Patterns of multimorbidity and their effects on adverse outcomes in rheumatoid arthritis: a study of 5658 UK Biobank participants

Trajectories of health status and their association with rheumatoid arthritis risk: insights from a national prospective cohort study

BACKGROUND

The association between trajectories of different health states and rheumatoid arthritis (RA) is unknown. Our cohort study aimed to investigate the impact of various trajectories (including depressive symptoms, physical activity and multimorbidity status) on subsequent RA risk.

METHODS

A prospective cohort study was conducted using seven waves of national data from the Health and Retirement Study (HRS 2004-2018) involving 9,795 US adults. A growth mixture model identified 6-year trajectories from 2004 to 2010, and participants were screened for RA by self-reported physician diagnosis in the subsequent four waves (2010-2018). Cox proportional hazards model calculated hazard ratios (HR).

RESULTS

Trajectories of depressive symptoms, physical activity, and multimorbidity status were all associated with the risk of RA. Specifically, keeping a low trajectories (HR = 0.649, 95%CI = 0.533-0.790) or maintaining a moderate rating trajectories (HR = 0.798, 95%CI = 0.644-0.988) for depressive reduced the risk of RA. For physical activity, both high and descending trajectories (HR = 1.456, 95%CI = 1.170-1.812) and high and rising trajectories (HR = 1.244, 95%CI = 1.016-1.522) increased the risk. High multimorbidity trajectories (HR = 1.305, 95%CI = 1.094-1.556) and highest multimorbidity trajectories (HR = 1.393, 95%CI = 1.131-1.715) increased the risk.

CONCLUSION

The results suggest that tracking trajectories of depressive symptoms, physical activity, and multiple disease states may be a potential and feasible screening method for identifying those at risk for RA.

Multimorbidity clusters and their associations with health-related quality of life in two UK cohorts

BACKGROUND

Identifying clusters of multiple long-term conditions (MLTCs), also known as multimorbidity, and their associated burden may facilitate the development of effective and cost-effective targeted healthcare strategies. This study aimed to identify clusters of MLTCs and their associations with long-term health-related quality of life (HRQoL) in two UK population-based cohorts.

METHODS

Age-stratified clusters of MLTCs were identified at baseline in UK Biobank (n = 502,363, 54.6% female) and UKHLS (n = 49,186, 54.8% female) using latent class analysis (LCA). LCA was applied to people who self-reported ≥ 2 LTCs (from n = 43 LTCs [UK Biobank], n = 13 LTCs [UKHLS]) at baseline, across four age-strata: 18-36, 37-54, 55-73, and 74 + years. Associations between MLTC clusters and HRQoL were investigated using tobit regression and compared to associations between MLTC counts and HRQoL. For HRQoL, we extracted EQ-5D index data from UK Biobank. In UKHLS, SF-12 data were extracted and mapped to EQ-5D index scores using a standard preference-based algorithm. HRQoL data were collected at median 5 (UKHLS) and 10 (UK Biobank) years follow-up. Analyses were adjusted for available sociodemographic and lifestyle covariates.

RESULTS

LCA identified 9 MLTC clusters in UK Biobank and 15 MLTC clusters in UKHLS. Clusters centred around pulmonary and cardiometabolic LTCs were common across all age groups. Hypertension was prominent across clusters in all ages, while depression featured in younger groups and painful conditions/arthritis were common in clusters from middle-age onwards. MLTC clusters showed different associations with HRQoL. In UK Biobank, clusters with high prevalence of painful conditions were consistently associated with the largest deficits in HRQoL. In UKHLS, clusters of cardiometabolic disease had the lowest HRQoL. Notably, negative associations between MLTC clusters containing painful conditions and HRQoL remained significant even after adjusting for number of LTCs.

CONCLUSIONS

While higher LTC counts remain important, we have shown that MLTC cluster types also have an impact on HRQoL. Health service delivery planning and future intervention design and risk assessment of people with MLTCs should consider both LTC counts and MLTC clusters to better meet the needs of specific populations.

Associations of accelerated biological aging and metabolic heterogeneity of obesity with rheumatoid arthritis: a prospective cohort study

OBJECTIVE

To evaluate the associations between biological aging, metabolic heterogeneity of obesity, and rheumatoid arthritis (RA).

METHODS

This prospective cohort study analyzed 268,184 individuals from the UK Biobank. Biological age was estimated using phenotypic age (PhenoAge), Klemera-Doubal methods (KDM-BA), and telomere length. We calculated KDM-BA acceleration and PhenoAge acceleration after subtracting the effect of chronological age by regression residual. The metabolic heterogeneity of obesity can be evaluated by four BMI metabolic phenotypes, namely metabolically unhealthy normal weight (MUNW), metabolically healthy normal weight (MHNW), metabolically unhealthy overweight/obesity (MUOO), and metabolically healthy overweight/obesity (MHOO). Cox models were employed to estimate the associations between biological aging, metabolic heterogeneity of obesity, and RA risk.

RESULTS

A total of 2842 patients experienced RA during a mean follow-up time of 12.21 years. A standard deviation (SD) increase in KDM-BA acceleration and PhenoAge acceleration was associated with an increased risk of RA by 13% (hazard ratio = 1.13; 95% CI, 1.09-1.17) and 39% (HR = 1.39; 95% CI, 1.34-1.44), respectively. A SD increase in telomere length was associated with a reduced risk of RA by 5% (HR = 0.95; 95% CI, 0.91-0.98). Compared to the MHNW group, the MUOO group was associated with a 51% increase in the risk of incident RA. In the joint effect analysis, compared to the MHNW + KDM-BA younger subgroup, the HR (95% CI) for RA was 1.68 (1.48, 1.90) in the MUOO + KDM-BA older subgroup.

