Identifying the association between serum urate levels and gout flares in patients taking urate-lowering therapy: a post hoc cohort analysis of the CARES trial with consideration of dropout.

OBJECTIVE: To investigate gout flare rates based on repeated serum urate (SU) measurements in a randomised controlled trial of urate-lowering therapy (ULT), accounting for dropout and death. METHODS: We performed a secondary analysis using data from Cardiovascular Safety of Febuxostat or Allopurinol in Patients with Gout, which randomised participants to febuxostat or allopurinol, titrated to target SU <6 mg/dL with flare prophylaxis for 6 months. SU was categorised as ≤3.9, 4.0-5.9, 6.0-7.9, 8.0-9.9 or ≥ 10 mg/dL at each 3-6 month follow-up. The primary outcome was gout flare. Poisson regression models, adjusted for covariates and factors related to participant retention versus dropout, estimated gout flare incidence rate ratios by time-varying SU category. RESULTS: Among 6183 participants, the median age was 65 years and 84% were male. Peak gout flare rates for all SU categories were observed in months 0-6, coinciding with the initiation of ULT and months 6-12 after stopping prophylaxis. Flare rates were similar across SU groups in the initial year of ULT. During months 36-72, a dose-response relationship was observed between the SU category and flare rate. Lower flare rates were observed when SU ≤3.9 mg/dL and greater rates when SU ≥10 mg/dL, compared with SU 4.0-5.9 mg/dL (p for trend <0.01). CONCLUSION: Gout flare rates were persistently higher when SU ≥6 mg/dL after the first year of ULT after accounting for censoring. The spike in flares in all categories after stopping prophylaxis suggests a longer duration of prophylaxis may be warranted.

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.

Changes in alcohol intake and serum urate changes: longitudinal analyses of annual medical examination database.

INTRODUCTION: Despite the established cross-sectional association between alcohol intake and serum urate (SU), its longitudinal association remains unknown. This study aimed to determine whether changes in alcohol intake have a clinically relevant association with SU change. METHOD: We conducted retrospective analyses using systematically collected annual medical examination data from October 2012 to October 2022 in a Japanese preventive medicine centre. The exposure was changes in alcohol intake between two consecutive visits. The association of SU changes with alcohol intake changes was estimated by mixed-effect linear regression with adjustment for relevant covariates. RESULTS: We analysed 63 486 participants (median age, 47.0 years; 55% women; 58.6% regular alcohol drinkers with a median of 1.4 drinks/day) with 370 572 visits. The median SU level was 5.3 mg/dL, and 506 (0.8%) participants had diagnoses of gout or hyperuricemia without medication use during the study period. Decreasing one daily alcohol intake had a clinically small association with SU changes (-0.019 (95% CI: -0.021 to -0.017) mg/dL). Beer had the largest association with SU (-0.036 (95% CI: -0.039 to -0.032) mg/dL for one beer decrease). Complete discontinuation of any alcohol from a mean of 0.8 drinks/day was associated with -0.056 mg/dL (95% CI: -0.068 to -0.043) decrease in SU; the association became larger in hyperuricemic participants (-0.110 mg/dL (95% CI: -0.154 to -0.066) for alcohol discontinuation from a mean of 1.0 drinks/day). CONCLUSIONS: This study revealed changes in alcohol intake had small associations with SU change at the general Japanese population level. Complete discontinuation of alcohol in hyperuricemic participants had only modest improvement in SU.

The 2023 ACR/EULAR classification criteria for calcium pyrophosphate deposition disease.

