1.89) 1.84z (1.24-2.75)
332 (87) 88 (36)
1.15 (0.82-1.61) 1.99z (1.21-3.29)
393 (112) 114 (46)
1.24 (0.91-1.69) 1.86z (1.19-2.92)
353 (45) 92 (22)
2.50x (1.48-4.25) 5.40x (2.80-10.4)
382 (52) 100 (25)
3.07x (1.81-5.22) 6.00x (3.12-11.5)
43 (11) 94 (48)
2.36y (1.05-5.28) 6.68x (3.79-11.7)
43 (12) 94 (27)
1.53 (0.75-3.13) 1.46 (0.86-2.49)
20 (13) 12 (8)
4.07z (1.51-11.0) 4.64y (1.29-16.7)
28 (16) 38 (23)
2.89y (1.28-6.53) 3.38x (1.64-6.95)
na na
na na
19 (5) 15 (7)
4.01y (1.23-13.0) 16.71x (5.07-55.0)
F.J. García-García et al. / JAMDA xxx (2020) 1e7
Supplementary Table 3 OR of Relevant Outcomes for Older Adults According to Fried Phenotype Status by FTS3
2.64y (1.01-6.93)
e, number of events; na, not available. *P < .1; yP < .05; zP < .01; xP < .001.
7.e2
JAMDA journal homepage: www.jamda.com
Original Study
Frailty Trait ScaleeShort Form: A Frailty Instrument for Clinical Practice Francisco Jose García-García MD, PhD a, b, *, Jose Antonio Carnicero PhD b, Jose Losa-Reyna PhD a, b, c, Ana Alfaro-Acha MD, PhD a, b, Carmen Castillo-Gallego MD, PhD a, b, Cristina Rosado-Artalejo MD, PhD a, b, Gonzalo Gutiérrrez-Ávila MD, PhD b, d, Leocadio Rodriguez-Mañas MD, PhD b, e a
Department of Geriatrics, Hospital Virgen del Valle, Complejo Hospitalario de Toledo, Toledo, Spain CIBER of Frailty and Healthy Aging (CIBERFES), Madrid, Spain GENUD Toledo Research Group, Universidad de Castilla La Mancha, Toledo, Spain d Epidemiologic Department, Consejería de Sanidad de Castilla la Mancha, Toledo, Spain e Geriatric Department, Hospital Universitario de Getafe, Getafe, Spain b c
a b s t r a c t Keywords: Frailty phenotype frailty assessment frailty diagnosis frailty scales risk adverse event
Objectives: To develop short versions of the Frailty Trait Scale (FTS) for use in clinical settings. Design: Prospective population-based cohort study. Setting and Participants: Data from 1634 participants from the Toledo Study for Healthy Aging. Methods: The 12-item Frailty Trait Scale (FTS) reduction was performed based on an area under the curve (AUC) analysis adjusted by age, sex, and comorbidity. Items that maximized prognostic information for adverse events were selected. Each item score was done at the same time as the reduction, identifying the score that maximized the predictive ability for adverse events. For each short version of the FTS, cutoffs that optimized the prognostic information (sensitivity and specificity) were chosen, and their predictive value was later compared with a surrogate gold standard for frailty (the Fried Phenotype). Results: Two short forms, the 5-item (FTS5) (range 0-50) and 3-item (FTS3) (range 0-30), were identified, both with AUCs for health adverse events similar to the 12-item FTS. The identified cutoffs were >25 for the FTS5 scale and >15 for the FTS3. The frailty prevalence with these cutoffs was 24% and 20% for the FTS5 and FTS3, respectively, whereas frailty according to Fried Phenotype (FP) reached 8% and prefrailty reached 41%. In general, the FTS5 showed better prognostic performance than the FP, especially with prefrail individuals, in whom the FTS5 form identified 65% of participants with an almost basal risk and 35% with a very high risk for mortality (OR: 4) and frailty (OR: 6.6-8.7), a high risk for hospitalization (OR: 1.9-2.1), and a moderate risk for disability (OR: 1.7) who could be considered frail. The FTS3 form had worse performance than the FTS5, showing 31% of false negatives between frail participants identified by FP with a high risk of adverse events. Conclusions and Implications: The FTS5 is a short scale that is easy to administer and has a similar performance to the FTS, and it can be used in clinical settings for frailty diagnosis and evolution. Ó 2019 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
The authors were supported by grants PI15/01305, CB16/10/00456 and CB16/ 10/00464 from the Instituto de Salud Carlos III (FEDER funds, Ministerio de Ciencia e Innovación, Spain), RD12/0043 from the Instituto de Salud Carlos III (Ministerio de Economía y Competitividad, Spain), PI2010/020 from FISCAM (Junta de Comunidades de Castilla La Mancha, Spain), FP7-305483-2 (“Frailomic Iniciative”) from FP7-Health-2012-Innovation (European Union). The authors declare no conflicts of interest. * Address correspondence to Francisco Jose García-García, MD, PhD, Geriatric Department, Complejo Hospitalario de Toledo, Ctra de Cobisa s/n, 45071, Toledo, Spain. E-mail address: [email protected] (F.J. García-García). https://doi.org/10.1016/j.jamda.2019.12.008 1525-8610/Ó 2019 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
Owing to its prognostic value, frailty has emerged as a priority in daily clinical practice in the care of older adults,1 influencing the management of the patient and the decision-making process.2 However, the implementation of frailty assessment in clinical scenarios is a challenge, because of several factors that are delaying its use in clinical settings1 and public health.3 One of the most relevant factors is the difficulty in diagnosing frailty. Indeed, the few studies that have assessed the usefulness of several tools to screen or diagnose frailty, in terms of their sensitivity, specificity, or predictive value, have raised disappointing results.4 This inconsistency is caused by the lack of a gold standard, because each diagnostic
2
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approach to frailty evaluates different aspects of a polyhedral syndrome. On the other hand, current criteria have been mostly developed and validated in epidemiologic cohorts with the main purpose of defining risks for precise adverse health outcomes such as death, disability, hospitalization, falls, etc, but not to be used in clinical settings, where the main purpose is to screen or diagnose the syndrome on individual bases and monitor the clinical evolution. In this scenario, a scale should have the following characteristics: first, a good diagnostic accuracy to properly stratify the population; second, the ability to detect small changes in the clinical progression or in the response to treatment, that is, to be sensitive to change; and third, feasibility to use in a limited clinical setting. However, frailty is not the typical syndrome with a group of symptoms that coexist and define a disease. In fact, it is a biological state that an individual reaches as a result of the decline of multiple systems, and of the interaction between physiological aging, diseases, and certain lifestyles. Actually, there are no specific biomarkers, so that individuals are classified as frail when crossing a certain, arbitrary threshold, from which the risk