CONCLUSION

Accelerated biological aging may heighten the susceptibility to RA, particularly in individuals with obesity or metabolic dysfunction. Key Points •Accelerated biological aging increases the risk of developing RA. •Overweight/obese people with a healthy metabolism have a higher risk of RA than those with normal weight and healthy metabolism. •The BMI metabolic phenotype has a strong modifying effect on the association between KDM-BA/PhenoAge and RA risk.

Osteoporosis and Rheumatoid Arthritis: A Review of Current Understanding and Practice

This review presents a current perspective on the association between rheumatoid arthritis (RA) and osteoporosis. Many factors contribute to the increased risk of osteoporosis and fracture in RA patients. These factors include advanced age, duration of disease, long-term glucocorticoid use, and poor inflammation control inflammation in RA. This review discusses current guidelines and their limitations in assessing bone health in RA-related osteoporosis. Available anti-osteoporotic treatments, their mechanisms of action, and their potential benefits in managing the interaction between RA and osteoporosis are discussed. We also consider potential advancements, including areas of future development in RA and osteoporosis diagnosis and management.

Is cardiovascular risk profiling from UK Biobank retinal images using explicit deep learning estimates of traditional risk factors equivalent to actual risk measurements? A prospective cohort study design

OBJECTIVE

Despite extensive exploration of potential biomarkers of cardiovascular diseases (CVDs) derived from retinal images, it remains unclear how retinal images contribute to CVD risk profiling and how the results can inform lifestyle modifications. Therefore, we aimed to determine the performance of cardiovascular risk prediction model from retinal images via explicitly estimating 10 traditional CVD risk factors and compared with the model based on actual risk measurements.

DESIGN

A prospective cohort study design.

SETTING

The UK Biobank (UKBB), a prospective cohort study, following the health conditions including CVD outcomes of adults recruited between 2006 and 2010.

PARTICIPANTS

A subset of data from the UKBB which contains 52 297 entries with retinal images and 5-year cumulative incidence of major adverse cardiovascular events (MACE) was used. Our dataset is split into 3:1:1 as training set (n=31 403), validation set (n=10 420) and testing set (n=10 474). We developed a deep learning (DL) model to predict 5-year MACE using a two-stage DL neural network.

PRIMARY AND SECONDARY OUTCOME MEASURES

We computed accuracy, area under the receiver operating characteristic curve (AUC) and compared variations in the risk prediction models combining CVD risk factors and retinal images.

RESULTS

The first-stage DL model demonstrated that the 10 CVD risk factors can be estimated from a given retinal image with an accuracy ranging between 65.2% and 89.8% (overall AUC of 0.738 with 95% CI: 0.710 to 0.766). In MACE prediction, our model outperformed the traditional score-based models, with 8.2% higher AUC than Systematic COronary Risk Evaluation (SCORE), 3.5% for SCORE 2 and 7.1% for the Framingham Risk Score (with p value<0.05 for all three comparisons).

CONCLUSIONS

Our algorithm estimates the 5-year risk of MACE based on retinal images, while explicitly presenting which risk factors should be checked and intervened. This two-stage approach provides human interpretable information between stages, which helps clinicians gain insights into the screening process copiloting with the DL model.

Longitudinal reciprocal association between rheumatoid arthritis and chronic obstructive pulmonary disease and mediation of inflammation

OBJECTIVES

To elucidate the longitudinal reciprocal association between RA and chronic obstructive pulmonary disease (COPD) and the mediating role of systemic inflammation in the association.

METHODS

A total of 403 045 participants from UK Biobank were enrolled in this study. A cross-lagged panel model was used to investigate the longitudinal reciprocal association between RA and COPD. Cox proportional hazards regression and logistic regression models were also conducted to examine the association between baseline RA and COPD during follow-up, and vice versa. Causal mediation analysis was then performed to explore the mediating roles of 160 systemic inflammatory biomarkers in the bidirectional association.

RESULTS

At baseline, 4755 (1.2%) and 6989 (1.7%) individuals were diagnosed with RA and COPD, respectively. After adjusting for the covariates, the result of a cross-lagged panel model revealed a bidirectional association between RA and COPD (β = 0.018, P < 0.001 for the RA→COPD path; β = 0.010, P < 0.001 for the COPD→RA path). In the non-COPD population, the risk of future COPD was increased in RA patients [Cox model: hazard ratio (HR) 1.65 (95% CI 1.50, 1.83); logistic model: odds ratio (OR) 1.85 (95% CI 1.66, 2.07)]. In the non-RA population, baseline COPD was associated with a higher risk of RA during follow-up [Cox model: HR 1.67 (95% CI 1.44, 1.92); logistic model: OR 1.70 (95% CI 1.47, 1.97)]. Five inflammatory factors mediated the RA→COPD path and CRP mediated the COPD→RA path (false discovery rate < 0.05).

CONCLUSIONS

A significant bidirectional association exists between RA and COPD and it is partially mediated by systemic inflammation.

Rheumatoid arthritis, cardiometabolic comorbidities, and related conditions: need to take action

Rheumatoid Arthritis (RA) is associated with an increased risk of cardiovascular disease and mortality, however, traditional cardiovascular risk factors do not fully explain this relationship. This high risk of cardiovascular morbidity and mortality in RA has been increasingly acknowledged in past decades, with accumulating evidence that RA is an independent cardiovascular risk factor; RA is also associated with metabolic syndrome, which correlates with disease activity, contributing to the increased prevalence of coronary heart disease in RA patients. Moreover, multimorbidity, including the presence of long-term conditions, impacts adverse clinical outcomes in RA patients, emphasizing the need for holistic management that requires an understanding of shared pathophysiological mechanisms, such as systemic inflammation and immune dysregulation. For all these reasons, the management of RA patients with cardiometabolic comorbidities is a complex endeavor that requires a patient-centered, multidisciplinary approach. In this sense, there is a need to re-evaluate the approach toward a proactive model of care, moving away from a reactive medical paradigm to a multidimensional integrated management model, including aggressive screening, preventive strategies, and tailored therapeutic interventions. The aim of this review was to thoroughly review the literature on cardiometabolic comorbidities and related conditions linked to RA to enable us to identify the necessary actions required to effectively tackle the increasing burden of illness from a fully comprehensive perspective.

