Data Resource Profile: Clinical Practice Research Datalink (CPRD).

The Clinical Practice Research Datalink (CPRD) is an ongoing primary care database of anonymised medical records from general practitioners, with coverage of over 11.3 million patients from 674 practices in the UK. With 4.4 million active (alive, currently registered) patients meeting quality criteria, approximately 6.9% of the UK population are included and patients are broadly representative of the UK general population in terms of age, sex and ethnicity. General practitioners are the gatekeepers of primary care and specialist referrals in the UK. The CPRD primary care database is therefore a rich source of health data for research, including data on demographics, symptoms, tests, diagnoses, therapies, health-related behaviours and referrals to secondary care. For over half of patients, linkage with datasets from secondary care, disease-specific cohorts and mortality records enhance the range of data available for research. The CPRD is very widely used internationally for epidemiological research and has been used to produce over 1000 research studies, published in peer-reviewed journals across a broad range of health outcomes. However, researchers must be aware of the complexity of routinely collected electronic health records, including ways to manage variable completeness, misclassification and development of disease definitions for research.LS is supported by a Wellcome Trust Senior Research Fellowship in Clinical Science grant number 098504/Z/12/Z

Novel insights into the aetiology of granulomatosis with polyangiitis—a case–control study using the Clinical Practice Research Datalink

Objectives We aimed to provide insights into the aetiology of granulomatosis with polyangiitis (GPA), by conducting a large case–control study using a general population-based, prospectively collected database of healthcare records. Methods We compared all incident cases of GPA in the Clinical Practice Research Datalink 1990–2014, with up to 10 age-, sex- and general practice-matched controls. We identified potential risk factors, recorded numbers of cases and controls exposed to each, and calculated odds ratios (ORs) using conditional logistic regression. Our main analysis excluded data recorded during 1 year before diagnosis, to prevent early symptoms being mistaken for risk factors. Results We identified 757 people with GPA and matched 7546 controls. People with GPA were five times more likely to have a previous diagnosis of bronchiectasis (OR = 5.1, 95% CI: 2.7, 9.4; P 5 years prior to diagnosis. People with GPA were two to three times more likely than controls to have previous diagnoses of autoimmune diseases or chronic renal impairment, and these effects also remained stable >5 years prior to diagnosis. People with GPA were more likely to have a diagnosis of pulmonary fibrosis (OR = 5.7, 95% CI: 1.7, 19.5; P = 0.01) and sinus infections (OR = 2.7, 95% CI: 1.8, 4.2; P < 0.0001) recorded in the 3 years before diagnosis, but not before this. We also found former smoking, some medications and higher socio-economic status significantly, but less strongly, associated. Conclusion We found novel long-term associations between GPA and pre-existing bronchiectasis and autoimmune diseases

Optimal strategies for monitoring lipid levels in patients at risk or with cardiovascular disease: a systematic review with statistical and cost-effectiveness modelling

Background: Various lipid measurements in monitoring/screening programmes can be used, alone or in cardiovascular risk scores, to guide treatment for prevention of cardiovascular disease (CVD). Because some changes in lipids are due to variability rather than true change, the value of lipid-monitoring strategies needs evaluation. Objective: To determine clinical value and cost-effectiveness of different monitoring intervals and different lipid measures for primary and secondary prevention of CVD. Data sources: We searched databases and clinical trials registers from 2007 [including the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, the Clinical Trials Register, the Current Controlled Trials (CCT) register, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL)] to update and extend previous systematic reviews. Patient-level data from the Clinical Practice Research Datalink (CPRD) and St Luke’s Hospital, Japan, were used in statistical modelling. Utilities and health-care costs were drawn from the literature. Methods: In two meta-analyses, we used prospective studies to examine associations of lipids with CVD and mortality, and randomised controlled trials to estimate lipid-lowering effects of atorvastatin doses. Patient-level data were used to estimate progression and variability of lipid measurements over time, and hence to model lipid-monitoring strategies. Results are expressed as rates of true-/false-positive and true-/false-negative tests for high lipid or high CVD risk. We estimated incremental costs per quality-adjusted life-year. Results: A total of 115 publications reported strength of association between different lipid measures and CVD events in 138 data sets. The summary adjusted hazard ratio (HR) per standard deviation of total cholesterol (TC) to high-density lipoprotein (HDL) cholesterol ratio was 1.25 [95% confidence interval 1.15 to 1.35] for CVD in a primary prevention population but heterogeneity was high (I 2 = 98%); similar results were observed for non-HDL cholesterol, apolipoprotein B and other ratio measures. Associations were smaller for other single lipid measures. Across 10 trials, low-dose atorvastatin (10 and 20 mg) effects ranged from a TC reduction of 0.92 mmol/l to 2.07 mmol/l, and low-density lipoprotein reduction of between 0.88 mmol/l and 1.86 mmol/l. Effects of 40 mg and 80 mg were reported by one trial each. For primary prevention, over a 3-year period, we estimate annual monitoring would unnecessarily treat 9 per 1000 more men (28 vs. 19 per 1000) and 5 per 1000 more women (17 vs. 12 per 1000) than monitoring every 3 years. However, annual monitoring would also undertreat 9 per 1000 fewer men (7 vs. 16 per 1000) and 4 per 1000 fewer women (7 vs. 11 per 1000) than monitoring at 3-year intervals. For secondary prevention, over a 3-year period, annual monitoring would increase unnecessary treatment changes by 66 per 1000 men and 31 per 1000 women, and decrease undertreatment by 29 per 1000 men and 28 per 1000 men, compared with monitoring every 3 years. In cost-effectiveness, strategies with increased screening/monitoring dominate. Exploratory analyses found that any unknown harms of statins would need utility decrements as large as 0.08 (men) to 0.11 (women) per statin user to reverse this finding in primary prevention. Limitation: Heterogeneity in meta-analyses. Conclusions: While acknowledging known and potential unknown harms of statins, we find that more-frequent monitoring strategies are cost-effective compared with others. Regular lipid monitoring in those with and without CVD is likely to be beneficial to patients and to the health service. Future research should include trials of the benefits and harms of atorvastatin 40 and 80 mg, large-scale surveillance of statin safety, and investigation of the effect of monitoring on medication adherence