of adverse health events is higher. In such cases, the diagnostic accuracy is reached when the diagnostic scale includes the syndrome nuclear domains, and the sensitivity to change is reached when the impairment in each domain is captured over time. One of these scales, the Frailty Trait Scale (FTS), was recently validated.5 Its approach is based on the premise that the pathway to frailty is a continuous, unstable, and reversible process similar to a biological trait that is reached over time and that could be defined as the “trait of frailty.” The scale measures the load of frailty across the frailty trait including 7 dimensions. Since its publication, the scale has shown good ability to stratify the risk for adverse events in the general population of individuals aged 65 years5 and in diabetics,6 as well as good sensitivity to stratify cognitive performance7,8 or sedentary lifestyle.9,10 However, it is a time-consuming scale, making it difficult to be widely used in clinical settings. The aim of our study is, starting from the full FTS developed in the Toledo Study for Healthy Aging (TSHA),5 to build a short, objective, and valuable instrument that can be used to assess frailty in clinical settings in daily practice. Methods Design We used data from the TSHA obtained in the first (2006-2009) and second waves (2011-2013). This is a population-based, prospective, cohort study created to evaluate the characteristics and consequences of frailty in individuals aged 65 years living in the province of Toledo (Spain), which is described elsewhere.11 Basically, the study is carried out in different phases: first, there was an interview in the participant’s home and, second, a nurse carried out a physical battery task and obtained blood and urine samples. Participants A total of 1972 individuals participated in both phases, and 1755 participants, 985 women and 770 men, completed all of the physical performance tests and were included in the analysis. The study obtained approval from the local ethics committee, and the participants signed a written informed consent. Frailty Measures Three frailty measurements were used in the Frailty Trait ScaleeShort Form (FTSSF) validation process. Because there is no gold standard to measure frailty, we used the Fried criteria12 as a reference,
because it is a successful phenotype that has become a surrogate standard in frailty. The Frailty Index was also used13 as a frailty outcome, because it is a phenotype with a substantially different approach to the measurement of frailty compared with Fried criteria and FTS. Finally, we used the FTS as the phenotype of interest for this project. The description and process of creation of the 3 constructs of frailty are described elsewhere.5 In brief, the FTS evaluates 7 domains (energy balance and nutrition, activity, nervous system, vascular system, weakness, endurance, and slowness). These domains become operational through 12 items (Table 1). Each item score represents a biological trait and ranges from 0 (the best) to 4 or 5 (the worst). The final score is obtained by adding the scores from each of the items and dividing it by the maximum score possible. The measurement was standardized to obtain a range between 0 and 100. Those participants with a score of 50 or higher were considered frail. The FTS short forms (5- and 3-item) were constructed with the items that better optimized its predictive ability. Likewise, to keep a range for the scale that would give a high evaluative capacity, we set a range from 0 to 10 for each item (Tables 1 and 2). The Frailty Index of TSHA5 was built following the methodology proposed by Searle et al,13 by developing a scale of 40 items with scores of 0 and 1. To be considered frail, the 90th centile was used so that the prevalence of frailty in both constructs (ie, Fried criteria and Frailty index) could be balanced. At last, as a standard measurement of frailty, the Fried criteria was chosen using the methodology accepted internationally and cutoffs adopted for our population.12 Fried criteria include weakness, low energy, slowness, low physical activity, and weight loss. Each factor was given a point, so participants with a score of 0 were considered robust, 1 or 2 points were prefrail, and 3 to 5 points were frail. Outcomes Mortality We obtained the date of death from the National Death Index (Ministry of Health, Consumer Affairs, and Social Welfare), hospital registry, and phone contact during the study follow-up. Hospitalization We obtained hospitalization data from the Toledo Hospital Complex, which is the study population’s referral hospital. Incident disability We evaluated the incident disability for basic activities of daily living using the Katz index14 in 2 ways: (1) new disability, which includes those participants who have developed new disability for basic activities of daily living between the first and second waves of the study; and (2) functional decline from their basic activities of daily living baseline, expressed by a worsening in 1 or more points of the Katz index. Incident frailty Development of new frailty was measured according to the Fried criteria and the Frailty Index, using cutoffs described before. Statistical Analysis The item reduction and scoring were done in 1 phase, with an algorithm that maximizes the AUC sum of the logistic models for each outcome. The models were adjusted for age, sex, and comorbidity (Charlson index),15 and the score for the variable that is created during the process of reduction until that moment. In each step, the item was scored such that, for an item with a standardized scoring algorithm (Romberg progressive), its score was rescaled so that the score ranged from 0 to 10. For the rest, an optimization algorithm identified a basal risk level and step size obtaining 10 equally spaced points above and/
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3
Table 1 Domain and Item Composition in FTS Forms Domain
Item
Criteria FTS-12
FTS-5
FTS-3
Energetic balance or nutrition
Body mass index Weight loss (4.5 kg) Abdominal obesity (waist perimeter) Albumin serum levels (mg/dL) PASE (total score) Verbal fluency (no. of animals in 60 s) Progressive Romberg test Brachial ankle index Grip strength (kg)* Knee extension strength (kg) Chair test (times standing up in 30 s) Walking speed (usual pace in 3 m)y
x x x x x (quintiles) x x x x (quintiles) x x x (quintiles)
x (new scoring)
x (new scoring)
x (new scoring)
x (new scoring)
x
x
Activity Nervous system Vascular system Strength Endurance Gait speed
x (new scoring)
x (new scoring)
PASE, Physical Activity Scale for the Elderly. *Jamar dynamometer. y Rolling start.