OBJECTIVE: Calcium pyrophosphate deposition (CPPD) disease is prevalent and has diverse presentations, but there are no validated classification criteria for this symptomatic arthritis. The American College of Rheumatology (ACR) and EULAR have developed the first-ever validated classification criteria for symptomatic CPPD disease. METHODS: Supported by the ACR and EULAR, a multinational group of investigators followed established methodology to develop these disease classification criteria. The group generated lists of candidate items and refined their definitions, collected de-identified patient profiles, evaluated strengths of associations between candidate items and CPPD disease, developed a classification criteria framework, and used multi-criterion decision analysis to define criteria weights and a classification threshold score. The criteria were validated in an independent cohort. RESULTS: Among patients with joint pain, swelling, or tenderness (entry criterion) whose symptoms are not fully explained by an alternative disease (exclusion criterion), the presence of crowned dens syndrome or calcium pyrophosphate crystals in synovial fluid are sufficient to classify a patient as having CPPD disease. In the absence of these findings, a score>56 points using weighted criteria, comprising clinical features, associated metabolic disorders, and results of laboratory and imaging investigations, can be used to classify as CPPD disease. These criteria had a sensitivity of 92.2% and specificity of 87.9% in the derivation cohort (190 CPPD cases, 148 mimickers), whereas sensitivity was 99.2% and specificity was 92.5% in the validation cohort (251 CPPD cases, 162 mimickers). CONCLUSION: The 2023 ACR/EULAR CPPD disease classification criteria have excellent performance characteristics and will facilitate research in this field.

Risk of cardiovascular events in patients having had acute calcium pyrophosphate crystal arthritis.

OBJECTIVES: Calcium pyrophosphate deposition (CPPD) disease, broadly defined, has been associated with increased risk of cardiovascular (CV) events. We investigated risk of CV events in patients with acute CPP crystal arthritis, the acute manifestation of CPPD. METHODS: Cohort study using Mass General Brigham electronic health record (EHR) data, 1991-2017. Patients with acute CPP crystal arthritis were identified using a published machine learning algorithm with positive predictive value 81%. Comparators were matched on year of EHR entry and index date of patients with acute CPP crystal arthritis (first positive synovial fluid CPP result or mention of 'pseudogout', or matched encounter). Major adverse cardiovascular event (MACE) was a composite of non-fatal CV event (myocardial infarction, acute coronary syndrome, coronary revascularisation, stroke) and death. We estimated incidence rates (IRs) and adjusted hazard ratios for MACE, non-fatal CV event and death, allowing for differential estimates during years 0-2 and 2-10. Sensitivity analyses included: (1) patients with acute CPP crystal arthritis diagnosed during outpatient visits, (2) patients with linked Medicare data, 2007-2016 and (3)patients matched on number of CV risk factors. RESULTS: We matched 1200 acute CPP crystal arthritis patients to 3810 comparators. IR for MACE in years 0-2 was 91/1000 person-years (p-y) in acute CPP crystal arthritis and 59/1000 p-y in comparators. In years 2-10, IR for MACE was 58/1000 p-y in acute CPP crystal arthritis and 53/1000 p-y in comparators. Acute CPP crystal arthritis was significantly associated with increased risk for MACE in years 0-2 (HR 1.32, 95% CI 1.01 to 1.73) and non-fatal CV event in years 0-2 (HR 1.92, 95% CI 1.12 to 3.28) and years 2-10 (HR 2.18, 95% CI 1.27 to 3.75), but not death. Results of sensitivity analyses were similar to the primary analysis; in the outpatient-only analysis, risk of non-fatal CVE was significantly elevated in years 2-10 but not in years 0-2. CONCLUSIONS: Acute CPP crystal arthritis was significantly associated with elevated short and long-term risk for non-fatal CV event.

Using observational study data as an external control group for a clinical trial: an empirical comparison of methods to account for longitudinal missing data.

BACKGROUND: Observational data are increasingly being used to conduct external comparisons to clinical trials. In this study, we empirically examined whether different methodological approaches to longitudinal missing data affected study conclusions in this setting. METHODS: We used data from one clinical trial and one prospective observational study, both Norwegian multicenter studies including patients with recently diagnosed rheumatoid arthritis and implementing similar treatment strategies, but with different stringency. A binary disease remission status was defined at 6, 12, and 24 months in both studies. After identifying patterns of longitudinal missing outcome data, we evaluated the following five approaches to handle missingness: analyses of patients with complete follow-up data, multiple imputation (MI), inverse probability of censoring weighting (IPCW), and two combinations of MI and IPCW. RESULTS: We found a complex non-monotone missing data pattern in the observational study (N = 328), while missing data in the trial (N = 188) was monotone due to drop-out. In the observational study, only 39.0% of patients had complete outcome data, compared to 89.9% in the trial. All approaches to missing data indicated favorable outcomes of the treatment strategy in the trial and resulted in similar study conclusions. Variations in results across approaches were mainly due to variations in estimated outcomes for the observational data. CONCLUSIONS: Five different approaches to handle longitudinal missing data resulted in similar conclusions in our example. However, the extent and complexity of missing observational data affected estimated comparative outcomes across approaches, highlighting the need for careful consideration of methods to account for missingness in this setting. Based on this empirical examination, we recommend using a prespecified advanced missing data approach to account for longitudinal missing data, and to conduct alternative approaches in sensitivity analyses.

