Self-reported Rheumatoid Arthritis Research Articles

A novel method to monitor rheumatoid arthritis prevalence using hospital and medication databases

BackgroundMost estimates of rheumatoid arthritis (RA) prevalence, including all official figures in Australia and many other countries, are based on self-report. Self-report has been shown to overestimate RA, but the ‘gold standard’ of reviewing individual medical records is costly, time-consuming and impractical for large-scale research and population monitoring. This study provides an algorithm to estimate RA cases using administrative data that can be adjusted for use in multiple contexts to provide the first approximate RA cohort in Australia that does not rely on self-report.MethodsSurvey data on self-reported RA and medications from 25 467 respondents of the Australian Longitudinal Study on Women’s Health (ALSWH) were linked with data from the national medication reimbursement database, hospital and emergency department (ED) episodes, and Medicare Benefits codes. RA prevalence was calculated for self-reported RA, self-reported RA medications, dispensed RA medications, and hospital/ED RA presentations. Linked data were used to exclude individuals with confounding autoimmune conditions.ResultsOf 25 467 survey respondents, 1367 (5·4%) women self-reported disease. Of the 26 840 women with hospital or ED presentations, 292 (1·1%) received ICD-10 codes for RA. There were 1038 (2·8%) cases by the medication database definition, and 294 cases (1·5%) by the self-reported medication definition. After excluding individuals with other rheumatic conditions, prevalence was 3·9% for self-reported RA, 1·9% based on the medication database definition and 0·5% by self-reported medication definition. This confirms the overestimation of RA based on self-reporting.ConclusionsWe provide an algorithm for identifying individuals with RA, which could be used for population studies and monitoring RA in Australia and, with adjustments, internationally. Its balance of accuracy and practicality will be useful for health service planning using relatively easily accessible input data.

Association of Diet Quality With Risk of Incident Rheumatoid Arthritis in the Women’s Health Initiative

BackgroundVarious foods and nutrients are linked with higher or lower risk of rheumatoid arthritis (RA), yet these associations are inconsistent across studies. Limited research has been done evaluating the association between diet quality and RA in a larger-scale prospective study on postmenopausal women. ObjectiveThe objective of this study was to evaluate the association between dietary quality and risk of incident RA in postmenopausal women. DesignThis was a prospective cohort study as part of the Women’s Health Initiative (WHI), with an average follow-up time of 8.1 years. Baseline diet was measured using a food frequency questionnaire (FFQ). Diet quality was evaluated by the Healthy Eating Index (HEI)-2015 total score. In addition, intake of food groups and nutrients that align with HEI-2015 components was assessed. Participants/settingPostmenopausal women (N = 109 591) were included in this study, which was conducted at various clinical centers across the United States with recruitment from 1993 to 1998. Women’s Health Initiative participants who were missing outcome data, had unreliable/missing FFQ data, or had RA at baseline were excluded. Main outcome measuresThe primary outcome measure was incident RA. Statistical analyses performed Multivariable Cox proportional regression analysis was performed evaluating the association of diet quality with self-reported physician-diagnosed RA after adjusting for age, race, ethnicity, education status, income, and body mass index (BMI). ResultsDuring 857 517 person-years of follow-up, 5823 incident RA cases were identified. After adjustment for multiple comparisons, compared with quartile 1, quartiles 2, 3, and 4 of the HEI-2015 total scores were associated with lower RA risks of 1%, 10%, and 19%, respectively (P-trend < .001). Greater consumption of total fruits (P-trend = .014), whole fruits (P-trend < .0002), total vegetables (P-trend = .008), greens and beans (P-trend < .0002), whole grains (P-trend = .008), and dairy (P-trend = .018) were significantly associated with lower rates of incident RA. Conversely, higher consumption of saturated fat (P-trend = .002) was significantly associated with higher rates of incident RA. ConclusionA higher-quality diet reflected by higher HEI-2015 total scores was inversely associated with incident RA in postmenopausal women.