or under the basal risk according to linear increasing or decreasing risk (gait speed, handgrip, physical activity), or U-shaped risk [body mass index (BMI)]. In each step, using the scoring method described previously for each item, the FTSSF score was computed with all the included items and the candidate item, and the AUC was estimated for the full models. The step size that maximized the sum of the AUC was selected as the best way to introduce it within the FTSSF score. The candidate item that maximized the AUC sum was included in the FTSSF. The optimal cutoffs for each FTSSF were identified for evaluating their prognostic performance with the AUC for each outcome (death, hospitalization, disability, and frailty) using a regression logistic model. Those cutoffs that best optimized the diagnostic classification were selected. In the second phase, the prognostic performance of each short form was compared with the Fried Phenotype using Cox multivariate regression models (outcome time dependent) and logistic models (dichotomous dependent variable). All the analyses were done with R, version 3.3.2 for Windows,16 and statistical significance was set at P < .05. Results A total of 1735 participants met the inclusion criteria, but 101 were lost to follow-up, so 1634 were included in the analysis (721 men and 913 women). The participants’ mean age was 74.7 years. They were followed for an average of 5.59 years for mortality, 3.27 years for hospitalization, and 4.98 years for frailty and disability. The incidence
rates for mortality, hospitalization, disability, and frailty were 16.77%, 21.05%, 25.25%, and 9.06%, respectively. In general, higher comorbidity, worse physical performance, and higher adverse event rates could be observed in participants who are frail according to the scales used for evaluation.
Item Reduction, Scoring, and Cutoff Selection The items that best optimized the prediction ability were the BMI, progressive Romberg, physical activity measured with the Physical Activity Scale for the Elderly (PASE), usual walking speed, and hand grip strength. Two scales of 5 and 3 items, respectively, were built. The scoring criteria for the 5 best items are included in Table 2. In Table 3, the areas under the curves (AUCs) from the basal model (age, sex, and Charlson index) and the added models from the 5 items that were selected are shown. The complete 5-item model (range 0-50) was the one with the highest AUC in each health event, and in the aggregate of possibilities regarding the Fried Phenotype (FP) and Frailty Index (FI) models. It also had a better diagnostic performance than the 12-item FTS, but the differences were not statistically significant. To avoid some of the problems in standardizing the performance task (gait speed and hand grip), a 3-item model including only BMI, physical activity, and progressive Romberg (range 0-30) was selected. In Table 4, the sensitivity and specificity for the Short Forms (FTS5 and FTS3, respectively) are shown. The cutoffs that maximized the prognostic information were >25 for FTS5 and >15 for FTS3.
Table 2 FTS Short Forms Scoring Table Score
0 1 2 3 4 5 6 7 8 9 10
BMI, kg/m2
23.01-26.99 27-28.99 29-30.99 31-32.99 33-34.99 35-36.99 37-38.99 39-40.99 41-42.99 43-44.99 45
PASE
21.01-23 19.01-21 17.01-19 15.01-17 13.01-15y 11.01-13y NA NA NA NA
>194 174.61-194 155.21-174.6 135.81-155.2 116.41-135.8 97.01-116.4 77.61-97 58.21-77.6 38.81-58.2 19.41-38.8 0-19.4
Gait Speed, s*
<2.45 2.45-2.99 3.00-3.54 3.55-4.09 4.10-4.64 4.65-5.19 5.20-5.74 5.75-6.29 6.30-6.84 6.85-7.39 7.4
Grip Strength, kg
Score
Women
Men
>22 19.81-22 17.61-19.8 15.41-17.6 13.21-15.4 11.01-13.2 8.81-11.0 6.61-8.8 4.41-6.6 2.21-4.4 0-2.2
>29 26.11-29 23.21-26.1 20.31-23.2 17.41-20.3 14.51-17.4 11.61-14.5 8.71-11.6 5.81-8.7 2.91-5.8 0-2.9
0 2.5 5 7.5 10
Progressive Romberg Position
Seconds
Tandem Tandem Tandem Semitandem Semitandem Side by side Side by side
10 3.01-9.99 3 10 <10 10 <10
PASE, Physical Activity Scale for the Elderly. FTS5 includes all the items of the table (range 0-50), and frail participants are those with FTS5 scores >25. FTS3 includes BMI, PASE, and Romberg test (range 0-30), and frail participants are those with FTS3 scores >15. *Gait speed refers to time in accomplish 3-metres at usual pace. y Model estimation.
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Table 3 Area Under the Curve for Different Outcomes According to Frailty Models Model
Death
Hospitalization
Incident Disability
Incident Frailty (FP)
Incident Frailty (FI)
Sum of Probabilities
Basic B BþP FTS3: BþPþBMI BþPþBMIþG FTS5: BþPþBMIþGþGS Fried Phenotype FTS12 Frailty Index
0.7803 0.7964 0.8062 0.8070 0.8124 0.8130 0.8002 0.8122 0.8094
0.6133 0.6383 0.6410 0.6415 0.6445 0.6509 0.6223 0.6378 0.6352
0.7001 0.7138 0.7185 0.7300 0.7353 0.7332 0.7065 0.7317 0.7261
0.7511 0.7852 0.8012 0.8102 0.8205 0.8175 0.7779 0.8171 0.8195
0.7712 0.8111 0.8354 0.8332 0.8498 0.8504 0.8145 0.8431 0.8380
3.6160 3.7449 3.8023 3.8220 3.8626 3.8650 3.7214 3.8419 3.8282
B, balance; G, grip strength; GS, gait speed; P, Physical Activity Scale for the Elderly. Basic model: age, sex, Charlson Index.
