How accurate are diagnoses for rheumatoid arthritis and juvenile idiopathic arthritis in the general practice research database?

Trends for opioid prescribing and the impact of the COVID-19 pandemic in patients with rheumatic and musculoskeletal diseases between 2006 and 2021

OBJECTIVE

To investigate opioid prescribing trends and assess the impact of the COVID-19 pandemic on opioid prescribing in rheumatic and musculoskeletal diseases (RMDs).

METHODS

Adult patients with RA, PsA, axial spondyloarthritis (AxSpA), SLE, OA and FM with opioid prescriptions between 1 January 2006 and 31 August 2021 without cancer in UK primary care were included. Age- and gender-standardized yearly rates of new and prevalent opioid users were calculated between 2006 and 2021. For prevalent users, monthly measures of mean morphine milligram equivalents (MME)/day were calculated between 2006 and 2021. To assess the impact of the pandemic, we fitted regression models to the monthly number of prevalent opioid users between January 2015 and August 2021. The time coefficient reflects the trend pre-pandemic and the interaction term coefficient represents the change in the trend during the pandemic.

RESULTS

The study included 1 313 519 RMD patients. New opioid users for RA, PsA and FM increased from 2.6, 1.0 and 3.4/10 000 persons in 2006 to 4.5, 1.8 and 8.7, respectively, in 2018 or 2019. This was followed by a fall to 2.4, 1.2 and 5.9, respectively, in 2021. Prevalent opioid users for all RMDs increased from 2006 but plateaued or dropped beyond 2018, with a 4.5-fold increase in FM between 2006 and 2021. In this period, MME/day increased for all RMDs, with the highest for FM (≥35). During COVID-19 lockdowns, RA, PsA and FM showed significant changes in the trend of prevalent opioid users. The trend for FM increased pre-pandemic and started decreasing during the pandemic.

CONCLUSION

The plateauing or decreasing trend of opioid users for RMDs after 2018 may reflect the efforts to tackle rising opioid prescribing in the UK. The pandemic led to fewer people on opioids for most RMDs, providing reassurance that there was no sudden increase in opioid prescribing during the pandemic.

Developing electronic health record algorithms that accurately identify patients with juvenile idiopathic arthritis

BACKGROUND

The objective of this study was to develop an algorithm that accurately identifies juvenile idiopathic arthritis (JIA) patients in the electronic health record (EHR).

METHODS

Algorithms were developed in a de-identified EHR by searching for a priori JIA ICD-9 (International Classification of Diseases, Ninth Revision) and ICD-10-CM (International Classification of Diseases, Tenth Revision, Clinical Modification) codes and JIA-related keywords. Exclusion criteria were selected to remove other autoimmune diseases. A training set of 200 patients was randomly selected from patients containing ≥1 occurrence of a JIA ICD-9 or ICD-10-CM code. Case status was determined by a rheumatology clinic note documenting a JIA diagnosis before age 20. For each algorithm, positive predictive value (PPV), sensitivity, and F-measure were determined using the training set.

RESULTS

We developed 103 algorithms using combinations of ICD codes, keywords, and exclusion criteria. The algorithm requiring 4 or more counts of JIA ICD-9 or ICD-10-CM codes, keywords "enthesitis" and "uveitis", and exclusion of ICD-9 or ICD-10-CM codes for systemic lupus erythematosus, dermatomyositis, polymyositis, and dermatopolymyositis had the highest PPV of 97% in the training set with an F-measure of 87%. There were 1,131 JIA cases returned by this algorithm. We validated the highest performing algorithm in a separate cohort from the training set with a PPV of 92% and an F-measure of 75%.

CONCLUSION

We developed and validated JIA EHR algorithms with ICD-9 and ICD-10-CM codes to accurately identify a JIA cohort. Three algorithms achieved PPVs of 97%, each with different algorithm criteria, allowing for users to select an algorithm to best fit their research needs.

Reduction of Cardiovascular Disease and Mortality Versus Risk of New-Onset Diabetes Mellitus With Statin Use in Patients With Rheumatoid Arthritis

OBJECTIVE

To assess the effect of statin use on the risk of cardiovascular disease (CVD), all-cause mortality, and type 2 diabetes mellitus (DM) in patients with rheumatoid arthritis (RA).

METHODS

We identified a cohort of patients with RA between 1989 and 2018, within the UK Clinical Practice Research Datalink. We employed a prevalent new-user cohort design by which patients initiating statins were each matched to 2 concurrent nonusers by the time-conditional propensity score (TCPS). Patients were followed until the occurrence of the composite end point of myocardial infarction, stroke, hospitalized heart failure or CVD mortality, all-cause mortality, and incident type 2 DM. The Cox proportional hazards model was used to estimate the hazard ratio (HR) of each outcome associated with as-treated statin use, with adjustment for TCPS deciles and imbalanced covariables.

RESULTS

Among 1,768 statin initiators and 3,528 nonusers, 63 versus 340 CVD (3.0 per 100 person-years versus 2.7 per 100 person-years) and 62 versus 525 deaths (2.8 per 100 person-years versus 4.1 per 100 person-years) occurred. Incident type 2 DM was noted in 128 of 3,608 statin initiators (3.0 per 100 person-years) and 518 of 7,208 nonusers (2.0 per 100 person-years). Statin initiation was associated with 32% (HR 0.68 [95% confidence interval (95% CI) 0.51-0.90]) reduction in CVD, 54% (HR 0.46 [95% CI 0.35-0.60]) reduction in all-cause mortality, and 33% increase in type 2 DM (HR 1.33 [95% CI 1.09-1.63]). The number needed to treat/number needed to harm to prevent a CVD or all-cause mortality or to cause type 2 DM in 1 year was 102, 42, and 127, respectively.

CONCLUSION

Statins are associated with important reductions in CVD and mortality that outweigh the modest increase in type 2 DM risk in RA patients.

The validity of rheumatoid arthritis diagnoses in Finnish biobanks

OBJECTIVE

The aim of this study was to determine the validity of rheumatoid arthritis (RA) diagnoses in patients participating in Finnish biobanks.

METHOD

We reviewed the electronic medical records of 500 Finnish biobank participants: 125 patients with at least one visit with a diagnosis of seropositive RA, 125 patients with at least one visit with a diagnosis of seronegative RA, and 250 age- and gender-matched controls. The patients were chosen from five different biobank hospitals in Finland. A rheumatologist reviewed the medical records to assess whether each patients' diagnosis was correct. The diagnosis was compared with the diagnostic codes in the Finnish Care Register for Health Care (CRHC) and special reimbursement data of the Social Insurance Institution of Finland.

RESULTS

The positive predictive value (PPV) of CRHC diagnosis of RA (for seropositive and seronegative RA combined) was 0.82. For patients with a special reimbursement for anti-rheumatic medications for RA, the PPV was 0.89. The PPV was higher in patients with more than one visit. For one, two, five, and 10 visits, the PPV was 0.82, 0.85, 0.89, and 0.90, respectively, and for patients who also had the special reimbursement, the PPV was 0.89, 0.91, 0.93, and 0.94 for one, two, five, and 10 visits, respectively. In patients positive for anti-citrullinated protein antibodies, the PPV was 0.98.

CONCLUSION

These results demonstrate that the validity of RA diagnoses in Finnish biobanks was good and can be further improved by including data on special reimbursement for medication, number of visits, and serological data.

Quality of rheumatoid arthritis recording in United Kingdom Clinical Practice Research Datalink Aurum

PURPOSE

While several studies have assessed quality and completeness of recording acute medical events in Clinical Practice Research Datalink (CPRD) Aurum, evaluation of additional chronic conditions is warranted.

METHODS

We selected patients with a first diagnosis of rheumatoid arthritis (RA) coded in their CPRD Aurum record between 2005 and 2019. We assessed quality of RA diagnosis by evaluating additional information in the patient record that would corroborate the diagnosis. We report recording of diagnoses, prescriptions, labs, and referrals expected to be present based on NICE guidelines for RA management.

RESULTS

There were 53 083 patients with a first recorded RA diagnosis during the study period: 43606 (82%) patients had RA drug treatments in their record, 7596 (14%) had supporting codes without drug treatment, and 1881 (4%) patients had only a RA diagnoses recorded in their medical record with no supporting codes or RA treatments. Patients with RA diagnosis only were more likely to be first diagnosed in the earliest time period of study. Labs for diagnosing and monitoring RA were most common among patients with RA treatment. Analgesic and glucocorticoid prescriptions were common in all study patients but were highest among patients with RA treatment. Among patients with RA diagnosis only, the overwhelming majority had only one RA diagnosis recorded (76%).

CONCLUSIONS

Our findings suggest that codes expected for monitoring and treatment of RA are routinely recorded in CPRD Aurum. These results support previous assessments, which found data recorded in CPRD Aurum to be of good quality for use in research.

Rheumatoid arthritis, psoriatic arthritis, and axial spondyloarthritis epidemiology in England from 2004 to 2020: An observational study using primary care electronic health record data

BACKGROUND

Contemporary data on rheumatoid arthritis (RA), psoriatic arthritis (PsA) and axial spondyloarthritits (SpA) epidemiology in England are lacking. This knowledge is crucial to planning healthcare services. We updated algorithms defining patients with diagnoses of RA, PsA, and axial SpA in primary care and applied them to describe their incidence and prevalence in the Clinical Practice Research Datalink Aurum, an electronic health record (EHR) database covering ∼20% of England.

