Relationship between Frailty Assessed Using the Kihon Checklist and Rheumatoid Arthritis

ABSTRACT

Objectives: This study investigated the relationship between frailty as assessed using the Kihon checklist (KCL) and rheumatoid arthritis (RA) status.

Methods: In total, 626 consecutive patients with RA were enrolled in this cross-sectional study. We examined the patients’ KCL scores, characteristics, and clinical data. The patients were grouped according to their KCL scores as follows: robust (scores of 0–3), pre-frailty (scores of 4–7), and frailty (scores ≥8).

Results: Frailty, pre-frailty, and robust groups accounted for 36.9%, 30.5%, and 32.6% of the patients, respectively. Significant factors comparing frailty and robust groups were age (P < 0.001), Health Assessment Questionnaire Disability Index (HAQ-DI) (P < 0.001), and habitual exercise (P = 0.004). Significant factors comparing the pre-frailty and robust groups were age (P < 0.001) and HAQ-DI (P = 0.041).

Conclusions: In patients with RA, HAQ-DI and exercise should be managed to prevent frailty and avoid the need for long-term care. Our results will help identify those patients who can most benefit from aggressive management of RA.

INTRODUCTION

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that leads to joint destruction and impairment of physical function.¹⁾ Patients with RA have shown an increased Health Assessment Questionnaire Disability Index (HAQ-DI), an assessment of physical function, over recent decades and are at high risk of developing frailty, sarcopenia, and locomotive syndrome.^{2,3,4,5,6,7,8)}

The Kihon checklist (KCL) was developed by the Ministry of Health, Labour, and Welfare of Japan as a tool to identify individuals who are at risk of needing long-term care in the near future. The KCL consists of questions designed to assess the instrumental and social activities of daily living, physical functions, nutritional status, oral function, cognitive function, and depressive mood.⁹⁾ Frailty encompasses aspects such as strength, balance, nutrition, endurance, mobility, physical activity, and cognitive function; the relationship between the KCL score and frailty has been reported and established in various contexts.^{10,11,12,13,14)}

With improved life expectancy and aging in patients with RA, it is important to understand the relationship between frailty and RA status.^15,16,17,18) This study aimed to investigate the relationship between frailty and RA status.

MATERIALS AND METHODS

Patients

A total of 626 consecutive patients with RA were included in this cross-sectional study. The assessment included frailty using the KCL and the following clinical characteristics: age; sex; body mass index (BMI); duration of rheumatoid status; anti-cyclic citrullinated peptide antibody positivity; use of drugs such as biological disease-modifying antirheumatic drugs (bDMARDs), targeted synthetic DMARDs (tsDMARDs), methotrexate (MTX), and glucocorticoids (GC) for RA treatment; rheumatoid factor (RF) titer; levels of C-reactive protein (CRP) and Krebs von den Lungen-6 (KL-6); Visual Analog Scale (VAS) score; Clinical Disease Activity Index (CDAI); Health Assessment Questionnaire Disability Index (HAQ-DI); habitual exercise; and T-scores in the lumbar spine (L1-L4), total hip, and femoral neck. Exercise habits were defined as performance at least twice a week for 30 min or more.¹⁹⁾ The T-scores were measured using dual-energy X-ray absorptiometry (PROGIDY system; GE Healthcare, Madison, WI, USA).

This study was conducted in accordance with the principles stated in the Declaration of Helsinki and written informed consent was obtained from all patients. The Ethics Committee for Clinical Research of Kamagaya General Hospital approved this study (approval number: TGE00652-064).

Frailty Assessment

The KCL (Kihon checklist) comprises 25 items divided into seven categories: Activities of Daily Living (5 items), Physical Function (5 items), Nutritional Status (3 items), Oral Function (3 items), House Boundedness (2 items), Cognitive Function (3 items), and Depressive Mood (3 items). Each item is scored either 0 or 1, resulting in a total score ranging from 0 to 25.⁹⁾ Patients were divided into three categories according to their KCL scores: 0–3, robust (R); 4–7, pre-frail (PF); 8 or higher, frail (F).⁹⁾

Statistical Analysis

Statistical analysis was performed by comparing groups using analysis of variance. To identify the factors associated with frailty and pre-frailty, the characteristics and clinical data of the two groups (F vs. R group, PF vs. R group, and F vs. PF group) were compared using the Wilcoxon rank-sum test and Fisher’s exact test (as appropriate). Significant variables in the univariate analysis were evaluated using multiple regression analysis. The correlation between the KCL scores (total and the seven sections) and patient background was identified using Spearman’s rank correlation analysis. Statistical significance was set at P < 0.05. All analyses were performed using the R Statistical Package, version 3.3.2 (http://www.r-project.org/).