Association between flavonoid intake and rheumatoid arthritis among US adults

Basic research shows that flavonoids have anti-inflammatory effects that influence rheumatoid arthritis (RA) in rats. Investigating potential dietary interventions for RA helps prevent the onset and progression of the disease. Clinical evidence on the association of flavonoid and subclass intake with RA is lacking. Using three survey cycles of 2007–2008, 2009–2010, and 2017–2018 from the National Health and Nutrition Survey and the United States Department of Agriculture's Food and Nutrient Database for Dietary Studies (FNDDS), we analyzed 7,419 American adults (≥20 years old). The values of flavonoid and subclass intake were calculated using FNDDS. The status questions for self-reported RA were from the NHANES codebook. Weighted analyses, revealed that among the 7,419 participants included in this study (mean age of 44.69 years [standard error, 0.40] and 3,584 [48.31%] were female), 408 met the classification criteria for RA. According to the multivariable logistic regression model, compared with the risk of RA in the first quartile (Q1), the risks of RA in the second quartile (Q2), the third quartile (Q3) and the fourth quartile (Q4) were lower (Q2: OR=0.55, 95% CI: 0.38–0.80; Q3: OR=0.66, 95% CI: 0.44–0.97; Q4: OR=0.64, 95% CI: 0.46–0.89; trend: P=.03). The association between total flavonoids and RA remained significant after full consideration of confounding factors. With regard to the subclasses of flavonoids, high flavanones intake was associated with low RA prevalence in Model 3 (Q3: OR= 0.60, 95% CI:0.39–0.92; Q4: OR = 0.56, 95% CI: 0.32–0.99, trend: P=.02), but no such association was found in the other subclasses. Total flavonoids intake protected against RA, and the risk of developing RA decreased significantly with increasing intake of total flavonoids. Total flavonoids and flavanones were significantly associated with reduced RA risk for the American adult population. We highlighted the importance of employing diverse methodologies to assess the health effects of flavonoids.

Classifying Self-Reported Rheumatoid Arthritis Flares Using Daily Patient-Generated Data From a Smartphone App: Exploratory Analysis Applying Machine Learning Approaches.

The ability to predict rheumatoid arthritis (RA) flares between clinic visits based on real-time, longitudinal patient-generated data could potentially allow for timely interventions to avoid disease worsening. This exploratory study aims to investigate the feasibility of using machine learning methods to classify self-reported RA flares based on a small data set of daily symptom data collected on a smartphone app. Daily symptoms and weekly flares reported on the Remote Monitoring of Rheumatoid Arthritis (REMORA) smartphone app from 20 patients with RA over 3 months were used. Predictors were several summary features of the daily symptom scores (eg, pain and fatigue) collected in the week leading up to the flare question. We fitted 3 binary classifiers: logistic regression with and without elastic net regularization, a random forest, and naive Bayes. Performance was evaluated according to the area under the curve (AUC) of the receiver operating characteristic curve. For the best-performing model, we considered sensitivity and specificity for different thresholds in order to illustrate different ways in which the predictive model could behave in a clinical setting. The data comprised an average of 60.6 daily reports and 10.5 weekly reports per participant. Participants reported a median of 2 (IQR 0.75-4.25) flares each over a median follow-up time of 81 (IQR 79-82) days. AUCs were broadly similar between models, but logistic regression with elastic net regularization had the highest AUC of 0.82. At a cutoff requiring specificity to be 0.80, the corresponding sensitivity to detect flares was 0.60 for this model. The positive predictive value (PPV) in this population was 53%, and the negative predictive value (NPV) was 85%. Given the prevalence of flares, the best PPV achieved meant only around 2 of every 3 positive predictions were correct (PPV 0.65). By prioritizing a higher NPV, the model correctly predicted over 9 in every 10 non-flare weeks, but the accuracy of predicted flares fell to only 1 in 2 being correct (NPV and PPV of 0.92 and 0.51, respectively). Predicting self-reported flares based on daily symptom scorings in the preceding week using machine learning methods was feasible. The observed predictive accuracy might improve as we obtain more data, and these exploratory results need to be validated in an external cohort. In the future, analysis of frequently collected patient-generated data may allow us to predict flares before they unfold, opening opportunities for just-in-time adaptative interventions. Depending on the nature and implication of an intervention, different cutoff values for an intervention decision need to be considered, as well as the level of predictive certainty required.