Prognostic Performance of the FTS Short Forms Table 5 shows the OR adjusted for each model for every health event. The prognostic performance for each short form was contrasted with a well-established frailty phenotype, and every participant was classified in terms of frailty according to the FTS5 and FTS3 in each of the frailty stratum, taking into account the Fried criteria (robust, prefrail, and frail). The frailty prevalence, according to the FTS and its short forms (FTS5 and FTS3), reached 28%, 24%, and 20%, respectively, whereas frailty according to the FP reached 8% and prefrailty, 41% (Table 5). In the different forms of the FTS, frail participants had a high risk for mortality (OR: 2.6-3.6) and disability (OR: 1.89-2.1), a very high risk for frailty (OR: 4.5-6.3, except FTS3, OR: 2.6-2.8), and a low to moderate risk for hospitalization (OR: 1.37-1.8). On the other hand, frail individuals in the Fried Phenotype comprised a very high-risk group for mortality (OR: 4.6), disability (OR: 4.0), and frailty (OR: 6.5), and had no relevant risk for hospitalization, whereas prefrail individuals were identified as participants with a high risk for mortality (OR: 2.1) and frailty (OR: 2.7-3.1), a mild risk for hospitalization (OR: 1.4), and no significant relevant risk for disability (OR: 1.2). Table 5 shows the FTS short forms’ (FTS5, FTS3) prognostic performance in each of the Fried Phenotype strata. The FTS5 discriminated 4.6% of robust according to FP with high risk for disability (OR: 2.3) and frailty (ORFried: 3.9). On the contrary, in those frail participants according to FP, the FTS5 identified 8.7% with low risk in every outcome. The behavior in prefrail FP participants is even more interesting, with the FTS5 stratifying them in 2 big groups. The first group (FPprefrail-FTS5 frail) was composed of 35% of the participants with a very high risk for mortality (OR: 4.0) and frailty (OR: 6.6-8.7), a high risk for hospitalization (OR: 2.1), and a moderate risk for disability (OR: 1.7). The second group comprised 65% (FPprefrail-FTS5 nonfrail) of the participants, with a basal risk for hospitalization and disability, a mild or basal risk for mortality (OR: 1.5; NS), and a high risk for frailty according to the Frailty Index (ORFI: 2.1) and nonexistent or mild according to FP (ORFP: 1.6; NS). Finally, the FTS3 had a similar behavior as the FTS5, but its ability to discriminate participants with high or low risk in each of the Fried Phenotype strata was much lower. In fact, it classified as nonfrail 31% of the participants identified as frail according to FP, although they present a high risk for mortality (OR: 2.3), a high or very high risk for disability (OR: 2.8-4), and a very high risk for frailty (ORFI: 4.0). Discussion The aim of this study was to simplify the FTS for its use in screening and monitor frailty in a clinical setting. To do so, the FTS, which is a scale that shares the Fried and Walston’s approach12 to evaluate frailty, was simplified and reduced, and it proved to be very useful in identifying individuals at risk for health adverse events6e12 in a
population research setting. Two FTS Short forms were identified, and the best prognostic performance was obtained with the 5-item scale (FTS5) that evaluates core aspects of frailty, such as BMI, energy expenditure, and the state of the neuromuscular interface (balance, gait speed, and hand grip). The FTS5 performance is less demanding for frailty than Fried Phenotype but more inclusive, identifying 24% of participants with high risk for mortality, hospitalization, disability, and progression to frailty (according to other phenotypes), and is susceptible to intervention, therefore, helping medical practitioners and health providers in decision making. The 3 forms of FTS showed similar prognostic performance, just like Frailty Index and Fried Phenotype, so all of them can be used in clinical settings. However, choosing which one to use will depend on the time available to run them, the presence or not of the instrument for measurement, and the sensitivity to change, among others factors. Interestingly, although the FTS-12 and FI incorporate biological (albumin, vascular state evaluation, etc), functional, and clinical variables, they did not have higher AUC in comparison with the short versions (FTS5 and FTS3) and Fried Phenotype. So, some of those items may be redundant. We know that in clinical practice it is important to classify patients according to their risk for adverse health events with the lowest cost possible. However, among all the studied scales, this is only achieved with the short forms of the FTS (mainly the FTS5) and the Fried Phenotype. In our opinion, the FTS5 presents a better profile for its use because the (1) FTS5 provides an opportunity for tracking trajectories inside each category (frail or nonfrail) and between categories, supporting the fact that frailty is not a “categorical” issue but a continuous, discrete one; (2) FTS5 has a range from 0 to 25 that evaluates the path from robust to frailty and from 26 (frail) to 50 who are extremely frail; and (3) the FTS5 identifies a cutoff above which participants (24% of the sample) have a higher risk for adverse health events and is able to classify the risk of the people with a high accuracy. In contrast, the Fried model identifies a group that is at a very high risk (ie, frail; 8%) for adverse health events and another one of intermediate risk (ie, prefrail; 41% of the sample), the latter being a heterogeneous group (Table 5). The frail phenotype in the FTS5 included 124 from the 137 classified as frail according to Fried criteria, 238 of the 677 prefrail that are considered high risk, and 37 of 797 robust of Fried with high levels of disability and frailty (Table 5). Thus, its prognostic performance compared to a standard of frailty such as the Fried Phenotype is better to stratify the risk, identifying 8% of frail and 4.5% of robust who were false positives and false negatives, respectively. Yet, the main FTS5 performance was found to be with prefrail participants, according to Fried criteria, in which it identified a big group (65%) classified as robust with a risk that is almost negligible and the remaining group (35%) with very high risk, categorized as frail. So, the FTS5 included 35% of the prefrail with a high risk and the frail with a very high risk from the Fried model in a single group. In this way, the FTS5 clarified the group of interest for a determinate intervention to 24% of the
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5
Table 4 Sensitivity and Specificity of FTS5 and FTS3 by Different Cutoffs Cutoff Score
FTS5 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 FTS3 10 11 12 13 14 15 16 17 18 19 20
Death
Hospitalization
Disability
Frailty (FP)
Frailty (FI)
S
SP
S
SP
S
SP
S
SP
S
SP
0.885 0.881 0.857 0.817 0.794 0.738 0.714 0.690 0.663 0.619 0.563 0.508 0.468 0.440 0.385 0.313 0.238 0.194 0.155 0.131
0.315 0.377 0.424 0.470 0.517 0.557 0.589 0.636 0.688 0.733 0.768 0.813 0.846 0.878 0.900 0.925 0.938 0.956 0.966 0.975
0.834 0.795 0.756 0.709 0.670 0.634 0.604 0.551 0.493 0.443 0.380 0.319 0.271 0.235 0.199 0.147 0.122 0.091 0.075 0.061
0.317 0.375 0.420 0.465 0.509 0.553 0.584 0.625 0.670 0.714 0.744 0.788 0.818 0.848 0.873 0.899 0.921 0.940 0.954 0.964
0.825 0.767 0.733 0.692 0.644 0.623 0.575 0.524 0.462 0.397 0.346 0.284 0.229 0.185 0.144 0.106 0.089 0.065 0.048 0.031
0.405 0.478 0.528 0.579 0.628 0.673 0.703 0.754 0.797 0.829 0.860 0.902 0.926 0.949 0.959 0.974 0.983 0.992 0.994 0.994
0.912 0.882 0.853 0.814 0.765 0.745 0.735 0.716 0.676 0.608 0.539 0.441 0.363 0.265 0.216 0.127 0.088 0.088 0.049 0.029
0.363 0.436 0.487 0.544 0.593 0.638 0.675 0.731 0.785 0.823 0.854 0.898 0.922 0.941 0.953 0.963 0.970 0.985 0.990 0.992
0.943 0.935 0.935 0.902 0.854 0.821 0.789 0.780 0.732 0.642 0.553 0.463 0.390 0.309 0.252 0.163 0.146 0.138 0.098 0.073
0.366 0.438 0.490 0.542 0.590 0.634 0.670 0.724 0.777 0.814 0.841 0.883 0.909 0.935 0.950 0.961 0.973 0.987 0.992 0.993
0.881 0.837 0.802 0.726 0.659 0.567 0.433 0.353 0.270 0.194 0.135
0.346 0.425 0.493 0.564 0.643 0.728 0.802 0.859 0.902 0.929 0.950
0.809 0.751 0.693 0.604 0.504 0.388 0.291 0.233 0.166 0.130 0.097
0.345 0.423 0.487 0.555 0.625 0.703 0.783 0.844 0.888 0.921 0.947
0.812 0.719 0.654 0.545 0.449 0.339 0.267 0.171 0.123 0.075 0.055
0.434 0.520 0.593 0.658 0.724 0.805 0.871 0.914 0.947 0.959 0.977
0.912 0.843 0.794 0.755 0.667 0.510 0.392 0.255 0.196 0.137 0.098
0.393 0.479 0.555 0.635 0.714 0.795 0.861 0.906 0.937 0.956 0.970
0.951 0.894 0.862 0.780 0.650 0.520 0.423 0.285 0.220 0.154 0.114
0.395 0.484 0.559 0.636 0.712 0.796 0.865 0.904 0.936 0.954 0.972
S, sensitivity; SP, specificity.
population compared with the 49% of frail and prefrail participants identified by the Fried Phenotype. Accordingly, the FTS5 is less demanding but more inclusive, identifying 24% of the participants who were susceptible and at a high risk for mortality, hospitalization, and disability, for intervention and thus helping with clinical decisions. This fact, along with the wide range of evaluation of this scale (050) and the short time taken to perform the test (5 minutes), makes the FTS5 a very useful measurement in multiple scenarios: (1) Clinical Environment, for diagnosis and to monitor patients across a wide range; (2) Research Environment, for its ability to classify individuals and its sensitivity to change derived from its wide range; and (3) Public Health, simplifying the amount of patients who should receive treatment to a group at a high or very high risk. Finally, because of its characteristics, FTS5 can be considered complementary to other very well-known and broadly used scales in clinical settings (eg, Clinical Frailty Scale). Likewise, it shows some advantages mainly in controlled clinical settings in which the goal is to monitor the trajectory of the frailty status in response to interventions or intercurrent diseases. The other scale (FTS3), which included 3 of the items (BMI, energy expenditure, and progressive Romberg) from the FTS5, is short but has a prognostic performance similar to the FTS5 (Table 3). However, this scale loses prognostic accuracy by excluding 2 items that are part of the core of frailty, since it classified 31% of frail participants as robust but with a high risk for adverse health events. The FTS and its short forms share with Fried and Walston’s Phenotype their approximation to the study and evaluation of frailty and includes almost all their items. Four criteria of the Fried Phenotype are included in the complete version of the FTS, sharing the same