RESULTS

The F, PF, and R groups made up 36.9%, 30.5%, and 32.6% of the patients, respectively. The following prevalences of frailty according to age were observed: 64 years or younger, 18.4% (38/207); 65–69 years, 33.7% (28/83);70–74 years, 29.2% (33/113);75–79 years, 47.6% (50/105);80–84 years, 64.7% (55/85); 85 years or older, 81.8% (27/33) (Fig. 1).

Fig. 1.

Prevalences of frailty by age in this study. N, total number of participants in the respective age groups.

Table 1 shows the characteristics and clinical data of all the patients in the F, PF, and R groups. The variables that showed significant differences among the three groups were age; duration of RA; b-DMARD or tsDMARD, MTX, or GC use; RF titer; CRP level; KL-6 level; VAS score; CDAI; HAQ-DI; and T-scores for the total hip and femoral neck.

Table 1. Patient characteristics and clinical data

Characteristic	All (n=626)	Frailty (n=231)	Pre-frailty (n=191)	Robust (n=204)	P value
Age, years	67.9 ± 13.1	74.0 ± 11.2	67.9 ± 11.4	60.9 ± 13.3	<0.001
Female	512 (81.8)	195 (84.4)	155 (81.2)	162 (79.4)	0.367
Body mass index	22.5 ± 4.0	22.1 ± 3.9	22.8 ± 4.2	22.6 ± 3.9	0.195
Duration of RA, years	14.0 ± 10.8	15.9 ± 11.8	14.3 ± 11.2	11.5 ± 8.5	<0.001
Anti-CCP Ab positive	486 (77.6)	188 (81.4)	146 (76.4)	152 (74.5)	0.200
b or tsDMARDs use	355 (56.7)	150 (64.9)	109 (57.1)	96 (47.1)	<0.001
MTX use	404 (64.5)	127 (55.0)	129 (67.5)	148 (72.5)	<0.001
Glucocorticoid use	107 (17.1)	51 (22.1)	29 (15.2)	27 (13.2)	0.039
RF titer, IU/mL	143.6 ± 419.1	192.8 ± 623.4	113.8 ± 196.9	115.8 ± 244.7	0.008
CRP, mg/dL	0.4 ± 0.9	0.6 ± 1.3	0.3 ± 0.6	0.3 ± 0.6	<0.001
KL-6, U/mL	280.1 ± 158.0	299.7 ± 165.6	279.6 ± 146.0	258.5 ± 157.8	0.025
Pain VAS	27.5 ± 26.5	38.4 ± 28.4	23.9 ± 24.0	18.4 ± 21.9	<0.001
CDAI	4.8 ± 4.7	6.4 ± 4.7	4.4 ± 4.7	3.3 ± 4.2	<0.001
HAQ-DI	0.4 ± 0.7	0.9 ± 0.9	0.2 ± 0.3	0.1 ± 0.3	<0.001
Habitual exercise	282 (45.0)	86 (37.2)	89 (46.6)	107 (52.5)	0.002
T-score in lumbar spine	−0.6 ± 1.5	−0.6 ± 1.6	−0.6 ± 1.5	−0.5 ± 1.4	0.395
T-score in total hip	−1.7 ± 1.1	−2.0 ± 1.2	−1.7 ± 1.0	−1.4 ± 1.1	<0.001
T-score in femoral neck	−1.4 ± 1.0	−1.7 ± 1.0	−1.3 ± 0.9	−1.1 ± 1.0	<0.001

Data given as mean ± standard deviation or number (percentage).

Significant factors comparing the F and R groups were age; duration of RA; b-DMARD or tsDMARD, MTX, or GC use; CRP level; KL-6 level; VAS score; CDAI; HAQ-DI; and T-score for the total hip and femoral neck. The multivariate analysis identified age (P < 0.001), HAQ-DI (P < 0.001), and habitual exercise (P = 0.004) to be significant factors (Table 2). Significant factors comparing the PF and R groups were age, duration of rheumatoid activity, VAS score, CDAI, HAQ-DI, and T-score for the total hip and femoral neck. The multivariate analysis identified age (P < 0.001) and HAQ-DI (P = 0.041) to be significant factors (Table 2). Significant factors comparing the F and PF groups were age, MTX use, CRP level, VAS score, CDAI, HAQ-DI, and T-scores for the total hip and femoral neck. Multivariate analysis identified age (P < 0.001), VAS score (P = 0.017), and HAQ-DI (P < 0.001) as significant factors (Table 2).

