System-wide approaches to antimicrobial therapy and antimicrobial resistance in the UK: the AMR-X framework

Antimicrobial resistance (AMR) threatens human, animal, and environmental health. Acknowledging the urgency of addressing AMR, an opportunity exists to extend AMR action-focused research beyond the confines of an isolated biomedical paradigm. An AMR learning system, AMR-X, envisions a national network of health systems creating and applying optimal use of antimicrobials on the basis of their data collected from the delivery of routine clinical care. AMR-X integrates traditional AMR discovery, experimental research, and applied research with continuous analysis of pathogens, antimicrobial uses, and clinical outcomes that are routinely disseminated to practitioners, policy makers, patients, and the public to drive changes in practice and outcomes. AMR-X uses connected data-to-action systems to underpin an evaluation framework embedded in routine care, continuously driving implementation of improvements in patient and population health, targeting investment, and incentivising innovation. All stakeholders co-create AMR-X, protecting the public from AMR by adapting to continuously evolving AMR threats and generating the information needed for precision patient and population care.

Risk of Falls and Fractures in Individuals With Cataract, Age-Related Macular Degeneration, or Glaucoma

Importance

Three leading disease causes of age-related visual loss are cataract, age-related macular degeneration (AMD), and glaucoma. Although all 3 eye diseases have been implicated with falls and fracture risk, evidence is mixed, with the contribution of different eye diseases being uncertain.

Objective

To examine whether people with cataract, AMD, or glaucoma have higher risks of falls or fractures than those without.

Design, Setting, and Participants

This cohort study was a population-based study in England using routinely collected electronic health records from the Clinical Practice Research Datalink (CPRD) GOLD and Aurum primary care databases with linked hospitalization and mortality records from 2007 to 2020. Participants were people with cataract, AMD, or glaucoma matched to comparators (1:5) by age, sex, and general practice. Data were analyzed from May 2021 to June 2023.

Exposures

For each eye disease, we estimated the risk of falls or fractures using separate multivariable Cox proportional hazards regression models.

Main Outcomes

Two primary outcomes were incident falls and incident fractures derived from general practice, hospital, and mortality records. Secondary outcomes were incident fractures of specific body sites.

Results

A total of 410 476 people with cataract, 75 622 with AMD, and 90 177 with glaucoma were matched (1:5) to 2 034 194 (no cataract), 375 548 (no AMD), and 448 179 (no glaucoma) comparators. The mean (SD) age was 73.8 (11.0) years, 79.4 (9.4) years, and 69.8 (13.1) years for participants with cataract, AMD, or glaucoma, respectively. Compared with comparators, there was an increased risk of falls in those with cataract (adjusted hazard ratio [HR], 1.36; 95% CI, 1.35-1.38), AMD (HR, 1.25; 95% CI, 1.23-1.27), and glaucoma (HR, 1.38; 95% CI, 1.35-1.41). Likewise for fractures, there were increased risks in all eye diseases, with an HR of 1.28 (95% CI, 1.27-1.30) in the cataract cohort, an HR of 1.18 (95% CI, 1.15-1.21) for AMD, and an HR of 1.31 (95% CI, 1.27-1.35) for glaucoma. Site-specific fracture analyses revealed increases in almost all body sites (including hip, spine, forearm, skull or facial bones, pelvis, ribs or sternum, and lower leg fractures) compared with matched comparators.

Conclusions and Relevance

The results of this study support recognition that people with 1 or more of these eye diseases are at increased risk of both falls and fractures. They may benefit from improved advice, access, and referrals to falls prevention services.

The Impact of Oral Antibiotics Prior to Cancer Diagnosis on Overall Patient Survival: Findings from an English Population-Based Cohort Study

BACKGROUND

There is limited evidence in humans as to whether antibiotics impact the effectiveness of cancer treatments. Rodent studies have shown that disruption in gut microbiota due to antibiotics decreases cancer therapy effectiveness. We evaluated the associations between the antibiotic treatment of different time periods before cancer diagnoses and long-term mortality.

METHODS

Using the Clinical Practice Research Datalink GOLD, linked to the Cancer Registry's and the Office for National Statistics' mortality records, we delineated a study cohort that involved cancer patients who were prescribed antibiotics 0-3 months; 3-24 months; or more than 24 months before cancer diagnosis. Patients' exposure to antibiotics was compared according to the recency of prescriptions and time-to-event (all-cause mortality) by applying Cox models.

