Impact of RA treatment strategies on lipids and vascular inflammation in rheumatoid arthritis: a secondary analysis of the TARGET randomized active comparator trial.

BACKGROUND: Treatments for rheumatoid arthritis (RA) are associated with complex changes in lipids and lipoproteins that may impact cardiovascular (CV) risk. The objective of this study was to examine lipid and lipoprotein changes associated with two common RA treatment strategies, triple therapy or tumor necrosis factor inhibitor (TNFi), and association with CV risk. METHODS: In this secondary data analysis of the TARGET trial, methotrexate (MTX) inadequate responders with RA were randomized to either add sulfasalazine and hydroxychloroquine (triple therapy), or TNFi for 24-weeks. The primary trial outcome was the change in arterial inflammation measured in the carotid arteries or aorta by FDG-PET/CT at baseline and 24-weeks; this change was described as the target-to-background ratio (TBR) in the most diseased segment (MDS). Routine lipids and advanced lipoproteins were measured at baseline and 24-weeks; subjects on statin therapy at baseline were excluded. Comparisons between baseline and follow-up lipid measurements were performed within and across treatment arms, as well as change in lipids and change in MDS-TBR. RESULTS: We studied 122 participants, 61 in each treatment arm, with median age 57 years, 76% female, and 1.5 year median RA disease duration. When comparing treatment arms, triple therapy had on average a larger reduction in triglycerides (15.9 mg/dL, p = 0.01), total cholesterol to HDL-C ratio (0.29, p-value = 0.01), and LDL particle number (111.2, p = 0.02) compared to TNFi. TNFi had on average a larger increase in HDL particle number (1.6umol/L, p = 0.006). We observed no correlation between change in lipid measurements and change in MDS-TBR within and across treatment arms. CONCLUSIONS: Both treatment strategies were associated with improved lipid profiles via changes in different lipids and lipoproteins. These effects had no correlation with change in CV risk as measured by vascular inflammation by FDG-PET/CT. TRIAL REGISTRATION: ClinicalTrials.gov ID NCT02374021.

Gout risk in adults with pre-diabetes initiating metformin.

OBJECTIVE: Despite the strong association between gout and pre-diabetes, the role of metformin in gout among individuals with pre-diabetes remains uncertain. We compared the incidence rates of gout in adults with pre-diabetes starting metformin with those not using antidiabetic treatments. METHODS: We conducted a new-user, propensity score-matched cohort study using electronic health records from an academic health system (2007-2022). Pre-diabetes was defined based on haemoglobin A1c levels. Metformin users were identified and followed from the first metformin prescription date. Non-users of antidiabetic medications were matched to metformin users based on propensity score and the start of follow-up. The primary outcome was incident gout. Cox proportional hazards models estimated the HR for metformin. Linear regression analyses assessed the association between metformin use and changes in serum urate (SU) or C-reactive protein (CRP). RESULTS: We identified 25 064 individuals with pre-diabetes and propensity score-matched 1154 metformin initiators to 13 877 non-users. Baseline characteristics were well balanced (all standardised mean differences <0.1). The median follow-up was 3.9 years. The incidence rate of gout per 1000 person-years was lower in metformin users 7.1 (95% CI 5.1 to 10) compared with non-users 9.5 (95% CI 8.8 to 10.2). Metformin initiation was associated with a reduced relative risk of gout (HR 0.68, 95% CI 0.48 to 0.96). No relationship was found between metformin and changes in SU or CRP. CONCLUSIONS: Metformin use was associated with a reduced risk of gout among adults with pre-diabetes, suggesting that metformin may be important in lowering gout risk in individuals with pre-diabetes.

Classifying Individuals With Rheumatic Conditions as Financially Insecure Using Electronic Health Record Data and Natural Language Processing: Algorithm Derivation and Validation.

OBJECTIVE: We aimed to examine the feasibility of applying natural language processing (NLP) to unstructured electronic health record (EHR) documents to detect the presence of financial insecurity among patients with rheumatologic disease enrolled in an integrated care management program (iCMP). METHODS: We incorporated supervised, rule-based NLP and statistical methods to identify financial insecurity among patients with rheumatic conditions enrolled in an iCMP (n = 20,395) in a multihospital EHR system. We constructed a lexicon for financial insecurity using data from available knowledge sources and then reviewed EHR notes from 538 randomly selected individuals (training cohort n = 366, validation cohort n = 172). We manually categorized records as having "definite," "possible," or "no" mention of financial insecurity. All available notes were processed using Narrative Information Linear Extraction, a rule-based version of NLP. Models were trained using the NLP features for financial insecurity using logistic, least absolute shrinkage operator (LASSO), and random forest performance characteristic and were compared with the reference standard. RESULTS: A total of 245,142 notes were processed from 538 individual patient records. Financial insecurity was present among 100 (27%) individuals in the training cohort and 63 (37%) in the validation cohort. The LASSO and random forest models performed identically and slightly better than logistic regression, with positive predictive values of 0.90, sensitivities of 0.29, and specificities of 0.98. CONCLUSION: The development of a context-driven lexicon used with rule-based NLP to extract data that identify financial insecurity is feasible for use and improved the capture for presence of financial insecurity with high accuracy. In the absence of a standard lexicon and construct definition for financial insecurity status, additional studies are needed to optimize the sensitivity of algorithms to categorize financial insecurity with construct validity.