Table 2. Significant factors compared between frail, pre-frail, and robust groups using multivariate analysis

Comparison	P value	Odds ratio (95% CI)
F group vs. R group
Age	<0.001	1.083 (1.053–1.113)
HAQ-DI	<0.001	18.000 (6.780–47.787)
Habitual exercise	0.004	0.431 (0.241–0.770)
PF group vs. R group
Age	<0.001	1.038 (1.018–1.059)
HAQ-DI	0.041	2.508 (1.037–6.068)
F group vs. PF group
Age	0.001	0.963 (0.941–0.985)
Pain VAS	0.015	0.981 (0.966–0.997)
HAQ-DI	<0.001	0.170 (0.096–0.302)

Table 3 shows the correlation coefficients between the KCL scores (total and seven sections) and patient background. HAQ-DI showed the strongest correlations with the total KCL score and the KCL sections of activities of daily living, physical functions, house boundedness, and depressive mood. BMI showed the strongest correlation with nutritional status. Age showed the strongest correlations with oral function and cognitive function.

Table 3. Correlation between the Kihon checklist score (total and seven sections) and patient background

Parameter	Total	ADL	PF	NS	OF	HB	CF	DM
Age	0.402**	0.252**	0.406**	0.014	0.247**	0.297**	0.218**	0.227**
Body mass index	−0.036	−0.038	0.071	−0.219**	−0.004	−0.043	−0.020	−0.031
Duration of RA	0.164**	0.147**	0.191**	0.026	0.100*	0.091*	0.069	0.048
RF titer	0.067	0.128**	0.078	0.073	−0.021	0.023	−0.015	0.003
CRP	0.163**	0.117**	0.168**	0.094*	0.044	0.106**	0.060	0.100*
Pain VAS	0.327**	0.214**	0.282**	0.108**	0.152**	0.137**	0.084*	0.309**
CDAI	0.272**	0.173**	0.256**	0.059	0.132**	0.110**	0.078	0.248**
HAQ-DI	0.579**	0.546**	0.579**	0.097*	0.207**	0.344**	0.180**	0.336**
T-score in lumbar spine	−0.048	−0.030	−0.016	−0.028	0.008	−0.057	−0.071	−0.038
T-score in total hip	−0.252**	−0.211**	−0.245**	−0.052	−0.069	−0.195	−0.105**	−0.152**
T-score in femoral neck	−0.278**	−0.268**	−0.260**	−0.076	−0.074	−0.218	−0.096*	−0.152**

ADL, activities of daily living; PF, physical functions; NS, nutritional status; OF, oral function; HB, house boundedness; CF, cognitive function; DM, depressive mood.

^* P < 0.05; ^** P < 0.01.

DISCUSSION

In this study, we investigated the association between frailty and RA. Patients with RA and frailty tended to be older, have greater functional disability, and not undertake regular exercise. Similarly, patients with RA and pre-frailty tended to be older and have greater functional disabilities. Age, HAQ-DI, and VAS scores were significantly different between patients with RA and frailty and those with RA and pre-frailty.

The prevalences of frailty and pre-frailty in this study were 36.9% and 30.5%, respectively. Recently, there have been reports evaluating frailty in Japanese patients with RA using KCL, including this study.^20,21,22) Therefore, descriptive statistics are possible using KCL-based frailty assessment. The relationship between RA and frailty has been identified through reports on prevalence rates and related factors. In previous studies, the prevalences of frailty and pre-frailty in patients with RA were 18.9%–39.6% and 33.6%–34.9%, respectively.^4,5,14) In the general older population (frailty 17.2% and pre-frailty 29.3%), hazard ratios of long-term care insurance within 3 years in subjects with frailty and pre-frailty were 4.77 [95% confidence interval (CI): 3.73–6.09] and 2.03 (95% CI: 1.58–2.61), respectively.¹²⁾ We believe that patients with RA have high risk of requiring a long-term care in the future. To avoid long-term care for patients with RA, factors associated with frailty must be improved.