METHODS

Algorithms for ascertaining patients with RA, axial SpA, and PsA diagnoses validated in primary care EHR databases using Read codes were updated (to account for the English NHS change to SNOMED CT diagnosis coding) and applied. Updated diagnosis and synthetic disease-modifying anti-rheumatic drug code lists were devised by rheumatologists and general practitioners. Annual incidence/point-prevalence of RA, PsA, and axial SpA diagnoses were calculated from 2004 to 2020 and stratified by age/sex.

FINDINGS

Point-prevalence of RA/PsA diagnoses increased annually, peaking in 2019 (RA 0·779% [95% confidence interval (CI) 0·773, 0·784]; PsA 0·287% [95% CI 0·284, 0·291]) then falling slightly. Point-prevalence of axial SpA diagnoses increased annually (except in 2018/2019), peaking in 2020 (0·113% [95% CI 0·111, 0·115]). RA diagnosis annual incidence was higher between 2013-2019 (after inclusion in the Quality and Outcomes Framework, range 49·1 [95% CI 47·7, 50·5] to 52·1 [95% CI 50·6, 53·6]/100,000 person-years) than 2004-2012 (range 34·5 [95% CI 33·2, 35·7] to 40·0 [95% CI 38·6, 41·4]/100,000 person-years). Increases in the annual incidence of PsA/axial SpA diagnosis occurred following new classification criteria publication. Annual incidence of RA, PsA and axial SpA diagnoses fell by 40·1%, 67·4%, and 38·1%, respectively between 2019 and 2020, likely reflecting the COVID-19 pandemic's impact on their diagnosis.

INTERPRETATION

Recorded RA, PsA, and axial SpA diagnoses are increasingly prevalent in England, underlining the importance of organising healthcare services to provide timely, treat-to-target care to optimise the health of >1% of adults in England.

FUNDING

National Institute for Health and Care Research (NIHR300826).

Body surface area affected by psoriasis and the risk for psoriatic arthritis: a prospective population-based cohort study

OBJECTIVE

Increasing psoriasis severity has been associated with comorbidities including cardiovascular disease. The objective of this study was to examine the association of psoriasis severity with the development of PsA.

METHODS

A prospective population-based cohort study was performed within The Health Improvement Network, a UK medical record database. Patients aged 25-60 years with a code for psoriasis were randomly selected between 2008 and 2011. Questionnaires were sent to their general practitioners to confirm the diagnosis of psoriasis and provide the patient's approximate body surface area (BSA). Incidence of PsA was calculated by BSA, and Cox proportional hazard ratios were used to examine the risk of developing PsA by BSA category after adjusting for other covariates.

RESULTS

Among 10 474 questionnaires sent, 9987 (95%) were returned, 9069 (91%) had confirmed psoriasis, and BSA was provided for 8881 patients: 52% had mild psoriasis, 36% moderate psoriasis and 12% severe psoriasis. The mean age was 46, and 49% were female. Mean follow-up time was 4.2 years (s.d. 2.1); the incidence of PsA was 5.4 cases per 1000 person-years. After adjusting for age and sex, BSA >10% [hazard ratio (HR) 2.01, 95% CI: 1.29, 3.13], BSA 3-10% (HR 1.44, 95% CI: 1.02, 2.03), obesity (HR 1.64, 95% CI: 1.19, 2.26) and depression (HR 1.68, 95% CI: 1.21, 2.33) were associated with incident PsA.

CONCLUSIONS

In this large prospective cohort study, BSA assessed by general practitioners was a strong predictor of developing PsA, and obesity and depression were additive risk factors.

Validation of knee osteoarthritis case identification algorithms in a large electronic health record database

Purpose:

To facilitate studies of knee osteoarthritis (OA) in large databases, case finding algorithms with high levels of diagnostic performance are needed.

Methods:

From a UK general practitioner (GP) practice derived database, we selected adults ages 40–90 years meeting algorithms that included various combinations of codes for knee OA or knee pain and imaging. The GP for each patient was mailed a questionnaire to assess the cause of knee pain and provide knee x-ray and/or MRI findings. We considered knee pain with x-ray and/or MRI findings consistent with OA the gold standard. We calculated positive predictive values (PPV) and sensitivity for case identification algorithms.

Results:

Of 100 questionnaires sent, 93 were returned; we excluded 8 subjects who had other rheumatic disorders or total knee replacements. Among those with one code for OA, the PPV was 64% (95% CI = 49%–79%) and it increased to 92% (95% CI = 76%–100%) when two or more OA codes over six months were required. The increase in PPV was accompanied by a drop in sensitivity from 44% (95% CI = 31%–57%) to 19% (95% CI = 9%–30%). Use of one pain code yielded similar results to use of one OA code. Requiring two or more knee pain codes over six months yielded a PPV of 68% (95% CI = 49%–88%) and sensitivity of 26% (95% CI = 15%–38%).

Discussion:

A case identification algorithm requiring two or more knee OA codes yielded the highest PPV at the cost of reduced sensitivity. Tradeoffs between PPV and sensitivity will need to be weighed alongside study goals when selecting a case identification algorithm.

Analgesia Prescribing in Patients with Inflammatory Arthritis in England: An Observational Study Using Electronic Healthcare Record Data

Objectives

International data suggest inflammatory arthritis (IA) pain management frequently involves opioid prescribing, despite little evidence of efficacy, and potential harms. We evaluated analgesic prescribing in English National Health Service-managed patients with IA.

Methods

Repeated cross-sectional analyses in the Consultations in Primary Care Archive (primary care consultation and prescription data in nine general practices from 2000 to 2015) evaluated the annual prevalence of analgesic prescriptions in: (i) IA cases (RA, PsA or axial spondyloarthritis [SpA]), and (ii) up to five age-, sex- and practice-matched controls. Analgesic prescriptions were classified into basic, opioids, gabapentinoids and oral NSAIDs, and sub-classified into chronic and intermittent (≥3 and 1–2 prescriptions per calendar year, respectively).

Results

In 2000, there were 594 cases and 2652 controls, rising to 1080 cases and 4703 controls in 2015. In all years, most (65.3–78.5%) cases received analgesics, compared with fewer (37.5–41.1%) controls. Opioid prescribing in cases fell between 2000 and 2015 but remained common with 45.4% (95% CI: 42.4%, 48.4%) and 32.9% (95% CI: 29.8%, 36.0%) receiving at least 1 and ≥3 opioid prescriptions, respectively, in 2015. Gabapentinoid prescription prevalence in cases increased from 0% in 2000 to 9.5% (95% CI: 7.9%, 11.4%) in 2015, and oral NSAID prescription prevalence fell from 53.7% (95% CI: 49.6%, 57.8%) in 2000 to 25.0% (95% CI: 22.4%, 27.7%) in 2015. Across years, analgesic prescribing was commoner in RA than PsA/axial SpA, and 1.7–2.0 times higher in cases than controls.

Conclusions

Analgesic prescribing in IA is common. This is at variance with existing evidence of analgesic efficacy and risks, and guidelines. Interventions are needed to improve analgesic prescribing in this population.

Mining Primary Care Electronic Health Records for Automatic Disease Phenotyping: A Transparent Machine Learning Framework

(1) Background: We aimed to develop a transparent machine-learning (ML) framework to automatically identify patients with a condition from electronic health records (EHRs) via a parsimonious set of features. (2) Methods: We linked multiple sources of EHRs, including 917,496,869 primary care records and 40,656,805 secondary care records and 694,954 records from specialist surgeries between 2002 and 2012, to generate a unique dataset. Then, we treated patient identification as a problem of text classification and proposed a transparent disease-phenotyping framework. This framework comprises a generation of patient representation, feature selection, and optimal phenotyping algorithm development to tackle the imbalanced nature of the data. This framework was extensively evaluated by identifying rheumatoid arthritis (RA) and ankylosing spondylitis (AS). (3) Results: Being applied to the linked dataset of 9657 patients with 1484 cases of rheumatoid arthritis (RA) and 204 cases of ankylosing spondylitis (AS), this framework achieved accuracy and positive predictive values of 86.19% and 88.46%, respectively, for RA and 99.23% and 97.75% for AS, comparable with expert knowledge-driven methods. (4) Conclusions: This framework could potentially be used as an efficient tool for identifying patients with a condition of interest from EHRs, helping clinicians in clinical decision-support process.

Validation of algorithms for selecting rheumatoid arthritis patients in the Tuscan healthcare administrative databases

Validation of algorithms for selecting patients from healthcare administrative databases (HAD) is recommended. This PATHFINDER study section is aimed at testing algorithms to select rheumatoid arthritis (RA) patients from Tuscan HAD (THAD) and assessing RA diagnosis time interval between the medical chart date and that of THAD. A population was extracted from THAD. The information of the medical charts at the Rheumatology Unit of Pisa University Hospital represented the reference. We included first ever users of biologic disease modifying anti-rheumatic drugs (bDMARDs) between 2014 and 2016 (index date) with at least a specialist visit at the Rheumatology Unit of the Pisa University Hospital recorded from 2013 to the index date. Out of these, we tested four index tests (algorithms): (1) RA according to hospital discharge records or emergency department admissions (ICD-9 code, 714*); (2) RA according to exemption code from co-payment (006); (3) RA according to hospital discharge records or emergency department admissions AND RA according to exemption code from co-payment; (4) RA according to hospital discharge records or emergency department admissions OR RA according to exemption code from co-payment. We estimated sensitivity, specificity, positive and negative predicted values (PPV and NPV) with 95% confidence interval (95% CI) and the RA diagnosis median time interval (interquartile range, IQR). Two sensitivity analyses were performed. Among 277 reference patients, 103 had RA. The fourth algorithm identified 96 true RA patients, PPV 0.78 (95% CI 0.70-0.85), sensitivity 0.93 (95% CI 0.86-0.97), specificity 0.84 (95% CI 0.78-0.90), and NPV 0.95 (95% CI 0.91-0.98). The sensitivity analyses confirmed performance. The time measured between the actual RA diagnosis date recorded in medical charts and that assumed in THAD was 2.2 years (IQR 0.5-8.4). In conclusion, this validation showed the fourth algorithm as the best. The time interval elapsed between the actual RA diagnosis date in medical charts and that extrapolated from THAD has to be considered in the design of future studies.

