A promise of machine learning in health care is the avoidance of biases in diagnosis and treatment; a computer algorithm could objectively synthesize and interpret the data in the medical record. ...Integration of machine learning with clinical decision support tools, such as computerized alerts or diagnostic support, may offer physicians and others who provide health care targeted and timely information that can improve clinical decisions. Machine learning algorithms, however, may also be subject to biases. The biases include those related to missing data and patients not identified by algorithms, sample size and underestimation, and misclassification and measurement error. There is concern that biases and deficiencies in the data used by machine learning algorithms may contribute to socioeconomic disparities in health care. This Special Communication outlines the potential biases that may be introduced into machine learning–based clinical decision support tools that use electronic health record data and proposes potential solutions to the problems of overreliance on automation, algorithms based on biased data, and algorithms that do not provide information that is clinically meaningful. Existing health care disparities should not be amplified by thoughtless or excessive reliance on machines.
Electronic health records (EHRs) are widely used in epidemiological research, but the validity of the results is dependent upon the assumptions made about the healthcare system, the patient, and the ...provider. In this review, we identify four overarching challenges in using EHR-based data for epidemiological analysis, with a particular emphasis on threats to validity. These challenges include representativeness of the EHR to a target population, the availability and interpretability of clinical and non-clinical data, and missing data at both the variable and observation levels. Each challenge reveals layers of assumptions that the epidemiologist is required to make, from the point of patient entry into the healthcare system, to the provider documenting the results of the clinical exam and follow-up of the patient longitudinally; all with the potential to bias the results of analysis of these data. Understanding the extent of as well as remediating potential biases requires a variety of methodological approaches, from traditional sensitivity analyses and validation studies, to newer techniques such as natural language processing. Beyond methods to address these challenges, it will remain crucial for epidemiologists to engage with clinicians and informaticians at their institutions to ensure data quality and accessibility by forming multidisciplinary teams around specific research projects.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
To determine factors associated with COVID-19-related death in people with rheumatic diseases.
Physician-reported registry of adults with rheumatic disease and confirmed or presumptive COVID-19 (from ...24 March to 1 July 2020). The primary outcome was COVID-19-related death. Age, sex, smoking status, comorbidities, rheumatic disease diagnosis, disease activity and medications were included as covariates in multivariable logistic regression models. Analyses were further stratified according to rheumatic disease category.
Of 3729 patients (mean age 57 years, 68% female), 390 (10.5%) died. Independent factors associated with COVID-19-related death were age (66-75 years: OR 3.00, 95% CI 2.13 to 4.22; >75 years: 6.18, 4.47 to 8.53; both vs ≤65 years), male sex (1.46, 1.11 to 1.91), hypertension combined with cardiovascular disease (1.89, 1.31 to 2.73), chronic lung disease (1.68, 1.26 to 2.25) and prednisolone-equivalent dosage >10 mg/day (1.69, 1.18 to 2.41; vs no glucocorticoid intake). Moderate/high disease activity (vs remission/low disease activity) was associated with higher odds of death (1.87, 1.27 to 2.77). Rituximab (4.04, 2.32 to 7.03), sulfasalazine (3.60, 1.66 to 7.78), immunosuppressants (azathioprine, cyclophosphamide, ciclosporin, mycophenolate or tacrolimus: 2.22, 1.43 to 3.46) and not receiving any disease-modifying anti-rheumatic drug (DMARD) (2.11, 1.48 to 3.01) were associated with higher odds of death, compared with methotrexate monotherapy. Other synthetic/biological DMARDs were not associated with COVID-19-related death.
Among people with rheumatic disease, COVID-19-related death was associated with known general factors (older age, male sex and specific comorbidities) and disease-specific factors (disease activity and specific medications). The association with moderate/high disease activity highlights the importance of adequate disease control with DMARDs, preferably without increasing glucocorticoid dosages. Caution may be required with rituximab, sulfasalazine and some immunosuppressants.
To investigate baseline use of biologic or targeted synthetic (b/ts) disease-modifying antirheumatic drugs (DMARDs) and COVID-19 outcomes in rheumatoid arthritis (RA).
We analysed the COVID-19 Global ...Rheumatology Alliance physician registry (from 24 March 2020 to 12 April 2021). We investigated b/tsDMARD use for RA at the clinical onset of COVID-19 (baseline): abatacept (ABA), rituximab (RTX), Janus kinase inhibitors (JAKi), interleukin 6 inhibitors (IL-6i) or tumour necrosis factor inhibitors (TNFi, reference group). The ordinal COVID-19 severity outcome was (1) no hospitalisation, (2) hospitalisation without oxygen, (3) hospitalisation with oxygen/ventilation or (4) death. We used ordinal logistic regression to estimate the OR (odds of being one level higher on the ordinal outcome) for each drug class compared with TNFi, adjusting for potential baseline confounders.
Of 2869 people with RA (mean age 56.7 years, 80.8% female) on b/tsDMARD at the onset of COVID-19, there were 237 on ABA, 364 on RTX, 317 on IL-6i, 563 on JAKi and 1388 on TNFi. Overall, 613 (21%) were hospitalised and 157 (5.5%) died. RTX (OR 4.15, 95% CI 3.16 to 5.44) and JAKi (OR 2.06, 95% CI 1.60 to 2.65) were each associated with worse COVID-19 severity compared with TNFi. There were no associations between ABA or IL6i and COVID-19 severity.