In previous reports, the factors associated with frailty were age, disease duration, RA disease activity, physical function, pain, depression, cognitive functional impairment, and oral function.^{3,5,21,22,23,24)} Based on our results, factors associated with frailty were age, physical function, and exercise habits. Frailty is an aging state characterized by a reduced ability to recover from stress, resulting in increased vulnerability to disease.²⁵⁾ In a systematic review and meta-analysis of frailty in the general Japanese population,²⁶⁾ the following age-related prevalences of frailty were reported: 65–69 years, 1.9% (95% CI, 0.9–3.3); 70–74 years, 3.8% (95% CI, 2.3–5.7); 75–79 years, 10.0% (95% CI, 6.6–14.2); 80–84 years, 20.4% (95% CI, 18.2–22.6); 85 years or older, 35.1% (95% CI, 30.6–39.8). Although the prevalence of frailty increases with age in the general population, based on our results, it is more pronounced in patients with RA. Maintaining physical function is important because 10 points of the KCL score are assessed with activities of daily living and physical functions. We believe that engaging in exercise to maintain a low HAQ-DI may prevent frailty.

Physical activity helps to decrease oxidative stress and inflammation, while promoting autophagy, the release of myokines, and the production of insulin-like growth factor-1. These actions can improve muscle mass, strength, and function.²⁷⁾ Previous studies have shown that exercises including aerobic, resistance, balance, and mobility training are effective in reversing frailty to pre-frailty, preventing frailty, and improving physical performance in community-dwelling older adults.^28,29) Similarly, in frail older adults, multicomponent aerobic training and resistance training or home-based low-level exercise could improve physical function, according to a systematic review.³⁰⁾ Based on our results, exercise habits are recommended for patients with RA.

The HAQ-DI and VAS scores were correlated with the total and seven sections of the KCL score. The HAQ-DI showed the highest correlation with total scores, activities of daily living, physical functions, house boundedness, and depressive mood in this study. In previous studies, the HAQ-DI had a high correlation coefficient (0.58 to 0.619) with the total KCL score.^5,14) Improvements in the HAQ-DI are expected to improve many sections. Pain assessed using the VAS score is a factor that can determine the relationship between frailty and pre-frailty. In particular, improvements in pain (the VAS scores) were expected to improve the total and depressive mood in the KCL score. In the nutritional status section, BMI showed the strongest correlation. Moreover, like the results of this study, the Mini Nutritional Assessment score correlated with the HAQ-DI in previous studies.^31,32) Patients with RA are more likely to have a low BMI than the general population.³³⁾ Nutrition, not to mention frailty, is an important factor in BMI and HAQ-DI.

This study had several limitations. First, all patients included in this study were older adults. This study could not investigate previously reported factors related to frailty such as comorbidities and polypharmacy in older adults.^34,35,36) Second, this was a cross-sectional study. Therefore, we could not establish a causal relationship between frailty, its characteristics, and the clinical data of patients with RA. Finally, the enrolled patients were relatively older, had suppressed disease activity, and lower HAQ-DI scores. Therefore, secondary outcomes may have been influenced by patients’ clinical profiles. However, we believe that our results will contribute to the efforts to address this issue in daily clinical practice. A prospective longitudinal study with various variables is required to clarify this relationship.

CONCLUSION

This study demonstrated the prevalence of frailty, factors associated with frailty, and the correlation between the KCL score and patient background. In patients with RA, efforts should be taken to manage HAQ-DI, exercise, and pain to prevent frailty and avoid the need for long-term care.

ACKNOWLEDGMENTS

The authors are grateful to the participants and the medical staff for their contributions to this study.

CONFLICTS OF INTEREST

T. Mochizuki has received honorariums for lectures from Astellas, Bristol-Myers, Chugai, Eli Lilly, and Mochida. K. Yano has received honoraria for lectures from AbbVie, Chugai, Eisai, Gilead Sciences, Janssen, Kaken, Pfizer, and UCB. K. Ikari has received honoraria for lectures from Asahi Kasei, Astellas, AbbVie, Ayumi, Bristol Myers, Chugai, Eisai, Eli Lilly, Janssen, Kaken, Mitsubishi Tanabe, Pfizer, Takeda, Teijin, and UCB. The other authors declare no conflict of interest. The sponsors were not involved in the study design; collection, analysis, and interpretation of data; writing of the article; and/or decision to submit the results for publication.

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