Arthritis Care & Research最新文献

Objective: The aim of this research was to determine how common gout flares are after ceasing anti-inflammatory prophylaxis.

Methods: A rapid literature review and meta-analysis were undertaken. PubMed was searched from inception to February 2024. Eligibility criteria included any clinical trial of people with gout with at least one arm starting or intensifying urate-lowering therapy (ULT) with coprescription of anti-inflammatory prophylaxis and that had the percentage of participants experiencing one or more gout flares reported during and after the period of prophylaxis. Random effects meta-analyses were used to generate pooled estimates of the percentage of participants experiencing one or more flares in each period.

Results: Six trials were included, together with aggregated, unpublished data from the VA STOP Gout trial (2,972 participants). Pooled random effects estimates of the percentage of participants having one or more gout flares were 14.7% (95% confidence interval [CI] 11.3-18.5%) during prophylaxis, 29.7% (95% CI 22.9-37.0%) in the three-month period after ceasing prophylaxis, and 12.2% (95% CI 6.8-19.0%) during the last study period. The mean difference in the percentage of participants having one or more gout flare while taking prophylaxis and immediately after ceasing prophylaxis was -14.8.0% (95% CI -21.2% to -8.5%; P < 0.0001). The mean difference from the period immediately following prophylaxis discontinuation compared to the last study period was 16.0% (P < 0.001). Sensitivity analyses indicated no material effects of prophylaxis duration, trial duration, ULT class, or placebo arms.

Conclusion: Gout flares are common after stopping anti-inflammatory prophylaxis but return to levels seen during prophylaxis. Patients should be cautioned about the risk of gout flares and have a plan for effective gout flare management in the three months after stopping anti-inflammatory prophylaxis.

There are over 100 rheumatic diseases and approximately 300,000 children with a pediatric rheumatic disease (PRD) in the United States. The most common PRDs are juvenile idiopathic arthritis (JIA), childhood-onset systemic lupus erythematosus (cSLE), and juvenile dermatomyositis (JDM). Effective and safe medications are essential because there are generally no cures for these conditions. Etanercept was the first biologic therapy for the treatment of JIA, approved in 1999. Since then, other biologic disease-modifying antirheumatic drugs (bDMARDs) and targeted synthetic disease-modifying antirheumatic drugs (tsDMARDs) blocking relevant immunologic pathways have been approved for the treatment of JIA, resulting in a marked improvement of disease prognosis. Conversely, there is only one bDMARD that has been approved for cSLE, but none are approved for the treatment of JDM. Lack of approved therapeutic options, with established dosing regimens and known efficacy and safety, remains a central challenge in the treatment of all PRDs, including autoinflammatory diseases, and for complications of PRDs. This review provides an overview of bDMARD and tsDMARD treatments studied for the treatment of various subtypes of JIA, summarizes information from bDMARD studies in other PRDs, with a focus on pivotal trials that led to regulatory approvals, and highlights improved outcomes in patients with JIA with the reception of these newer medications. Further, we outline barriers and challenges in the treatment of other PRDs. Last, we summarize the current regulatory landscape for bDMARD studies and medication approvals for patients with PRDs.

Objective: We aimed to characterize patients with hand osteoarthritis (OA) with deteriorating or improving hand pain and to investigate patients achieving good clinical outcome after four years.

Methods: We used four-year annual Australian/Canadian Hand Osteoarthritis Index (AUSCAN) pain subscale (range 0-20) measurements from the Hand OSTeoArthritis in Secondary Care cohort (patients with hand OA). Pain changes were categorized as deterioration, stable, and improvement using the Minimal Clinical Important Improvement. Good clinical outcome was categorized using the Patient Acceptable Symptom State (PASS). Associations between baseline characteristics (patient and disease characteristics, coping styles, and illness perceptions) and outcomes were investigated using multinomial or binary logistic regression, adjusted for baseline pain, age, sex, and body mass index (BMI).

Results: A total of 356 patients (83% female, mean age 60.6 years, mean AUSCAN score 9.1) were analyzed. Pain improved for 38% of patients, deteriorated for 30% of patients, and remained stable for 32% of patients over four years. Four-year pain development followed annual trends. At baseline, 44% of patients reached PASS, and 49% of patients reached PASS at follow-up. Higher BMI, coping through comforting cognitions, and illness comprehension were positively associated with pain deterioration. Higher AUSCAN function score, mental well-being, and illness consequences were negatively associated with pain improvement. Employment (positive) and emotional representations (negative) were associated with both improvement and deterioration. Higher baseline AUSCAN function, tender joint count, and symptoms attributed to hand OA were associated negatively with PASS after four years.

