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Background: The objective of this study was to evaluate the performance of risk scores (Framingham, Assign and QRISK2) in predicting high cardiovascular disease (CVD) risk in individuals rather than populations. Methods and findings: This study included 1.8 million persons without CVD and prior statin prescribing using the Clinical Practice Research Datalink. This contains electronic medical records of the general population registered with a UK general practice. Individual CVD risks were estimated using competing risk regression models. Individual differences in the 10-year CVD risks as predicted by risk scores and competing risk models were estimated; the population was divided into 20 subgroups based on predicted risk. CVD outcomes occurred in 69,870 persons. In the subgroup with lowest risks, risk predictions by QRISK2 were similar to individual risks predicted using our competing risk model (99.9% of people had differences of less than 2%); in the subgroup with highest risks, risk predictions varied greatly (only 13.3% of people had differences of less than 2%). Larger deviations between QRISK2 and our individual predicted risks occurred with calendar year, different ethnicities, diabetes mellitus and number of records for medical events in the electronic health records in the year before the index date. A QRISK2 estimate of low 10-year CVD risk (<15%) was confirmed by Framingham, ASSIGN and our individual predicted risks in 89.8% while an estimate of high 10-year CVD risk (≥20%) was confirmed in only 48.6% of people. The majority of cases occurred in people who had predicted 10-year CVD risk of less than 20%. Conclusions: Application of existing CVD risk scores may result in considerable misclassification of high risk status. Current practice to use a constant threshold level for intervention for all patients, together with the use of different scoring methods, may inadvertently create an arbitrary classification of high CVD risk. [ABSTRACT FROM AUTHOR]

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT Non-steroidal anti-inflammatory drugs (NSAIDs) and paracetamol are widely used analgesics in the prescription and non-prescription settings. Although both classes of drug are generally well tolerated, they can lead to well-characterized adverse effects. Both drugs are widely co-prescribed and it is of interest to understand better safety outcomes when the two drugs are taken concomitantly. WHAT THIS STUDY ADDS? Relative rates and hazard ratio patterns of safety outcomes were broadly similar for patients prescribed ibuprofen alone, paracetamol alone and concomitant ibuprofen and paracetamol. The risks of the various safety outcomes examined do not appear to be modified by concomitant use of ibuprofen and paracetamol compared with paracetamol or ibuprofen alone. AIMS To evaluate and compare the risk of specific safety outcomes in patients prescribed ibuprofen and paracetamol concomitantly with those in patients prescribed ibuprofen or paracetamol alone. The outcomes were evaluated according to dose, duration and exposure. METHODS The study used a retrospective longitudinal cohort design with data from the UK General Practice Research Database (GPRD). The study population included patients aged 18 years or over who were prescribed ibuprofen alone, paracetamol alone or concomitant ibuprofen and paracetamol (tablets or capsules only). The safety outcomes evaluated were upper gastrointestinal events, myocardial infarction, stroke, renal failure (excluding chronic), congestive heart failure, intentional or accidental overdose, suicidal behaviour and mortality. Time-dependent Cox regression was used to estimate relative rates for the safety outcomes, by treatment group. A further analysis evaluated whether the hazard rates (i.e. absolute risks) varied over time with changes in drug exposure. RESULTS The study population included 1.2 million patients. There was considerable heterogeneity in both patient and exposure characteristics. When comparing with past users, for most safety outcomes, current users of concomitant paracetamol and ibuprofen had relative rates between those for current users of ibuprofen alone and paracetamol alone. The hazard rates were generally proportional over time, from current to past exposure, following a prescription for concomitant paracetamol and ibuprofen compared with ibuprofen alone or paracetamol alone. CONCLUSIONS The known risk of the safety outcomes examined does not appear to be modified by concomitant use of ibuprofen and paracetamol compared with paracetamol or ibuprofen alone. [ABSTRACT FROM AUTHOR]

The article discusses the importance of public support to the use of large scale health data which can benefit patient care, public health and research. Topics covered include the problem encountered in initiatives intended to improve the accessibility of healthcare records, the key elements for success of big health data projects and the need for the public to access clear, high quality summaries of healthcare improvements.

Background: Two recent case-control studies by Meier et al. and van Staa et al. used the UK General Practice Research Database (GPRD) to examine the association between the use of statins and the risk of fractures, with different results. The objective of the present study was to examine methodological explanations for the discrepant results.Methods: We created two datasets, which mimicked the previous study designs: a 'selected population' (SP) case-control dataset, with fracture cases matched to controls nested within a selected cohort (Meier et al.), and an 'entire population' (EP) case-control dataset, with both cases and controls sampled from the total GPRD population (van Staa et al.). Cases and controls were matched by gender, age (year of birth or 5 year age bands), and general practice.Results: The study included 131 855 fracture cases. The crude odds ratio (OR) for hip fracture in statin users was 0.37 (95% CI 0.27-0.52) in the SP and 0.54 (95% CI 0.39-0.74) in the EP dataset. This difference was reduced when matching by year of birth, rather than by 5 year age bands: crude ORs were 0.58 (95% CI 0.43-0.79) and 0.61 (95% CI 0.44-0.88), respectively. In the SP dataset, 37% of the cases could be matched by year of birth, while this was achieved for 99% in the 'EP' dataset. The exposure time-window, the selection of confounders, and exclusion of high-risk patients also influenced results.Conclusion: Residual confounding by a matching variable and different definitions of the exposure time window explained differences in results. In case-control studies of drug use and fracture risk, broad matching criteria for age should be avoided and the selection of the time-window for exposure should be carefully considered. [ABSTRACT FROM AUTHOR]