Mortality in patients with incident rheumatoid arthritis and depression: a Danish cohort study of 11 071 patients and 55 355 comparators

OBJECTIVES

In patients with RA, the association between mortality and depression has been investigated only in patients with prevalent RA. In this study, we estimated the mortality risk associated with depression, defined as the first filling of a prescription for antidepressants, in patients with incident RA and background population comparators.

METHODS

From 2008 to 2018, we identified patients with incident RA in the nationwide Danish rheumatologic database, DANBIO. For each patient, we randomly selected five comparators. Participants were not treated with antidepressants or diagnosed with depression 3 years prior to the index date. From other registers we collected data on socioeconomic status, mortality and cause of death using unique personal identifiers. Using Cox models, we calculated hazard rate ratios (HRR) with 95% CI.

RESULTS

In depressed patients with RA vs patients without depression, adjusted HRR for all-cause mortality was 5.34 (95% CI 3.02, 9.45) during 0-2 years and 3.15 (95% CI 2.62, 3.79) during the total follow-up period, and highest in patients <55 years with HRR 8.13 (95% CI 3.89, 17.02). In comparators with depression vs comparators without depression, the association with mortality was similar to that in patients with RA. There were no unnatural causes of death among depressed patients with RA. The most frequent natural causes of death were cancer, cardiovascular disease, stroke and pneumonia.

CONCLUSION

In patients with RA, depression was a predictor of death but with a strength similar to that in matched comparators.

Hormonal and reproductive factors in relation to the risk of rheumatoid arthritis in women: a prospective cohort study with 223 526 participants

OBJECTIVE

This study aimed to examine rheumatoid arthritis (RA) risk associated with hormonal and reproductive factors in women from the large cohort of the UK Biobank.

METHODS

Data on hormonal and reproductive factors in women were collected from a prospective cohort of 223 526 UK Biobank participants. The potential relationship between reproductive factors and RA risk was assessed using restricted cubic spline. Hazard ratios (HR) were estimated using Cox proportional hazard regressions.

RESULTS

During a median follow-up of 12.39 years, 3313 women with RA were identified. Age at menarche >14 years was associated with a greater RA risk (HR 1.13, 95% CI 1.02 to 1.26) compared with menarche at 13. The multiple adjusted HR for RA in women with menopause at <45 years was 1.46. Reproductive years <33 increased the risk of RA (HR 1.39, 95% CI 1.21 to 1.59). Compared with those with 2 children, women with ≥4 children were associated with a higher risk of RA (HR 1.18, 95% CI 1.04 to 1.34). Women who had a hysterectomy (HR 1.40, 95% CI 1.25 to 1.56) or oophorectomy (HR 1.21, 95% CI 1.08 to 1.35) had a higher risk of RA than those without a hysterectomy or oophorectomy. Both hormone replacement therapy (HRT) use (HR 1.46, 95% CI 1.35 to 1.57) and HRT duration (HR 1.02, 95% CI 1.01 to 1.03) were associated with a higher risk of RA.

CONCLUSIONS

Some hormonal and reproductive factors were associated with a higher risk of RA. Hormonal and reproductive factors should be considered in risk assessment and formulating management plans in female patients with RA.

Multimorbidity in Rheumatoid Arthritis: Literature Review and Future Directions

PURPOSE OF REVIEW

To offer a narrative review of literature and an update on rheumatoid arthritis (RA) multimorbidity research over the past five years as well as future directions.

RECENT FINDINGS

Patients with RA experience higher prevalence of multimorbidity (31-86% vs 18-71% in non-RA) and faster accumulation of comorbidities. Patients with multimorbidity have worse outcomes compared to non-RA multimorbid patients and RA without multimorbidity including mortality, cardiac events, and hospitalizations. Comorbid disease clusters often included: cardiopulmonary, cardiometabolic, and depression and pain-related conditions. High-frequency comorbidities included interstitial lung disease, asthma, chronic obstructive pulmonary disease, cardiovascular disease, fibromyalgia, osteoarthritis, and osteoporosis, thyroid disorders, hypertension, and cancer. Furthermore, patients with RA and multimorbidity are paradoxically at increased risk of high RA disease activity but experience a lower likelihood of biologic use and more biologic failures. RA patients experience higher prevalence of multimorbidity and worse outcomes versus non-RA and RA without multimorbidity. Findings call for further studies.

Multimorbidity in rheumatoid arthritis: common mechanistic links and impact and challenges in routine clinical practice

Early identification and management of multimorbidity in patients with rheumatic and musculoskeletal diseases (RMDs), such as RA, is an integral, but often neglected, aspect of care. The prevalence and incidence of conditions such as osteoporosis, cardiovascular disease, pulmonary disease and malignancies, often co-existing with RA, continues to have significant implications for the management of this patient group. Multimorbidity in RMDs can be associated with inflammatory disease activity and target organ damage. Lifestyle factors, such as smoking and inactivity, further contribute to the burden of disease. Inflammation is the underlying factor, not just in RA but also many comorbidities. The current framework of a treat-to-target approach focuses on achieving early remission and inflammatory activity suppression. We describe how the comorbidity burden in people with RMDs impacts on disease outcome and treatment response. The importance of addressing comorbidity at an early stage and adopting a patient centred approach is critical in modern practice.