RESULTS

111,260 cancer patients from England were included in the analysis. Compared with antibiotic prescriptions that were issued in the past, patients who had been prescribed antibiotics shortly before cancer diagnosis presented an increased hazard ratio (HR) for mortality. For leukaemia, the HR in the Cancer Registry was 1.32 (95% CI 1.16-1.51), for lymphoma it was 1.22 (1.08-1.36), for melanoma it was 1.28 (1.10-1.49), and for myeloma it was 1.19 (1.04-1.36). Increased HRs were observed for cancer of the uterus, bladder, and breast and ovarian and colorectal cancer.

CONCLUSIONS

Antibiotics that had been issued within the three months prior to cancer diagnosis may reduce the effectiveness of chemotherapy and immunotherapy. Judicious antibiotic prescribing is needed among cancer patients.

Developing prediction models to estimate the risk of two survival outcomes both occurring: A comparison of techniques

INTRODUCTION

This study considers the prediction of the time until two survival outcomes have both occurred. We compared a variety of analytical methods motivated by a typical clinical problem of multimorbidity prognosis.

METHODS

We considered five methods: product (multiply marginal risks), dual-outcome (directly model the time until both events occur), multistate models (msm), and a range of copula and frailty models. We assessed calibration and discrimination under a variety of simulated data scenarios, varying outcome prevalence, and the amount of residual correlation. The simulation focused on model misspecification and statistical power. Using data from the Clinical Practice Research Datalink, we compared model performance when predicting the risk of cardiovascular disease and type 2 diabetes both occurring.

RESULTS

Discrimination was similar for all methods. The product method was poorly calibrated in the presence of residual correlation. The msm and dual-outcome models were the most robust to model misspecification but suffered a drop in performance at small sample sizes due to overfitting, which the copula and frailty model were less susceptible to. The copula and frailty model's performance were highly dependent on the underlying data structure. In the clinical example, the product method was poorly calibrated when adjusting for 8 major cardiovascular risk factors.

DISCUSSION

We recommend the dual-outcome method for predicting the risk of two survival outcomes both occurring. It was the most robust to model misspecification, although was also the most prone to overfitting. The clinical example motivates the use of the methods considered in this study.

Comparing antibiotic prescribing between clinicians in UK primary care: an analysis in a cohort study of eight different measures of antibiotic prescribing

BACKGROUND

There is a need to reduce antimicrobial uses in humans. Previous studies have found variations in antibiotic (AB) prescribing between practices in primary care. This study assessed variability of AB prescribing between clinicians.

METHODS

Clinical Practice Research Datalink, which collects electronic health records in primary care, was used to select anonymised clinicians providing 500+ consultations during 2012-2017. Eight measures of AB prescribing were assessed, such as overall and incidental AB prescribing, repeat AB courses and extent of risk-based prescribing. Poisson regression models with random effect for clinicians were fitted.

RESULTS

6111 clinicians from 466 general practices were included. Considerable variability between individual clinicians was found for most AB measures. For example, the rate of AB prescribing varied between 77.4 and 350.3 per 1000 consultations; percentage of repeat AB courses within 30 days ranged from 13.1% to 34.3%; predicted patient risk of hospital admission for infection-related complications in those prescribed AB ranged from 0.03% to 0.32% (5th and 95th percentiles). The adjusted relative rate between clinicians in rates of AB prescribing was 5.23. Weak correlation coefficients (<0.5) were found between most AB measures. There was considerable variability in case mix seen by clinicians. The largest potential impact to reduce AB prescribing could be around encouraging risk-based prescribing and addressing repeat issues of ABs. Reduction of repeat AB courses to prescribing habit of median clinician would save 21 813 AB prescriptions per 1000 clinicians per year.

CONCLUSIONS

The wide variation seen in all measures of AB prescribing and weak correlation between them suggests that a single AB measure, such as prescribing rate, is not sufficient to underpin the optimisation of AB prescribing.

Comparative genetic analysis of psoriatic arthritis and psoriasis for the discovery of genetic risk factors and risk prediction modelling

Objectives

Psoriatic arthritis (PsA) has a strong genetic component, and the identification of genetic risk factors could help identify the ~30% of psoriasis patients at high risk of developing PsA. Our objectives were to identify genetic risk factors and pathways that differentiate PsA from cutaneous‐only psoriasis (PsC) and to evaluate the performance of PsA risk prediction models.