Incidence and prevalence of Juvenile Idiopathic Arthritis in the United Kingdom 2000-2018: results from the Clinical Practice Research Datalink

Objective

The incidence and prevalence of JIA was last estimated in the UK in 1994. Since then the disease has been reclassified, the specialty of paediatric rheumatology has evolved and there has been a significant shift in disease management with new advanced therapies. This study aimed to provide up-to-date national estimates of this disease.

Methods

Children and young people (CYP) with JIA were identified in the Clinical Practice Research Datalink (CPRD) GOLD and Aurum databases, which source data from the two most commonly used primary care electronic health record systems in the UK. These databases were combined and the cohort was identified (2000–18) using predefined code lists. Validation was performed through linkage to the England Hospital Episode Statistics. Annual incidence and prevalence rates were calculated and stratified by gender, age group and nation of the UK. Direct standardization to the UK population was performed and 5 year incidence rates were calculated between 2003 and 2018.

Results

The age-standardized incidence rate was 5.61 per 100 000 population. The age-standardized prevalence rate in 2018 was 43.5 per 100 000. Rates were higher in Scotland compared with England: incidence rate ratio 1.27 (95% CI 1.11, 1.46). The 5 year incidence rates did not change significantly over time.

Conclusions

This study has provided the first contemporaneous estimates of occurrence of JIA in the UK in 25 years. These data provide important estimates to inform resource allocation and health service development for management of JIA.

Machine Learning in Rheumatic Diseases

With advances in information technology, the demand for using data science to enhance healthcare and disease management is rapidly increasing. Among these technologies, machine learning (ML) has become ubiquitous and indispensable for solving complex problems in many scientific fields, including medical science. ML allows the development of guidelines and framing of the evaluation system for complex diseases based on massive data. In the analysis of rheumatic diseases, which are chronic and remarkably heterogeneous, ML can be anticipated to be extremely helpful in deciphering and revealing the inherent interrelationships in disease development and progression, which can further enhance the overall understanding of the disease, optimize patients' stratification, calibrate therapeutic strategies, and predict prognosis and outcomes. In this review, the basics of ML, its potential clinical applications in rheumatology, together with its strengths and limitations are summarized.

Risk of venous thromboembolism in immune-mediated inflammatory diseases: a UK matched cohort study

Objectives

To describe the risk of venous thromboembolism (VTE), and risk factors for VTE, in people with immune-mediated inflammatory diseases (IMID) (ulcerative colitis, Crohn’s disease (CD), rheumatoid arthritis (RA) and psoriatic arthritis (PsA)), compared with a matched control population.

Methods

A total of 53 378 people with an IMID were identified over 1999–2019 in the UK Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) primary care database and were matched to 213 512 people without an IMID. The association between the presence of any IMID, and each IMID separately, and risk of VTE was estimated using unadjusted and multivariable-adjusted Cox proportional hazards models. The prevalence of VTE risk factors, and associations between VTE risk factors and risk of VTE, were estimated in people with and without an IMID.

Results

People with an IMID were at increased risk of VTE (adjusted HR [aHR] 1.46, 95% CI 1.36,1.56), compared with matched controls. When assessing individual diseases, risk was increased for CD (aHR 1.74, 95% CI 1.45 to 2.08), ulcerative colitis (aHR 1.27, 95% CI 1.10 to 1.45) and RA (aHR 1.54, 95% CI 1.40 to 1.70) but there was no evidence of an association for PsA (aHR 1.21, 95% CI 0.96 to 1.52). In people with an IMID, independent risk factors for VTE included male sex, overweight/obese body mass index, current smoking, history of fracture, and, across study follow-up, abnormal platelet count.

Conclusions

VTE risk is increased in people with IMIDs. Routinely available clinical information may be helpful to identify individuals with an IMID at increased future risk of VTE.

Observational study registration number

Clinicaltrials.gov (NCT03835780).

Low-dose oral glucocorticoid therapy and risk of osteoporotic fractures in patients with rheumatoid arthritis: a cohort study using the Clinical Practice Research Datalink

Objectives

Clinical trials have shown that low-dose glucocorticoid therapy in patients with RA reduces bone loss in hands or hip, but the effect on osteoporotic fractures is not yet clear. Therefore, we investigated the use of low-dose oral glucocorticoids and risk of osteoporotic fractures among patients with RA.

Methods

This was a cohort study including patients with RA aged 50+ years from the Clinical Practice Research Datalink between 1997 and 2017. Exposure to oral glucocorticoids was stratified by the most recent prescription in current (<6 months), recent (7–12 months) and past (>1 year) use, and average daily and cumulative doses. Risk of incident osteoporotic fractures (including hip, vertebrae, humerus, forearm, pelvis and ribs) was estimated by time-dependent Cox proportional-hazards models, adjusted for lifestyle parameters, comorbidities and comedications. Secondary analyses assessed osteoporotic fracture risk with a combination of average daily and cumulative doses of oral glucocorticoids.

Results

Among 15 123 patients with RA (mean age 68.8 years, 68% females), 1640 osteoporotic fractures occurred. Current low-dose oral glucocorticoid therapy (≤7.5 mg prednisolone equivalent dose/day) in patients with RA was not associated with overall risk of osteoporotic fractures (adjusted hazard ratio 1.14, 95% CI 0.98, 1.33) compared with past glucocorticoid use, but was associated with an increased risk of clinical vertebral fracture (adjusted hazard ratio 1.59, 95% CI 1.11, 2.29). Results remained unchanged regardless of a short-term or a long-term use of oral glucocorticoids.

Conclusion

Clinicians should be aware that even in RA patients who receive low daily glucocorticoid doses, the risk of clinical vertebral fracture is increased.

An Efficient CNN for Hand X-Ray Classification of Rheumatoid Arthritis

Hand Radiography (RA) is one of the prime tests for checking the progress of rheumatoid joint inflammation in human bone joints. Recognizing the specific phase of RA is a difficult assignment, as human abilities regularly curb the techniques for it. Convolutional neural network (CNN) is the center for hand recognition for recognizing complex examples. The human cerebrum capacities work in a high-level way, so CNN has been planned depending on organic neural-related organizations in humans for imitating its unpredictable capacities. This article accordingly presents the convolutional neural network (CNN) which has the ability to naturally gain proficiency with the qualities and anticipate the class of hand radiographs from an expansive informational collection. The reproduction of the CNN halfway layers, which depict the elements of the organization, is likewise appeared. For arrangement of the model, a dataset of 290 radiography images is utilized. The result indicates that hand X-rays are rated with an accuracy of 94.46% by the proposed methodology. Our experiments show that the network sensitivity is observed to be 0.95 and the specificity is observed to be 0.82.

Glucocorticoid use is associated with an increased risk of hypertension

OBJECTIVES

Patients with RA are frequently treated with glucocorticoids (GCs), but evidence is conflicting about whether GCs are associated with hypertension. The aim of this study was to determine whether GCs are associated with incident hypertension in patients with RA.

METHODS

A retrospective cohort of patients with incident RA and without hypertension was identified from UK primary care electronic medical records (Clinical Practice Research Datalink). GC prescriptions were used to determine time-varying GC use, dose and cumulative dose, with a 3 month attribution window. Hypertension was identified through either: blood pressure measurements >140/90 mmHg, or antihypertensive prescriptions and a Read code for hypertension. Unadjusted and adjusted Cox proportional hazards regression models were fitted to determine whether there was an association between GC use and incident hypertension.

RESULTS

There were 17 760 patients in the cohort. A total of 7421 (42%) were prescribed GCs during follow-up. The incident rate of hypertension was 64.1 per 1000 person years (95% CI: 62.5, 65.7). The Cox proportional hazards model indicated that recent GC use was associated with a 17% increased hazard of hypertension (hazard ratio 1.17; 95% CI: 1.10, 1.24). When categorized by dose, only doses above 7.5 mg were significantly associated with hypertension. Cumulative dose did not indicate a clear pattern.

CONCLUSION

Recent GC use was associated with incident hypertension in patients with RA, in particular doses ≥7.5 mg were associated with hypertension. Clinicians need to consider cardiovascular risk when prescribing GCs, and ensure blood pressure is regularly monitored and treated where necessary.

Concomitant use of oral glucocorticoids and proton pump inhibitors and risk of osteoporotic fractures among patients with rheumatoid arthritis: a population-based cohort study

BACKGROUND

Patients with rheumatoid arthritis (RA) commonly use oral glucocorticoids (GCs) and proton pump inhibitors (PPIs), both associated with osteoporotic fractures. We investigated the association between concomitant use of oral GCs and PPIs and the risk of osteoporotic fractures among patients with RA.

METHODS

This was a cohort study including patients with RA aged 50+ years from the Clinical Practice Research Datalink between 1997 and 2017. Exposure to oral GCs and PPIs was stratified by the most recent prescription as current use (<6 months), recent use (7-12 months) and past use (>1 year); average daily and cumulative dose; and duration of use. The risk of incident osteoporotic fractures (including hip, vertebrae, humerus, forearm, pelvis and ribs) was estimated by time-dependent Cox proportional-hazards models, statistically adjusted for lifestyle parameters, comorbidities and comedications.