Mortality Trends Among Patients with Rheumatoid Arthritis in Western Australia

INTRODUCTION

With scarce comparative data on mortality in Australian patients with rheumatoid arthritis (RA), we investigated temporal changes in standardized mortality rates for patients with RA using longitudinal linked population-wide health data in Western Australia (WA) over the period 1980 to 2015.

METHODS

The study included 17,125 patients with a first-time hospital contact for RA (ICD-10-AM M05.00-M06.99 and ICD-9-AM 714.00-714.99) in the study period. Standardized mortality rate ratios (SMRRs) for the RA cohort versus the WA general population was estimated using direct age standardization. We analyzed temporal trends over with dates and causes provided by the WA Death Registry.

RESULTS

During 356,069 patient-years of follow-up, a total of 8955 (52%) deaths occurred in the RA cohort. The SMRR was 2.24 (95% CI 2.15-2.34) in males and 3.09 (95% CI 3.00-3.19) in females over the study period. SMRR decreased since 2000 to 1.59 (95% CI 1.39-1.81) for the period 2011-2015. Median survival was 26.80 years (95% CI 26.30-27.30), where age and comorbidity independently increased the risk of death. The leading causes of deaths were cardiovascular diseases (26.60%), cancer (16.80%), rheumatic diseases (5.80%), chronic pulmonary disease 491 (5.50%), dementia (3.00%), and diabetes 235 (2.6%).

CONCLUSIONS

The mortality rate in patients with RA in WA has decreased but remains 1.59-times higher than in community counterparts, suggesting that there is room for further improvement. Comorbidity is the main modifiable risk factor to further reduce mortality in patients with RA.

Association of Combined Exposure to Ambient Air Pollutants, Genetic Risk, and Incident Rheumatoid Arthritis: A Prospective Cohort Study in the UK Biobank

BACKGROUND

Evidence for a potential link between air pollution and rheumatoid arthritis (RA) is inconsistent, and the modified effect of genetic susceptibility on the relationship between air pollution and RA has not been well studied.

OBJECTIVE

Using a general population cohort from the UK Biobank, this study aimed to investigate the associations between various air pollutants and the risk of incident RA and to further estimate the impact of combined exposure to ambient air pollutants on the risk of developing RA under the modification effect of genetic predisposition.

METHODS

A total of 342,973 participants with completed genotyping data and who were free of RA at baseline were included in the study. An air pollution score was constructed by summing the concentrations of each pollutant weighted by the regression coefficients with RA from single-pollutant models to assess the combined effect of air pollutants, including particulate matter (PM) with diameters ≤ 2.5 μ m (PM 2.5 ), between 2.5 and 10 μ m (PM 2.5 - 10 ), and ≤ 10 μ m (PM 10 ), as well as nitrogen dioxide (NO 2 ) and nitrogen oxides (NO x ). In addition, the polygenic risk score (PRS) of RA was calculated to characterize individual genetic risk. The Cox proportional hazard model was used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) of associations of single air pollutant, air pollution score, or PRS with incident RA.

RESULTS

During a median follow-up time of 8.1 y, 2,034 incident events of RA were recorded. The HRs (95% CIs) of incident RA per interquartile range increment in PM 2.5 , PM 2.5 - 10 , PM 10 , NO 2 , and NO x were 1.07 (1.01, 1.13), 1.00 (0.96, 1.04), 1.01 (0.96, 1.07), 1.03 (0.98, 1.09), and 1.07 (1.02, 1.12), respectively. We also found a positive exposure-response relationship between air pollution score and RA risk (p Trend = 0.000053 ). The HR (95% CI) of incident RA was 1.14 (1.00, 1.29) in the highest quartile group compared with the lowest quartile group of the air pollution score. Furthermore, the results of the combined effect of air pollution score and PRS on the RA risk showed that the risk of RA incidence in the highest genetic risk and air pollution score group was almost twice that of the lowest genetic risk and air pollution score group [incidence rate (IR) per 100,000 person-years: 98.46 vs. 51.19, and HR = 1.73 (95% CI: 1.39, 2.17) vs. 1 (reference)], although no statistically significant interaction between the air pollution and genetic risk for incident RA was found (p Interaction > 0.05 ).

DISCUSSION

The results revealed that long-term combined exposure to ambient air pollutants might increase the risk of RA, particularly in those with high genetic risk. https://doi.org/10.1289/EHP10710.

Association between risk, duration and cause of hospitalisations in people with rheumatoid arthritis and multimorbidity in the UK Biobank and Scottish Early Rheumatoid Arthritis (SERA) cohorts: Longitudinal observational study

OBJECTIVES

To investigate association between presence of multimorbidity in people with established and early rheumatoid arthritis (RA) and risk, duration and cause of hospitalisations.

DESIGN

Longitudinal observational study.

SETTING

UK Biobank, population-based cohort recruited between 2006 and 2010, and the Scottish Early Rheumatoid Arthritis (SERA), inception cohort recruited between 2011 and 2015. Both linked to mortality and hospitalisation data.

PARTICIPANTS

4757 UK Biobank participants self-reporting established RA; 825 SERA participants with early RA meeting the 2010 ACR/EULAR classification criteria. Participants stratified by number of long-term conditions (LTCs) in addition to RA (RA only, RA + 1 LTC and RA + ≥ 2 LTCs) and matched to five non-RA controls.

MAIN OUTCOME MEASURES

Number and duration of hospitalisations and their causes. Incidence rate ratios (IRR) and 95% confidence intervals (CI) calculated using negative binomial regression models.