Methods

Genome‐wide meta‐analyses were conducted separately for 5,065 patients with PsA and 21,286 healthy controls and separately for 4,340 patients with PsA and 6,431 patients with PsC. The heritability of PsA was calculated as a single‐nucleotide polymorphism (SNP)–based heritability estimate (h²_SNP) and biologic pathways that differentiate PsA from PsC were identified using Priority Index software. The generalizability of previously published PsA risk prediction pipelines was explored, and a risk prediction model was developed with external validation.

Results

We identified a novel genome‐wide significant susceptibility locus for the development of PsA on chromosome 22q11 (rs5754467; P = 1.61 × 10⁻⁹), and key pathways that differentiate PsA from PsC, including NF‐κB signaling (adjusted P = 1.4 × 10⁻⁴⁵) and Wnt signaling (adjusted P = 9.5 × 10⁻⁵⁸). The heritability of PsA in this cohort was found to be moderate (h²_SNP = 0.63), which was similar to the heritability of PsC (h²_SNP = 0.61). We observed modest performance of published classification pipelines (maximum area under the curve 0.61), with similar performance of a risk model derived using the current data.

Conclusion

Key biologic pathways associated with the development of PsA were identified, but the investigation of risk classification revealed modest utility in the available data sets, possibly because many of the PsC patients included in the present study were receiving treatments that are also effective in PsA. Future predictive models of PsA should be tested in PsC patients recruited from primary care.

The DynAIRx Project Protocol: Artificial Intelligence for dynamic prescribing optimisation and care integration in multimorbidity

BACKGROUND

Structured Medication Reviews (SMRs) are intended to help deliver the NHS Long Term Plan for medicines optimisation in people living with multiple long-term conditions and polypharmacy. It is challenging to gather the information needed for these reviews due to poor integration of health records across providers and there is little guidance on how to identify those patients most urgently requiring review.

OBJECTIVE

To extract information from scattered clinical records on how health and medications change over time, apply interpretable artificial intelligence (AI) approaches to predict risks of poor outcomes and overlay this information on care records to inform SMRs. We will pilot this approach in primary care prescribing audit and feedback systems, and co-design future medicines optimisation decision support systems.

DESIGN

DynAIRx will target potentially problematic polypharmacy in three key multimorbidity groups, namely, people with (a) mental and physical health problems, (b) four or more long-term conditions taking ten or more drugs and (c) older age and frailty. Structured clinical data will be drawn from integrated care records (general practice, hospital, and social care) covering an ∼11m population supplemented with Natural Language Processing (NLP) of unstructured clinical text. AI systems will be trained to identify patterns of conditions, medications, tests, and clinical contacts preceding adverse events in order to identify individuals who might benefit most from an SMR.

DISCUSSION

By implementing and evaluating an AI-augmented visualisation of care records in an existing prescribing audit and feedback system we will create a learning system for medicines optimisation, co-designed throughout with end-users and patients.

Using marginal structural models to adjust for treatment drop-in when developing clinical prediction models

Clinical prediction models (CPMs) can inform decision making about treatment initiation, which requires predicted risks assuming no treatment is given. However, this is challenging since CPMs are usually derived using data sets where patients received treatment, often initiated postbaseline as "treatment drop-ins." This study proposes the use of marginal structural models (MSMs) to adjust for treatment drop-in. We illustrate the use of MSMs in the CPM framework through simulation studies that represent randomized controlled trials and real-world observational data and the example of statin initiation for cardiovascular disease prevention. The simulations include a binary treatment and a covariate, each recorded at two timepoints and having a prognostic effect on a binary outcome. The bias in predicted risk was examined in a model ignoring treatment, a model fitted on treatment-naïve patients (at baseline), a model including baseline treatment, and the MSM. In all simulation scenarios, all models except the MSM underestimated the risk of outcome given absence of treatment. These results were supported in the statin initiation example, which showed that ignoring statin initiation postbaseline resulted in models that significantly underestimated the risk of a cardiovascular disease event occurring within 10 years. Consequently, CPMs that do not acknowledge treatment drop-in can lead to underallocation of treatment. In conclusion, when developing CPMs to predict treatment-naïve risk, researchers should consider using MSMs to adjust for treatment drop-in, and also seek to exploit the ability of MSMs to allow estimation of individual treatment effects.