RESULTS

Among 12 351 patients with RA (mean age of 68 years, 69% women), 1411 osteoporotic fractures occurred. Concomitant current use of oral GCs and PPIs was associated with a 1.6-fold increased risk of osteoporotic fractures compared with non-use (adjusted HR: 1.60, 95% CI: 1.35 to 1.89). This was statistically different from a 1.2-fold increased osteoporotic fracture risk associated with oral GC or PPI use alone. Most individual fracture sites were significantly associated with concomitant use of oral GCs and PPIs. Among concomitant users, fracture risk did not increase with higher daily dose or duration of PPI use.

CONCLUSIONS

There was an interaction in the risk of osteoporotic fractures with concomitant use of oral GCs and PPIs. Fracture risk assessment could be considered when a patient with RA is co-prescribed oral GCs and PPIs.

Rheumatoid Arthritis Real-world Management Over 20 Years

Clinical trials show which treatments improve rheumatoid arthritis (RA), whereas observational studies show how patients are managed in routine practice. Prospective cohort studies give the most detailed information about what happens to patients, but being a part of a prospective study influences patient management because patients are no longer routine cases.

Statin use and risk of joint replacement due to osteoarthritis and rheumatoid arthritis: a propensity-score matched longitudinal cohort study

OBJECTIVE

Statins are reported to have a potential benefit on progression of OA and on disease activity in RA, but existing evidence is conflicting. Our objective was to examine whether statins associate with reduction in the risk for joint replacement due to OA and RA.

METHODS

This was a propensity score-matched cohort study. Electronic health records from the UK Clinical Practice Research Datalink were used. We selected people prescribed statins and people never prescribed statins. Each statin user was matched to a non-user by age, gender, practice and propensity score for statin prescription. The main outcome measures were knee or hip joint replacement overall, and specifically because of OA or RA. The association between statins and risk of joint replacement was assessed using Cox proportional hazard regression. Statin exposure was categorized according to the potency of reducing low-density lipoprotein as low (21-28%), medium (32-38%) or high (42-55%) intensity.

RESULTS

A total of 178 467 statin users were matched with 178 467 non-users by age, gender, practice and propensity score. Overall, statin was not associated with reduced risk of knee or hip replacement (hazard ratio 0.99, 95% CI: 0.97, 1.03), unless prescribed at high strength (0.86, 0.75-0.98). The reduced risk was only observed for joint replacement due to RA (0.77, 0.63-0.94) but not OA (0.97, 0.94-1.01).

CONCLUSION

Statins at high intensity may reduce the risk of hip or knee replacement. This effect may be RA specific. Further studies to investigate mechanisms of risk reduction and the impact in people with RA are warranted.

Effect of pre-exposure use of hydroxychloroquine on COVID-19 mortality: a population-based cohort study in patients with rheumatoid arthritis or systemic lupus erythematosus using the OpenSAFELY platform

BACKGROUND

Hydroxychloroquine has been shown to inhibit entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into epithelial cells in vitro, but clinical studies found no evidence of reduced mortality when treating patients with COVID-19. We aimed to evaluate the effectiveness of hydroxychloroquine for prevention of COVID-19 mortality, as opposed to treatment for the disease.

METHODS

We did a prespecified observational, population-based cohort study using national primary care data and linked death registrations in the OpenSAFELY platform, which covers approximately 40% of the general population in England, UK. We included all adults aged 18 years and older registered with a general practice for 1 year or more on March 1, 2020. We used Cox regression to estimate the association between ongoing routine hydroxychloroquine use before the COVID-19 outbreak in England (considered as March 1, 2020) compared with non-users of hydroxychloroquine and risk of COVID-19 mortality among people with rheumatoid arthritis or systemic lupus erythematosus. Model adjustment was informed by a directed acyclic graph.

FINDINGS

Between Sept 1, 2019, and March 1, 2020, of 194 637 people with rheumatoid arthritis or systemic lupus erythematosus, 30 569 (15·7%) received two or more prescriptions of hydroxychloroquine. Between March 1 and July 13, 2020, there were 547 COVID-19 deaths, 70 among hydroxychloroquine users. Estimated standardised cumulative COVID-19 mortality was 0·23% (95% CI 0·18 to 0·29) among users and 0·22% (0·20 to 0·25) among non-users; an absolute difference of 0·008% (-0·051 to 0·066). After accounting for age, sex, ethnicity, use of other immunosuppressive drugs, and geographical region, no association with COVID-19 mortality was observed (HR 1·03, 95% CI 0·80 to 1·33). We found no evidence of interactions with age or other immunosuppressive drugs. Quantitative bias analyses indicated that our observed associations were robust to missing information for additional biologic treatments for rheumatological disease. We observed similar associations with the negative control outcome of non-COVID-19 mortality.

INTERPRETATION

We found no evidence of a difference in COVID-19 mortality among people who received hydroxychloroquine for treatment of rheumatological disease before the COVID-19 outbreak in England. Therefore, completion of randomised trials investigating pre-exposure prophylactic use of hydroxychloroquine for prevention of severe outcomes from COVID-19 are warranted.

FUNDING

Medical Research Council.

Juvenile idiopathic arthritis is associated with higher healthcare utilization after total knee or hip replacement

Objective: To assess whether juvenile idiopathic arthritis (JIA) is associated with healthcare utilization and in-hospital complications after total hip or knee arthroplasty (THA/TKA). Method: We used the 1998-2014 US National Inpatient Sample. We performed multivariable-adjusted logistic regression, adjusted for age, race/ethnicity, gender, income, Deyo-Charlson comorbidity index, insurance payer, and the underlying diagnosis. Results: Of the 4 116 485 THAs and 8 127 282 TKAs, 1882 people with JIA had THAs (0.02%) and 1388 had TKAs (0.01%). Compared to people without JIA, people with JIA post-THA and post-TKA had higher odds ratio [OR (95% confidence interval), respectively] of total hospital charges above the median [1.30 (1.05, 1.60) and 1.37 (1.08, 1.74)], length of hospital stay > 3 days [1.64 (1.27, 2.12) and 1.44 (1.07, 1.93)], and discharge to non-home settings [1.37 (1.07, 1.76)] post-THA, but not post-TKA [1.02 (0.77, 1.36)]. People with JIA also had higher OR of transfusion post-TKA [1.92 (1.44, 2.55)], but not post-THA [1.00 (0.77, 1.30)]. Sensitivity analyses that adjusted for hospital characteristics confirmed the main study findings with minimal or no attenuation of OR. Conclusions: People with JIA utilized more healthcare services post-THA/TKA and were more likely to receive transfusions post-TKA. Interventions to reduce the risk of higher resource utilization are needed in people with JIA.

Prognostic value of comorbidity indices and lung diseases in early rheumatoid arthritis: a UK population-based study

OBJECTIVES

We assessed comorbidity burden in people with RA at diagnosis and early disease (3 years) and its association with early mortality and joint destruction. The association between lung disease and mortality in RA is not well studied; we also explored this relationship.

METHODS

From a contemporary UK-based population (n = 1, 475 762) we identified a cohort with incident RA (n = 6591). The prevalence of comorbidities at diagnosis of RA and at 3 years was compared with age- and gender-matched controls (n = 6591). In individuals with RA we assessed the prognostic value of the Charlson Comorbidity Index and Rheumatic Disease Comorbidity Index calculated at diagnosis for all-cause mortality and joint destruction (with joint surgery as a surrogate marker). We separately evaluated the association between individual lung diseases [chronic obstructive pulmonary disease (COPD), asthma and interstitial lung disease] and mortality.

RESULTS

Respiratory disease, cardiovascular disease, stroke, diabetes, previous fracture and depression were more common (P < 0.05) in patients with RA at diagnosis than controls. Comorbidity (assessed using RDCI) was associated with all-cause mortality in RA [adjusted hazard ratio (HR) 1.26, 95% CI 1.00-1.60]. There was no association with joint destruction. COPD, but not asthma, was associated with mortality (COPD HR 2.84, 95% CI 1.13-7.12).

CONCLUSION

There is an excess burden of comorbidity at diagnosis of RA including COPD, asthma and interstitial lung disease. COPD is a major predictor of early mortality in early RA. Early assessment of comorbidity including lung disease should form part of the routine management of RA patients.

Lifetime risk of knee and hip replacement following a diagnosis of RA: findings from a cohort of 13 961 patients from England

Objective

To estimate the lifetime risk of knee and hip replacement following a diagnosis of RA.

Methods

The analysis was undertaken using routinely collected data from the English NHS. Diagnosis of RA was identified using primary care records, with knee and hip replacement observed in linked hospital records. Parametric survival models were fitted for up to 15 years of follow-up, with age, sex, Charlson comorbidity score, socioeconomic status, BMI and smoking status included as explanatory variables. A decision model was used to combine and extrapolate survival models to estimate lifetime risk.

Results

The number of individuals with a diagnosis of RA and included in the study was 13 961. Lifetime risk of knee replacement and hip replacement was estimated to be 22% (95% CI: 16, 29%) and 17% (95% CI: 11, 26%) following a diagnosis of RA for the average patient profile (non-smoking women aged 64 with no other comorbidities, BMI of 27 and in the top socioeconomic quintile). Risks were higher for younger patients.

Conclusion

The lifetime risk of knee and hip replacement for individuals with a diagnosis of RA is approximately double that of the general population. These findings allow for a better understanding of long-term prognosis and healthcare resource use, and highlight the importance of timely diagnosis and effective treatment.