RESULTS

Participants with RA + ≥ 2 LTCs experienced higher hospitalisation rates compared to those with RA alone (UK Biobank: IRR 2.10, 95% CI 1.91 to 2.30; SERA: IRR 1.74, 95% CI 1.23 to 2.48). Total duration of hospitalisation in RA + ≥ 2 LTCs was also higher (UK Biobank: IRR 2.48, 95% CI 2.17 to 2.84; SERA: IRR 1.90, 95% CI 1.07 to 3.38) than with RA alone. Rate and total duration of hospitalisations was higher in UK Biobank RA participants than non-RA controls with equivalent number of LTCs. Hospitalisations for respiratory infection were higher in early RA than established RA and were the commonest cause of hospital admission in early RA.

CONCLUSIONS

Participants with established or early RA with multimorbidity experienced a higher rate and duration of hospitalisations than those with RA alone and with non-RA matched controls.

Classification of long-term condition patterns in rheumatoid arthritis and associations with adverse health events: a UK Biobank cohort study

PURPOSE

We aimed to classify individuals with RA and ≥2 additional long-term conditions (LTCs) and describe the association between different LTC classes, number of LTCs and adverse health outcomes.

METHODS

We used UK Biobank participants who reported RA (n=5,625) and employed latent class analysis (LCA) to create classes of LTC combinations for those with ≥2 additional LTCs. Cox-proportional hazard and negative binomial regression were used to compare the risk of all-cause mortality, major adverse cardiac events (MACE), and number of emergency hospitalisations over an 11-year follow-up across the different LTC classes and in those with RA plus one additional LTC. Persons with RA without LTCs were the reference group. Analyses were adjusted for demographic characteristics, smoking, BMI, alcohol consumption and physical activity.

RESULTS

A total of 2,566 (46%) participants reported ≥2 LTCs in addition to RA. This involved 1,138 distinct LTC combinations of which 86% were reported by ≤2 individuals. LCA identified 5 morbidity-classes. The distinctive condition in the class with the highest mortality was cancer (class 5; HR 2.66 95%CI (1.91-3.70)). The highest MACE (HR 2.95 95%CI (2.11-4.14)) and emergency hospitalisations (rate ratio 3.01 (2.56-3.54)) were observed in class 3 which comprised asthma, COPD & CHD. There was an increase in mortality, MACE and emergency hospital admissions within each class as the number of LTCs increased.

CONCLUSIONS

The risk of adverse health outcomes in RA varied with different patterns of multimorbidity. The pattern of multimorbidity should be considered in risk assessment and formulating management plans in patients with RA.

Association between Rheumatic Disease Comorbidity Index and factors of poor prognosis in a cohort of 280 patients with rheumatoid arthritis

BACKGROUND

Rheumatoid arthritis (RA) is commonly associated with higher rates of comorbidities. Recent recommendations highlight screening comorbidities during the disease course because of their impact on patients' ability to function, on disease outcome, but also on treatment choices. Hence the interest of our study that aimed to quantify the impact of comorbidities among RA patients using a validated tool the Rheumatic Disease Comorbidity Index (RDCI) and to explore the association between comorbidities and disease characteristics.

METHODS

We conducted a cross-sectional study over 12 months period, including patients followed for an established RA according to the ACR/EULAR 2010 criteria and hospitalized in our rheumatology department. Patients' characteristics and disease features were collected for each patient. Comorbidities were quantified using the RDCI. We looked for the association between RDCI and patients characteristics and RA parameters. Univariable and multivariable analysis were made.

RESULTS

They were 280 patients: 233 female (83.2%) and 47 male (16.8%) with a mean age of 58.07 (SD 11.12) years. The mean follow-up period was 14.74 (SD 1.63) years. Comorbidities were noted in 133 patients (47.5%). The mean comorbidity score measured by the RDCI was 1.05 (SD 1.23). RDCI was positively correlated with age (p < 0.001, r = 0.359). RA patients whose age of disease onset exceeds 40 years have significantly higher RDCI (1.8 (SD 1.3) [CI 95%: 1.36-1.88] vs. 1.5 (SD 1.2), p = 0.007). Moreover, RDCI was significantly associated with the presence pulmonary involvement (p < 0.001) and ocular involvement (p = 0.002). RDCI was also associated with erosive RA (p = 0.006), the presence of atlanto-axial dislocation (p = 0.014), and coxitis (p = 0.029). Regarding therapy regimen, RDCI was statistically increased in patients receiving bDMARDs compared to patients under csDMARDs (2.8 (SD 1.6) vs. 1.0 (SD 1.0), p = 0.021).

CONCLUSION

In this study, comorbidity index was associated with signs of poor prognosis such as erosions, coxitis, and atlanto-axial dislocation. This confirmed the hypothesis that comorbidity can be a threat to the improvement in the long-term prognosis in RA patients.

Increased Frailty in Individuals With Osteoarthritis and Rheumatoid Arthritis and the Influence of Comorbidity: An Analysis of the UK Biobank Cohort

OBJECTIVE

To determine the association between osteoarthritis (OA), rheumatoid arthritis (RA), and frailty and to determine whether comorbidities interact with OA and RA to further increase the likelihood of frailty.

METHODS

Participants of the UK Biobank age 40-69 years at baseline were included. Demographic, lifestyle, and clinical data were collected at baseline and follow-up in a subset. Frailty was assessed using a frailty index (FI) (continuous) and a modified frailty phenotype (robust, pre-frail, frail). The association between RA and OA and frailty at baseline and follow-up was assessed using multiple regression models. We looked at whether comorbidities, including cardiovascular disease, diabetes mellitus, chronic obstructive pulmonary disease, and depression interacted additively with OA and RA to increase the likelihood of frailty.