Is occupational noise associated with arthritis? Cross-sectional evidence from US population

BackgroundThe impact of occupational noise exposure on various diseases, including ear and cardiovascular diseases, has been studied extensively. Nevertheless, the connection between osteoarthritis (OA) and rheumatoid arthritis (RA) and occupational noise exposure remains largely unexplored in real-world scenarios. This study assessed the association between occupational noise exposure and the prevalence of two types of arthritis.MethodsThis study used database data from 2005 to 2012 and 2015–March 2020 from the prepandemic National Health and Nutrition Examination Survey (NHANES) related to occupational noise exposure and arthritis. Multivariate logistic regression analysis was used to estimate the association between occupational noise exposure and RA/OA, adjusting for age, gender, race, education level, marital status, the ratio of family income to poverty, trouble sleeping, smoking status, alcohol consumption, diabetes, hypertension, body mass index (BMI), metabolic equivalents (METs), and thyroid disease.ResultsThis study included 11,053 participants. Multivariate logistic regression analysis demonstrated that previous exposure to occupational noise was positively associated with self-reported RA (OR = 1.43, 95% CI = 1.18–1.73) and OA (OR = 1.25, 95% CI = 1.07–1.46). Compared to individuals without a history of occupational noise exposure, those with an exposure duration of 1 year or greater exhibited higher odds of prevalent RA, though there was no apparent exposure response relationship for noise exposure durations longer than 1 year. The results of our subgroup analyses showed a significant interaction between age and occupational noise exposure on the odds of self-reported prevalent OA.ConclusionsOur findings suggest an association between occupational noise exposure and the prevalence of RA and OA. Nevertheless, further clinical and basic research is warranted to better explore their associations.

Prevalence of Steatotic Liver Disease Among US Adults with Rheumatoid Arthritis.

The prevalence of steatotic liver disease (SLD) among patients with rheumatoid arthritis (RA) remains largely unknown. To investigate the prevalence of SLD and liver fibrosis among patients with RA. We utilized data from the United States (US)-based National Health and Nutrition Examination Survey (NHANES) 2017-2020 cycle. After applying established sample weights, we estimated the age-adjusted prevalence of SLD and its subclassifications (CAP ≥ 285 dB/m), high-risk NASH (FAST score) and liver fibrosis (LSM) among participants with self-reported RA. Multivariable logistic regression was performed to identify independent risk factors for metabolic dysfunction associated SLD (MASLD), high-risk NASH and fibrosis, respectively, among participants with RA. We present adjusted odds ratios (aORs) and 95% confidence intervals (CIs). Age-adjusted prevalence of MASLD among US adults with RA was 34.91% (95% CI: 24.02-47.65%). We also found that the age-adjusted prevalence of high-risk NASH (FAST score > 0.35) and significant fibrosis (LSM > 8.6kPa) was 12.97% (95% CI: 6.89-23.07%) and 10.35% (95% CI: 5.55-18.48%), respectively. BMI ≥ 30kg/m2, (aOR 6.23; 95% CI: 1.95-19.88), diabetes (aOR 5.90; 95% CI: 1.94-17.94), and dyslipidemia (aOR 2.83; 95% CI: 1.12-7.11) were independently associated with higher odds of MASLD among participants with RA. Diabetes (aOR 19.34; 95% CI: 4.69-79.70) was also independently associated with high-risk NASH. The prevalence of MASLD, high-risk NASH, and liver fibrosis among patients with RA is equal or higher than the general population. Future studies of large cohorts are needed to substantiate the role of systemic inflammation in the pathophysiology of MASLD.

Abstract 12 — Prevalence and Risk Factors of Non-Alcoholic Fatty Liver Disease in Patients with Rheumatoid Arthritis: A Nationwide Population-Based Study