problems of external validity, especially regarding its standardization with other cultures, races, and regions, of 2 criteria: gait speed and hand grip. Thus, there are substantial differences in regard to distribution, by income, race and population extraction, that could partially explain interregional differences in a given country17 and in between countries.18,19 Therefore, estimates of frailty prevalence can vary substantially if the cutoffs are not adjusted to a given population, as it happens in Spain.20 Even though the FTS5 results of this study are valid for the Spanish population, there should be some comments regarding its strength to extrapolate the results to other populations. On the one hand, there is the inclusive construct related to the risk levels; thus, the FTS5 score covers a range that reaches all the spectrum of risk in each domain in physical activity (PASE: 194-0), gait speed (1.2-0.4 m/s) (20), BMI (complete range), and peripheral Romberg (complete range) (Table 2), minimizing the effects of different cutoffs for each population. Furthermore, special mention should be made with the hand grip behavior in our sample, with a range starting from 22 kg in women and 29 kg in men. Both points represent a threshold risk from which it increases and initiates the score, which correspond to centiles 84 and 54 in women and men, respectively. It is known that the differences in hand grip between regions are important, being higher in North Europe and North America than in Asia, Africa, or South America.21 Likewise, there are substantial interregional differences, so hand grip is stronger in North Europe than in Mediterranean populations.18 Although these data are real, when strength is assessed in respect to adverse health events the differences between populations decrease substantially. Thus, even though the German population (as an average) is much more robust than the Spanish one, the threshold from which the mortality risk is increased is similar in women
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Table 5 OR of Relevant Outcomes According to FTS Forms, Fried Phenotype, and Fried Phenotype Status by FTS5 and FTS3 Mortality n (e) Fried Phenotype Robust 797 (54) Prefrail 677 (124) Frail 137 (59) FTS No frail 1154 (100) Frail 457 (137) FTS5 No frail 1211 (108) Frail 400 (129) FTS3 No frail 1288 (136) Frail 323 (101) Fried Phenotype status by FTS5 Robust FTS5, No frail 760 (50) FTS5, Frail 37 (4) Prefrail FTS5, No frail 439 (56) FTS5, Frail 238 (68) Frail 12 (2) FTS5, No frail FTS5, Frail 125 (57) Fried Phenotype status by FTS3 Robust FTS3, No frail 736 (48)
Hospitalization OR
n (e)
First Disability
Worsening Disability
Incident Frailty (FP)
Incident Frailty (FI)
OR
n (e)
OR
n (e)
OR
n (e)
OR
n (e)
OR
1 2.15* 4.65*
797 (134) 677 (171) 137 (39)
1 1.46y 1.4
633 (130) 420 (123) 32 (21)
1 1.22 3.97*
688 (147) 507 (158) 66 (39)
1 1.26 2.89*
626 (30) 445 (67) na
1 2.78* na
688 (30) 482 (77) 34 (12)
1 3.13* 6.52*
1 3.11*
1154 (214) 457 (130)
1 1.50y
878 (177) 207 (97)
1 2.12*
971 (206) 290 (138)
1 2.03*
874 (45) 197 (52)
1 5.17*
967 (51) 237 (68)
1 4.46*
1 3.61*
1211 (220) 400 (124)
1 1.83*
917 (193) 168 (81)
1 2.05*
1016 (225) 245 (119)
1 1.92*
915 (49) 156 (48)
1 6.34*
1008 (58) 196 (61)
1 4.46*
1 2.57*
1288 (252) 323 (92)
1 1.37z
946 (214) 139 (60)
1 1.93y
1060 (254) 201 (90)
1 1.88*
937 (70) 134 (27)
1 2.64*
1040 (80) 164 (39)
1 2.83*
1 1.34
760 (126) 37 (8)
1 1.36
609 (117) 24 (13)
1 2.63z
656 (130) 32 (17)
1 2.35z
598 (24) 28 (6)
1 3.93z
657 (25) 31 (5)
1 1.9
1.50x 4.04*
439 (93) 238 (78)
1.21 2.19*
301 (73) 119 (50)
1.13 1.74z
352 (92) 155 (66)
1.21 1.68z
317 (25) 128 (42)
1.62 8.72*
345 (33) 137 (44)
2.10y 6.64*
1.01 6.09*
12 (1) 125 (38)
0.31 1.70z
7 (3) 25 (18)
2.04 5.51*
8 (3) 58 (36)
1.59 3.49*
na na
na na
6 (0) 28 (12)
1
736 (120)
1
1
584 (25)
1
639 (23)
FTS3, Frail
61 (6)
1.31
Prefrail FTS3, No frail
509 (77)
1.85
y
FTS3, Frail
168 (47)
3.46*
Frail FTS3, No frail
43 (11)
2.36
FTS3, Frail
94 (48)
6.68*
z
594 (114)
61 (14)
1.49
509 (120)
1.41z y
1
639 (126)
11.3*
1
39 (16)
2.01x
49 (21)
2.13z
42 (5)
2.15
49 (7)
2.64z
332 (87)
1.15
393 (112)
1.24
353 (45)
2.50*
382 (52)
3.07*
92 (22)
5.40*
100 (25)
6.00*
4.01z
88 (36)
y
y
1.99
114 (46)
1.86
168 (51)
1.84
43 (12)
1.53
20 (13)
4.07y
28 (16)
2.89z
na
na
19 (5)
94 (27)
1.46
12 (8)
4.64z
38 (23)
3.38*
na
na
15 (7)
16.7*
e, number of events; na, not available. *P < .001; yP < .01; zP < .05; xP < .1.
(average in German women: 21 kg) and somewhat higher in men (average in German men: 32.9 kg).22 So, if needed, this problem could be overcome by adjusting the risk threshold adapted to each population if there are enough data to do so. Therefore, although we need studies to guarantee the prognostic value of FTS5, the inclusive construct of the scale minimizes the standardization issues for other populations present in the Fried and Walston Phenotype. Likewise, the wide range bases on a score that covers all, or almost all, of the path of each domain from robust to frail and ensures its sensitivity to change, which is needed to monitor patients in a clinical setting and provides a very useful measurement to assess the response to therapy. Finally, this study presents some weaknesses and strengths. The absence of interregional validation may be the main weakness for the FTS5. However, its construct, with a wide range of measurement in each dimension, minimizes any issue with external validity. On the other hand, although the FTS5 presents an optimal profile to be used in clinical practice, its performance still needs to be evaluated in this scenario. Some strengths could be highlighted: (1) the population source rules out bias in the diagnostic and prognostic accuracy parameters that are usually present in clinical samples and (2) its diagnostic performance has been tested against a wide range of outcomes (mortality, resources use, functional) and a frailty standard (Fried criteria).