RESULTS

In total, 457,561 participants contributed data. Those with (versus without) RA (n = 4,894) and OA (n = 35,884), respectively, were more likely to be frail (adjusted relative risk ratio 10.7 [95% confidence interval (95% CI) 9.7, 11.7] and 3.4 [95% CI 3.3, 3.6]) and were more likely to have a higher FI at baseline. There was evidence of additive interaction between RA, OA, and common comorbidities increasing the occurrence of prevalent frailty. Among 25,163 participants included in longitudinal analysis, patients with RA (n = 202) and OA (n = 1,811) at baseline had an increased adjusted frailty incidence rate ratio (2.8 [95% CI 1.7, 4.6] and 1.7 [95% CI 1.3, 2.1], respectively) and also a higher FI during follow-up.

CONCLUSION

Individuals with RA and OA are more likely to have, or develop, frailty. Common comorbidities interact with OA and RA to further increase the likelihood of frailty.

Frailty in people with rheumatoid arthritis: a systematic review of observational studies

Background: Frailty, an age-related decline in physiological reserve, is an increasingly important concept in the management of chronic diseases. The implications of frailty in people with rheumatoid arthritis are not well understood. We undertook a systematic review to assess prevalence of frailty in people with rheumatoid arthritis, and the relationship between frailty and disease activity or clinical outcomes. Methods: We searched four electronic databases (January 2001 to April 2021) for observational studies assessing the prevalence of frailty (any frailty measure) in adults (≥18 years) with rheumatoid arthritis, or analysing the relationship between frailty and disease activity or clinical outcomes (e.g. quality of life, hospitalisation or mortality) in people with rheumatoid arthritis. Study quality was assessed using an adapted Newcastle-Ottawa Scale. Screening, quality assessment and data extraction were performed independently by two reviewers. We used narrative synthesis. Results: We identified 17 analyses, from 14 different populations. 15/17 were cross-sectional. Studies used 11 different measures of frailty. Frailty prevalence ranged from 10% (frailty phenotype) to 36% (comprehensive rheumatologic assessment of frailty) in general adult populations with rheumatoid arthritis. In younger populations (<60 or <65 years) prevalence ranged from 2.4% (frailty phenotype) to 19.9% (Kihon checklist) while in older populations (>60 or >65) prevalence ranged from 31.2% (Kihon checklist) to 55% (Geriatric 8 tool). Frailty was cross-sectionally associated with higher disease activity (10/10 studies), lower physical function (7/7 studies) and longer disease duration (2/5 studies), and with hospitalization and osteoporotic fractures (1/1 study, 3.7 years follow-up). Conclusion: Frailty is common in rheumatoid arthritis, including those aged <65 years, and is associated with a range of adverse features. However, these is heterogeneity in how frailty is measured. We found few longitudinal studies making the impact of frailty on clinical outcomes over time and the extent to which frailty is caused by rheumatoid arthritis unclear.

Frailty in people with rheumatoid arthritis: a systematic review of observational studies

Background: Frailty, an age-related decline in physiological reserve, is an increasingly important concept in the management of chronic diseases. The implications of frailty in people with rheumatoid arthritis are not well understood. We undertook a systematic review to assess prevalence of frailty in people with rheumatoid arthritis, and the relationship between frailty and disease activity or clinical outcomes. Methods: We searched four electronic databases (January 2001 to April 2021) for observational studies assessing the prevalence of frailty (any frailty measure) in adults (≥18 years) with rheumatoid arthritis, or analysing the relationship between frailty and disease activity or clinical outcomes (e.g. quality of life, hospitalisation or mortality) in people with rheumatoid arthritis. Study quality was assessed using an adapted Newcastle-Ottawa Scale. Screening, quality assessment and data extraction were performed independently by two reviewers. We used narrative synthesis. Results: We identified 17 analyses, from 14 different populations. 15/17 were cross-sectional. Studies used 11 different measures of frailty. Frailty prevalence ranged from 10% (frailty phenotype) to 36% (comprehensive rheumatologic assessment of frailty) in general adult populations with rheumatoid arthritis. In younger populations (<60 or <65 years) prevalence ranged from 2.4% (frailty phenotype) to 19.9% (Kihon checklist) while in older populations (>60 or >65) prevalence ranged from 31.2% (Kihon checklist) to 55% (Geriatric 8 tool). Frailty was cross-sectionally associated with higher disease activity (10/10 studies), lower physical function (7/7 studies) and longer disease duration (2/5 studies), and with hospitalization and osteoporotic fractures (1/1 study, 3.7 years follow-up). Conclusion: Frailty is common in rheumatoid arthritis, including those aged <65 years, and is associated with a range of adverse features. However, these is heterogeneity in how frailty is measured. We found few longitudinal studies making the impact of frailty on clinical outcomes over time and the extent to which frailty is caused by rheumatoid arthritis unclear.

How do multiple long-term conditions impact on the cost-of-illness in early rheumatoid arthritis?

OBJECTIVE

Multiple long-term conditions (MLTCs) are prevalent in rheumatoid arthritis (RA) and associated with worse outcomes and greater economic burden. However, little is known about the impact of MLTCs on the cost-of-illness (COI) in early RA, including direct and indirect costs. The objective of this study was to quantify this impact on COI.

METHODS

The Scottish Early Rheumatoid Arthritis study is a national cohort of adults with new-onset RA. Direct costs were estimated applying relevant unit costs to health resource utilisation; indirect costs were measured by productivity loss due to health conditions. Two-part models were used, adjusting for age, gender, baseline functional disability and health-related quality of life. The Charlson Comorbidity Index score was calculated using ICD-10 diagnoses. Individuals were defined as 'RA alone', 'RA plus LTC' and 'RA plus MLTCs' according to the number of coexisting LTCs.