Background Rheumatoid arthritis (RA) is a debilitating and financially burdensome disease because of frequent presence of comorbidities including metabolic and cardiovascular abnormalities. Growing evidence suggests a link between RA and nonalcoholic fatty liver disease (NAFLD). We aimed to determine the prevalence and explore the risk factors of developing NAFLD in RA population. Methods This population-based, cross-sectional study utilized data on US adults aged [Formula: see text]20 years old from the National Health and Nutrition Examination Survey (NHANES) 2017-2018, a representative sample of the general US population. Diagnosis of RA was derived from questionnaire data. NAFLD was defined by controlled attenuation parameter (CAP) scores of [Formula: see text]278 dB/m using vibration controlled transient elastography (VCTE) in the absence of other liver disease. Weighted multiple regression analysis was further performed to assess the independent risk factors. Results Of 2,848 people included in this study, 224 of them had self-reported RA. The prevalence of NAFLD in the overall sample was 41%, with a numerically higher prevalence in RA patients than those without arthritis (47% vs. 40%, p=0.30). Compared to those without NAFLD, RA patients with concomitant NAFLD had more prevalent metabolic comorbidities including obese (75% vs. 32%, p=0.006), central obesity (100% vs. 71%, p=0.008), diabetes (39% vs. 14%, p=0.003) and hyperlipidemia (88% vs. 76%, p=0.042). Regarding laboratory findings, RA patients with NAFLD exhibited higher levels of triglyceride (188 mg/dL vs. 131 mg/dL, p=0.010), fasting plasma glucose (131 mg/dL vs. 109 mg/dL, p=0.010) and HbA1c (5.77% vs. 6.41%, p=0.002). Meanwhile, elevated levels of liver enzymes (ALT: 29 U/L vs. 19 U/L, p=0.015; AST: 25 U/L vs. 19 U/L, p=0.007) and inflammatory indicator CRP (5.1 mg/dL vs. 3.4 mg/dL, p&lt;0.001]) were more frequently reported in RA patients with NAFLD as compared with those without. Further, weighted multivariate logistic regression analysis showed that the presence of central obesity (adjusted OR=1.56 [95% CI 1.16-2.11], p=0.008) and diabetes (adjusted OR=1.28 [95% CI 1.07-1.54], p=0.014) were significantly associated with prevalent NAFLD in patients with RA. Conclusion In this population-based study, about one in two patients with RA had NAFLD, which is higher than its overall prevalence among general population. Central obesity and diabetes are predisposing factors for NAFLD in RA. Our results highlight the importance of active NAFLD screening in RA population, especially for high-risk subsets.

Should complete B cell depletion be maintained in patients treated long-term with rituximab for rheumatoid arthritis?

To determine whether persistent complete B cell (BC) depletion was associated with a better clinical response in rheumatoid arthritis (RA) patients long-term treated with rituximab (RTX). We conducted a retrospective study including RA patients admitted for a new infusion between 2019 and 2021. The primary endpoint was the comparison of the mean disease activity score based on 28 joints (DAS28)-CRP at each of the four last infusion visits between patients with persistent complete BC depletion (mean CD19 counts <18/µl at each of the last four visits) or without persistent complete BC depletion (mean CD19 counts of the last four visits ≥18/µl). Secondary endpoints included DAS28, pain/fatigue visual analogue scale, CRP, gammaglobulins and the frequency of self-reported RA flares. Of the 126 patients in maintenance therapy with RTX [exposure period: 76 (5) months, 14 (7) infusions received], 43 (34%) had persistent complete BC depletion at each of the four last infusions. The mean DAS28-CRP calculated at each of the four last infusion visits did not significantly differ according to persistence or not of complete BC depletion. This result remained unchanged after adjusting for antibody status, number of previous therapies, number of RTX infusion and cumulative RTX dose. All secondary outcomes were also not significantly different between the two groups. Maintaining complete BC depletion does not appear to be a therapeutic target to achieve in RA patients in long-term maintenance therapy with RTX. There is a limited benefit of monitoring CD19 in RA patients long-term treated with RTX and having achieved low disease activity/remission.

The association of milk products with rheumatoid arthritis: A cross-sectional study from NHANES

ObjectiveMilk products are a major part of the western diet, but the role of their effect in rheumatoid arthritis (RA) is controversial. The objective of this study was to explore the relationship between milk products and RA in the United States (US) population. MethodsIn the cross-sectional study, a total of 12,813 participants aged 20years or older were selected from the National Health and Nutrition Examination Survey (NHANES). Consumption of milk products was collected by personal interview, and RA status was obtained by self-reported questionnaires. The association between milk products and RA was estimated by using the weighted logistic regression model. ResultsWe found a negative association of once a day or more milk products intake with self-reported RA prevalence (odds ratio [OR]: 0.68; 95% confidence interval [CI]: 0.53 to 0.86; P<0.001). A linear trend between consumption of milk products and the prevalence of RA (P<0.01) was also observed. In subgroup analysis, protective effects of milk products on RA were more pronounced in several groups (i.e., Mexican Americans, highly educated and drinking individuals, etc.). However, no interaction effect of stratification variables and the frequency of milk products intake with RA was detected. After imputing missing data, the sensitivity analysis showed the same association. ConclusionThis study suggested a negative association between consumption of milk products and RA among US population. Further investigations are warranted to validate the causal association and the underlying mechanism.

Machine Learning Approaches to Classify Self-Reported Rheumatoid Arthritis Health Scores Using Activity Tracker Data.