Study investigating the generalisability of a COPD trial based in primary care (Salford Lung Study) and the presence of a Hawthorne effect

Introduction

Traditional phase IIIb randomised trials may not reflect routine clinical practice. The Salford Lung Study in chronic obstructive pulmonary disease (SLS COPD) allowed broad inclusion criteria and followed patients in routine practice. We assessed whether SLS COPD approximated the England COPD population and evidence for a Hawthorne effect.

Methods

This observational cohort study compared patients with COPD in the usual care arm of SLS COPD (2012–2014) with matched non-trial patients with COPD in England from the Clinical Practice Research Datalink database. Generalisability was explored with baseline demographics, clinical and treatment variables; outcomes included COPD exacerbations in adjusted models and pretrial versus peritrial comparisons.

Results

Trial participants were younger (mean, 66.7 vs 71.1 years), more deprived (most deprived quintile, 51.5% vs 21.4%), more current smokers (47.5% vs 32.1%), with more severe Global initiative for chronic Obstructive Lung Disease stages but less comorbidity than non-trial patients. There were no material differences in other characteristics. Acute COPD exacerbation rates were high in the trial population (98.37th percentile).

Conclusion

The trial population was similar to the non-trial COPD population. We observed some evidence of a Hawthorne effect, with more exacerbations recorded in trial patients; however, the largest effect was observed through behavioural changes in patients and general practitioner coding practices.

Antibiotic prescribing patterns in general medical practices in England: Does area matter?

Antimicrobial resistance is an important public health concern. As most antibiotics are prescribed in primary care, understanding prescribing patterns in General Medical (GP) practices is vital. The aim of this study was a spatial pattern analysis of antibiotic prescribing rates in GP practices in England and to examine the association of potential clusters with area level socio-economic deprivation. The pattern analysis identified a number of hot and cold spots of antibiotic prescribing, with hot spots predominantly in the North of England. Spatial regression showed that patient catchments of hot spot practices were significantly more deprived than patient catchments of cold spot practices, especially in the domains of income, employment, education and health. This study suggests the presence of area level drivers resulting in clusters of high and low prescribing. Consequently, area level strategies may be needed for antimicrobial stewardship rather than national level strategies.

A nationwide cohort study of slipped capital femoral epiphysis

OBJECTIVES

To describe the epidemiology of slipped capital femoral epiphysis (SCFE), to examine associations with childhood obesity and socioeconomic deprivation, and to explore factors associated with diagnostic delays.

DESIGN

Historic cohort study using linked primary and secondary care data from the Clinical Practice Research Datalink and Hospital Episode Statistics.

SETTING

All contacts with healthcare services, including emergency presentations, outpatient appointments, inpatient admissions and primary care visits, within the UK National Health Service.

PATIENTS

All individuals <16 years old with a diagnosis of SCFE and whose electronic medical record was held by one of 650 primary care practices in the UK between 1990 and 2013.

MAIN OUTCOME MEASURES

Annual incidence, missed opportunities for diagnosis and diagnostic delay.

RESULTS

Over the 23-year period the incidence remained constant at 4.8 (95% CI 4.4 to 5.2) cases per 100,000 0-16-year-olds. There was a strong association with socioeconomic deprivation. Predisease obesity was also strongly associated with SCFE; mean predisease z-score of body mass index was 1.43 (95% CI 1.20 to 1.68) compared with the UK reference mean. Diagnostic delays were common, with most children (75.4%) having multiple primary care contacts with relevant symptomatology, and those who presented with knee pain having significantly longer diagnostic delay (median 161 (IQR 27-278) days) than those with hip pain (20 (5-126)) or gait abnormalities (21 (7-72)).

CONCLUSIONS

SCFE has a strong association with both area-level socioeconomic deprivation and predisease obesity. The majority of patients with SCFE are initially misdiagnosed and those presenting with knee pain are particularly at risk.