RESULTS

Data were available for 818 participants. Average annualised direct costs incurred by people with early RA plus MLTCs (£4444; 95% CI £3100 to £6371) were twice as, and almost five times higher than, those with a single LTC (£2184; 95% CI £1596 to £2997) and those without LTC (£919; 95% CI £694 to £1218), respectively. Indirect costs incurred by RA plus MLTCs (£842; 95% CI £377to £1521) were 3.1 times higher than RA alone (£530; 95% CI £273to £854). The relative proportion of direct costs increased with LTC category, ranging from 77.2% to 84.1%. In addition to increased costs with LTCs, costs also increased with age and were higher for men regardless of LTC category.

CONCLUSIONS

MLTCs impact on COI early in the course of RA. The presence of LTCs is associated with significant increases in both direct and indirect costs among people with early RA.

Elucidating a bidirectional association between rheumatoid arthritis and depression: A systematic review and meta-analysis

BACKGROUND

Rheumatoid arthritis (RA) and depression are conditions which commonly co-exist. Recent longitudinal studies now suggest a bidirectional association between these disorders, with inconsistent results. We conducted a systematic review and meta-analysis to examine this relationship.

METHODS

Three electronic databases (PubMed, Embase and PsycINFO) were searched from inception to September 4, 2021 for cohort studies evaluating either the risk of depression in RA patients or the risk of RA in patients with depression, as well as the secondary outcome of all-cause mortality risk in RA patients with depression. A random effects model was used to summarize the included studies.

RESULTS

Eleven cohort studies were included, comprising a total of 39,130 RA patients, 550,782 patients with depression and 7,802,230 controls. RA patients had a 47% greater risk of incident depression compared to controls, while patients with depression had a 34% greater risk of developing RA. Subgroup analysis by age was only significant in the ≥60 years old age group. RA patients with depression had an 80% increased risk of all-cause mortality compared to those without depression.

LIMITATIONS

The results may have been confounded by factors such as differing methods of depression ascertainment across studies and overlap in presentation between the two conditions.

CONCLUSION

There exists a bidirectional association between RA and depression especially in the elderly which increases mortality risk. This invites the need for clinicians to screen and be vigilant for the presence of these conditions.

Frailty in rheumatoidrmdopen-2021-002111 arthritis and its relationship with disease activity, hospitalisation and mortality: a longitudinal analysis of the Scottish Early Rheumatoid Arthritis cohort and UK Biobank

OBJECTIVE

To assess the prevalence of frailty in rheumatoid arthritis (RA) and its association with baseline and longitudinal disease activity, all-cause mortality and hospitalisation.

PARTICIPANTS

People with RA identified from the Scottish Early Rheumatoid Arthritis (SERA) inception cohort (newly diagnosed, mean age 58.2 years) and UK Biobank (established disease identified using diagnostic codes, mean age 59 years). Frailty was quantified using the frailty index (both datasets) and frailty phenotype (UK Biobank only). Disease activity was assessed using Disease Activity Score in 28 joints (DAS28) in SERA. Associations between baseline frailty and all-cause mortality and hospitalisation was estimated after adjusting for age, sex, socioeconomic status, smoking and alcohol, plus DAS28 in SERA.

RESULTS

Based on the frailty index, frailty was common in SERA (12% moderate, 0.2% severe) and UK Biobank (20% moderate, 3% severe). In UK Biobank, 23% were frail using frailty phenotype. Frailty index was associated with DAS28 in SERA, as well as age and female sex in both cohorts. In SERA, as DAS28 lessened over time with treatment, mean frailty index also decreased. The frailty index was associated with all-cause mortality (HR moderate/severe frailty vs robust 4.14 (95% CI 1.49 to 11.51) SERA, 1.68 (95% CI 1.26 to 2.13) UK Biobank) and unscheduled hospitalisation (incidence rate ratio 2.27 (95% CI 1.45 to 3.57) SERA 2.74 (95% CI 2.29 to 3.29) UK Biobank). In UK Biobank, frailty phenotype also associated with mortality and hospitalisation.

CONCLUSION

Frailty is common in early and established RA and associated with hospitalisation and mortality. Frailty in RA is dynamic and, for some, may be ameliorated through controlling disease activity in early disease.

COVID-19 hospitalizations, intensive care unit stays, ventilation and death among patients with immune mediated inflammatory diseases compared to controls

Objective

To investigate COVID-19 hospitalization risk in patients with immune mediated inflammatory diseases (IMIDs) compared with matched non-IMID comparators from the general population.

Methods

We conducted a population-based, matched cohort study using health administrative data from January to July 2020 in Ontario, Canada. Cohorts for each of the following IMIDs were assembled: rheumatoid arthritis (RA), psoriasis, psoriatic arthritis (PsA), ankylosing spondylitis, systemic autoimmune rheumatic diseases (SARDs), multiple sclerosis (MS), iritis, inflammatory bowel disease, polymyalgia rheumatica and vasculitis. Each patient was matched with 5 non-IMID comparators based on socio-demographic factors. We compared the cumulative incidence of hospitalizations for COVID-19 and their outcomes between IMID and non-IMID patients.

Results

A total of 493,499 IMID patients (417 hospitalizations) and 2,466,946 non-IMID comparators (1,519 hospitalizations) were assessed. The odds of being hospitalized for COVID- 19 was significantly higher in patients with IMIDs compared with their matched non-IMID comparators (matched unadjusted Odds Ratio (OR) 1.37, adjusted OR 1.23). Significantly higher risk of hospitalizations was found in patients with iritis (OR 1.46), MS (OR 1.83), PsA (OR 2.20), RA (OR 1.42), SARDs (OR 1.47) and vasculitis (OR 2.07). COVID-19 hospitalizations were associated with older age, male sex, long-term care residence, multimorbidity, and lower income. The odds of complicated hospitalizations was 21% higher among all IMID versus matched non-IMID patients, but this association was attenuated after adjusting for demographic factors and comorbidities.