The increasing use of activity trackers in mobile health studies to passively collect physical data has shown promise to lessen participation burden to provide actively contributed patient reported outcome (PRO) information. Our goal was to develop machine learning models to classify patient-reported outcome (PRO) scores using Fitbit data from a cohort of patients with rheumatoid arthritis (RA). The increasing use of activity trackers in mobile health studies to passively collect physical data has shown promise to lessen participation burden to provide actively contributed patient reported outcome (PRO) information. Our goal was to develop machine learning models to classify patient-reported outcome (PRO) scores using Fitbit data from a cohort of patients with rheumatoid arthritis (RA). Two different models were built to classify PRO scores; a random forest (RF) Classifier model that treated each week of observations independently when making weekly predictions of PRO scores, and a hidden Markov model (HMM) that additionally took correlations between successive weeks into account. Analyses compared model evaluation metrics for: 1) a binary task of distinguishing a normal PRO score from a severe PRO score, and 2) a multiclass task of classifying a PRO score state for a given week. For both the binary and multiclass tasks, the HMM significantly (p < 0.05) outperformed the RF for most PRO scores, and the highest AUC, Pearson's Correlation coefficient, and Cohen's Kappa coefficient were 0.751, 0.458, and 0.450 respectively. While further validation of our results and evaluation in a real-world setting yet remains, this study demonstrates the ability of physical activity tracker data to classify health status over time in patients with RA and enables the possibility of scheduling preventive clinical interventions as needed. If patient outcomes can be monitored in real time, there is potential to improve clinical care for patients with other chronic conditions.

Prevalence of rheumatoid arthritis in Greece: results from the national health examination survey EMENO

Rheumatoid arthritis (RA) is considered the most common form of autoimmune arthritis. The disease's prevalence is around 0.5-1% worldwide, but it seems to vary among different populations. The aim of this study was to estimate the prevalence of self-reported diagnosed RA in the general adult population in Greece. The data were derived from the Greek Health Examination Survey EMENO, a population-based survey performed between 2013 and 2016. Of the 6006 participants (response rate 72%), 5884 were eligible for this study. Prevalence estimates were calculated according to the study design. Prevalence of self-reported RA was estimated to be overall 0.5% (95% CI 0.4-0.7) being approximately three times higher in women than in men (0.7% vs 0.2%, p value = 0.004). A decrease in the prevalence of RA was observed in urban areas of the country. In contrast, higher disease rates were reported in individuals with lower socioeconomic status. Multivariable regression analysis showed that gender, age, and income were related to the occurrence of the disease. Osteoporosis and thyroid disease were the two comorbidities observed at statistically significant higher rates in individuals with self-reported RA. The prevalence of self-reported RA in Greece is similar to that reported in other European countries. Gender, age, and income are the main factors related to the disease's prevalence in Greece.

Association of Rheumatoid Arthritis with Opioid Pain Medication Overuse among Persons Exposed to the 9/11 World Trade Center Disaster.

We examined the association of post-9/11 rheumatoid arthritis (RA) diagnosis with opioid pain medication overuse among enrollees in the World Trade Center Health Registry (WTCHR). Opioid overuse was defined as the self-reported intake of prescribed opioids at a higher dosage or more often than directed in the last 12 months on one of the two most recent WTCHR surveys (2015-2016, 2020-2021). Post-9/11 RA was ascertained through self-reports and subsequently validated following medical record release by the enrollees' physicians or medical records review. We excluded those with self-reported RA that was not validated by their physicians and those who did not report being prescribed opioid pain medication in the last 12 months. Multivariable log-binomial regression was conducted to examine the relationship between post-9/11 RA diagnosis and opioid pain medication overuse, adjusting for sociodemographic characteristics and 9/11-related posttraumatic stress disorder (PTSD) symptoms. Of the 10,196 study enrollees, 46 had confirmed post-9/11 RA. The post-9/11 RA patients were mostly females (69.6% vs. 37.7%), less frequently non-Hispanic White (58.7% vs. 73.2%) individuals, and less often had attained a higher level of education (76.1% vs. 84.4%) compared to those without post-9/11 RA. Opioid pain medication overuse was significantly associated with a post-9/11 RA diagnosis (Adjusted Risk Ratio: 2.13, 95% CI: 1.44-3.17). More research is needed to better understand the use and management of prescribed opioids among WTC-exposed individuals with RA.

Association between Coffee Consumption, Caffeine Intake, and Metabolic Syndrome Severity in Patients with Self-Reported Rheumatoid Arthritis: National Health and Nutrition Examination Survey 2003-2018.