Biomarkers of Cardiovascular Risk in Patients With Rheumatoid Arthritis: Results From the TARGET Trial.

Cardiovascular disease remains an important comorbidity in patients with rheumatoid arthritis (RA), but traditional models do not accurately predict cardiovascular risk in patients with RA. The addition of biomarkers could improve prediction. METHODS AND RESULTS: The TARGET (Treatments Against RA and Effect on FDG PET/CT) trial assessed whether different treatment strategies in RA differentially impact cardiovascular risk as measured by the change in arterial inflammation on arterial target to background ratio on fluorodeoxyglucose positron emission tomography/computed tomography scans conducted 24 weeks apart. A group of 24 candidate biomarkers supported by prior literature was assessed at baseline and 24 weeks later. Longitudinal analyses examined the association between baseline biomarker values, measured in plasma EDTA, and the change in arterial inflammation target to background ratio. Model fit was assessed for the candidate biomarkers only, clinical variables only, and models combining both. One hundred nine patients with median (interquartile range) age 58 years (53-65 years), RA duration 1.4 years (0.5-6.6 years), and 82% women had biomarkers assessed at baseline and follow-up. Because the main trial analyses demonstrated significant target to background ratio decreases with both treatment strategies but no difference across treatment groups, we analyzed all patients together. Baseline values of serum amyloid A, C-reactive protein, soluble tumor necrosis factor receptor 1, adiponectin, YKL-40, and osteoprotegerin were associated with significant change in target to background ratio. When selected candidate biomarkers were added to the clinical variables, the adjusted R2 improved from 0.20 to 0.33 (likelihood ratio P=0.0005). CONCLUSIONS: A candidate biomarker approach identified several promising biomarkers that associate with baseline and treatment-associated changes in arterial inflammation in patients with RA. These will now be tested in an external validation cohort.

A Mobile Health Application Integrated in the Electronic Health Record for Rheumatoid Arthritis Patient-Reported Outcomes: A Controlled Interrupted Time-Series Analysis of Impact on Visit Efficiency.

OBJECTIVE: Patient-reported outcome (PRO) collection between visits for rheumatoid arthritis (RA) could improve visit efficiency, reducing in-person visits for patients with stable symptoms while facilitating access for those with symptoms. We examined whether a mobile health PRO application integrated in the electronic health record (EHR) could reduce visit volume for those with RA. METHODS: We developed an application for RA that prompted patients every other day to complete brief PRO questionnaires. Results of the application were integrated into the EHR. We tested the application in a controlled interrupted time-series analysis between 2020 and 2023. Rheumatologists received EHR-based messages based on PRO results recommending the patient receive a visit earlier or later than scheduled. The primary outcome was monthly visit volume during the year before versus the year after initiation. RESULTS: A total of 150 patients with RA consented and used the application. The median age was 62 years, 83% were female, 7% had fewer than 2 years of disease, and 50% were seropositive; 150 controls were well matched. Among those in the application cohort, the estimated monthly median visit volume in the year before use of the application was 31.2 (95% confidence interval [95% CI] 28.0-34.3); in controls, this was 30.4 (95% CI 27.3-33.6). In the year using the application, the estimated monthly visit volume was 36.8 (95% CI 33.4-40.3) compared to 38.7 (95% CI 35.2-42.3) in controls. The difference in the differences between the cohorts was not statistically significant (-2.7 visits, 95% CI -9.3 to 4.0). No differences were noted in flare rates or visit delays. CONCLUSION: In this initial trial of a PRO application intervention to improve visit efficiency, we found no association with reduced visit volume.

Assessing clusters of comorbidities in rheumatoid arthritis: a machine learning approach.