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.

Weakly Semi-supervised phenotyping using Electronic Health records.

OBJECTIVE: Electronic Health Record (EHR) based phenotyping is a crucial yet challenging problem in the biomedical field. Though clinicians typically determine patient-level diagnoses via manual chart review, the sheer volume and heterogeneity of EHR data renders such tasks challenging, time-consuming, and prohibitively expensive, thus leading to a scarcity of clinical annotations in EHRs. Weakly supervised learning algorithms have been successfully applied to various EHR phenotyping problems, due to their ability to leverage information from large quantities of unlabeled samples to better inform predictions based on a far smaller number of patients. However, most weakly supervised methods are subject to the challenge to choose the right cutoff value to generate an optimal classifier. Furthermore, since they only utilize the most informative features (i.e., main ICD and NLP counts) they may fail for episodic phenotypes that cannot be consistently detected via ICD and NLP data. In this paper, we propose a label-efficient, weakly semi-supervised deep learning algorithm for EHR phenotyping (WSS-DL), which overcomes the limitations above. MATERIALS AND METHODS: WSS-DL classifies patient-level disease status through a series of learning stages: 1) generating silver standard labels, 2) deriving enhanced-silver-standard labels by fitting a weakly supervised deep learning model to data with silver standard labels as outcomes and high dimensional EHR features as input, and 3) obtaining the final prediction score and classifier by fitting a supervised learning model to data with a minimal number of gold standard labels as the outcome, and the enhanced-silver-standard labels and a minimal set of most informative EHR features as input. To assess the generalizability of WSS-DL across different phenotypes and medical institutions, we apply WSS-DL to classify a total of 17 diseases, including both acute and chronic conditions, using EHR data from three healthcare systems. Additionally, we determine the minimum quantity of training labels required by WSS-DL to outperform existing supervised and semi-supervised phenotyping methods. RESULTS: The proposed method, in combining the strengths of deep learning and weakly semi-supervised learning, successfully leverages the crucial phenotyping information contained in EHR features from unlabeled samples. Indeed, the deep learning model's ability to handle high-dimensional EHR features allows it to generate strong phenotype status predictions from silver standard labels. These predictions, in turn, provide highly effective features in the final logistic regression stage, leading to high phenotyping accuracy in notably small subsets of labeled data (e.g. n = 40 labeled samples). CONCLUSION: Our method's high performance in EHR datasets with very small numbers of labels indicates its potential value in aiding doctors to diagnose rare diseases as well as conditions susceptible to misdiagnosis.

European League Against Rheumatism (EULAR)/American College of Rheumatology (ACR) SLE classification criteria item performance.

BACKGROUND/OBJECTIVES: The European League Against Rheumatism (EULAR)/American College of Rheumatology (ACR) 2019 classification criteria for systemic lupus erythematosus system showed high specificity, while attaining also high sensitivity. We hereby analysed the performance of the individual criteria items and their contribution to the overall performance of the criteria. METHODS: We combined the EULAR/ACR derivation and validation cohorts for a total of 1197 systemic lupus erythematosus (SLE) and n=1074 non-SLE patients with a variety of conditions mimicking SLE, such as other autoimmune diseases, and calculated the sensitivity and specificity for antinuclear antibodies (ANA) and the 23 specific criteria items. We also tested performance omitting the EULAR/ACR criteria attribution rule, which defines that items are only counted if not more likely explained by a cause other than SLE. RESULTS: Positive ANA, the new entry criterion, was 99.5% sensitive, but only 19.4% specific, against a non-SLE population that included other inflammatory rheumatic, infectious, malignant and metabolic diseases. The specific criteria items were highly variable in sensitivity (from 0.42% for delirium and 1.84% for psychosis to 75.6% for antibodies to double-stranded DNA), but their specificity was uniformly high, with low C3 or C4 (83.0%) and leucopenia <4.000/mm³ (83.8%) at the lowest end. Unexplained fever was 95.3% specific in this cohort. Applying the attribution rule improved specificity, particularly for joint involvement. CONCLUSIONS: Changing the position of the highly sensitive, non-specific ANA to an entry criterion and the attribution rule resulted in a specificity of >80% for all items, explaining the higher overall specificity of the criteria set.