Cost-effectiveness of antibiotics for COPD management: observational analysis using CPRD data

It is often difficult to determine the cause of chronic obstructive pulmonary disease (COPD) exacerbations, and antibiotics are frequently prescribed. This study conducted an observational cost-effectiveness analysis of prescribing antibiotics for exacerbations of COPD based on routinely collected data from patient electronic health records. A cohort of 45 375 patients aged 40 years or more who attended their general practice for a COPD exacerbation during 2000-2013 was identified from the Clinical Practice Research Datalink. Two groups were formed ("immediate antibiotics" or "no antibiotics") based on whether antibiotics were prescribed during the index general practice (GP) consultation, with data analysed according to subsequent healthcare resource use. A cost-effectiveness analysis was undertaken from the perspective of the UK National Health Service, using a time horizon of 4 weeks in the base case. The use of antibiotics for COPD exacerbations resulted in cost savings and an improvement in all outcomes analysed; i.e. GP visits, hospitalisations, community respiratory team referrals, all referrals, infections and subsequent antibiotics prescriptions were lower for the antibiotics group. Hence, the use of antibiotics was dominant over no antibiotics. The economic analysis suggests that use of antibiotics for COPD exacerbations is a cost-effective alternative to not prescribing antibiotics for patients who present to their GP, and remains cost-effective when longer time horizons of 3 months and 12 months are considered. It would be useful for a definitive trial to be undertaken in this area to determine the cost-effectiveness of antibiotics for COPD exacerbations.

Cancer recording in patients with type 2 diabetes in primary care and hospital admission data

ABSTRACTObjectiveElectronic health records are increasingly used to investigate associations between antidiabetic therapy and cancer. Misclassification can impact results, especially if differential between comparators. The objective of this study was to estimate cancer misclassification when using primary care or hospital data alone. ApproachAdults aged ≥40 years with an insulin or oral antidiabetic prescription in Clinical Practice Research Datalink (CPRD) primary care data at least a year after start of data collection, and no record of type 1 diabetes, were included. Patients were matched by year of birth (stepwise within 5 years), sex and GP practice to up to 1 non-diabetic patient. The cohort was restricted to those eligible for Hospital Episode Statistics (HES) linkage with follow-up during the study period (01/04/97-31/12/06). Follow-up started at the maximum of the registration date with the practice, practice up-to-standard date (a CPRD quality metric), and start of study period. Follow-up ended at the minimum of when the patient left the practice, the date CPRD last collected data from the practice, and end of study period. Cancer was identified in CPRD via Read codes and in HES via ICD10 codes. For each cancer case in CPRD, analysis evaluated whether there was a corresponding record in HES coded with same, different or unspecified site. Analysis was repeated for cancers identified in HES. Results53,585 diabetic patients were matched to 47,435 non-diabetic patients. 83% of cancer cases in CPRD had a corresponding record in HES (78% with the same type). Misclassification varied by cancer site, ranging from 3% (stomach cancer) to 57% (nonmelanoma skin cancer). 83% of cancer cases in HES had a corresponding record in CPRD, with all misclassification rates <20%. ConclusionA good level of concordance and low level of misclassification of cancer exist between CPRD primary care data and HES. The value of linking these data for establishing cancer outcomes lies more in the complimentary variables held than in reducing misclassification.

Optimal design and patient selection for interventional trials using radiogenomic biomarkers: A REQUITE and Radiogenomics consortium statement

The optimal design and patient selection for interventional trials in radiogenomics seem trivial at first sight. However, radiogenomics do not give binary information like in e.g. targetable mutation biomarkers. Here, the risk to develop severe side effects is continuous, with increasing incidences of side effects with higher doses and/or volumes. In addition, a multi-SNP assay will produce a predicted probability of developing side effects and will require one or more cut-off thresholds for classifying risk into discrete categories. A classical biomarker trial design is therefore not optimal, whereas a risk factor stratification approach is more appropriate. Patient selection is crucial and this should be based on the dose-response relations for a specific endpoint. Alternatives to standard treatment should be available and this should take into account the preferences of patients. This will be discussed in detail.

Impact of statin related media coverage on use of statins: interrupted time series analysis with UK primary care data

OBJECTIVE

 To quantify how a period of intense media coverage of controversy over the risk:benefit balance of statins affected their use.

DESIGN

 Interrupted time series analysis of prospectively collected electronic data from primary care.

SETTING

 Clinical Practice Research Datalink (CPRD) in the United Kingdom.

PARTICIPANTS

 Patients newly eligible for or currently taking statins for primary and secondary cardiovascular disease prevention in each month in January 2011-March 2015.