Rheumatoid arthritis (RA) is chronic inflammatory disease. Although coffee impacts metabolism, no evidence has shown an association between coffee consumption and decreased risk for developing metabolic syndrome (MetS) among RA patients. Hence, we examined the association between coffee consumption and metabolic syndrome severity among 1094 participants with self-reported RA. Accordingly, patients with MetS z-scores of <0 and ≥0 were designated as low- and high-risk groups, respectively. In the fully adjusted model, drinking over two cups of coffee daily was associated with a decrease in the MetS z-score (p = 0.04). Subgroup analysis showed that in the low-risk group, daily intake of <2 cups of coffee was associated with low MetS z-scores (p = 0.003), scores (p = 0.03). Coffee intake was associated with low body mass index (p = 0.03 for 0−2 cups per day; p = 0.02 for >2 cups per day) and low HOMA-IR (β, −2.62; 95%CI, −5.13 to −0.11; p = 0.04). Our study suggests that coffee, but not decaffeinated coffee consumption and total caffeine intake, is associated with MetS severity in RA.

Driving Impairment and Healthcare Provider Counseling in Rheumatoid Arthritis and Osteoarthritis Patients: A Cross-Sectional Survey

Background/objective: To examine rates of counseling on driving for individuals with osteoarthritis (OA) and/or rheumatoid arthritis (RA) and evaluate the Health Assessment Questionnaire Disability Index (HAQ-DI) as a screening tool for further driving evaluation.Methods: A cross-sectional survey was completed by individuals recruited via ResearchMatch (a national web-based recruitment tool) between March 5 and April 20, 2020. Individuals with a current US driver's license, ≥18 years old, with self-reported OA and/or RA diagnosis were surveyed about driving difficulty and vehicle modification and completed a HAQ-DI assessment. Respondents were dichotomized based on reporting vehicle modification(s) due to arthritis versus no modification(s) for univariate and multivariate analyses.Results: Of 4,435 recruited patients, 304 (6.9%) met inclusion/exclusion criteria and completed the surveys. Of all respondents, 259 (85.2%) reported at least some difficulty with one or more driving activities, but only 47 (15.5%) reported discussion with a physician and/or healthcare professional. A total of 184 (60.5%) respondents had HAQ-DI ≥ 1 and were more likely to report vehicle modification(s) compared to respondents with HAQ-DI score < 1 (OR = 5.00, 95% CI = 2.69-9.32, p < 0.011) after controlling for age, gender, type of arthritis, and driving behaviors.Conclusion: Few respondents report discussion of driving difficulties with healthcare providers, although many report driving-related impairments, particularly those with HAQ-DI scores ≥ 1. Our data suggest a strong association between HAQ-DI scores and vehicle modification. The HAQ-DI may serve as a screening tool to predict a patient’s need for driving evaluation and vehicle modification(s).

Evaluation of Patients With Rheumatoid Arthritis in Teleconsultation During the First Wave of the COVID-19 Pandemic.

To describe which variables were collected by rheumatologists to monitor patients with rheumatoid arthritis (RA) during teleconsultation and identify which ones have more impact on clinician intervention. Retrospective monocentric, routine care cross-sectional study including patients with RA seen in teleconsultation between March and September 2020. Available variables assessing disease status were collected in teleconsultation files. Clinician intervention was defined by treatment escalation and/or the need for a rapid face-to-face consultation or day hospitalization. One hundred forty-three patients with RA were included (116 females, mean age of 58 [SD 16] yrs, mean disease duration of 14 [SD 11] yrs). The presence or absence of patient self-reported RA flares was mentioned in all medical files, followed by the presence and/or the number of tender joints (76%), the duration of morning stiffness (66%), the number of pain-related nocturnal awakenings (66%) and the C-reactive protein (CRP) value (54%). Teleconsultation led to a clinician intervention in 22/143 patients (15%), representing 51% of patients with self-reported flares (22/43 patients). Therapeutic escalation was necessary in 13 patients and/or face-to-face consultation or day hospitalization were organized for 10 patients. Multivariate analysis identified RA flares (odds ratio [OR] 15.6, 95% CI 3.37-68.28) and CRP values > 10 mg/L (OR 3.32, 95% CI % 1.12-13.27) as the variables independently associated with clinician intervention. Our study identified patient-reported RA flares and increased CRP values as 2 red flags in teleconsultation, independently associated with therapeutic modification and/or the need for a rapid face-to-face consultation. These indicators may help clinicians' decision making in teleconsultation.

