Antiphospholipid Antibody Testing in a General Population Sample from the USA: An Administrative Database Study

We sought to characterized patterns of aPL testing in a large general population sample from the United States. Using Truven Health MarketScan laboratory data from 2010-2015 we identified individuals tested for lupus anticoagulant(LA), anti-cardiolipin (aCL), and anti-beta2-glycoprotein1(aGP1). Our research was approved by the McGill institutional review board (A04-M47-12B). We identified 33,456 individuals with at least one aPL test. Among these, only 6,391 (19%) had all three tests (LA, aCL, aGP1) performed. Confirmatory aPL testing was performed at least 12 weeks later in 77%, 45%, and 41% of initially positive LA, aCL, and aGP1, respectively. Of those re-tested after ≥12 weeks, only 255 (10.6%) were found to have a confirmatory positive aPL test. These findings highlight that aPL testing may often be incompletely performed. Further investigations will be required to better understand the low rate of a confirmatory positive aPL test ≥12 weeks after the initial test

Rheumatoid arthritis is getting less frequent—results of a nationwide population-based cohort study

Objectives: The objectives of this study were to examine changes in incidence and prevalence of RA between 1990 and 2014, and to explore if there is any geographic variation in incidence and prevalence of RA in the UK Methods: Design Prospective cohort study Setting Primary care Participants People contributing acceptable data to Clinical Practice Research Datalink (CPRD) between 01/01/1990 and 31/12/2014 were included. Read codes were used to identify RA cases ≥18 years in age. Outcomes Prevalence and incidence rates for each year standardised to the 2014 population. Region specific incidence and prevalence of RA for the year 2014 standardized to the overall population. Results: The incidence and prevalence of RA was 3.81 per 10,000 person-years and 0.67% respectively in 2014. The annual incidence of RA reduced by -1.6%(-0.8% to - 2.5%) between 1990 and 2014, with significant joinpoints at 1994 and 2002. The prevalence of RA increased by 3.7%(3.2% to 4.1%)/year from 1990 to 2005; and reduced by -1.1%(-2.0% to -0.2%)/year between 2005 and 2014. There were significant differences in the occurrence of RA throughout different regions of the UK, with highest incidence in East Midlands, Yorkshire and Humber; and highest prevalence in North East, and Yorkshire and Humber. Conclusion: The incidence of RA is decreasing, with a reduction in prevalence in recent years. There is significant geographic variation in occurrence of RA in UK. Further research is required to identify the reasons underlying this phenomenon so that public-health interventions can be designed to further reduce the incidence of RA

An administrative data validation study of the accuracy of algorithms for identifying rheumatoid arthritis: the influence of the reference standard on algorithm performance

BACKGROUND: We have previously validated administrative data algorithms to identify patients with rheumatoid arthritis (RA) using rheumatology clinic records as the reference standard. Here we reassessed the accuracy of the algorithms using primary care records as the reference standard. METHODS: We performed a retrospective chart abstraction study using a random sample of 7500 adult patients under the care of 83 family physicians contributing to the Electronic Medical Record Administrative data Linked Database (EMRALD) in Ontario, Canada. Using physician-reported diagnoses as the reference standard, we computed and compared the sensitivity, specificity, and predictive values for over 100 administrative data algorithms for RA case ascertainment. RESULTS: We identified 69 patients with RA for a lifetime RA prevalence of 0.9%. All algorithms had excellent specificity (>97%). However, sensitivity varied (75-90%) among physician billing algorithms. Despite the low prevalence of RA, most algorithms had adequate positive predictive value (PPV; 51-83%). The algorithm of “[1 hospitalization RA diagnosis code] or [3 physician RA diagnosis codes with ≥1 by a specialist over 2 years]” had a sensitivity of 78% (95% CI 69–88), specificity of 100% (95% CI 100–100), PPV of 78% (95% CI 69–88) and NPV of 100% (95% CI 100–100). CONCLUSIONS: Administrative data algorithms for detecting RA patients achieved a high degree of accuracy amongst the general population. However, results varied slightly from our previous report, which can be attributed to differences in the reference standards with respect to disease prevalence, spectrum of disease, and type of comparator group