BACKGROUND: Comorbid conditions are very common in rheumatoid arthritis (RA) and several prior studies have clustered them using machine learning (ML). We applied various ML algorithms to compare the clusters of comorbidities derived and to assess the value of the clusters for predicting future clinical outcomes. METHODS: A large US-based RA registry, CorEvitas, was used to identify patients for the analysis. We assessed the presence of 24 comorbidities, and ML was used to derive clusters of patients with given comorbidities. K-mode, K-mean, regression-based, and hierarchical clustering were used. To assess the value of these clusters, we compared clusters across different ML algorithms in clinical outcome models predicting clinical disease activity index (CDAI) and health assessment questionnaire (HAQ-DI). We used data from the first 3 years of the 6-year study period to derive clusters and assess time-averaged values for CDAI and HAQ-DI during the latter 3 years. Model fit was assessed via adjusted R2 and root mean square error for a series of models that included clusters from ML clustering and each of the 24 comorbidities separately. RESULTS: 11,883 patients with RA were included who had longitudinal data over 6 years. At baseline, patients were on average 59 (SD 12) years of age, 77% were women, CDAI was 11.3 (SD 11.9, moderate disease activity), HAQ-DI was 0.32 (SD 0.42), and disease duration was 10.8 (SD 9.9) years. During the 6 years of follow-up, the percentage of patients with various comorbidities increased. Using five clusters produced by each of the ML algorithms, multivariable regression models with time-averaged CDAI as an outcome found that the ML-derived comorbidity clusters produced similarly strong models as models with each of the 24 separate comorbidities entered individually. The same patterns were observed for HAQ-DI. CONCLUSIONS: Clustering comorbidities using ML algorithms is not computationally complex but often results in clusters that are difficult to interpret from a clinical standpoint. While ML clustering is useful for modeling multi-omics, using clusters to predict clinical outcomes produces models with a similar fit as those with individual comorbidities.

Public Insurance and Single-Guardian Households Are Associated with Diagnostic Delay in Slipped Capital Femoral Epiphysis.

BACKGROUND: Extensive literature documents the adverse sequelae of delayed diagnosis of slipped capital femoral epiphysis (SCFE), including worsening deformity and surgical complications. Less is known about predictors of delayed diagnosis of SCFE, particularly the effects of social determinants of health. The purpose of this study was to evaluate the impact of insurance type, family structure, and neighborhood-level socioeconomic vulnerability on the delay of SCFE diagnosis. METHODS: We reviewed medical records of patients who underwent surgical fixation for stable SCFE at a tertiary pediatric hospital from 2002 to 2021. We abstracted data on demographic characteristics, insurance status, family structure, home address, and symptom duration. We measured diagnostic delay in weeks from the date of symptom onset to diagnosis. We then geocoded patient addresses to determine their Census tract-level U.S. Centers for Disease Control and Prevention (CDC) and Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index (SVI), using U.S. Census and American Community Survey data. We performed 3 separate logistic regression models to examine the effects of (1) insurance status, (2) family structure, and (3) SVI on a delay of ≥12 weeks (reference, <12 weeks). We adjusted for age, sex, weight status, number of siblings, and calendar year. RESULTS: We identified 351 patients with SCFE; 37% (129) had a diagnostic delay of ≥12 weeks. In multivariable logistic regression models, patients with public insurance were more likely to have a delay of ≥12 weeks than patients with private insurance (adjusted odds ratio [OR], 1.83 [95% confidence interval (CI), 1.12 to 2.97]; p = 0.015) and patients from single-guardian households were more likely to have a delay of ≥12 weeks than patients from multiguardian households (adjusted OR, 1.95 [95% CI, 1.11 to 3.45]; p = 0.021). We did not observe a significant increase in the odds of delay among patients in the highest quartile of overall SVI compared with patients from the lower 3 quartiles, in both the U.S. comparison (adjusted OR, 1.43 [95% CI, 0.79 to 2.58]; p = 0.24) and the Massachusetts comparison (adjusted OR, 1.45 [95% CI, 0.79 to 2.66]; p = 0.23). CONCLUSIONS: The delay in diagnosis of SCFE remains a concern, with 37% of patients with SCFE presenting with delay of ≥12 weeks. Public insurance and single-guardian households emerged as independent risk factors for diagnostic delay. Interventions to reduce delay may consider focusing on publicly insured patients and those from single-guardian households. LEVEL OF EVIDENCE: Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Derivation and external validation of a risk score for clinically important declines in health and function among two longitudinal cohorts of women in the mid-life.