Delayed Denosumab Injections and Fracture Risk Among Patients With Osteoporosis : A Population-Based Cohort Study.

BACKGROUND: Denosumab is effective for osteoporosis, but discontinuation leads to rapid reversal of its therapeutic effect. OBJECTIVE: To estimate the risk for fracture among users of denosumab who delayed subsequent doses compared with users who received doses on time. DESIGN: Population-based cohort study. SETTING: The Health Improvement Network U.K. primary care database, 2010 to 2019. PATIENTS: Persons aged 45 years or older who initiated denosumab therapy for osteoporosis. MEASUREMENTS: Observational data were used to emulate an analysis of a hypothetical trial with 3 dosing intervals: subsequent denosumab injection given within 4 weeks after the recommended date ("on time"), delay by 4 to 16 weeks ("short delay"), and delay by more than 16 weeks ("long delay"). The primary outcome was a composite of all fracture types at 6 months after the recommended date. Secondary outcomes were major osteoporotic fracture, vertebral fracture, hip fracture, and nonvertebral fracture. RESULTS: Investigators identified 2594 patients initiating denosumab therapy. The risk for composite fracture over 6 months was 27.3 in 1000 for on-time dosing, 32.2 in 1000 for short delay, and 42.4 in 1000 for long delay. Compared with on-time injections, short delay had a hazard ratio (HR) for composite fracture of 1.03 (95% CI, 0.63 to 1.69) and long delay an HR of 1.44 (CI, 0.96 to 2.17) (P for trend = 0.093). For vertebral fractures, short delay had an HR of 1.48 (CI, 0.58 to 3.79) and long delay an HR of 3.91 (CI, 1.62 to 9.45). LIMITATION: Dosing schedules were not randomly assigned. CONCLUSION: Although delayed administration of subsequent denosumab doses by more than 16 weeks is associated with increased risk for vertebral fracture compared with on-time dosing, evidence is insufficient to conclude that fracture risk is increased at other anatomical sites with long delay. PRIMARY FUNDING SOURCE: National Clinical Research Center for Orthopedics, Sports Medicine & Rehabilitation.

Adverse Effects of Low-Dose Methotrexate: A Randomized Trial.

Background: Low-dose methotrexate (LD-MTX) is the most commonly used drug for systemic rheumatic diseases worldwide and is the recommended first-line agent for rheumatoid arthritis. Despite extensive clinical use for more than 30 years, few data on adverse event (AE) rates derive from randomized, placebo-controlled trials, where both causality and magnitude of risk can be inferred. Objective: To investigate AE rates, risk, and risk differences comparing LD-MTX versus placebo. Design: Prespecified secondary analyses of a double-blind, placebo-controlled, randomized trial. (ClinicalTrials.gov: NCT01594333). Setting: North America. Participants: Adults with known cardiovascular disease and diabetes or metabolic syndrome. Intervention: Random allocation to LD-MTX (≤20 mg/wk) or placebo. All participants received folic acid, 1 mg/d, 6 days per week. Measurements: Risks for specific AEs of interest, as well as for all AEs, were compared across treatment groups after blinded adjudication. Results: After an active run-in period, 6158 patients were enrolled and 4786 randomly assigned to a group; median follow-up was 23 months and median dosage 15 mg/wk. Among the randomly assigned participants, 81.2% were male, median age was 65.7 years, and median body mass index was 31.5 kg/m2. Of 2391 participants assigned to LD-MTX, 2080 (87.0%) had an AE of interest, compared with 1951 of 2395 (81.5%) assigned to placebo (hazard ratio [HR], 1.17 [95% CI, 1.10 to 1.25]). The relative hazards of gastrointestinal (HR, 1.91 [CI, 1.75 to 2.10]), pulmonary (HR, 1.52 [CI, 1.16 to 1.98]), infectious (HR, 1.15 [CI, 1.01 to 1.30]), and hematologic (HR, 1.15 [CI, 1.07 to 1.23]) AEs were elevated for LD-MTX versus placebo. With the exception of increased risk for skin cancer (HR, 2.05 [CI, 1.28 to 3.28]), the treatment groups did not differ in risk for other cancer or mucocutaneous, neuropsychiatric, or musculoskeletal AEs. Renal AEs were reduced in the LD-MTX group (HR, 0.85 [CI, 0.78 to 0.93]). Limitation: The trial was done in patients without rheumatic disease who tolerated LD-MTX during an active run-in period. Conclusion: Use of LD-MTX was associated with small to moderate elevations in risks for skin cancer and gastrointestinal, infectious, pulmonary, and hematologic AEs, whereas renal AEs were decreased. Primary Funding Source: National Institutes of Health.

