Giant cell arteritis treatment patterns and rates of serious infections.

OBJECTIVES: Giant cell arteritis (GCA) afflicts older adults who may have age- and comorbidity-related risks for infection and is treated with immunosuppressants that increase risk of infection. We examined GCA treatment patterns and rates of serious infections in two real-world cohorts in the U.S. METHODS: We identified two GCA cohorts using two U.S. health insurance databases, Medicare (public, 2007-2017) and MarketScan (commercial, 2015-2019), by applying a validated claims-based algorithm with positive predictive value 79.0% for GCA. We required age ≥50 years and assessed baseline comorbidities, dispensing of immunosuppressants and prophylactic antibiotics, and vaccine administration. We calculated incidence rates (IR) of serious infections, defined as bacterial or viral infections requiring hospitalisation based on primary inpatient diagnosis code. Multivariable Cox proportional hazards models estimated hazard ratios for risk of serious infection for prespecified covariates. RESULTS: The Medicare cohort included 734 patients, 28% male, mean age 77.1; the MarketScan cohort included 1022 patients, 30% male, mean age 68.4. More than 85% used prednisone ≥60mg daily at index date and <10% used tocilizumab. Serious infections developed in 27.9% of Medicare and 7.2% of MarketScan patients: IR per 100 person-years = 10.7 (95% CI 9.3, 12.2) in Medicare and 6.3 (95% CI 5.0, 7.9) in MarketScan. Older age and higher frailty score were significantly associated with increased risk for serious infection. CONCLUSIONS: In these two U.S. GCA cohorts, high-dose glucocorticoids were the most common initial treatment, and over 25% of Medicare and 7% of MarketScan patients developed serious infection during follow-up. Older age and higher frailty score were associated with higher risk of serious infections, though maximum daily prednisone dose was not. Pneumocystis jiroveci pneumonia was rare in two GCA cohorts despite infrequent use of prophylactic antibiotics.

A tool for empirical equipoise assessment in multigroup comparative effectiveness research.

PURPOSE: In observational research, equipoise concerns whether groups being compared are similar enough for valid inference. Empirical equipoise was previously proposed as a tool to assess patient similarity based on propensity scores (PS). We extended this work for multigroup observational studies. METHODS: We modified the tool to allow for multinomial exposures such that the proposed definition reduces to the original when there are only two groups. We illustrated how the tool can be used as a method to assess study design within three-group clinical examples. We then conducted three-group simulations to assess how the tool performed in a setting with residual confounding after PS weighting. RESULTS: In a clinical example based on rheumatoid arthritis, 44.5% of the sample fell within the region of empirical equipoise when considering first-line biologics, whereas 57.7% did so for second-line biologics, consistent with the expectation that a second-line design results in better equipoise. In a simulation where the unmeasured confounder had the same magnitude of association with the treatment as the measured confounders and a 25% greater association with the outcome, the tool crossed the proposed threshold for empirical equipoise at a residual confounding of 20% on the ratio scale. When the unmeasured variable had a twice larger association with treatment, the tool became less sensitive and crossed the threshold at a residual confounding of 30%. CONCLUSION: Our proposed tool may be useful in guiding cohort identification in multigroup observational studies, particularly with similar effects of unmeasured and measured covariates on treatment and outcome.

Comparative Fracture Risks Among United States Medicaid Enrollees With and Those Without Systemic Lupus Erythematosus.

OBJECTIVE: Poor bone health is common in systemic lupus erythematosus (SLE) patients. This study was undertaken to evaluate fracture risks among low-income SLE and lupus nephritis patients compared to those without SLE. METHODS: We performed a cohort study among SLE patients for whom there were Medicaid claims in 2007-2010, and age- and sex-matched non-SLE comparators. SLE was defined by the presence of ≥3 International Classification of Diseases, Ninth Revision codes for SLE. Patients with lupus nephritis additionally had ≥2 codes for renal disease. The primary outcome measure was fracture of the pelvis, wrist, hip, or humerus. Demographics, prescriptions, and comorbidities were assessed during the 180-day baseline period. We calculated fracture incidence rates and 95% confidence intervals (95% CIs) in SLE, lupus nephritis, and non-SLE comparator cohorts, and estimated adjusted hazard ratios (HRs) for fractures. Sensitivity analyses evaluated the impact of glucocorticoids and comorbidities. We compared subsets of SLE patients with and those without lupus nephritis. RESULTS: Among 47,709 SLE patients (19.8% with lupus nephritis) matched to 190,836 non-SLE comparators, the mean age was 41.4 years and 92.6% were female. The fracture incidence rate was highest among SLE patients with lupus nephritis (4.60 per 1,000 person-years). SLE patients had 2-fold higher fracture risks than matched comparators (HR 2.09 [95% CI 1.85-2.37]; P < 0.01). Lupus nephritis patients had the greatest fracture risks versus matched comparators (HR 3.06 [95% CI 2.24-4.17]; P < 0.01), and had a 1.6 times higher fracture risk than SLE patients without nephritis (HR 1.58 [95% CI 1.20-2.07]; P < 0.01). Adjustment for glucocorticoid use and comorbidities slightly attenuated risks. CONCLUSION: Fracture risks were increased in SLE patients, particularly those with lupus nephritis, compared to matched non-SLE Medicaid recipients. Increased risks persisted after adjustment for baseline glucocorticoid treatment and comorbidities.

Multicriteria decision analysis process to develop new classification criteria for systemic lupus erythematosus.

European League Against Rheumatism and are jointly supporting multiphase development of systemic lupus erythematosus (SLE) classification criteria based on weighted criteria and a continuous probability scale. Prior steps included item generation, item reduction and hierarchical organisation of candidate criteria using an evidence-based approach. Our objectives were to determine relative weights using multicriteria decision analysis (MCDA) and to set a provisional threshold score for SLE classification. An SLE Expert Panel (8 European, 9 North American) submitted 164 real, unique cases with a wide range of SLE probability in a standardised format. Using the candidate criteria, experts scored and rank-ordered 20 representative cases. At an in-person meeting, experts reviewed inter-rater reliability of scoring, further refined criteria definitions and participated in an MCDA exercise. Based on expert consensus decisions on pairwise comparisons of criteria, 1000minds software calculated criteria weights and rank-ordered the remaining 144 cases based on their additive scores. The score of the lowest-ranked case for which complete expert consensus was achieved defined the provisional threshold classification score. Inter-rater reliability of scoring cases with the candidate criteria was good. MCDA involved 74 pairwise decisions and was repeated for the arthritis and mucocutaneous domains when the initial ranking of some cases did not match expert opinion. After criteria weights and additive scores were recalculated once, experts reached consensus for SLE classification for all cases scoring>83. Using an iterative process, the candidate criteria definitions were refined, preliminary weights were calculated and a provisional threshold score for SLE classification was determined.