The Risk of Lung Cancer in Rheumatoid Arthritis and Rheumatoid Arthritis-Associated Interstitial Lung Disease.

OBJECTIVE: We aimed to evaluate lung cancer risk in patients with rheumatoid arthritis (RA) and RA-interstitial lung disease (ILD). METHODS: We performed a retrospective, matched cohort study of RA and RA-ILD within the Veterans Health Administration (VA) between 2000 and 2019. Patients with RA and RA-ILD were identified with validated administrative-based algorithms, then matched (up to 1:10) on age, gender, and VA enrollment year to individuals without RA. Lung cancers were identified from a VA oncology database and the National Death Index. Conditional Cox regression models assessed lung cancer risk adjusting for race, ethnicity, smoking status, Agent Orange exposure, and comorbidity burden among matched individuals. Several sensitivity analyses were performed. RESULTS: We matched 72,795 patients with RA with 633,937 patients without RA (mean age 63 years; 88% male). Over 4,481,323 patient-years, 17,099 incident lung cancers occurred. RA was independently associated with an increased lung cancer risk (adjusted hazard ratio [aHR] 1.58 [95% confidence interval (CI) 1.52-1.64]), which persisted in never smokers (aHR 1.65 [95% CI 1.22-2.24]) and in those with incident RA (aHR 1.54 [95% CI 1.44-1.65]). Compared to non-RA controls, prevalent RA-ILD (n = 757) was more strongly associated with lung cancer risk (aHR 3.25 [95% CI 2.13-4.95]) than RA without ILD (aHR 1.57 [95% CI 1.51-1.64]). Analyses of both prevalent and incident RA-ILD produced similar results (RA-ILD vs non-RA aHR 2.88 [95% CI 2.45-3.40]). CONCLUSION: RA was associated with a >50% increased risk of lung cancer, and those with RA-ILD represented a particularly high-risk group with an approximate three-fold increased risk. Increased lung cancer surveillance in RA, and especially RA-ILD, may be a useful strategy for reducing the burden posed by the leading cause of cancer death.

Missed opportunities for treatment of inflammatory arthritis and factors associated with non-treatment: An observational cohort study in United States Veterans with rheumatoid arthritis, psoriatic arthritis, or ankylosing spondylitis.

OBJECTIVE: To identify factors associated with non-treatment with biologic and non-biologic disease modifying anti-rheumatic drugs (DMARDs) during the 12 months after initial inflammatory arthritis (IA) diagnosis. METHODS: We identified Veterans with incident IA diagnosed in 2007-2019. We assessed time to treatment with Kaplan-Meier curves. We identified associations between non-treatment and factors relating to patients, providers, and the health system with multivariate Generalized Estimation Equation (GEE) log-Poisson. Subgroup analyses included IA subtypes (rheumatoid arthritis [RA], psoriatic arthritis [PsA], and ankylosing spondylitis [AS]) and timeframes of the initial IA diagnosis (2007-11, 2012-15, and 2016-19). RESULTS: Of 18,318 study patients, 40.7 % did not receive treatment within 12 months after diagnosis. In all patients, factors associated with non-treatment included Black race (hazard ratio, 95 % confidence interval: 1.13, 1.08-1.19), Hispanic ethnicity (1.14, 1.07-1.22), Charlson Comorbidity Index ≥2, (1.15, 1.11-1.20), and opiate use (1.09, 1.05-1.13). Factors associated with higher frequency of DMARD treatment included married status (0.86, 0.81-0.91); erosion in joint imaging report (HR: 0.86, 0.81-0.91); female diagnosing provider (0.90, CI: 0.85-0.96), gender concordance between patient and provider (0.91, CI: 0.86-0.97), and diagnosing provider specialty of rheumatology (0.53, CI: 0.49-0.56). CONCLUSION: A high proportion of Veterans with IA were not treated with a biologic or non-biologic DMARD within one year after their initial diagnosis. A wide range of factors were associated with non-treatment of IA that may represent missed opportunities for improving the quality of care through early initiation of DMARDs.

Diversity, equity, and inclusion (DEI) in medical education: DEI at the bedside.