Can the Use of Bayesian Analysis Methods Correct for Incompleteness in Electronic Health Records Diagnosis Data? Development of a Novel Method Using Simulated and Real-Life Clinical Data

Background: Patient health information is collected routinely in electronic health records (EHRs) and used for research purposes, however, many health conditions are known to be under-diagnosed or under-recorded in EHRs. In research, missing diagnoses result in under-ascertainment of true cases, which attenuates estimated associations between variables and results in a bias toward the null. Bayesian approaches allow the specification of prior information to the model, such as the likely rates of missingness in the data. This paper describes a Bayesian analysis approach which aimed to reduce attenuation of associations in EHR studies focussed on conditions characterized by under-diagnosis.

Methods: Study 1: We created synthetic data, produced to mimic structured EHR data where diagnoses were under-recorded. We fitted logistic regression (LR) models with and without Bayesian priors representing rates of misclassification in the data. We examined the LR parameters estimated by models with and without priors. Study 2: We used EHR data from UK primary care in a case-control design with dementia as the outcome. We fitted LR models examining risk factors for dementia, with and without generic prior information on misclassification rates. We examined LR parameters estimated by models with and without the priors, and estimated classification accuracy using Area Under the Receiver Operating Characteristic.

Results: Study 1: In synthetic data, estimates of LR parameters were much closer to the true parameter values when Bayesian priors were added to the model; with no priors, parameters were substantially attenuated by under-diagnosis. Study 2: The Bayesian approach ran well on real life clinic data from UK primary care, with the addition of prior information increasing LR parameter values in all cases. In multivariate regression models, Bayesian methods showed no improvement in classification accuracy over traditional LR.

Conclusions: The Bayesian approach showed promise but had implementation challenges in real clinical data: prior information on rates of misclassification was difficult to find. Our simple model made a number of assumptions, such as diagnoses being missing at random. Further development is needed to integrate the method into studies using real-life EHR data. Our findings nevertheless highlight the importance of developing methods to address missing diagnoses in EHR data.

The effect of glucocorticoid therapy on mortality in patients with rheumatoid arthritis and concomitant type II diabetes: a retrospective cohort study

BACKGROUND

Patients with rheumatoid arthritis (RA) have increased cardiovascular (CV) and mortality risk. Patients with RA are also frequently prescribed glucocorticoids (GCs) which have been associated with increased risk of mortality. In addition, for patients who have concomitant diabetes mellitus (DM), GCs are known to worsen glycaemic control and hence may further increase CV and mortality risk. This study aimed to understand the relationship between GCs, DM and mortality in patients with RA.

METHODS

This was a retrospective cohort study of patients with incident RA identified from UK primary care electronic medical records. Patients with linkage to Office for National Statistics (ONS) for mortality data (N = 9085) were included. DM was identified through Read codes, prescriptions and blood tests, and GC use was identified through prescriptions. Mortality rate ratios (RR) and rate differences (RD) were calculated across the different exposure groups. Cox proportional hazards regression models were used to estimate interaction on the multiplicative and additive scales.

RESULTS

In those without DM GC use had a 4.4-fold increased all-cause mortality RR (95% confidence interval (CI): 3.83 to 5.14) compared to non-use, whilst those with DM had a lower RR for GC use (3.02 (95% CI: 2.34, 3.90)). However, those with DM had a higher RD associated with GC use because of their higher baseline risk. In those with DM, GC use was associated with an additional 46.7 deaths/1000 person-years (pyrs) (95% CI: 34.1 to 59.3) compared to non-use, while in those without DM GC use was associated with an additional 36.2 deaths/1000 pyrs (95% CI: 31.6 to 40.8). A similar pattern was seen for CV mortality. The adjusted Cox proportional hazards model showed no evidence of multiplicative interaction, but additive interaction indicated a non-significant increased risk. For CV mortality there was no interaction on either scale.

CONCLUSIONS

GC use was associated with higher mortality rates in people with comorbid DM compared to people without DM, despite apparently reassuring similar relative risks. Clinicians need to be aware of the higher baseline risk in patients with DM, and consider this when prescribing GCs in patients with RA and comorbid DM.

The impact of BMI and smoking on risk of revision following knee and hip replacement surgery: evidence from routinely collected data

OBJECTIVE

The aim of this study was to assess the association of body mass index (BMI) and smoking with risk of revision following total knee replacement (TKR) and total hip replacement (THR).

DESIGN

Primary care data, from the Clinical Practice Research Datalink (CPRD), was linked to inpatient hospital records, from Hospital Episode Statistics Admitted Patient Care (HES APC), and covered 1997 to 2014. Parametric survival models, with BMI and smoking status included as explanatory variables, were estimated for 10-year risk of revision and mortality, and were extrapolated to estimate lifetime risk of revision.

FINDINGS

TKR and THR cohorts included 10,260 and 10,961 individuals, respectively. For a change in BMI from 25 to 35, the 10-year risk of revision is expected change from 4.6% (3.3-6.4%) to 3.7% (2.6-5.1%) for TKR and 3.7% (2.8-5.1%) to 4.0% (2.8-5.7%) for THR for an otherwise average patient profile. Meanwhile, changing from a non-smoker to a current smoker is expected to change the risk of revision from 4.1% (3.1-5.5%) to 2.8% (1.7-4.7%) for TKR and from 3.8% (2.8-5.3%) to 2.9% (1.9-4.7%) for THR for an otherwise average patient profile. Estimates of lifetime risk were also similar for different values of BMI or smoking status.

CONCLUSIONS

Obesity and smoking do not appear to have a meaningful impact on the risk of revision following TKR and THR.

The perspective of patients with early rheumatoid arthritis on the journey from symptom onset until referral to a rheumatologist

Objective

Timely treatment of patients with early RA (ERA) favours a beneficial disease outcome. However, individuals often delay their contact with a health-care professional (HCP) after ERA-related symptom onset. The aim of this study was to investigate the perspective of patients on the journey of a patient from RA symptom onset until referral to a specialist.

Methods

A subgroup of patients with ERA from the Care in ERA (CareRA) trial were interviewed retrospectively to discuss their initial ERA-related experiences preceding diagnosis, using a bespoke assessment form. The first section of the form focused on initial symptoms and help-seeking behaviour by the patients. The second part probed the actions of the HCPs consulted. Additional notes derived from the patient stories were analysed thematically.

Results

Among 94 patients, pain (97%), swelling (73%) and stiffness (52%), typically in multiple joints, were reported as initial ERA symptoms. The general practitioner (GP) was generally the first HCP to be contacted (87%). Frequently reported reasons to visit an HCP were intense pain (90.4%) and difficulties in performing daily activities (69%). In 44.1% of patients, the HCP suspected ERA at the first visit. Approximately 25% of patients needed more than five visits before detection of ERA. GPs mainly referred patients to rheumatologists (71%). Thematic analysis uncovered that multiple HCPs were often involved in the journey to RA detection and referral.

Conclusion

Pain is the most commonly reported initial symptom of ERA and the main reason to visit an HCP, usually a GP. These GPs play a pivotal role in early detection and correct referral. Furthermore, the journey of a patient seems complex, often with multiple HCPs being involved.

Descriptive epidemiology of hip and knee replacement in rheumatoid arthritis: An analysis of UK electronic medical records

OBJECTIVE

To provide descriptive data on rates of total hip replacement (THR) and total knee replacement (TKR) within a large RA cohort and describe variation in risk.

METHODS

Incident RA patients (1995 to 2014) were identified from the Clinical Practice Research Datalink (CPRD). First subsequent occurrence of THR and TKR were identified (analysed separately) and incidence rates calculated, stratified by sex, age, BMI, geographic region, and quintiles of the index of multiple deprivation (IMD) score.

RESULTS

There were 27,607 RA patients included, with a total of 1,028 THRs (mean age at surgery: 68.4 years) and 1,366 TKRs (mean age at surgery: 67.6 years), at an overall incidence rate per 1,000 person-years (PYs) [95% CI] of 6.38 [6.00-6.78] and 8.57 [8.12-9.04], respectively. TKR incidence was similar by gender but THR rates were higher in females than males. Rates of TKR but not THR rose according to BMI. An increasing trend was observed in rates of both outcomes according to age (although not ≥75) but of decreasing rates according to socio-economic deprivation. There was some evidence for regional variation in TKR. The 10-year cumulative incidence was 5.2% [4.9, 5.6] and 7.0% [6.6, 7.4] for THR and TKR, respectively.

CONCLUSION

We provide generalizable estimates of THR and TKR incidence in the UK RA patient population and note variation across several key variables. Increased BMI was associated with a large increase in TKR but not THR incidence. Increased deprivation was associated with a downward trend in rates of THR and TKR.

Antibiotic use and the risk of rheumatoid arthritis: a population-based case-control study

BACKGROUND

Antibiotic-induced disturbances of the human microbiota have been implicated in the development of chronic autoimmune conditions. This study aimed to assess whether antibiotic use is associated with the onset of rheumatoid arthritis (RA).

METHODS

A nested case-control study was conducted utilising data from the primary care Clinical Practice Research Datalink (CPRD). Patients with an incident diagnosis of RA were identified (1995-2017). Each case was matched on age, gender, and general practice to ≥ 5 controls without RA. Conditional logistic regression was used to examine previous antibiotic prescriptions and RA onset after controlling for confounding factors.

RESULTS

We identified 22,677 cases of RA, matched to 90,013 controls, with a median follow-up of 10 years before RA diagnosis. The odds of developing RA were 60% higher in those exposed to antibiotics than in those not exposed (OR 1.60; 95% CI 1.51-1.68). A dose- or frequency-dependent association was observed between the number of previous antibiotic prescriptions and RA. All classes of antibiotics were associated with higher odds of RA, with bactericidal antibiotics carrying higher risk than bacteriostatic (45% vs. 31%). Those with antibiotic-treated upper respiratory tract (URT) infections were more likely to be RA cases. However, this was not observed for URT infections not treated with antibiotics. Antifungal (OR = 1.27; 95% CI 1.20-1.35) and antiviral (OR = 1.19; 95% CI 1.14-1.24) prescriptions were also associated with increased odds of RA.