OBJECTIVES: Women in mid-life often develop chronic conditions and experience declines in physical health and function. Identifying factors associated with declines provides opportunity for targeted interventions. We derived and externally validated a risk score for clinically important declines over 10 years among women ages 55-65 using the Physical Component Summary Score (PCS) of the SF-36. DESIGN: Derivation and validation of a risk score. SETTING: Two longitudinal cohorts from sites in the USA were used. PARTICIPANTS: Women from the Study of Women's Health Across the Nation (SWAN) and women from the Women's Health Initiative (WHI) Observational Study and/or clinical trials. OUTCOME MEASURES: A clinically important decline over 10 years among women ages 55-65 using the PCS of the SF-36 predictors was measured at the beginning of the 10 years of follow-up. RESULTS: Seven factors-lower educational attainment, smoking, higher body mass index, history of cardiovascular disease, history of osteoarthritis, depressive symptoms and baseline PCS level-were found to be significant predictors of PCS decline among women in SWAN with an area under the curve (AUC)=0.71 and a Brier Score=0.14. The same factors were associated with a decline in PCS in WHI with an AUC=0.64 and a Brier Score=0.18. Regression coefficients from the SWAN analysis were used to estimate risk scores for PCS decline in both cohorts. Using a threshold of a 30% probability of a significant decline, the risk score created a binary test with a specificity between 89%-93% and an accuracy of 73%-79%. CONCLUSIONS: Seven clinical variables were used to create a valid risk score for PCS declines that was replicated in an external cohort. The risk score provides a method for identifying women at high risk for a significant mid-life PCS decline.

Social Determinants of Health Documentation Among Individuals With Rheumatic and Musculoskeletal Conditions in an Integrated Care Management Program.

OBJECTIVE: Social determinants of health (SDoH), such as poverty, are associated with increased burden and severity of rheumatic and musculoskeletal diseases. This study was undertaken to study the prevalence and documentation of SDoH-related needs in electronic health records (EHRs) of individuals with these conditions. METHODS: We randomly selected individuals with ≥1 International Classification of Diseases, Ninth/Tenth Revision (ICD-9/10) code for a rheumatic/musculoskeletal condition enrolled in a multihospital integrated care management program that coordinates care for medically and/or psychosocially complex individuals. We assessed SDoH documentation using terms for financial needs, food insecurity, housing instability, transportation, and medication access according to EHR note review and ICD-10 SDoH billing codes (Z codes). We used multivariable logistic regression to examine associations between demographic factors (age, gender, race, ethnicity, insurance) and ≥1 (versus 0) SDoH need as the odds ratio (OR) with 95% confidence interval (95% CI). RESULTS: Among 558 individuals with rheumatic/musculoskeletal conditions, 249 (45%) had ≥1 SDoH need documented in EHR notes by social workers, care coordinators, nurses, and physicians. A total of 171 individuals (31%) had financial insecurity, 105 (19%) had transportation needs, 94 (17%) had food insecurity; 5% had ≥1 related Z code. In the multivariable model, the odds of having ≥1 SDoH need was 2.45 times higher (95% CI 1.17-5.11) for Black versus White individuals and significantly higher for Medicaid or Medicare beneficiaries versus commercially insured individuals. CONCLUSION: Nearly half of this sample of complex care management patients with rheumatic/musculoskeletal conditions had SDoH documented within EHR notes; financial insecurity was the most prevalent. Only 5% of patients had representative billing codes suggesting that systematic strategies to extract SDoH from notes are needed.

Physical and Behavioral Factors Associated With Improvement in Physical Health and Function Among US Women During Midlife.

Importance: Women often experience physiological and functional changes in their health during midlife. Identifying women who have clinically important improvements in physical health and function and evaluating the factors associated with these improvements can identify intervention targets at midlife. Objective: To identify factors associated with improvements in physical health and function among women during midlife. Design, Setting, and Participants: Participants were part of the Study of Women's Health Across the Nation (SWAN), a diverse cohort of US women early in midlife, and followed up annually for up to 21 years between 1996 and 2017. Analyses were based on visit 8 (2004-2006) through visit 15 (2015-2017). Statistical analysis was conducted from October 2021 to March 2023. Exposures: Sociodemographic indicators, health status measures, and comorbidities measured at visit 8. Main Outcomes and Measures: The main outcome was a clinically important (≥5 points) improvement in the physical component score (PCS) of the 36-item Short-Form Health Survey between visit 8 and visit 15. Results: Of the 1807 women (at visit 8: mean [SD] age, 54.5 [2.7] years; 898 [50%] White participants) in SWAN who qualified for analysis, 265 (15%) experienced a clinically important improvement in PCS over a median of 11.1 years (IQR, 10.9-11.4 years). Factors associated with improvement in PCS included no financial strain (odds ratio [OR], 1.73; 95% CI, 1.18-2.52), no sleep disturbances (OR, 1.43; 95% CI, 1.05-1.96), no osteoarthritis (OR, 1.42; 95% CI, 1.01-1.99), and having a higher physical activity score (OR, 1.17; 95% CI, 1.00-1.37) as assessed at visit 8. Women who had a higher PCS at visit 8 (OR, 0.84; 95% CI, 0.83-0.86), who had a higher body mass index (OR, 0.95; 95% CI, 0.93-0.97), or who were taking more medications (OR, 0.93; 95% CI, 0.88-0.98) had lower odds of an improved PCS. Conclusions and Relevance: This cohort study of women in midlife suggests that approximately 15% of women experienced clinically important improvements in health and function over an 11-year period. Several potentially modifiable factors associated with improvements may inform women of variables to target for future interventions.