People with RA treated with RTX or JAKi had worse COVID-19 severity than those on TNFi. The strong association of RTX and JAKi use with poor COVID-19 outcomes highlights prioritisation of risk mitigation strategies for these people.
The disproportionate impact of coronavirus-2019 (COVID-19) on communities of color is gaining global attention. Current research demonstrates that historically marginalized populations are ...experiencing disproportionate levels of SARS-Cov-2 infection and adverse clinical outcomes. However, research examining whether COVID-19 outcomes vary by race and ethnicity within the rheumatic disease population is limited. This paper will review data showing how SARS-CoV-2 infection has differentially affected racial and ethnic minorities in the general population and those with rheumatic disease. We will also highlight disparities in rheumatic disease risk and severity that existed prior to the pandemic, and discuss recent work examining severe outcomes of COVID-19 in rheumatic disease patients by race and ethnicity. Finally, we propose several actionable steps for the rheumatology community to address COVID-19 health disparities, which may have long-term effects on patients with rheumatic disease.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Behçet's disease (BD), a chronic systemic vasculitis, has distinct geographical and ethnic variation. Data regarding the epidemiology of patients with BD in the U.S. are limited; therefore, we sought ...to describe BD patient characteristics and medication use in the U.S., and compared them with data from patients from endemic regions.
We conducted a cross-sectional study using data from the RISE registry (2014-2018). Patients aged ≥ 18 years with BD were included. Sociodemographic and treatment information was extracted. We compared patients from the RISE registry to data from other published studies of patients with BD from endemic areas.
One thousand three hundred twenty-three subjects with BD from the RISE registry were included. Mean age was 48.7 ± 16.3 years, female to male ratio was 3.8:1, and 66.7% were White. The most frequently used medications included glucocorticoids (67.6%) and colchicine (55.0%). Infliximab and adalimumab were the most used biologics (14.5% and 14.1%, respectively); 3.2% of patients used apremilast. The RISE registry had more women (79.3%), and patients were older compared to previously published BD studies from endemic areas. Methotrexate and TNFi were more commonly reported in RISE (21.8% and 29.4%) compared to studies from Egypt and Turkey. Colchicine, cyclosporine, and cyclophosphamide were more commonly used in cohorts from Egypt, Turkey, and Iran.
Findings from the largest BD dataset in the U.S. suggest that BD patients are predominantly female. Further research is needed to explore the reasons for the higher prevalence of BD among women in the U.S. and its possible impact on disease severity and management.
Objective
Ankylosing spondylitis (AS) is associated with elevated cardiovascular risk, and obesity is a common, modifiable risk factor. Our aims were to assess the relationship of body mass index ...(BMI) with disease activity in AS patients and to assess the extent to which the effect is mediated through exercise.
Methods
We used data from a prospective AS cohort with a median follow‐up of 7 years. To determine the association of BMI (kg/m2) with disease activity as measured by the Ankylosing Spondylitis Disease Activity Score (ASDAS), we used generalized estimating equations with inverse probability weighting to account for repeated measures per subject and time‐varying confounding. To estimate the direct effect of overweight/obese BMI on disease activity and the indirect effect through exercise, we performed a mediation analysis.
Results
There were 183 subjects with available BMI and disease activity data (77% male, 70% White, mean ± SD age 40.8 ± 13.3 years). Higher BMI was significantly associated with higher disease activity over time; on average, for a 1 kg/m2 higher BMI, the ASDAS was 0.06 units higher (95% confidence interval 0.04–0.08) after adjustment for important confounders. The direct effect of an overweight/obese BMI accounted for most of the total effect on disease activity, with a smaller indirect effect mediated by exercise (7%).
Conclusion
Higher BMI was associated with higher disease activity in a prospective AS cohort. We found that being overweight/obese largely influenced disease activity directly rather than indirectly through exercise. Other mechanisms, such as increased inflammation, may better explain the obesity–disease activity association.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Objective
Racial/ethnic minorities experience more severe outcomes of coronavirus disease 2019 (COVID‐19) in the general US population. This study was undertaken to examine the association between ...race/ethnicity and COVID‐19 hospitalization, ventilation status, and mortality in people with rheumatic disease.
Methods
US patients with rheumatic disease and COVID‐19 were entered into the COVID‐19 Global Rheumatology Alliance physician registry between March 24, 2020 and August 26, 2020 were included. Race/ethnicity was defined as White, African American, Latinx, Asian, or other/mixed race. Outcome measures included hospitalization, requirement for ventilatory support, and death. Multivariable regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) adjusted for age, sex, smoking status, rheumatic disease diagnosis, comorbidities, medication use prior to infection, and rheumatic disease activity.
Results
A total of 1,324 patients were included, of whom 36% were hospitalized and 6% died; 26% of hospitalized patients required mechanical ventilation. In multivariable models, African American patients (OR 2.74 95% CI 1.90–3.95), Latinx patients (OR 1.71 95% CI 1.18–2.49), and Asian patients (OR 2.69 95% CI 1.16–6.24) had higher odds of hospitalization compared to White patients. Latinx patients also had 3‐fold increased odds of requiring ventilatory support (OR 3.25 95% CI 1.75–6.05). No differences in mortality based on race/ethnicity were found, though power to detect associations may have been limited.
Conclusion
Similar to findings in the general US population, racial/ethnic minorities with rheumatic disease and COVID‐19 had increased odds of hospitalization and ventilatory support. These results illustrate significant health disparities related to COVID‐19 in people with rheumatic diseases. The rheumatology community should proactively address the needs of patients currently experiencing inequitable health outcomes during the pandemic.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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