BACKGROUND: The ability to recognize and address bias is an important communication skill not typically addressed during training. We describe the design of an educational curriculum that aims to identify and change behavior related to diversity, equity, and inclusion (DEI). "DEI at the Bedside" uses the existing infrastructure of bedside teaching and provides a tool to normalize DEI discussions and develop skills to address bias during a neurology inpatient rotation. METHODS: As part of traditional clinical rounds, team members on an inpatient service shared experiences with DEI topics, including bias. The team developed potential responses should they encounter a similar situation in the future. We report the results of our needs assessment and curriculum development to evaluate the feasibility of incorporating a DEI educational curriculum in the neurology inpatient setting. RESULTS: Forty-two DEI experiences were recorded. Medical students were the most frequent discussants (44%). Direction of bias occurred between healthcare team members (33%), against patients (31%), and patients against healthcare team members (28%). Experiences ranged from microaggressions to explicit comments of racism, sexism, and homophobia. CONCLUSIONS: Based on needs assessment data, we developed a DEI educational curriculum for the inpatient neurology setting aimed to improve knowledge and skills related to DEI topics as well as to normalize conversation of DEI in the clinical setting. Additional study will demonstrate whether this initiative translates into measurable and sustained improvement in knowledge of how bias and disparity show up in the clinical setting and behavioral intent to discuss and address them.

Associations between Adiponectin and the Development of Diabetes in Rheumatoid Arthritis.

PURPOSE: We evaluated associations between adiponectin and the risk of diabetes among patients with rheumatoid arthritis (RA), a systemic inflammatory disease associated with metabolic disturbance. METHODS: This prospective cohort study included adults with RA from the Veteran's Affairs Rheumatoid Arthritis Registry. Adiponectin and inflammatory cytokines/chemokines were measured at enrollment on stored serum samples. Adiponectin levels were categorized and clinical variables were described across categories (<10 µg/mL; 10-40 µg/mL; > 40 µg/mL. Multivariable Cox proportional hazard models evaluated associations between adiponectin and incident diabetes adjusting for age, sex, race, smoking status, body mass index (BMI), disease-modifying therapy use, calendar year, and comorbidity. Testing for modification of effect in the context of elevated cytokines/chemokines was performed. RESULTS: Among 2595 patients included in the analysis, those with adiponectin levels >40 µg/mL (N = 379; 15%) were older and had lower BMI. There were 125 new cases of diabetes among 1,689 patients without prevalent disease at enrollment. There was an inverse association between adiponectin and incident diabetes, however, the association was positive among patients with adiponectin levels >40 µg/mL. Patients with levels >40 µg/mL were at higher risk compared to those with levels 10-40 µg/mL [HR: 1.70 (1.34,2.16) p < 0.001]. Those with adiponectin levels >40 µg/mL had significantly higher levels of inflammatory cytokines with evidence of a modified effect of adiponectin on diabetes risk in the setting of inflammation. CONCLUSIONS: The relationship between adiponectin and incident diabetes risk is U-shaped in RA. Patients with very high adiponectin levels have greater systemic inflammation and an altered relationship between adiponectin and diabetes risk.

Extracting forced vital capacity from the electronic health record through natural language processing in rheumatoid arthritis-associated interstitial lung disease.

PURPOSE: To develop a natural language processing (NLP) tool to extract forced vital capacity (FVC) values from electronic health record (EHR) notes in patients with rheumatoid arthritis-interstitial lung disease (RA-ILD). METHODS: We selected RA-ILD patients (n = 7485) in the Veterans Health Administration (VA) between 2000 and 2020 using validated ICD-9/10 codes. We identified numeric values in proximity to FVC string patterns from clinical notes in the EHR. Subsequently, we performed processing steps to account for variability in note structure, related pulmonary function test (PFT) output, and values copied across notes, then assigned dates from linked administrative procedure records. NLP-derived FVC values were compared to values recorded directly from PFT equipment available on a subset of patients. RESULTS: We identified 5911 FVC values (n = 1844 patients) from PFT equipment and 15 383 values (n = 4982 patients) by NLP. Among 2610 date-matched FVC values from NLP and PFT equipment, 95.8% of values were within 5% predicted. The mean (SD) difference was 0.09% (5.9), and values strongly correlated (r = 0.94, p < 0.001), with a precision of 0.87 (95% CI 0.86, 0.88). NLP captured more patients with longitudinal FVC values (n = 3069 vs. n = 1164). Mean (SD) change in FVC %-predicted per year was similar between sources (-1.5 [30.0] NLP vs. -0.9 [16.6] PFT equipment; standardized response mean = 0.05 for both). CONCLUSIONS: NLP of EHR notes increases the capture of accurate, longitudinal FVC values by three-fold over PFT equipment. Use of this NLP tool can facilitate pharmacoepidemiologic research in RA-ILD and other lung diseases by capturing this critical measure of disease severity.