Predictors of low spike antibody response in patients with systemic rheumatic disease after an initial course of COVID-19 vaccination.

BACKGROUND: Patients with rheumatic disease may mount a suboptimal serologic response to COVID-19 vaccination. We evaluated predictors of low antibody response in a clinic-based cohort. METHODS: We conducted a cross-sectional study using electronic health record (EHR) data at Brigham and Women's Hospital, Boston, MA. Patients with systemic rheumatic disease that had SARS-CoV-2 spike antibody (Ab) tested using the Roche Elecsys immunoassay, February-August 2021, after 2 doses of mRNA vaccine or 1 dose of adenovirus vector vaccine were identified. Demographics, systemic rheumatic disease, vaccination dates, and disease-modifying antirheumatic drugs (DMARDs) were extracted. The primary outcome was low spike Ab (≤ 200 U/mL). Logistic regression models estimated predictors of low spike Ab. RESULTS: Among 382 patients, the mean age was 57 years, 77% were female, and 37% had low spike Ab. Older age (OR 1.03, 95% CI [1.02, 1.05]), SLE (OR 4.81 [2.08, 8.43], reference: inflammatory arthritis), prednisone (OR 1.67 [1.03, 2.74]), and rituximab (OR 22.91 [9.85, 53.29]) were significantly associated with higher odds of low spike Ab. Use of csDMARD monotherapy (OR 0.12 [0.04, 0.33]) and JAK inhibitors (OR 0.41 [0.18, 0.92]) were associated with significantly lower odds for low spike Ab. After adjusting for systemic rheumatic disease and DMARDs, SLE and rituximab remained significantly associated with low spike Ab. CONCLUSIONS: Over a third of patients with systemic rheumatic disease with spike Ab tested in routine care had low spike Ab after 2 doses of mRNA or 1 dose of adenovirus vector COVID-19 vaccine. SLE and rituximab were significant risk factors for low spike Ab. KEY POINTS: • More than one-third of patients with systemic rheumatic disease that had spike Ab tested in routine care had low spike Ab after 2 doses of mRNA or 1 dose of adenovirus vector COVID-19 vaccine. • Diagnosis of SLE, use of prednisone, and use of rituximab were significantly associated with greater odds of low spike antibodies. • These data underscore the importance of additional doses of COVID-19 vaccine and prophylactic Evusheld in immunosuppressed patients with systemic rheumatic disease as recommended by the US Centers for Disease Control.

Association of Area-Level Heat and Social Vulnerability With Recurrent Hospitalizations Among Individuals With Rheumatic Conditions.

OBJECTIVE: Climate and social vulnerability contribute to morbidity and health care utilization. We examined associations between the neighborhood Social Vulnerability Index (SVI) and the Heat Vulnerability Index (HVI) and recurrent hospitalizations among individuals with rheumatic conditions. METHODS: Using a Massachusetts multihospital centralized clinical data repository, we identified individuals ≥18 years of age with a rheumatic condition who received rheumatology care within 3 years of April 2021. We defined the index date as 2 years before the last encounter and the baseline period as 1 year pre-index date. Addresses were geocoded and linked by census tract to the SVI and the HVI. We used multilevel, multinomial logistic regression to examine the odds of 1-3 and ≥4 hospitalizations (reference = 0) over 2 years post index date by vulnerability index, adjusting for age, gender, race/ethnicity, insurance, and comorbidities. RESULTS: Among 14,401 individuals with rheumatic conditions, the mean ± age was 61.9 ± 15.7 years, 70% were female, 79% White, 7% Black, and 2% Hispanic. There were 8,251 hospitalizations; 11,649 individuals (81%) had 0 hospitalizations, 2,063 (14%) had 1-3, and 689 (5%) had ≥4. Adjusting for individual-level factors, individuals living in the highest versus lowest SVI areas had 1.84 times higher odds (95% confidence interval [95% CI] 1.43-2.36) of ≥4 hospitalizations. Individuals living in the highest versus lowest HVI areas had 1.64 times greater odds (95% CI 1.17-2.31) of ≥4 hospitalizations. CONCLUSION: Individuals with rheumatic conditions living in areas with high versus low social and heat vulnerability had significantly greater odds of recurrent hospitalizations. Studies are needed to determine modifiable factors to mitigate risks.

Reducing cardiovascular risk with immunomodulators: a randomised active comparator trial among patients with rheumatoid arthritis.