Conclusions and Implications The FTS short forms, especially the FTS5, provide a frailty measurement that is valid, short, and helps identify individuals who are at high risk for frailty and is potentially useful in multiple settings (clinical, research, public health, etc). Its main advantages in comparison with the currently used tools inside the conceptual framework of the frailty phenotype can be summarized by its better classification of the risks for adverse events and the possibility of monitoring frailty trajectories. However, more interregional and validation studies are needed throughout the clinical spectrum to refine its diagnostic and prognostic value in scenarios different from community settings.
References 1. Rodriguez-Manas L, Fried LP. Frailty in the clinical scenario. Lancet 2015;385: e7ee9. 2. Dunning T, Sinclair A, Colagiuri S. New IDF guideline for managing type 2 diabetes in older people. Diabetes Res Clin Pract 2014;103:538e540. 3. Rodriguez-Artalejo F, Rodriguez-Manas L. The frailty syndrome in the public health agenda. J Epidemiol Community Health 2014;68:703e704. 4. Aguayo GA, Donneau AF, Vaillant MT, et al. Agreement between 35 published frailty scores in the general population. Am J Epidemiol 2017;186:420e434.
F.J. García-García et al. / JAMDA xxx (2020) 1e7 5. Garcia-Garcia FJ, Carcaillon L, Fernandez-Tresguerres J, et al. A new operational definition of frailty: The Frailty Trait Scale. J Am Med Dir Assoc 2014;15:371. e7-371.e13. 6. Castro-Rodriguez M, Carnicero JA, Garcia-Garcia FJ, et al. Frailty as a major factor in the increased risk of death and disability in older people with diabetes. J Am Med Dir Assoc 2016;17:949e955. 7. Rosado-Artalejo C, Carnicero JA, Losa-Reyna J, et al. Global performance of executive function is predictor of risk of frailty and disability in older adults. J Nutr Health Aging 2017;21:980e987. 8. Rosado-Artalejo C, Carnicero JA, Losa-Reyna J, et al. Cognitive performance across 3 frailty phenotypes: Toledo Study for Healthy Aging. J Appl Physiol (1985) 2017;18:785e790. 9. Del Pozo-Cruz B, Manas A, Martin-Garcia M, et al. Frailty is associated with objectively assessed sedentary behaviour patterns in older adults: Evidence from the Toledo Study for Healthy Aging (TSHA). PLoS One 2017;12:e0183911. 10. Manas A, Del Pozo-Cruz B, Guadalupe-Grau A, et al. Reallocating accelerometer-assessed sedentary time to light or moderate- to vigorousintensity physical activity reduces frailty levels in older adults: An isotemporal substitution approach in the TSHA study. J Am Med Dir Assoc 2018; 19:185.e1e185.e6. 11. Garcia-Garcia FJ, Gutierrez Avila G, Alfaro-Acha A, et al. The prevalence of frailty syndrome in an older population from Spain. The Toledo Study for Healthy Aging. J Nutr Health Aging 2011;15:852e856. 12. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: Evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56:M146eM156. 13. Searle SD, Mitnitski A, Gahbauer EA, et al. A standard procedure for creating a frailty index. BMC Geriatr 2008;8:24.
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14. Katz JN, Chang LC, Sangha O, et al. Can comorbidity be measured by questionnaire rather than medical record review? Med Care 1996;34: 73e84. 15. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis 1987;40:373e383. 16. R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2014. 17. Bandeen-Roche K, Seplaki CL, Huang J, et al. Frailty in older adults: A nationally representative profile in the United States. J Gerontol A Biol Sci Med Sci 2015; 70:1427e1434. 18. Andersen-Ranberg K, Petersen I, Frederiksen H, et al. Cross-national differences in grip strength among 50þ year-old Europeans: Results from the SHARE study. Eur J Ageing 2009;6:227e236. 19. Siriwardhana DD, Hardoon S, Rait G, et al. Prevalence of frailty and prefrailty among community-dwelling older adults in low-income and middle-income countries: A systematic review and meta-analysis. BMJ Open 2018;8: e018195. 20. Alonso Bouzon C, Carnicero JA, Turin JG, et al. The standardization of frailty phenotype criteria improves its predictive ability: The Toledo Study for Healthy Aging. J Am Med Dir Assoc 2017;18:402e408. 21. Dodds RM, Syddall HE, Cooper R, et al. Global variation in grip strength: A systematic review and meta-analysis of normative data. Age Ageing 2016;45: 209e216. 22. Steiber N. Strong or weak handgrip? Normative reference values for the German population across the life course stratified by sex, age, and body height. PLoS One 2016;11:e0163917.
