Comparison of Indexes to Measure Comorbidity Burden and Predict All-Cause Mortality in Rheumatoid Arthritis

A Frailty Index to Predict Mortality, Resource Utilization and Costs in Patients Undergoing Coronary Artery Bypass Graft Surgery in Ontario

Background

People living with frailty are vulnerable to poor outcomes and incur higher health care costs after coronary artery bypass graft (CABG) surgery. Frailty-defining instruments for population-level research in the CABG setting have not been established. The objectives of the study were to develop a preoperative frailty index for CABG (pFI-C) surgery using Ontario administrative data; assess pFI-C suitability in predicting clinical and economic outcomes; and compare pFI-C predictive capabilities with other indices.

Methods

A retrospective cohort study was conducted using health administrative data of 50,682 CABG patients. The pFI-C comprised 27 frailty-related health deficits. Associations between index scores and mortality, resource use and health care costs (2022 Canadian dollars [CAD]) were assessed using multivariable regression models. Capabilities of the pFI-C in predicting mortality were evaluated using concordance statistics; goodness of fit of the models was assessed using Akakie Information Criterion.

Results

As assessed by the pFI-C, 22% of the cohort lived with frailty. The pFI-C score was strongly associated with mortality per 10% increase (odds ratio [OR], 3.04; 95% confidence interval [CI], [2.83,3.27]), and was significantly associated with resource utilization and costs. The predictive performances of the pFI-C, Charlson, and Elixhauser indices and Johns Hopkins Aggregated Diagnostic Groups were similar, and mortality models containing the pFI-C had a concordance (C)-statistic of 0.784. Cost models containing the pFI-C showed the best fit.

Conclusions

The pFI-C is predictive of mortality and associated with resource utilization and costs during the year following CABG. This index could aid in identifying a subgroup of high-risk CABG patients who could benefit from targeted perioperative health care interventions.

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.

Clinical Features Associated With Rate of Fractures in Patients With Systemic Sclerosis: A US Cohort Study

OBJECTIVE

Systemic sclerosis (SSc) is associated with several specific risk factors for fracture due to the complications of the disease and related medications. The present study was undertaken to examine the relationship between SSc-associated clinical features and fracture rate in a large US cohort.

METHODS

Participants with SSc in FORWARD, The National Databank for Rheumatic Diseases, were included (1998-2019). Age- and sex-matched individuals with osteoarthritis (OA) from the same database were included as comparators. The primary end point was self-reported major osteoporotic fracture. Cox proportional hazards models were used to study the associations between risk factors and fractures.

RESULTS

The study included 922 individuals (SSc patients, n = 154; OA patients, n = 768). Eighty-seven percent were female, with a mean age of 57.8 years. Fifty-one patients developed at least 1 fracture during a median of 4.2 years (0.5-22.0 years) of follow-up. Patients with SSc had more frequent fractures compared to OA comparators (hazard ratio [HR] 2.38 [95% confidence interval (95% CI) 1.47-3.83]). Among patients with SSc, a higher Rheumatic Disease Comorbidity Index score (HR 1.45 [95% CI 1.20-1.75]) and a higher Health Assessment Questionnaire disability index score (HR 3.83 [95% CI 2.12-6.93]) were associated with more fractures. Diabetes mellitus (HR 5.89 [95% CI 2.51-13.82]) and renal disease (HR 2.43 [95% CI 1.10-5.37]) were independently associated with fracture among SSc patients relative to SSc patients without these comorbidities.

CONCLUSION

Our findings highlight factors associated with fracture among patients with SSc. Disability as measured by the HAQ DI is a particularly strong indicator of fracture rate in SSc. Improving SSc patients' functional status, where possible, may lead to better long-term outcomes.

Viewpoint: how to measure comorbidities in patients with rheumatoid arthritis - clinical and academic value

Given the high prevalence and the enormous impact on key outcomes, comorbidities are important to consider, especially in patients with RA. Comorbidity indices are tools to quantify the impact of the overall burden of coexisting diseases on a specific outcome of interest. Until now, no gold standard exists on how to measure comorbidities. A large variety of indices have been developed using different settings and therefore leading to conceptual differences. Choosing the right tool clearly depends on the intention (clinical or research purpose) and the specific research question. The current article will address the purpose and challenge of measuring comorbidities in RA patients.

PDCD5 as a Potential Biomarker for Improved Prediction of the Incidence and Remission for Patients with Rheumatoid Arthritis

INTRODUCTION

Rheumatoid arthritis (RA) often involves an altered T-cell subpopulation, higher levels of inflammatory cytokines, and auto-antibodies. This study investigated whether PDCD5 could be a biomarker to predict the incidence and remission of RA so as to guide the therapeutic management of clinical RA.

METHODS

One hundred fifty-two patients (41 being in both active status and stable remission status) who were newly diagnosed with RA and 38 healthy controls were enrolled. Basic clinical data were collected before using blood samples remaining in the clinic after routine complete blood count. The ability of PDCD5 and important indicators to predict the remission of RA was estimated based on receiver operating characteristic curve (ROC) analysis.