Performance of the 2019 EULAR/ACR classification criteria for systemic lupus erythematosus in early disease, across sexes and ethnicities.

OBJECTIVES: The European League Against Rheumatism (EULAR)/American College of Rheumatology (ACR) 2019 Classification Criteria for systemic lupus erythematosus (SLE) have been validated with high sensitivity and specificity. We evaluated the performance of the new criteria with regard to disease duration, sex and race/ethnicity, and compared its performance against the Systemic Lupus International Collaborating Clinics (SLICC) 2012 and ACR 1982/1997 criteria. METHODS: Twenty-one SLE centres from 16 countries submitted SLE cases and mimicking controls to form the validation cohort. The sensitivity and specificity of the EULAR/ACR 2019, SLICC 2012 and ACR 1982/1997 criteria were evaluated. RESULTS: The cohort consisted of female (n=1098), male (n=172), Asian (n=118), black (n=68), Hispanic (n=124) and white (n=941) patients; with an SLE duration of 1 to <3 years (n=196) and ≥5 years (n=879). Among patients with 1 to <3 years disease duration, the EULAR/ACR criteria had better sensitivity than the ACR criteria (97% vs 81%). The EULAR/ACR criteria performed well in men (sensitivity 93%, specificity 96%) and women (sensitivity 97%, specificity 94%). Among women, the EULAR/ACR criteria had better sensitivity than the ACR criteria (97% vs 83%) and better specificity than the SLICC criteria (94% vs 82%). Among white patients, the EULAR/ACR criteria had better sensitivity than the ACR criteria (95% vs 83%) and better specificity than the SLICC criteria (94% vs 83%). The EULAR/ACR criteria performed well among black patients (sensitivity of 98%, specificity 100%), and had better sensitivity than the ACR criteria among Hispanic patients (100% vs 86%) and Asian patients (97% vs 77%). CONCLUSIONS: The EULAR/ACR 2019 criteria perform well among patients with early disease, men, women, white, black, Hispanic and Asian patients. These criteria have superior sensitivity than the ACR criteria and/or superior specificity than the SLICC criteria across many subgroups.

Circulating plasma metabolites and risk of rheumatoid arthritis in the Nurses' Health Study.

OBJECTIVES: RA develops slowly over years. We tested for metabolic changes prior to RA onset using a large non-targeted metabolomics platform to identify novel pathways and advance understanding of RA development. METHODS: Two hundred and fifty-four incident RA cases with plasma samples drawn pre-RA onset in the Nurses' Health Study (NHS) cohorts were matched 1:2 to 501 controls on age, race, menopause/post-menopausal hormone use and blood collection features. Relative abundances of 360 unique, known metabolites were measured. Conditional logistic regression analyses assessed associations between metabolites and incidence of RA, adjusted for age, smoking and BMI, accounting for multiple comparisons. Subgroup analyses investigated seropositive (sero+) RA and RA within 5 years of sample collection. Significant metabolites were then tested in a female military pre-RA case-control study (n = 290). RESULTS: In the NHS, metabolites associated with RA and sero+RA in multivariable models included 4-acetamidobutanoate (odds ratio (OR) = 0.80/S.d., 95% CI: 0.66, 0.95), N-acetylputrescine (OR = 0.82, 95% CI: 0.69, 0.96), C5 carnitine (OR = 0.84, 95% CI: 0.71, 0.99) and C5:1 carnitine (OR = 0.81, 95% CI: 0.68, 0.95). These were involved primarily in polyamine and leucine, isoleucine and valine metabolism. Several metabolites associated with sero+RA within 5 years of diagnosis were replicated in the independent military cohort: C5 carnitine (OR = 0.55, 95% CI: 0.33, 0.92), C5:1 carnitine (OR = 0.62, 95% CI: 0.39, 0.99) and C3 carnitine (OR = 0.57, 95% CI: 0.36, 0.91). CONCLUSION: Several metabolites were inversely associated with incidence of RA among women. Three short-chain acylcarnitines replicated in a smaller dataset and may reflect inflammation in the 5-year period prior to sero+RA diagnosis.