Conclusion

Patients with IMIDs were at higher risk of being hospitalized with COVID-19. This risk was explained in part by their comorbidities.

Hospitalisation events in people with chronic kidney disease as a component of multimorbidity: parallel cohort studies in research and routine care settings

BACKGROUND

Chronic kidney disease (CKD) typically co-exists with multimorbidity (presence of 2 or more long-term conditions: LTCs). The associations between CKD, multimorbidity and hospitalisation rates are not known. The aim of this study was to examine hospitalisation rates in people with multimorbidity with and without CKD. Amongst people with CKD, the aim was to identify risk factors for hospitalisation.

METHODS

Two cohorts were studied in parallel: UK Biobank (a prospective research study: 2006-2020) and Secure Anonymised Information Linkage Databank (SAIL: a routine care database, Wales, UK: 2011-2018). Adults were included if their kidney function was measured at baseline. Nine categories of participants were used: zero LTCs; one, two, three and four or more LTCs excluding CKD; and one, two, three and four or more LTCs including CKD. Emergency hospitalisation events were obtained from linked hospital records.

RESULTS

Amongst 469,339 UK Biobank participants, those without CKD had a median of 1 LTC and those with CKD had a median of 3 LTCs. Amongst 1,620,490 SAIL participants, those without CKD had a median of 1 LTC and those with CKD had a median of 5 LTCs. Compared to those with zero LTCs, participants with four or more LTCs (excluding CKD) had high event rates (rate ratios UK Biobank 4.95 (95% confidence interval 4.82-5.08)/SAIL 3.77 (3.71-3.82)) with higher rates if CKD was one of the LTCs (rate ratios UK Biobank 7.83 (7.42-8.25)/SAIL 9.92 (9.75-10.09)). Amongst people with CKD, risk factors for hospitalisation were advanced CKD, age over 60, multiple cardiometabolic LTCs, combined physical and mental LTCs and complex patterns of multimorbidity (LTCs in three or more body systems).

CONCLUSIONS

People with multimorbidity have high rates of hospitalisation. Importantly, the rates are two to three times higher when CKD is one of the multimorbid conditions. Further research is needed into the mechanism underpinning this to inform strategies to prevent hospitalisation in this very high-risk group.

Relationship between rheumatoid arthritis and pulmonary function measures on spirometry in the UK Biobank

OBJECTIVE

We investigated the independent relationship of rheumatoid arthritis (RA) with type and severity of pulmonary patterns on spirometry compared to general population controls.

METHODS

This cross-sectional study investigated the association of RA and pulmonary function measures on spirometry among subjects who had spirometry performed for research purposes in the UK Biobank. RA cases were identified by self-report and current DMARD/glucocorticoid use. General population controls denied RA. Outcomes included continuous % predicted forced expiratory volume in 1 second (FEV₁ ) and forced vital capacity (FVC), type of spirometric pattern (restrictive or obstructive), and severity. We used multivariable regression to estimate the effects of RA cases versus controls, adjusting for age, sex, body mass index (BMI), and smoking status/pack-years.

RESULTS

Among 350,776 analyzed subjects with spirometry performed (mean age 56.3 years, 55.8% female, and 45.5% ever smokers), we identified 2,008 cases of treated RA. In multivariable analyses, RA was associated with lower % predicted FEV₁ (β -2.93, 95%CI -3.63,-2.24), % predicted FVC (β -2.08, 95%CI -2.72,-1.45), and FEV₁ /FVC (β -0.008, 95%CI -0.010,-0.005) than controls. RA was associated with restrictive (OR 1.36, 95%CI 1.21,1.52) and obstructive (OR 1.21, 95%CI 1.07,1.37) patterns independent of confounders. RA had the strongest associations for severe restrictive and obstructive patterns.

CONCLUSION

RA was associated with increased odds of restrictive and obstructive patterns, and this relationship was not explained by confounders including smoking. In addition to restrictive lung disease, clinicians should also be aware that airflow obstruction may be a pulmonary manifestation of RA.

High Comorbidity Burden in Patients with SLE: Data from the Community-Based Lupus Registry of Crete

Comorbidities and multimorbidity, often complicating the disease course of patients with chronic inflammatory rheumatic diseases, may be influenced by disease-intrinsic and extrinsic determinants including regional and social factors. We analyzed the frequency and co-segregation of self-reported comorbid diseases in a community-based Mediterranean registry of patients (n = 399) with systemic lupus erythematosus (SLE). Predictors for multimorbidity were identified by multivariable logistic regression, strongly-associated pairs of comorbidities by the Cramer's V-statistic, and comorbidities clusters by hierarchical agglomerative clustering. Among the most prevalent comorbidities were thyroid (45.6%) and metabolic disorders (hypertension: 24.6%, dyslipidemia: 33.3%, obesity: 35.3%), followed by osteoporosis (22.3%), cardiovascular (20.8%), and allergic (20.6%) disorders. Mental comorbidities were also common, particularly depression (26.7%) and generalized anxiety disorder (10.7%). Notably, 51.0% of patients had ≥3 physical and 33.1% had ≥2 mental comorbidities, with a large fraction (n = 86) displaying multimorbidity from both domains. Sociodemographic (education level, marital status) and clinical (disease severity, neurological involvement) were independently associated with physical or mental comorbidity. Patients were grouped into five distinct clusters of variably prevalent comorbid diseases from different organs and domains, which correlated with SLE severity patterns. Conclusively, our results suggest a high multimorbidity burden in patients with SLE at the community, advocating for integrated care to optimize outcomes.