The article discusses a study to evaluate whether bariatric surgery increases the risk of fracture in morbidly obese patients in Great Britain. The study concluded that bariatric surgery did not affect fracture risk significantly; however, there is an increase in risk after three to five years, and in patients who have a greater decrease in body mass index (BMI) after surgery. Thus, the need for a degree of caution to be exerted before going in for bariatric surgery is highlighted.

Background: High levels of antibiotic prescribing are a major concern as they drive antimicrobial resistance. It is currently unknown whether practices that prescribe higher levels of antibiotics also prescribe more medicines in general., Aim: To evaluate the relationship between antibiotic and general prescribing levels in primary care., Design and Setting: Cross-sectional study in 2014-2015 of 6517 general practices in England using NHS digital practice prescribing data (NHS-DPPD) for the main study, and of 587 general practices in the UK using the Clinical Practice Research Datalink for a replication study., Method: Linear regression to assess determinants of antibiotic prescribing., Results: NHS-DPPD practices prescribed an average of 576.1 antibiotics per 1000 patients per year (329.9 at the 5th percentile and 808.7 at the 95th percentile). The levels of prescribing of antibiotics and other medicines were strongly correlated. Practices with high levels of prescribing of other medicines (a rate of 27 159.8 at the 95th percentile) prescribed 80% more antibiotics than low-prescribing practices (rate of 8815.9 at the 5th percentile). After adjustment, NHS-DPPD practices with high prescribing of other medicines gave 60% more antibiotic prescriptions than low-prescribing practices (corresponding to higher prescribing of 276.3 antibiotics per 1000 patients per year). Prescribing of non-opioid painkillers and benzodiazepines were also strong indicators of the level of antibiotic prescribing. General prescribing levels were a much stronger driver for antibiotic prescribing than other risk factors, such as deprivation., Conclusion: The propensity of GPs to prescribe medications generally is an important driver for antibiotic prescribing. Interventions that aim to optimise antibiotic prescribing will need to target general prescribing behaviours, in addition to specifically targeting antibiotics., (© British Journal of General Practice 2019.)