CONCLUSION

Antibiotic prescriptions are associated with a higher risk of RA. This may be due to microbiota disturbances or underlying infections driving risk. Further research is needed to explore these mechanisms.

Androgen Deprivation Therapy for Prostate Cancer and the Risk of Rheumatoid Arthritis: A Population-Based Cohort Study

INTRODUCTION

Two recent observational studies have investigated the association between androgen deprivation therapy (ADT) and rheumatoid arthritis (RA), but generated discrepant findings and had important methodological limitations. Thus, the objective of this study was to determine whether the use of ADT is associated with an increased risk of RA in men with prostate cancer.

PATIENTS AND METHODS

We conducted a population-based cohort study using the United Kingdom Clinical Practice Research Datalink. The cohort included all men, at least 40 years of age, newly diagnosed with prostate cancer between 1 January 1988 and 31 March 2014, with follow-up until 30 September 2014. Exposure to ADT was treated as a time-varying variable and lagged by 1 year to account for diagnostic delays and latency. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of RA, comparing use of ADT with non-use. Secondary analyses were conducted to assess whether the association varied according to ADT type and cumulative duration of use. Finally, we conducted several sensitivity analyses to assess the robustness of our findings.

RESULTS

The cohort included 32,302 men followed for a median of 3.3 years. During follow-up, 63 patients were newly diagnosed with RA, generating an incidence rate of 46.5/100,000 person-years. Compared with non-use, the use of ADT was not associated with an increased risk of RA (HR 0.84, 95% CI 0.49-1.45). In secondary analyses, the association did not vary according to ADT type or with cumulative duration of use (p trend = 0.53). The results remained consistent in sensitivity analyses.

CONCLUSION

In this population-based study, the use of ADT was not associated with an increased risk of RA in men with prostate cancer.

Antibiotic treatment and flares of rheumatoid arthritis: a self-controlled case series study analysis using CPRD GOLD

There is emerging evidence of the impact of infections on rheumatoid arthritis pathogenesis and flares. We aimed to study the association between antibiotic use (and timing of use), and the occurrence of flares in patients with RA. We nested a self-controlled case series (SCCS) of patients who have RA flares within a newly diagnosed RA cohort (n = 31,992) from the UK Clinical Practice Research Datalink (CPRD) GOLD dataset. We determined associations between exposure to antibiotics (beta-lactam, imidazole, macrolide, nitrofurantoin, quinolone, sulphonamide and trimethoprim, and tetracycline) and the occurrence of RA flares. Conditional fixed-effects Poisson regression models were used to determine incidence rate ratios (IRR), offset by the natural logarithm of risk periods. A total of 1,192 (3.7%) of RA subjects had one or more flare/s during the study period, and were therefore included. Use of sulphonamide and trimethoprim was associated with an increased risk of RA flare at 29–90 days (IRR 1.71, CI 1.12–2.59, p = 0.012); 91–183 days (IRR 1.57, CI 1.06–2.33, p = 0.025); and 184–365 days (IRR 1.44, CI 1.03–2.02, p = 0.033) after commencement of antibiotic treatment. No other antibiotic group/s appear associated with RA flare/s risk. Usage of sulphonamide and trimethoprim antibiotics, is associated with a 70% increased risk of RA flare at 1–3 months, which decreases but remains significant up to 12 months after treatment. We hypothesise that the delayed onset of RA flares after specific antibiotics is mediated through the gut or urinary microbiomes. Further epidemiological and mechanistic research is needed to determine the role of infections in RA.

Searching for a prodrome for rheumatoid arthritis in the primary care record: A case-control study in the clinical practice research datalink

BACKGROUND

Rheumatoid arthritis (RA) has articular and non-articular manifestations. Early, intensive treatment has substantial benefit for both. This requires patients be identified as soon as symptoms develop.

OBJECTIVES

To determine whether selected signs and symptoms can be identified in the primary care records of patients prior to a formal diagnosis of RA being made and, if so, how early they can be identified.

METHODS

A case-control study was constructed within the UK Clinical Practice Research Datalink (CPRD). 3577 individuals with 'definite' RA, were matched to 14,287 individuals without inflammatory arthritis. An index date was established (i.e., date general practitioner (GP) first appeared to suspect RA). Rates of consultation and consultations for suspected early RA symptoms were compared in cases and controls in the two years prior to the index date using conditional logistic regression, adjusted for number of consultations.

RESULTS

The mean (standard deviation) age of participants was 58.8 (14.5) years and 66.8% were female. Rates of any consultation were significantly higher in RA cases than in controls for at least two years prior to the index date. Cases were more likely to have a pre-diagnosis coded consultation for joint, and particularly hand symptoms (aOR 11.44 (9.60, 13.63)), morning stiffness (8.10 (3.54, 18.5)), carpal tunnel syndrome (4.57 (3.54, 5.88)) and other non-articular features.

CONCLUSIONS

In patients who develop RA, GP consultation rates are higher for at least two years prior to the first recorded suspicion of RA. This study highlights symptoms that should raise a GP's index of suspicion for RA.

Common mental disorders within chronic inflammatory disorders: a primary care database prospective investigation

Objective

There is inconsistent evidence about the association between inflammatory disorders and depression and anxiety onset in a primary care context. The study aimed to evaluate the risk of depression and anxiety within multisystem and organ-specific inflammatory disorders.

Methods

This is a prospective cohort study with primary care patients from the UK Clinical Practice Research Datalink diagnosed with an inflammatory disorder between 1 January 2001 and 31 December 2016. These patients were matched on age, gender, practice and index date with patients without an inflammatory disorder. The study exposures were seven chronic inflammatory disorders. Clinical diagnosis of depression and anxiety represented the outcome measures of interest.

Results

Among 538 707 participants, the incidence of depression ranged from 14 per 1000 person-years (severe psoriasis) to 9 per 1000 person-years (systemic vasculitis), substantively higher compared with their comparison group (5–7 per 1000 person-years). HRs of multiple depression and anxiety events were 16% higher within inflammatory disorders (HR, 1.16, 95% CI 1.12 to 1.21, p<0.001) compared with the matched comparison group. The incidence of depression and anxiety was strongly associated with the age at inflammatory disorder onset. The overall HR estimate for depression was 1.90 (95% CI 1.66 to 2.17, p<0.001) within early-onset disorder (<40 years of age) and 0.93 (95% CI 0.90 to 1.09, p=0.80) within late-onset disorder (≥60 years of age).

Conclusions

Primary care patients with inflammatory disorders have elevated rates of depression and anxiety incidence, particularly those patients with early-onset inflammatory disorders. This finding may reflect the impact of the underlying disease on patients’ quality of life, although the precise mechanisms require further investigation.

Use of Dipeptidyl Peptidase-4 Inhibitors and New-onset Rheumatoid Arthritis in Patients with Type 2 Diabetes.Epidemiology. 2018;29:904-912. [PMID: 30028343 DOI: 10.1097/EDE.0000000000000891]

BACKGROUND

Case reports have suggested a link between dipeptidyl peptidase-4 (DPP-4) inhibitors, antidiabetic drugs used as second- to third-line treatments, and incidence of rheumatoid arthritis. Because the DPP-4 enzyme is involved in several immunologic processes and possibly in the pathophysiology of rheumatoid arthritis, further research is warranted. This population-based study aimed to determine whether use of DPP-4 inhibitors is associated with incidence of rheumatoid arthritis.

METHODS

Using the United Kingdom Clinical Practice Research Datalink, we conducted a cohort study among 144,603 patients with type 2 diabetes initiating antidiabetic drugs between 2007 and 2016. We estimated hazard ratios (HRs) with 95% confidence intervals (CIs) for incident rheumatoid arthritis using time-dependent Cox proportional hazards models, comparing use of DPP-4 inhibitors with use of other antidiabetic drugs. We imposed a 6-month exposure lag period for latency and diagnostic delays. Secondary analyses included assessment of the duration-response relation and comparison with other second-line antidiabetic drugs, among others.

RESULTS

During 567,169 person-years of follow-up, 464 patients were newly diagnosed with rheumatoid arthritis (crude incidence rate: 82 per 100,000/year). Compared with use of other antidiabetic drugs, use of DPP-4 inhibitors was not associated with an increased risk of rheumatoid arthritis (82 vs. 79 per 100,000/year; HR = 1.0; 95% CI = 0.8, 1.3), with no evidence of duration-response relation. The results did not change after using second-line antidiabetic drugs as the comparator group.

CONCLUSIONS

In this large population-based study, use of DPP-4 inhibitors was not associated with an increased risk of incident rheumatoid arthritis.

The internal validation of weight and weight change coding using weight measurement data within the UK primary care Electronic Health Record

PURPOSE

To use recorded weight values to internally validate weight status and weight change coding in the primary care Electronic Health Record (EHR).

PATIENTS AND METHODS

We included adult patients with weight-related Read codes recorded in the UK's Clinical Practice Research Datalink EHR between 2000 and 2017. Weight status codes were compared to weight values recorded on the same day and positive predictive values (PPVs) were calculated for commonly used codes. Weight change codes were validated using three methods: the percentage (%) difference in kilograms at the time of the code and 1) the previous weight measurement, 2) the weight predicted using linear regression, and 3) the historic mean weight. Weight change codes were validated if estimates were consistent across two out of three methods.