The association between dietary inflammation index and the risk of rheumatoid arthritis in Americans

The correlation between dietary inflammation index (DII) and rheumatoid arthritis (RA) has been found, but the effect of confounding factors is not considered. This study aims to further explore the association between DII and RA risk by taking the Americans as the research object. The data from the 2005-2018 National Health and Nutrition Examination Survey (NHANES) database included 1819 self-reported RA individuals and 8602 non-RA individuals. The analytical methods include logistic regression, additive model, smooth curve fitting, and the recursive algorithm. There was a positive correlation between DII and RA in Americans (β = 1.068, 95% CI = 1.026 to 1.111, P = 0.001). This result was still presented in the subgroup analysis, including age less than 50years, female, other Hispanics, BMI ≥ 25, and federal poverty rate > 185%, and it was more pronounced in smokers. The results show that the superposition of DII and other risk factors would increase the risk of RA (β > 1.068). In addition, individuals with RA are inadequate in intake of anti-inflammatory foods, in line with the Mediterranean diet. The inflammatory potential of the diet is positively correlated with the risk of RA, and has a superimposed effect with other risk factors, increasing the probability of the risk of disease. These results emphasize that reducing the intake of pro-inflammatory foods may be an effective measure to prevent the onset of rheumatoid arthritis. However, eating anti-inflammatory foods exclusively is not the best option. Intaking some pro-inflammatory foods like protein, energy, and total saturated acids may be necessary to maintain the physiological function of the human body. Key Points • Dietary inflammation index (DII) is positively correlated with RA risk. • When DII and other risk factors appear at the same time, the effects of the two will be superimposed on each other, increasing the risk of RA. • When the DII is the same, Hispanic has a higher incidence of RA. • Among the pro-inflammatory foods, the intake of protein, energy, and saturated fatty acids is still required by RA patients.

Depression and food insecurity among patients with rheumatoid arthritis in NHANES

BackgroundSocial determinants of health (SDH), including food insecurity, are associated with depression in the general population. This study estimated the prevalence of depression and food insecurity and evaluated the impact of food insecurity and other SDH on depression in adults with rheumatoid arthritis (RA).MethodsAdults (≥ 18 years) with RA were identified from the 2013–2014 and 2015–2016 National Health and Nutrition Examination Survey (NHANES). Depression was defined as a score of ≥ 5 (mild depression: 5–9; moderate-to-severe depression: 10–27) using the Patient Health Questionnaire-9 (PHQ-9). Food insecurity was assessed with the 18-item US Household Food Security Survey Module. Adults with household-level marginal-to-very-low food security were classified as experiencing food insecurity. The prevalence of depression and food insecurity among participants with RA were estimated. Weighted logistic regression was used to evaluate the association between depression and participants’ characteristics including SDH. Penalized regression was performed to select variables included in the final multivariable logistic regression.ResultsA total of 251 and 276 participants from the 2013–2014 and the 2015–2016 NHANES, respectively, had self-reported RA. The prevalence of depression among these participants was 37.1% in 2013–2014 and 44.1% in 2015–2016. The prevalence of food insecurity was 33.1% in 2013–2014 and 43.0% in 2015–2016. Food insecurity was associated with higher odds of having depression (OR 2.17, 95% CI 1.27, 3.72), and the association varied by depression severity. Compared with participants with full food security, the odds of having depression was particularly pronounced for those with very low food security (OR 2.96, 95% CI 1.48, 5.90) but was not significantly different for those with marginal or low food security. In the multivariable regression, being female, having fair/poor health condition, any physical disability, and ≥ 4 physical limitations were significantly associated with depression.ConclusionsIn adults with self-reported RA, the prevalence of depression and food insecurity remained high from 2013 to 2016. We found that depression was associated with SDH such as food insecurity, although the association was not statistically significant once adjusted for behavioral/lifestyle characteristics. These results warrant further investigation into the relationship between depression and SDH among patients with RA.

Sunlight Exposure, Sun-Protective Behavior, and Anti-Citrullinated Protein Antibody Positivity: A General Population-Based Study in Quebec, Canada.