OBJECTIVE: Recent large-scale randomised trials demonstrate that immunomodulators reduce cardiovascular (CV) events among the general population. However, it is uncertain whether these effects apply to rheumatoid arthritis (RA) and if certain treatment strategies in RA reduce CV risk to a greater extent. METHODS: Patients with active RA despite use of methotrexate were randomly assigned to addition of a tumour necrosis factor (TNF) inhibitor (TNFi) or addition of sulfasalazine and hydroxychloroquine (triple therapy) for 24 weeks. Baseline and follow-up 18F-fluorodeoxyglucose-positron emission tomography/CT scans were assessed for change in arterial inflammation, an index of CV risk, measured as an arterial target-to-background ratio (TBR) in the carotid arteries and aorta. RESULTS: 115 patients completed the protocol. The two treatment groups were well balanced with a median age of 58 years, 71% women, 57% seropositive and a baseline disease activity score in 28 joints of 4.8 (IQR 4.0, 5.6). Baseline TBR was similar across the two groups. Significant TBR reductions were observed in both groups-ΔTNFi: -0.24 (SD=0.51), Δtriple therapy: -0.19 (SD=0.51)-without difference between groups (difference in Δs: -0.02, 95% CI -0.19 to 0.15, p=0.79). While disease activity was significantly reduced across both treatment groups, there was no association with change in TBR (ß=0.04, 95% CI -0.03 to 0.10). CONCLUSION: We found that addition of either a TNFi or triple therapy resulted in clinically important improvements in vascular inflammation. However, the addition of a TNFi did not reduce arterial inflammation more than triple therapy. TRIAL REGISTRATION NUMBER: NCT02374021.

Racial differences in persistent glucocorticoid use patterns among medicaid beneficiaries with incident systemic lupus erythematosus.

OBJECTIVE: Glucocorticoids ("steroids") are frequently used in systemic lupus erythematosus (SLE). Prolonged use may contribute to racial/ethnic disparities in avoidable adverse outcomes. We examined racial/ethnic differences in longitudinal patterns of steroid use and dose. METHODS: We identified Medicaid beneficiaries 18-65 years with incident SLE who received steroids for 12 months following the index date. Group-based trajectory modeling was used to identify patterns of daily prednisone-equivalent steroid doses. We examined demographic, clinical and healthcare utilization factors during the baseline period and used multinomial logistic regression to estimate the odds of belonging to the higher vs. lowest steroid dose trajectories over time. RESULTS: We identified 6314 individuals with SLE with ≥1 dispensed steroid prescription. The mean (SD) prednisone-equivalent dose was 7 (23) mg/day for Black, 7 (26) for Hispanic, 7 (13) for Asian, and 4 (10) for White individuals. Adjusted multinomial models demonstrated higher odds of belonging to the highest vs. lowest steroid trajectory for Black (OR 2.07, 95% CI 1.65-2.61), Hispanic (OR 1.81, 95% CI 1.38-2.39), and Asian (OR 2.42, 95% CI 1.53-3.83) vs. White individuals. Having >5 outpatient visits during the baseline period was associated with lower odds of being in the persistently high-dose steroid trajectory (OR 0.77; 95% CI 0.60-0.98). CONCLUSION: Black, Hispanic, and Asian (vs. White) individuals had higher odds of persistently high-dose steroid use. Sustained access to outpatient care and the development of standardized steroid-tapering regimens from clinical trials with diverse populations may be targets for intervention to mitigate disparities in steroid-related adverse outcomes.

Development and Testing of an Electronic Health Record-Integrated Patient-Reported Outcome Application and Intervention to Improve Efficiency of Rheumatoid Arthritis Care.

OBJECTIVE: Many patients with rheumatoid arthritis (RA) have difficulty finding clinicians to treat them because of workforce shortages. We developed an app to address this problem by improving care efficiency. The app collects patient-reported outcomes (PROs) and can be used to inform visit timing, potentially reducing the volume of low-value visits. We describe the development process, intervention design, and planned study for testing the app. METHODS: We employed user-centered design, interviewing patients and clinicians, to develop the app. To improve visit efficiency, symptom tracking logic alerts clinicians to PRO trends: worsening PROs generate alerts suggesting an earlier visit, and stable or improving PROs generate notifications that scheduled visits could be delayed. An interrupted time-series analysis with a nonrandomized control population will allow assessment of the impact of the app on visit frequency. RESULTS: Patient interviews identified several of the following needs for effective app and intervention design: the importance of a simple user interface facilitating rapid answering of PROs, the availability of condensed summary information with links to more in-depth answers to common questions regarding RA, and the need for clinicians to discuss the PRO data during visits with patients. Clinician interviews identified the following user needs: PRO data must be easy to view and use during the clinical workflow, and there should be reduced interval visits when PROs are trending worse. Some clinicians believed visits could be delayed for patients with stable PROs, whereas others raised concerns. CONCLUSION: PRO apps may improve care efficiency in rheumatology. Formal evaluation of an integrated PRO RA app is forthcoming.