RESULTS

A total of 8,108,481 weight codes were recorded in 1,000,002 patients' EHR. Twice as many were recorded in females (n=5,208,593, 64%). The mean body mass index for "overweight" codes ranged from 31.9 kg/m2 to 46.9 kg/m2 and from 17.4 kg/m2 to 19.2 kg/m2 for "underweight" codes. PPVs for the most commonly used weight status codes ranged from 81.3% (80%-82.5%) to 99.3% (99.2%-99.4%). Across the estimation methods, and using only validated weight change codes, mean weight loss ranged from - 5.2% (SD 5.8%) to -7.9% (SD 7.3%) and mean weight gain from 4.2 % (SD 5.5%) to 7.9 % (SD 8.2%). The previous and predicted weight methods were most consistent.

CONCLUSION

We have developed an internationally applicable methodology to internally validate weight-related EHR coding by using available weight measurement data. We demonstrate the UK Read codes that can be confidently used to classify weight status and weight change in the absence of weight values. We provide the first evidence from primary care that a Read code for unexpected weight loss represents a mean loss of ≥ 5 % in a 6-month period, which was broadly consistent across age groups and gender.

The limitations of using simple definitions of glucocorticoid exposure to predict fracture risk: A cohort study

PURPOSE

To evaluate the effects of different definitions of glucocorticoid (GC) exposure on the magnitude and pattern of fracture risk using the same dataset.

METHODS

Data from patients with rheumatoid arthritis (RA) were extracted from the Clinical Practice Research Datalink, a primary care database with electronic health records in the United Kingdom. Patients exposed to oral GCs were matched to up to two unexposed patients by age, gender and location. The first osteoporotic fracture was identified and adjusted and unadjusted cox proportional hazard ratios (HR) and 95% confidence intervals (CI) produced for fracture risk following GC therapy using different models of risk attribution. These include models demonstrating the effect of dose, duration and recency of GC exposure.

RESULTS

There were 16,507 patients included. Exposed patients were older and had more comorbidities. GC therapy was associated with an increased risk of fracture, with the effect size influenced by risk attribution model. The risk of fracture decreased with less recent exposure from HR (95% CI) 1.66 (1.27, 2.16) during the first month of stopping GCs to 1.11 (0.79, 1.57) for between 1 and 3 months. The risk of fracture increased with current daily dose, HR 1.44 (1.17, 1.77) for 5-9.9 mg prednisolone equivalent dose (PEQ) to 3.02 (1.77, 5.15) for 15-19.9 mg PEQ. Risk of fracture increased with cumulative dose, a function of dose and duration, from HR 1.22 (1.03, 1.44) for <1 g to 1.83 (1.35, 2.48) for 7.5-10 g.

CONCLUSION

GC exposure was associated with excess fracture risk, with effect size differing according to definition of exposure. This highlights the need to incorporate all exposure dimensions (dose, duration and recency) in these patient's fracture risk assessments.

Low salivary cortisol levels in patients with rheumatoid arthritis exposed to oral glucocorticoids: a cross-sectional study set within UK electronic health records

BACKGROUND

Glucocorticoids (GCs) suppress endogenous cortisol levels which can lead to adrenal insufficiency (AI). The frequency of GC-induced AI remains unclear. In this cross-sectional study, low morning salivary cortisol (MSC) levels were used as a measure of adrenal function. The study aim was to investigate the prevalence of low MSC in patients with rheumatoid arthritis (RA) currently and formerly exposed to oral GCs, and the association with potential risk factors.

METHODS

Sample collection was nested within UK primary care electronic health records (from the Clinical Practice Research Datalink). Participants were patients with RA with at least one prescription for oral GCs in the past 2 years. Self-reported oral GC use was used to define current use and current dose; prescription data were used to define exposure duration. MSC was determined from saliva samples; 5 nmol/L was the cut-off for low MSC. The prevalence of low MSC was estimated, and logistic regression was used to assess the association with potential risk factors.

RESULTS

66% of 38 current and 11 % of 38 former GC users had low MSC. Among former users with low MSC, the longest time since GC withdrawal was 6 months. Current GC dose, age and RA duration were significantly associated with increased risk of low MSC.

CONCLUSION

The prevalence of low MSC among current GC users is high, and MSC levels may remain suppressed for several months after GC withdrawal. Clinicians should therefore consider the risk of suppressed cortisol and remain vigilant for symptoms of AI following GC withdrawal.

Exposure measurement error when assessing current glucocorticoid use using UK primary care electronic prescription data

Purpose

To quantify misclassification in glucocorticoid (GC) exposure defined using UK primary care prescription data.

Methods

A cross‐sectional study including patients with rheumatoid arthritis prescribed oral GCs in the past 2 years. Glucocorticoid exposure based on electronic prescription records was compared with participant‐reported GC use captured using a paper diary. Prescription data (containing information about prescriptions issued but no dispensing information) was provided by the Clinical Practice Research Datalink. The following variables were defined: current use and dose of oral GCs and if (and when) participants had received a GC injection. For oral GCs, self‐reported use was taken to represent “true” exposure. A dataset representing a hypothetical population was generated to assess the impact of the misclassification found for current use.

Results

A total of 67 of 78 study participants (86%) were correctly classified as currently on/off oral GCs; 32/38 (84.2%) participants reporting current GC use and 35/40 (87.5%) participants not reporting current use were correctly classified. Estimated values of current dose were imprecise (correlation coefficient 0.46). Concordance between reported and prescribed GC injections was poor (kappa statistic 0.14). Misclassification bias was demonstrated in the hypothetical population: For “true” relative risks of 1.5, 4, and 9, the “observed” relative risks were 1.33, 2.48, and 3.58, respectively.

Conclusions

Misclassification of current use of oral GCs was low but sufficient to lead to significant bias. Researchers should take care to assess the likely impact of exposure misclassification on their analyses.

Inflammation and dementia: Using rheumatoid arthritis as a model to develop treatments?

Dementia is a major international public health problem which looks set to grow as the ageing population increases. Despite large amounts of investment there has been relatively little progress in developing new therapies to combat this. There is a growing body of evidence that both local and systemic inflammation are important in dementia; with cerebral inflammation occurring secondarily to beta-amyloid plaques, raised levels of serum inflammatory molecules and cytokines being present in Alzheimer's disease patients and systemic inflammation being associated with cerebral microvasculature disease in vascular dementia. Observational studies had suggested that non-steroidal anti-inflammatory drugs may reduce the risk of dementia, but subsequent interventional studies have been disappointing. More recently some observational studies have suggested a protective effect from conventional synthetic disease modifying anti-rheumatic drugs (csDMARDS) and tumour necrosis factor inhibiting (TNFi) biological therapies. Treatments for inflammatory rheumatic diseases have previously been repurposed and used successfully in other diseases, such as TNFi for inflammatory bowel disease. There are also studies looking at the use of csDMARDs such as methotrexate to improve outcomes after cardiovascular events. Ongoing interventional trials are currently looking at whether therapies designed to treat inflammatory and autoimmune diseases have the potential to be used to treat dementia.

Representativeness of a digitally engaged population and a patient organisation population with rheumatoid arthritis and their willingness to participate in research: a cross-sectional study

Objectives

To describe (1) the representativeness of (a) users of an online health community (HealthUnlocked.com (HU)) with rheumatoid arthritis (RA) and (b) paid members of an RA patient organisation, the National Rheumatoid Arthritis Society (NRAS), compared with the general RA population; and (2) the willingness of HU users with RA to participate in types of research (surveys, use of an app or activity tracker, and trials).

Methods

A pop-up survey was embedded on HU to determine the characteristics of users and their willingness to participate in research. An anonymous data set of NRAS member characteristics was provided by the NRAS (N=2044). To represent the general RA population, characteristics of people with RA were identified from the Clinical Practice Research Datalink (CPRD) (N=20 594). Cross-sectional comparisons were made across the three groups.

Results

Compared with CPRD, HU respondents (n=615) were significantly younger (49% aged below 55 years compared with 23% of CPRD patients), significantly more deprived (21% in the most deprived Townsend quintile compared with 12% of CPRD patients) and had more recent disease, with 62% diagnosed between 2010 and 2016 compared with 37% of CPRD patients. NRAS members were more similar to the CPRD, but significantly under-represented those aged 75 years or over and over-represented those aged 55–75 years compared with the CPRD. High proportions of HU users were willing to participate in future research of all types.

Conclusions

NRAS members were broadly representative of the general RA population. HU users were younger, more deprived and more recently diagnosed. HU users were willing to participate in most types of research.

The impact of rheumatoid arthritis on the risk of adverse events following joint replacement: a real-world cohort study

Purpose

To assess whether rheumatoid arthritis (RA) is associated with a greater risk of adverse events following total knee replacement (TKR) and total hip replacement (THR) than osteoarthritis (OA).

Patients and methods

Individuals with a diagnosis of RA or OA were identified using primary care records. TKR and THR following diagnosis were identified using linked hospital records. Myocardial infarction (MI), prosthetic joint infection (PJI), venous thromboembolism (VTE), and death were identified within 90 days following surgery, and revision procedures over 10 years following surgery. The impact of RA compared to OA on the risk for these adverse events was assessed using Cox proportional hazard models. Univariable models, with diagnosis as the only explanatory variable, and multivariable models, with age, gender, and year of surgery first added and then a measure of other comorbidities also included, were estimated.

Results

In all 20,763 individuals, with 10,260 TKR and 10,961 THR, were included in the analysis. Compared to those with OA, individuals with a diagnosis of RA had a greater incidence of MI over 90 days following TKR (OA: 0.28%, RA: 0.75%) and revision over 10 years following THR (OA: 5.55%, RA: 8.68%). Both of these differences were statistically significant with, for example, hazard ratios of 3.54 (1.44 to 8.73) for MI and 1.61 (1.06 to 2.46) for revision after controlling for age, gender, year of surgery, and other comorbidities.