Follow-up vascular ultrasounds in patients with giant cell arteritis.

OBJECTIVES: Literature describing follow-up vascular ultrasound (VUS) in giant cell arteritis (GCA) is limited. We report our experience with follow-up VUS obtained in clinical care of patients with GCA. METHODS: We retrospectively identified GCA patients with an abnormal initial VUS, defined as circumferential hypoechoic wall thickening ("halo sign"), or circumferential hyperechoic wall thickening without evidence of arteriosclerosis or arteritis, who subsequently underwent follow-up VUS during 2013-2018. Studies were interpreted as active arteritis, hyperechoic wall thickening without active arteritis, or no arteritis. We compared clinical and laboratory characteristics at time of initial VUS among patients with active arteritis vs. hyperechoic wall thickening without active arteritis. We described whether and how VUS interpretation changed from initial to follow-up VUS. Among individual vessels, we tested whether abnormal findings (e.g. halo sign) persisted at follow-up VUS using McNemar's test. RESULTS: 42 patients fulfilled study criteria. Median time between initial and follow-up VUS was 5.1 (IQR 2.6-7.9) months. Characteristics at initial VUS did not differ according to VUS interpretation. Among 36 patients with active arteritis on initial VUS, follow-up VUS showed active arteritis in 25.0%, hyperechoic wall thickening in 33.3% and no arteritis in 41.7%. Among 6 patients with hyperechoic wall thickening on initial VUS, half had no arteritis on follow-up VUS. Sonographic findings tended to persist in axillary arteries and were more likely to change in the superficial temporal arteries. CONCLUSIONS: Among 42 GCA patients, the majority had a change in VUS interpretation between initial and follow-up VUS. Sonographic findings in the temporal circulation more frequently changed than findings in axillary arteries.

Multinomial Extension of Propensity Score Trimming Methods: A Simulation Study.

Crump et al. (Biometrika. 2009;96(1):187-199), Stürmer et al. (Am J Epidemiol. 2010;172(7):843-854), and Walker et al. (Comp Eff Res. 2013;2013(3):11-20) proposed propensity score (PS) trimming methods as a means to improve efficiency (Crump) or reduce confounding (Stürmer and Walker). We generalized the trimming definitions by considering multinomial PSs, one for each treatment, and proved that these proposed definitions reduce to the original binary definitions when we have only 2 treatment groups. We then examined the performance of the proposed multinomial trimming methods in the setting of 3 treatment groups, in which subjects with extreme PSs more likely had unmeasured confounders. Inverse probability of treatment weights, matching weights, and overlap weights were used to control for measured confounders. All 3 methods reduced bias regardless of the weighting methods in most scenarios. Multinomial Stürmer and Walker trimming were more successful in bias reduction when the 3 treatment groups had very different sizes (10:10:80). Variance reduction, seen in all methods with inverse probability of treatment weights but not with matching weights or overlap weights, was more successful with multinomial Crump and Stürmer trimming. In conclusion, our proposed definitions of multinomial PS trimming methods were beneficial within our simulation settings that focused on the influence of unmeasured confounders.

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.

2019 European League Against Rheumatism/American College of Rheumatology classification criteria for systemic lupus erythematosus.