RESULTS

PDCD5 expression was found to be significantly increased in RA patients in active status in comparison with healthy controls or those in stable remission status. Compared with anti-CCP, ESR and DAS28 score, PDCD5 was of better predictive value with an AUC of 0.846 (95% CI 0.780-0.912) for RA remission. The incidence risk of RA increased with higher levels of PDCD5 (OR = 1.73, 95% CI = 1.45-1.98, P = 0.005) in multiple logistic regression analysis, with the risk increasing by 2.94-times for high-risk group in comparison with low-risk group (OR = 2.94, 95% CI = 2.35-4.62, P < 0.001). The association between PDCD5 and RA remission showed a similar result. For correlation analysis, significant associations were eventually found between PDCD5 and indicated genes (FOXP3, TNF-α, IL-17A, IFN-γ and IL-6) as well as several important clinical parameters including IgG, RF, CRP, ESR, anti-CCP and DAS28 score.

CONCLUSIONS

This study suggested that increased PDCD5 expression was significantly linked to the incidence and remission of RA. PDCD5 may be used as a novel biomarker for the prediction of RA incidence and remission, especially due to its potential involvement in the development of the condition.

Real-life data on the comorbidities in spondyloarthritis from our multicenter nationwide registry: BioStar

Objectives

Considering that the comorbid situations during the management of Spondyloarthritis (SpA) have been underlined in several recommendations, the main objective of this study was to evaluate the comorbid conditions of Turkish patients with SpA.

Patients and methods

This cross-sectional observational study was conducted with 1,242 SpA patients (844 males, 398 females; mean age: 43.9±11.0 years; range, 19 to 81 years) diagnosed according to the modified New York criteria for ankylosing spondylitis or the Assessment of SpondyloArthritis International Society (ASAS) criteria. The patient data were collected from the Biologic and targeted Synthetic antirheumatic drugs Registry (BioStar) between February 1, 2019, and December 29, 2020. Clinical and demographic data, including, age, sex, disease duration, body mass index (BMI), pain, patient's global assessment, physician's global assessment, Bath Ankylosing Spondylitis Disease Activity Index, Ankylosing Spondylitis Disease Activity Score, Bath Ankylosing Spondylitis Functional Index, Bath Ankylosing Spondylitis Metrology Index, and Maastricht Enthesitis Score, were recorded. Comorbid conditions were recorded by filling out a questionnaire according to the clinical history or medical records. Charlson Comorbidity Index and Rheumatic Disease Comorbidity Index scores were calculated from the gathered comorbidity information.

Results

Nine hundred thirteen patients had radiographic axial SpA, 153 had nonradiographic axial SpA, and 176 had peripheral SpA. The most common comorbidities were hypertension (HT) (n=167, 13.4%), diabetes mellitus (DM) (n=83, 6.7%), thyroid disorders (n=64, 5.6%), and depression (n=61, 4.9%). The comorbidities and the calculated comorbidity indices were significantly higher in females, in those with a BMI >25 kg/m2 , and those over 60 years of age. No relationship was found between smoking and alcohol use and comorbidities. A significantly higher prevalence of HT and DM in peripheral SpA patients and a lower prevalence of thyroid disorders in radiographic axial SpA patients were observed.

Conclusion

The most commonly reported comorbidities were HT, DM, thyroid disorders, and depression in SpA patients according to the BioStar database. The frequency of comorbidities and composite comorbidity scores were higher among females, older (>60 years) patients, and overweight (BMI >25 kg/m2 ) patients.

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.

Association Between Mental Health Conditions and Outpatient Care Fragmentation: a National Study of Older High-Risk Veterans

BACKGROUND

Healthcare fragmentation may lead to adverse consequences and may be amplified among older, sicker patients with mental health (MH) conditions.

OBJECTIVE

To determine whether older Veterans with MH conditions have more fragmented outpatient non-MH care, compared with older Veterans with no MH conditions.

DESIGN

Retrospective cohort study using FY2014 Veterans Health Administration (VHA) administrative data linked to Medicare data.

PARTICIPANTS

125,481 VHA patients ≥ 65 years old who were continuously enrolled in Medicare Fee-for-Service Parts A and B and were at high risk for hospitalization.

MAIN OUTCOME AND MEASURES

The main outcome was non-MH care fragmentation as measured by (1) non-MH provider count and (2) Usual Provider of Care (UPC), the proportion of care with the most frequently seen non-MH provider. We tested the association between no vs. any MH conditions and outcomes using Poisson regression and fractional regression with logit link, respectively. We also compared Veterans with no MH condition with each MH condition and combinations of MH conditions, adjusting for sociodemographics, comorbidities, and drive-time to VHA specialty care.

KEY RESULTS

In total, 47.3% had at least one MH condition. Compared to those without MH conditions, Veterans with MH conditions had less fragmented care, with fewer non-MH providers (IRR = 0.96; 95% CI: 0.96-0.96) and more concentrated care with their usual provider (OR = 1.08 for a higher UPC; 95% CI: 1.07, 1.09) in adjusted models. Secondary analyses showed that those with individual MH conditions (e.g., depression) had fewer non-MH providers (IRR range: 0.86-0.98) and more concentrated care (OR range: 1.04-1.20). A similar pattern was observed when examining combinations of MH conditions (IRR range: 0.80-0.90; OR range: 1.16-1.30).

CONCLUSIONS

Contrary to expectations, having a MH condition was associated with less fragmented non-MH care among older, high-risk Veterans. Further research will determine if this is due to different needs, underuse, or appropriate use of healthcare.