Conclusion

These findings suggest that, compared to individuals with OA, those with RA have an increased short-term risk of MI following TKR. While risk of MI remains below 1%, this does underline the importance of the management of cardiovascular risk factors for those with RA. RA was also associated with an increased long-term risk of revision following THR, which strengthens the argument for investing in therapies which may prevent the need for joint replacement.

Assumptions made when preparing drug exposure data for analysis have an impact on results: An unreported step in pharmacoepidemiology studies

Purpose

Real‐world data for observational research commonly require formatting and cleaning prior to analysis. Data preparation steps are rarely reported adequately and are likely to vary between research groups. Variation in methodology could potentially affect study outcomes. This study aimed to develop a framework to define and document drug data preparation and to examine the impact of different assumptions on results.

Methods

An algorithm for processing prescription data was developed and tested using data from the Clinical Practice Research Datalink (CPRD). The impact of varying assumptions was examined by estimating the association between 2 exemplar medications (oral hypoglycaemic drugs and glucocorticoids) and cardiovascular events after preparing multiple datasets derived from the same source prescription data. Each dataset was analysed using Cox proportional hazards modelling.

Results

The algorithm included 10 decision nodes and 54 possible unique assumptions. Over 11 000 possible pathways through the algorithm were identified. In both exemplar studies, similar hazard ratios and standard errors were found for the majority of pathways; however, certain assumptions had a greater influence on results. For example, in the hypoglycaemic analysis, choosing a different variable to define prescription end date altered the hazard ratios (95% confidence intervals) from 1.77 (1.56‐2.00) to 2.83 (1.59‐5.04).

Conclusions

The framework offers a transparent and efficient way to perform and report drug data preparation steps. Assumptions made during data preparation can impact the results of analyses. Improving transparency regarding drug data preparation would increase the repeatability, reproducibility, and comparability of published results.

Pattern of risks of rheumatoid arthritis among patients using statins: A cohort study with the clinical practice research datalink

We examined the association between statin use and the risk of rheumatoid arthritis (RA), with special focus on describing the patterns of risks of RA during statin exposure in a large population-based cohort in the United Kingdom. In the Clinical Practice Research Datalink, patients aged ≥40 years with at least one prescription of statins (1995–2009) were selected, and matched by age (+/-5 years), sex, practice and date of first prescription of statins to non-users. The follow-up period of statin use was divided into periods of current, recent and past exposure, with patients moving between these three exposure categories over time. Time-dependent Cox models were used to derive hazard ratios (HRs) of RA, adjusted for disease history and previous drug use. The study population included 1,023,240 patients, of whom 511,620 were statin users. No associations were found between RA and current (HR_adj,1.06;99%CI:0.88–1.27) or past statin users (HR_adj,1.18;99%CI:0.88–1.57). However, in patients who currently used statins, hazard rates were increased shortly after the first prescription of statins and then gradually decreased to baseline level. The risk of developing RA was increased in recent statin users, as compared to non-users (HR_adj,1.39;99%CI:1.01–1.90). The risk of RA is substantially increased in the first year after the start of statins and then diminishes to baseline level. These findings may suggest that statins might accelerate disease onset in patients susceptible to develop RA, but in other patients, statins are probably safe and well tolerated, even after prolonged use. Alternatively, we cannot rule out that confounding by cardiovascular risk factors and ascertainment bias may have influenced the findings.

A validation study of the CirCom comorbidity score in an English cirrhosis population using the Clinical Practice Research Datalink

Purpose

The CirCom score has been developed from Danish data as a specific measure of comorbidity for cirrhosis to predict all-cause mortality. We compared its performance with the Charlson Comorbidity Index (CCI) in an English cirrhosis population.

Patients and methods

We used comorbidity scores in a survival model to predict mortality in a cirrhosis cohort in the Clinical Practice Research Datalink. The discrimination of each score was compared by age, gender, socioeconomic status, cirrhosis etiology, cirrhosis stage, and year after cirrhosis diagnosis. We also measured their ability to predict liver-related versus non-liver-related death.

Results

There was a small improvement in the C statistic from the model using the CirCom score (C=0.63) compared to the CCI (C=0.62), and there was an overall improvement in the net reclassification index of 1.5%. The improvement was more notable in younger patients, those with an alcohol etiology, and those with compensated cirrhosis. Both scores performed better (C statistic >0.7) for non-liver-related deaths than liver-related deaths (C statistic <0.6), as comorbidity was only weakly predictive of liver-related death.

Conclusion

The CirCom score provided a small improvement in performance over the CCI in the prediction of all-cause and non-liver mortality, but not liver-related mortality. Therefore, it is important to include a measure of comorbidity in studies of cirrhosis survival, alongside a measure of cirrhosis severity.

Trends and determinants of length of stay and hospital reimbursement following knee and hip replacement: evidence from linked primary care and NHS hospital records from 1997 to 2014

OBJECTIVES

To measure changes in length of stay following total knee and hip replacement (TKR and THR) between 1997 and 2014 and estimate the impact on hospital reimbursement, all else being equal. Further, to assess the degree to which observed trends can be explained by improved efficiency or changes in patient profiles.

DESIGN

Cross-sectional study using routinely collected data.

SETTING

National Health Service primary care records from 1995 to 2014 in the Clinical Practice Research Datalink were linked to hospital inpatient data from 1997 to 2014 in Hospital Episode Statistics Admitted Patient Care.

PARTICIPANTS

Study participants had a diagnosis of osteoarthritis or rheumatoid arthritis.

INTERVENTIONS

Primary TKR, primary THR, revision TKR and revision THR.

PRIMARY OUTCOME MEASURES

Length of stay and hospital reimbursement.

RESULTS

10 260 primary TKR, 10 961 primary THR, 505 revision TKR and 633 revision THR were included. Expected length of stay fell from 16.0 days (95% CI 14.9 to 17.2) in 1997 to 5.4 (5.2 to 5.6) in 2014 for primary TKR and from 14.4 (13.7 to 15.0) to 5.6 (5.4 to 5.8) for primary THR, leading to savings of £1537 and £1412, respectively. Length of stay fell from 29.8 (17.5 to 50.5) to 11.0 (8.3 to 14.6) for revision TKR and from 18.3 (11.6 to 28.9) to 12.5 (9.3 to 16.8) for revision THR, but no significant reduction in reimbursement was estimated. The estimated effect of year of surgery remained similar when patient characteristics were included.

CONCLUSIONS

Length of stay for joint replacement fell substantially from 1997 to 2014. These reductions have translated into substantial savings. While patient characteristics affect length of stay and reimbursement, patient profiles have remained broadly stable over time. The observed reductions appear to be mostly explained by improved efficiency.

Incidence of shoulder dislocations in the UK, 1995-2015: a population-based cohort study

OBJECTIVE

This cohort study evaluates the unknown age-specific and gender-specific incidence of primary shoulder dislocations in the UK.

SETTING

UK primary care data from the Clinical Practice Research Datalink (CPRD) were used to identify patients aged 16-70 years with a shoulder dislocation during 1995-2015. Coding of primary shoulder dislocations was validated using the CPRD general practitioner questionnaire service.

PARTICIPANTS

A cohort of 16 763 patients with shoulder dislocation aged 16-70 years during 1995-2015 were identified.

PRIMARY OUTCOME MEASURE

Incidence rates per 100 000 person-years and 95% CIs were calculated.

RESULTS

Correct coding of shoulder dislocation within CPRD was 89% (95% CI 83% to 95%), and confirmation that the dislocation was a 'primary' was 76% (95% CI 67% to 85%). Seventy-two percent of shoulder dislocations occurred in men. The overall incidence rate in men was 40.4 per 100 000 person-years (95% CI 40.4 to 40.4), and in women was 15.5 per 100 000 person-years (95% CI 15.5 to 15.5). The highest incidence was observed in men aged 16-20 years (80.5 per 100 000 person-years; 95% CI 80.5 to 80.6). Incidence in women increased with age to a peak of 28.6 per 100 000 person-years among those aged 61-70 years.

CONCLUSIONS

This is the first time the incidence of shoulder dislocations has been studied using primary care data from a national database, and the first time the results for the UK have been produced. While most primary dislocations occurred in young men, an unexpected finding was that the incidence increased in women aged over 50 years, but not in men. The reasons for this are unknown. Further work is commissioned by the National Institute for Health Research to examine treatments and predictors for recurrent shoulder dislocation.

STUDY REGISTRATION

The design of this study was approved by the Independent Scientific Advisory Committee (15_260) for the Medicines & Healthcare products Regulatory Agency.

Protective effect of antirheumatic drugs on dementia in rheumatoid arthritis patients

Introduction

Rheumatoid arthritis is a systemic inflammatory disease, and classical disease-modifying antirheumatic drugs (cDMARDs) have proven efficacy. It is unknown what impact cDMARDs might have on dementia as an outcome.

Methods

Incident diagnoses of rheumatoid arthritis in persons over 18 years from 1995 to 2011 were identified from the UK Clinical Practice Research Datalink. There were 3876 cDMARD users and were propensity score matched to 1938 nonusers, on a wide range of confounders. Impact on dementia was assessed using survival models.

Results

cDMARD users were at reduced risk of dementia (hazard ratio: 0.60; 95% confidence interval: 0.42–0.85). The effect was strongest in methotrexate users (hazard ratio: 0.52; 95% confidence interval; 0.34–0.82).

Discussion

The strong effect of cDMARD use on halving of dementia risk requires replication in a trial and may provide an important therapeutic pharmacological treatment.