Satisfaction With a Virtual Learning Collaborative Aimed at Implementing Treat-to-Target in Rheumatoid Arthritis.

OBJECTIVE: Limited information is available concerning experiences of participants in a virtual learning collaborative (LC), and little qualitative data or participant feedback on how this format can be improved. One prior in-person LC in rheumatology successfully improved adherence with treat-to-target (TTT) for RA. We conducted a virtual LC on TTT and herein report on participant satisfaction. METHODS: We conducted a virtual LC with 18 rheumatology practices from across the United States during 2020 to 2021. The LC included a virtual kickoff meeting and monthly videoconferences, accompanied by data submission and feedback. At the conclusion of the LC, we surveyed the 45 LC participants concerning individual experience and satisfaction. RESULTS: All sites and 78% of participants responded to the surveys. The LC included small and large practices, 14 academic and 4 nonacademic, and respondents ranged in their roles: 24 physicians, 5 nurses or nurse practitioners, 3 administrators, and 3 other roles. Overall, 94% of respondents indicated they were either somewhat or very satisfied with the LC, and 94% said they would recommend a similar LC to a colleague. Aspects of the LC described as "very useful" included a kickoff meeting, intersite discussion, and monthly speakers; however, digital tools such as the Web site and meeting recordings were not found useful. CONCLUSIONS: Virtual LCs are feasible, and participants reported strong satisfaction. Virtual LCs were highly valued by rheumatologists, trainees, and their practice staffs. Potential topics were identified for future LCs that could improve the quality of care delivered to rheumatology patients.

Pregnancy Intention Screening in Patients With Systemic Rheumatic Diseases: Pilot Testing a Standardized Assessment Tool.

OBJECTIVE: Systemic rheumatic conditions affect reproductive-aged patients and often require potentially teratogenic medications. We assessed the feasibility and impact of a standardized pregnancy intention screening question (One Key Question [OKQ]) in a large academic rheumatology practice. METHODS: This 6-month pilot quality improvement initiative prompted rheumatologists to ask female patients aged 18 to 49 years about their pregnancy intentions using OKQ. We administered surveys to assess rheumatologists' barriers to and comfort with reproductive health issues. We performed chart reviews to assess uptake and impact on documentation, comparing charts with OKQ documented with 100 randomly selected charts eligible for pregnancy intention screening but without OKQ documented. RESULTS: When we compared 32 of 43 preimplementation responses with 29 of 41 postimplementation responses, the proportion of rheumatologists who reported they were very comfortable with assessing their patients' reproductive goals increased (31%-38%) and the proportion reporting obstetrics and gynecology (OB/GYN) referral challenges as barriers to discussing reproductive goals decreased (41%-21%). During the implementation period, 83 of 957 (9%) eligible patients had OKQ documented in their chart. Female providers were more likely to screen than male providers (odds ratio 2.42, 95% confidence interval 1.21-4.85). Screened patients were more likely to have their contraceptive method documented (P < 0.001) and more likely to have been referred to OB/GYN for follow-up (P = 0.003) compared with patients who were not screened with OKQ. CONCLUSION: Although uptake was low, this tool improved provider comfort with assessing reproductive goals, the quality of documentation, and the likelihood of OB/GYN referral. Future studies should examine whether automated medical record alerts to prompt screening increase uptake.

Implementing a Treat-to-Target Approach for Rheumatoid Arthritis During the COVID-19 Pandemic: Results of a Virtual Learning Collaborative Program.

OBJECTIVE: A treat-to-target (TTT) approach improves outcomes in rheumatoid arthritis (RA). In prior work, we found that a learning collaborative (LC) program improved implementation of TTT. We conducted a shorter virtual LC to assess the feasibility and effectiveness of this model for quality improvement and to assess TTT during virtual visits. METHODS: We tested a 6-month virtual LC in ambulatory care. The LC was conducted during the 2020-2021 COVID-19 pandemic when many patient visits were conducted virtually. All LC meetings used videoconferencing and a website to share data. The LC comprised a 6-hour kickoff session and 6 monthly webinars. The LC discussed TTT in RA, its rationale, and rapid cycle improvement as a method for implementing TTT. Practices provided de-identified patient visit data. Monthly webinars reinforced topics and demonstrated data on TTT adherence. This was measured as the percentage of TTT processes completed. We compared TTT adherence between in-person visits versus virtual visits. RESULTS: Eighteen sites participated in the LC, representing 45 rheumatology clinicians. Sites inputted data on 1,826 patient visits, 78% of which were conducted in-person and 22% of which were held in a virtual setting. Adherence with TTT improved from a mean of 51% at baseline to 84% at month 6 (P for trend < 0.001). Each aspect of TTT also improved. Adherence with TTT during virtual visits was lower (65%) than during in-person visits (79%) (P < 0.0001). CONCLUSION: Implementation of TTT for RA can be improved through a relatively low-cost virtual LC. This improvement in TTT implementation was observed despite the COVID-19 pandemic, but we did observe differences in TTT adherence between in-person visits and virtual visits.