OBJECTIVE: To develop new classification criteria for systemic lupus erythematosus (SLE) jointly supported by the European League Against Rheumatism (EULAR) and the American College of Rheumatology (ACR). METHODS: This international initiative had four phases. (1) Evaluation of antinuclear antibody (ANA) as an entry criterion through systematic review and meta-regression of the literature and criteria generation through an international Delphi exercise, an early patient cohort and a patient survey. (2) Criteria reduction by Delphi and nominal group technique exercises. (3) Criteria definition and weighting based on criterion performance and on results of a multi-criteria decision analysis. (4) Refinement of weights and threshold scores in a new derivation cohort of 1001 subjects and validation compared with previous criteria in a new validation cohort of 1270 subjects. RESULTS: The 2019 EULAR/ACR classification criteria for SLE include positive ANA at least once as obligatory entry criterion; followed by additive weighted criteria grouped in seven clinical (constitutional, haematological, neuropsychiatric, mucocutaneous, serosal, musculoskeletal, renal) and three immunological (antiphospholipid antibodies, complement proteins, SLE-specific antibodies) domains, and weighted from 2 to 10. Patients accumulating ≥10 points are classified. In the validation cohort, the new criteria had a sensitivity of 96.1% and specificity of 93.4%, compared with 82.8% sensitivity and 93.4% specificity of the ACR 1997 and 96.7% sensitivity and 83.7% specificity of the Systemic Lupus International Collaborating Clinics 2012 criteria. CONCLUSION: These new classification criteria were developed using rigorous methodology with multidisciplinary and international input, and have excellent sensitivity and specificity. Use of ANA entry criterion, hierarchically clustered and weighted criteria reflect current thinking about SLE and provide an improved foundation for SLE research.

Comparison of comorbidities and treatment between ankylosing spondylitis and non-radiographic axial spondyloarthritis in the United States.

OBJECTIVES: This study aimed to compare comorbidities and biologic DMARD (bDMARD) use between AS and non-radiographic axial SpA (nr-axSpA) patients, using a large cohort of patients from routine clinical practice in the United States. METHODS: We performed a cross-sectional study using electronic medical records from two academic hospitals in the United States. Data were extracted using automated searches (⩾3 ICD codes combined with text searches) and supplemented with manual chart review. Patients were categorized into AS or nr-axSpA according to classification criteria. Disease features, comorbidities (from a list of 39 chronic conditions) and history of bDMARD prescription were compared using descriptive statistics. RESULTS: Among 965 patients identified, 775 (80%) were classified as having axSpA. The cohort was predominantly male (74%) with a mean age of 52.5 years (s.d. 16.8). AS patients were significantly older (54 vs 46 years), more frequently male (77% vs 64%) and had higher serum inflammatory markers than those with nr-axSpA (median CRP 3.4 vs 2.2 mg/dl). Half of all patients had at least one comorbidity. The mean number of comorbidities was 1.5 (s.d. 2.2) and similar between AS and nr-axSpA groups. A history of bDMARD-use was seen in 55% of patients with no difference between groups. The most commonly prescribed bDMARDs were adalimumab (31%) and etanercept (29%). Ever-prescriptions of individual bDMARDs were similar between AS and nr-axSpA. CONCLUSION: Despite age differences, nr-axSpA patients had similar comorbidity burdens as those with AS. Both groups received comparable bDMARD treatment in this United States clinic-based cohort.

Issues in CPPD Nomenclature and Classification.

PURPOSE OF REVIEW: This paper covers confusion and challenges in the nomenclature of calcium pyrophosphate deposition disease. Clinicians, investigators, and patients are faced with a variety of terms that are used to describe CPPD and its phenotypes, and clarity is greatly needed to help advance research and patient care. Motivation for the upcoming development of CPPD classification criteria is reviewed. RECENT FINDINGS: EULAR proposed recommended terminology for CPPD in 2011. International Classification of Diseases (ICD-9 and ICD-10) billing codes identify definite or probable CPPD with variable accuracy depending on the clinical setting and comparator group. READ diagnostic codes have been employed to identify pseudogout in UK datasets but their accuracy has not been evaluated. CPPD classification criteria will provide a system for identifying a relatively homogenous group of patients to be included in clinical studies, enabling comparison of outcomes across studies. CPPD nomenclature remains challenging for clinicians, investigators, and patients. A lay-friendly definition of CPPD, using easily accessible terminology, would be welcome. CPPD classification criteria are a necessary step in moving forward CPPD clinical research and may involve a range of clinical, laboratory, and imaging modalities.

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.