To examine associations between sunlight exposure and anti-citrullinated protein antibodies (ACPAs) using general population data in Quebec, Canada. A random sample of 7,600 individuals (including 786 subjects who were ACPA positive and 201 self-reported rheumatoid arthritis [RA] cases) from the CARTaGENE cohort was studied cross-sectionally. All subjects were nested in 4 census metropolitan areas, and mixed-effects logistic regression models were used to calculate odds ratios (ORs) and 95% confidence intervals (95% CIs) for ACPA positivity related to sunlight exposure, adjusting for sun-block use, industrial fine particulate matter (PM2.5 ) exposures, smoking, age, sex, French Canadian ancestry, and family income. We also performed sensitivity analyses excluding subjects with RA, defining ACPA positivity by higher titers, and stratifying by age and sex. The adjusted ORs and 95% CIs did not suggest conclusive associations between ACPA and sunlight exposure or sun-block use, but robust positive relationships were observed between industrial PM2.5 emissions and ACPA (OR 1.19 per μg/m3 [95% CI 1.03-1.36] in primary analyses). We did not see clear links between ACPA and sunlight exposure or sun-block use, but we did note positive associations with industrial PM2.5 . Future studies of sunlight and RA (or ACPA) should take air pollution exposures into account.

Patient satisfaction, preferences, expectations, characteristics, and impact of suboptimal control of rheumatoid arthritis: A subgroup analysis of Japanese patients from a large international cohort study (SENSE).

ObjectiveTo evaluate treatment satisfaction, disease outcomes, and perspectives of patients with poorly controlled rheumatoid arthritis (RA) treated with conventional synthetic, targeted synthetic, or biologic disease-modifying antirheumatic drugs (DMARDs), we conducted a subgroup (post hoc) analysis of Japanese patients participating in the SENSE study.MethodsData for Japanese patients (n/N = 118/1629) from the global, multicenter, cross-sectional, observational SENSE study were analyzed. The primary endpoint was the global satisfaction subscore assessed using the Treatment Satisfaction Questionnaire for Medication (TSQM) version 1.4. Other patient-reported outcomes included self-reported RA medication adherence and Work Productivity and Activity Impairment-RA. Patient perspectives included patients’ expectations and preference of pharmacologic treatment.ResultsMedian (range) age and RA disease duration were 67.0 (18.0–87.0) years and 8 (0.0-54) years, respectively; 81.4% of patients were female. Mean (SD) TSQM global satisfaction subscore was 56.8 (17.5), and only 5.9% of patients reported good satisfaction with treatment (TSQM global ≥80). Mean (SD) self-reported treatment adherence using VAS was high (93.5% [13.8%]). Mean (SD) total work productivity impairment was 45.6% (32.0%); presenteeism contributed toward more total work productivity impairment (43.9% [30.4%]) than absenteeism (8.3% [24.4%]). Patients expected improvement in all parameters from their treatment, especially improvement in joint symptoms. Most patients (80.7%) preferred oral medication and 18.7% preferred monotherapy. Patient acceptability of potentially manageable side effects was high (7.5%-34.0%). Although most patients (81.3%) found combination therapy acceptable, 43.2% were receiving DMARD monotherapy.ConclusionAlthough most Japanese patients with RA with moderate-to-high disease activity were dissatisfied with their current DMARD treatment, high treatment adherence, high acceptability of combination therapy, high acceptability of manageable potential side effects, and preference for oral medication were reported. Data support the development of a more individualized and patient-centric approach for RA treatment.

Prevalence Trend and Disparities in Rheumatoid Arthritis among US Adults, 2005–2018

Rheumatoid arthritis (RA) trends among US adults and disparities in RA patients in recent years have not been well described. We aimed to examine the trend of RA prevalence and disparities among US adults. Data from the National Health and Nutrition Examination Survey (NHANES) of the years 2005–2018 were analyzed to examine the self-reported RA prevalence trend. Age-adjusted RA prevalence stratified by race/ethnicity and socioeconomic status (SES), as well as associated linear trends, were calculated for both genders. The multivariable adjustment was used to evaluate the association between race, SES, and RA. During 2005–2018, there was no significant linear trend in the age-adjusted self-reported RA prevalence among men and women, but significant differences among people from different races, educational levels, and family poverty income ratio (PIR) groups were observed. The RA rate difference was significant for both genders and between Non-Hispanic Caucasians and Non-Hispanic African Americans (both p-value ≤ 0.001). Both men and women with a higher educational level and a higher PIR had a lower age-adjusted RA rate. Age-adjusted RA prevalence fluctuated for both men and women during 2005–2018. Non-Hispanic African Americans and people with low SES had significantly higher age-adjusted RA prevalence and RA risk.