Factors Associated With 10-Year Declines in Physical Health and Function Among Women During Midlife.

Importance: Women in midlife often develop chronic conditions and experience declines in physical health and function. Identifying factors associated with declines in physical health and function among these women may allow for targeted interventions. Objective: To examine the factors associated with clinically important 10-year declines in the physical component summary score (PCS) of the Short Form 36 (SF-36), a widely used patient-reported outcome measure, in women in midlife. Design, Setting, and Participants: This longitudinal cohort study collected data from geographically dispersed sites in the US. Participants were part of the Study of Women's Health Across the Nation (SWAN), a racially and ethnically diverse cohort of women enrolled at or immediately before the menopause transition. Women have been followed for up to 21 years, between 1996 and 2016, with annual visits. Data were analyzed from October 2020 to March 2021. Exposures: Demographic indicators, health status measures, and laboratory and imaging assessments. Main Outcomes and Measures: The main outcome was a clinically important decline (≥8 points) on the PCS, based on the 10-year difference in scores between ages 55 and 65 years. Results: From the SWAN cohort of 3302 women, 1091 women (median [IQR] age, 54.8 [54.3-55.4] years; 264 [24.2%] Black women; 126 [11.6%] Chinese women; 135 [12.4%] Japanese women; 566 [51.9%] White women) were eligible for analyses based on duration of follow-up and availability of SF-36 data. At age 55, women had a median (IQR) body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) of 27.0 (23.2-32.6), a median (IQR) baseline PCS of 53.1 (46.8-56.7), 108 women (9.9%) were current smokers, and 938 women (86.3%) had at least 1 comorbidity. Between ages 55 and 65 years, the median (IQR) change in PCS was -1.02 (-6.11 to 2.53) points with 206 women (18.9%) experiencing declines of 8 points or more. In multivariable models, factors associated with clinically important decline included higher baseline PCS (odds ratio [OR], 1.08; 95% CI, 1.06-1.11), greater BMI (OR, 1.06; 95% CI, 1.03-1.09), less educational attainment (OR, 1.87; 95% CI, 1.32-2.65), current smoking (OR, 1.93; 95% CI, 1.14-3.26), osteoarthritis (OR, 1.46; 95% CI, 1.01-2.09), clinically significant depressive symptoms (OR, 2.03; 95% CI, 1.34-3.09), and cardiovascular disease (OR, 2.06; 95% CI, 1.26-3.36). Conclusions and Relevance: In this cohort study, clinically important declines in women's physical health and function were relatively common between ages 55 and 65 years. Several variables associated with these declines were identified as potentially useful components in a clinical score identifying women at increased risk of physical health and functional declines.

The relationship between 19-year trends in medication use and changes in physical function among women in the mid-life: A Study of Women's Health Across the Nation pharmacoepidemiology study.

PURPOSE: Medication side effects are a major concern in aging adults who report using an increasing number of medications. The relationship between accumulating medication use and physical function has not been examined in a longitudinal cohort. METHODS: We conducted a longitudinal cohort study using prospectively collected data from the Study of Women's Health Across the Nation (SWAN). Community-dwelling women from five US cities were followed for up to 20 years. The exposure of interest was the number of prescription medications. They were examined as a count variable and then for specific categories of medication. The outcome of interest was physical function measured repeatedly using the short form (SF)-36 physical function (PF) scale. Linear mixed models, using repeated measures of sociodemographics and comorbidities were assessed. RESULTS: 1452 participants qualified for the analyses with a median follow-up of 19.2 years. At baseline, the mean age was 46.5 years and 53.5% reported White race. Fully adjusted models demonstrated a reduction in the SF-36 PF of 0.99 for each additional prescription medication used or a 6.14-point reduction for women reporting more than five medications and an 8.92-point reduction among those reporting more than 10 medications. These results were similar across race and ethnicity. Specific medication categories with a significant and largely negative impact (at least a two-point reduction) on physical component score included beta-blockers, analgesics, glucocorticoids, anticonvulsants, anxiolytics, anticoagulants, and anti-depressants. CONCLUSIONS: There is a moderate association between increasing medication use and decreasing physical function among women transitioning through the mid-life.