Conclusion: The pain course of patients with hand OA is variable, not inevitably worsening, and various factors may play a role. Whether modification of these risk factors can influence pain outcomes requires further investigation.

Objective: Patients with rheumatoid arthritis (RA) are at increased risk of cardiovascular disease (CVD) including heart failure (HF). However, little is known regarding the relative risks of HF subtypes such as HF with preserved ejection fraction (HFpEF) or reduced ejection fraction (HFrEF) in RA compared with non-RA.

Methods: We identified patients with RA and matched non-RA comparators among participants consenting to broad research from two large academic centers. We identified incident HF and categorized HF subtypes based on EF closest to the HF incident date. Covariates included age, sex, and established CVD risk factors. Cox proportional hazards models were used to estimate the hazard ratios (HRs) for incident HF and HF subtypes.

Results: We studied 1,445 patients with RA and 4,335 matched non-RA comparators (mean age 51.4 and 51.7 years, respectively; 78.7% female). HFpEF was the most common HF subtype in both groups (65% in RA vs 59% in non-RA). Patients with RA had an HR of 1.79 (95% confidence interval [CI] 1.38-2.32) for incident HF compared with those without RA after adjusting for CVD risk factors. Patients with RA had a higher rate of HFpEF (HR 1.99, 95% CI 1.43-2.77), but there was no statistical difference in the HFrEF rate (HR 1.45, 95% CI 0.81-2.60).

Conclusion: RA was associated with a higher rate of HF overall compared with non-RA, even after adjustment for established CVD risk factors. The elevated risk was driven by HFpEF, supporting a role for inflammation in HFpEF and highlighting potential opportunities to address this excess risk in RA.

Objective: Recent research has explored frailty in systemic lupus erythematosus (SLE) using multiple measures. We examined the agreement among frailty measures and the association of each with cross-sectional and longitudinal health outcomes.

Methods: We used data from the California Lupus Epidemiology Study (CLUES) to examine the following measures of frailty: Systemic Lupus International Collaborating Clinics (SLICC) Frailty Index (SLICC-FI), Short Physical Performance Battery (SPPB), and Fatigue, Resistance, Ambulation, Illness, and Loss of Weight (FRAIL) scale questionnaire. PROMIS Physical Function 10a (PF) was tested as a proxy measure of frailty. Agreement between frailty classifications by each measure was assessed. Cross-sectional associations of frailty classifications with hospitalization, valued life activities disability, cognitive impairment, 6-minute walk test distance, self-reported disease damage, fatigue, and depressive symptoms were assessed with logistic and linear regression analyses. Associations with hospitalization, disease damage increase, and disability increase over the subsequent 3 years were assessed Cox proportional hazards analyses.

Results: Percentages of participants identified as frail varied among the measures, from 10.8% to 45.9%. Agreement among classifications ranged from slight to substantial (κ from 0.17 to 0.63). Most of the frailty measures were associated with both cross-sectional and longitudinal health outcomes, with the notable exception of the SPPB. SLICC-FI had the most consistent association with outcomes, followed by FRAIL and PF.

Conclusion: Multiple measures of frailty appear to identify the risk of poor health outcomes. The intended use, as well as the simplicity and practicality of implementing the measure, may be the most important considerations in choosing a frailty measure.

Objective: Patient education materials (PEMs) can help promote health literacy (HL) among patients. However, their use depends on how easily patients can read and comprehend the information. Several national organizations recommend that text be written at a sixth- to eighth-grade level. Herein, we assess and compare the readability and comprehension (RC) of PEMs for rheumatologic and general medical conditions.

Methods: We used six standardized RC metrics including the well-known Flesch Kincaid Readability Ease and Flesch Kincaid Grade Level to evaluate the RC of PEMs (n = 175) on the American College of Rheumatology (ACR) (n = 86) and the Journal of the American Medical Association (JAMA) (n = 89) websites. Two-sided t-tests compared RC between the two resources. P ≤ 0.05 was considered significant.

Results: On all six standardized metrics used, the mean reading level of all PEMs ranged from high school to college level. For example, the mean ± SD of Simple Measure of Gobbledygook was 10.89 ± 1.88, corresponding to a 10th-grade education, and the mean ± SD of Gunning Fog Score was 14.39 ± 2.49, corresponding to a 14th-grade education required to understand the text. JAMA PEMs had significantly more difficult RC levels compared to ACR PEMs based on five of the six indices used (P < 0.05).

Conclusion: PEMs available on the ACR and JAMA websites do not align with national organizations' recommendations for RC levels. To enhance patient understanding and promote HL, existing PEMs must be modified in line with these recommendations.