Objectives and Setting: Conflicting results from studies using electronic health records to evaluate the associations between type 2 diabetes and cancer fuel concerns regarding potential biases. This study aimed to describe completeness of cancer recording in UK primary care data linked to hospital admissions records., Design: Patients aged 40+ years with insulin or oral antidiabetic prescriptions in Clinical Practice Research Datalink (CPRD) primary care without type 1 diabetes were matched by age, sex and general practitioner practice to non-diabetics. Those eligible for linkage to Hospital Episode Statistics Admitted Patient Care (HES APC), and with follow-up during April 1997-December 2006 were included., Primary and Secondary Outcome Measures: Cancer recording and date of first record of cancer were compared. Characteristics of patients with cancer most likely to have the diagnosis recorded only in a single data source were assessed. Relative rates of cancer estimated from the two datasets were compared., Participants: 53 585 patients with type 2 diabetes matched to 47 435 patients without diabetes were included., Results: Of all cancers (excluding non-melanoma skin cancer) recorded in CPRD, 83% were recorded in HES APC. 94% of cases in HES APC were recorded in CPRD. Concordance was lower when restricted to same-site cancer records, and was negatively associated with increasing age. Relative rates for cancer were similar in both datasets., Conclusions: Good concordance in cancer recording was found between CPRD and HES APC among type 2 diabetics and matched controls. Linked data may reduce misclassification and increase case ascertainment when analysis focuses on site-specific cancers., Competing Interests: Competing interests: All authors confirm that they are not involved in any organisation or entity with a financial interest in or financial conflict with the subject matter or materials discussed in this manuscript. CPRD is owned by the Secretary of State of the UK Department of Health and operates within the MHRA. CPRD has received funding from the MHRA, Wellcome Trust, Medical Research Council, NIHR Health Technology Assessment programme, Innovative Medicine Initiative, UK Department of Health, Technology Strategy Board, Seventh Framework Programme EU, various universities, contract research organisations and pharmaceutical companies. The Department of Pharmacoepidemiology and Pharmacotherapy, Utrecht Institute for Pharmaceutical Sciences has received unrestricted funding for pharmacoepidemiological research from GlaxoSmithKline, Novo Nordisk, the private-public funded Top Institute Pharma (www.tipharma.nl, includes cofunding from universities, government and industry), the Dutch Medicines Evaluation Board and the Dutch Ministry of Health., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Background: During pandemics of novel influenza and outbreaks of emerging infections, surge in health-care demand can exceed capacity to provide normal standards of care. In such exceptional circumstances, triage tools may aid decisions in identifying people who are most likely to benefit from higher levels of care. Rapid research during the early phase of an outbreak should allow refinement and validation of triage tools so that in the event of surge a valid tool is available. The overarching study aim is to conduct a prospective near real-time analysis of structured clinical assessments of influenza-like illness (ILI) using primary care electronic health records (EHRs) during a pandemic. This abstract summarises the preparatory work, infrastructure development, user testing and proof-of-concept study., Objectives: (1) In preparation for conducting rapid research in the early phase of a future outbreak, to develop processes that allow near real-time analysis of general practitioner (GP) assessments of people presenting with ILI, management decisions and patient outcomes. (2) As proof of concept: conduct a pilot study evaluating the performance of the triage tools 'Community Assessment Tools' and 'Pandemic Medical Early Warning Score' to predict hospital admission and death in patients presenting with ILI to GPs during inter-pandemic winter seasons., Design: Prospective near real-time analysis of structured clinical assessments and anonymised linkage to data from EHRs. User experience was evaluated by semistructured interviews with participating GPs., Setting: Thirty GPs in England, Wales and Scotland, participating in the Clinical Practice Research Datalink., Participants: All people presenting with ILI., Interventions: None., Main Outcome Measures: Study outcome is proof of concept through demonstration of data capture and near real-time analysis. Primary patient outcomes were hospital admission within 24 hours and death (all causes) within 30 days of GP assessment. Secondary patient outcomes included GP decision to prescribe antibiotics and/or influenza-specific antiviral drugs and/or refer to hospital - if admitted, the need for higher levels of care and length of hospital stay., Data Sources: Linked anonymised data from a web-based structured clinical assessment and primary care EHRs., Results: In the 24 months to April 2015, data from 704 adult and 159 child consultations by 30 GPs were captured. GPs referred 11 (1.6%) adults and six (3.8%) children to hospital. There were 13 (1.8%) deaths of adults and two (1.3%) of children. There were too few outcome events to draw any conclusions regarding the performance of the triage tools. GP interviews showed that although there were some difficulties with installation, the web-based data collection tool was quick and easy to use. Some GPs felt that a minimal monetary incentive would promote participation., Conclusions: We have developed processes that allow capture and near real-time automated analysis of GP's clinical assessments and management decisions of people presenting with ILI., Future Work: We will develop processes to include other EHR systems, attempt linkage to data on influenza surveillance and maintain processes in readiness for a future outbreak., Study Registration: This study is registered as ISRCTN87130712 and UK Clinical Research Network 12827., Funding: The National Institute for Health Research Health Technology Assessment programme. MGS is supported by the UK NIHR Health Protection Research Unit in Emerging and Zoonotic Infections.

Background: Data on absolute risks of outcomes and patterns of drug use in cost-effectiveness analyses are often based on randomised clinical trials (RCTs). The objective of this study was to evaluate the external validity of published cost-effectiveness studies by comparing the data used in these studies (typically based on RCTs) to observational data from actual clinical practice. Selective Cox-2 inhibitors (coxibs) were used as an example., Methods and Findings: The UK General Practice Research Database (GPRD) was used to estimate the exposure characteristics and individual probabilities of upper gastrointestinal (GI) events during current exposure to nonsteroidal anti-inflammatory drugs (NSAIDs) or coxibs. A basic cost-effectiveness model was developed evaluating two alternative strategies: prescription of a conventional NSAID or coxib. Outcomes included upper GI events as recorded in GPRD and hospitalisation for upper GI events recorded in the national registry of hospitalisations (Hospital Episode Statistics) linked to GPRD. Prescription costs were based on the prescribed number of tables as recorded in GPRD and the 2006 cost data from the British National Formulary. The study population included over 1 million patients prescribed conventional NSAIDs or coxibs. Only a minority of patients used the drugs long-term and daily (34.5% of conventional NSAIDs and 44.2% of coxibs), whereas coxib RCTs required daily use for at least 6-9 months. The mean cost of preventing one upper GI event as recorded in GPRD was US$104k (ranging from US$64k with long-term daily use to US$182k with intermittent use) and US$298k for hospitalizations. The mean costs (for GPRD events) over calendar time were US$58k during 1990-1993 and US$174k during 2002-2005. Using RCT data rather than GPRD data for event probabilities, the mean cost was US$16k with the VIGOR RCT and US$20k with the CLASS RCT., Conclusions: The published cost-effectiveness analyses of coxibs lacked external validity, did not represent patients in actual clinical practice, and should not have been used to inform prescribing policies. External validity should be an explicit requirement for cost-effectiveness analyses.