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F.J. García-García et al. / JAMDA xxx (2020) 1e7
Supplementary Table 1 OR or HR of Relevant Outcomes for Older Adults According to FTS Forms and Fried Phenotype Mortality n (e) Fried phenotype Robust 797 (54) Prefrail 677 (124)
OR
Hospitalization
First Disability
Worsening Disability
Incident Frailty (FP)
Incident Frailty (FI)
n (e)
OR
n (e)
OR
n (e)
OR
n (e)
OR
n (e)
1 1.46y (1.12-1.90) 1.4 (0.89-2.21)
633 (130) 420 (123)
1 1.22 (0.90-1.66) 3.97* (1.79-8.84)
688 (147) 507 (158)
1 1.26 (0.95-1.67) 2.89* (1.65-5.06)
626 (30) 445 (67)
1 2.78* (1.74-4.44) na
688 (30) 482 (77)
1 2.15* (1.50-3.08) 4.65* (2.83-7.63)
797 (134) 677 (171)
32 (21)
66 (39)
na
34 (12)
1 3.13* (1.97-4.97) 6.52* (2.76-15.4)
Frail
137 (59)
FTS No frail Frail
1154 (100) 457 (137)
1 3.11* (2.22-4.37)
1154 (214) 457 (130)
1 1.50y (1.13-2.00)
878 (177) 207 (97)
1 2.12* (1.49-3.00)
971 (206) 290 (138)
1 2.03* (1.49-2.77)
874 (45) 197 (52)
1 5.17* (3.18-8.39)
967 (51) 237 (68)
1 4.46* (2.87-6.93)
FTS5 No frail Frail
1211 (108) 400 (129)
1 3.61* (2.54-5.12)
1211 (220) 400 (124)
1 1.83* (1.37-2.46)
917 (193) 168 (81)
1 2.05* (1.41-2.98)
1016 (225) 245 (119)
1 1.92* (1.38-2.65)
915 (49) 156 (48)
1 6.34* (3.81-10.57)
1008 (58) 196 (61)
1 4.46* (2.83-7.02)
FTS3 No frail Frail
1288 (136) 323 (101)
1 2.57* (1.84-3.58)
1288 (252) 323 (92)
1 1.37z (1.02-1.84)
946 (214) 139 (60)
1 1.93y (1.30-2.86)
1060 (254) 201 (90)
1 1.88* (1.34-2.62)
937 (70) 134 (27)
1 2.64* (1.57-4.44)
1040 (80) 164 (39)
1 2.83* (1.01-6.93)
e, number of events; na, not available. *P < .001; yP < .01; zP < .05.
137 (39)
OR
Supplementary Table 2 OR or HR of Relevant Outcomes for Older Adults According to Fried Phenotype Status by FTS5 Mortality
Robust FTS5, No frail FTS5, Frail Prefrail FTS5, No frail FTS5, Frail Frail FTS5, No frail FTS5, Frail
Hospitalization
First Disability
Worsening Disability
Incident Frailty (FP)
Incident Frailty (FI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
760 (50) 37 (4)
1 1.34 (0.42-4.24)
760 (126) 37 (8)
1 1.36 (0.59-3.12)
609 (117) 24 (13)
1 2.63*(1.08-6.42)
656 (130) 32 (17)
1 2.35* (1.08-5.11)
598 (24) 28 (6)
1 3.93* (1.29-11.9)
657 (25) 31 (5)
1
345 (33) 137 (44)
2.10z (1.21-3.66) 6.64x (3.74-11.8)
6 (0) 28 (12)
11.31x (4.53-28.2)
y
439 (56) 238 (68)
1.50 (0.98-2.28) 4.04x (2.57-6.36)
439 (93) 238 (78)
1.21 2.19x (0.89-1.64)
301 (73) 119 (50)
1.13 (0.80-1.60) 1.74* (1.11-2.74)
352 (92) 155 (66)
1.21 (0.88-1.66) 1.68*
317 (25) 128 (42)
1.62 (0.89-2.93) 8.72x (4.79-15.8)
12 (2) 125 (57)
1.01 (0.20-4.98) 6.09x (3.60-10.32)
12 (1) 12 (38)
0.31 (0.04-2.48) 1.70* (1.06-2.73)
7 (3) 25 (18)
2.04 (0.42-9.92) 5.51x (2.16-14.1)
8 (3) 58 (36)
1.59 (0.35-7.17) 3.49x (1.91-6.35)
na na
na na
1.9 (0.61-5.95)
e, number of events; na, not available. y P < .1; *P < .05; zP < .01; xP < .001.
Mortality
Fried Phenotype Status by FTS3 Robust FTS3, No frail FTS3, Frail Prefrail FTS3, No frail FTS3, Frail Frail FTS3, No frail FTS3, Frail
Hospitalization
First Disability
Worsening Disability
Incident Frailty (FP)
Incident Frailty (FI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
n (e)
OR (95% CI)
736 (48) 61 (6)
1 1.31 (0.51-3.34)
736 (120) 61 (14)
1 1.49 (0.78-2.82)
594 (114) 39 (16)
1 2.01* (0.98-4.12)
639 (126) 49 (21)
1 2.13y (1.13-4.03)
584 (25) 42 (5)
1 2.15 (0.72-6.38)
639 (23) 49 (7)
1
509 (77) 168 (47)
1.85z (1.24-2.76) 3.46x (2.14-5.59)
509 (120) 168 (51)
1.41y (1.06-1.89) 1.84z (1.24-2.75)
332 (87) 88 (36)
1.15 (0.82-1.61) 1.99z (1.21-3.29)
393 (112) 114 (46)
1.24 (0.91-1.69) 1.86z (1.19-2.92)
353 (45) 92 (22)
2.50x (1.48-4.25) 5.40x (2.80-10.4)
382 (52) 100 (25)
3.07x (1.81-5.22) 6.00x (3.12-11.5)
43 (11) 94 (48)
2.36y (1.05-5.28) 6.68x (3.79-11.7)
43 (12) 94 (27)
1.53 (0.75-3.13) 1.46 (0.86-2.49)
20 (13) 12 (8)
4.07z (1.51-11.0) 4.64y (1.29-16.7)
28 (16) 38 (23)
2.89y (1.28-6.53) 3.38x (1.64-6.95)
na na
na na
19 (5) 15 (7)
4.01y (1.23-13.0) 16.71x (5.07-55.0)
F.J. García-García et al. / JAMDA xxx (2020) 1e7
Supplementary Table 3 OR of Relevant Outcomes for Older Adults According to Fried Phenotype Status by FTS3
2.64y (1.01-6.93)
e, number of events; na, not available. *P < .1; yP < .05; zP < .01; xP < .001.
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