MAIN OUTCOME MEASURES

 Adjusted odds ratios for starting/stopping taking statins after the media coverage (October 2013-March 2014).

RESULTS

 There was no evidence that the period of high media coverage was associated with changes in statin initiation among patients with a high recorded risk score for cardiovascular disease (primary prevention) or a recent cardiovascular event (secondary prevention) (odds ratio 0.99 (95% confidence interval 0.87 to 1.13; P=0.92) and 1.04 (0.92 to 1.18; P=0.54), respectively), though there was a decrease in the overall proportion of patients with a recorded risk score. Patients already taking statins were more likely to stop taking them for both primary and secondary prevention after the high media coverage period (1.11 (1.05 to 1.18; P<0.001) and 1.12 (1.04 to 1.21; P=0.003), respectively). Stratified analyses showed that older patients and those with a longer continuous prescription were more likely to stop taking statins after the media coverage. In post hoc analyses, the increased rates of cessation were no longer observed after six months.

CONCLUSIONS

 A period of intense public discussion over the risks:benefit balance of statins, covered widely in the media, was followed by a transient rise in the proportion of people who stopped taking statins. This research highlights the potential for widely covered health stories in the lay media to impact on healthcare related behaviour.

Risk of spontaneous abortion and other pregnancy outcomes in 15-25 year old women exposed to human papillomavirus-16/18 AS04-adjuvanted vaccine in the United Kingdom

BACKGROUND

We assessed the risk of spontaneous abortion (SA) after inadvertent exposure to HPV-16/18-vaccine during pregnancy using an observational cohort design.

METHODS

The study population included women aged 15-25 years registered with the Clinical Practice Research Datalink General Practice OnLine Database in the United Kingdom (UK), who received at least one HPV-16/18-vaccine dose between 1st September 2008 and 30th June 2011. Exposed women had the first day of gestation between 30 days before and 45 days (90 days for the extended exposure period) after any HPV-16/18-vaccine dose. Non-exposed women had the first day of gestation 120 days-18 months after the last dose. SA defined as foetal loss between weeks 1 and 23 of gestation (UK definition).

RESULTS

The frequency of SA was 11.6% (among 207 exposed) and 9.0% (632 non-exposed), women: hazard ratio (HR) adjusted for age at first day of gestation 1.30 (95% confidence interval: 0.79-2.12). Sensitivity analysis per number of doses administered (-30 to +45-day risk period) showed a HR for SA of 1.11 (0.64-1.91) for 18/178 women with one dose during the risk period versus 2.55 (1.09-5.93) in 6/29 women with two doses within a 4-5 weeks period. The proportion of pre-term/full-term/postterm deliveries, small/large for gestational age infants, and birth defects was not significantly different between exposed and non-exposed women. Results were consistent using a (United States) SA definition of foetal loss between weeks 1-19 and/or the extended risk period.

CONCLUSION

There was no evidence of an increased risk of SA and other adverse pregnancy outcomes in young women inadvertently HPV-16/18-vaccinated around gestation. Nevertheless, women who are pregnant or trying to become pregnant are advised to postpone vaccination until completion of pregnancy.

Using linkage to electronic primary care records to evaluate recruitment and nonresponse bias in the Avon Longitudinal Study of Parents and Children

Supplemental Digital Content is available in the text.

Validating childhood asthma in an epidemiological study using linked electronic patient records

OBJECTIVE

To investigate the performance of parent-reported data in identifying physician-confirmed asthma.

DESIGN AND SETTING

Validation study using linkage between the Avon Longitudinal Study of Parents and Children (ALSPAC) and electronic patient records held within the General Practice Research Database (GPRD).

PARTICIPANTS

Participants were those eligible to participate in ALSPAC who also had a record in the GPRD; this included 765 individuals, just under 4% of ALSPAC-eligible participants. The analysis was based on 141 participants with complete parent-reported asthma data.

PRIMARY AND SECONDARY OUTCOME MEASURES

The main GPRD outcome measure was whether a child had a diagnosis of asthma before they were nine. Parent-reported measures were doctor diagnosis of asthma (before mean age 7.5 years), various outcomes based on wheezing and breathlessness recorded longitudinally between 6 months and 8.5 years. Secondary outcomes were bronchial hyper-responsiveness (BHR), forced expiratory volume in 1 s/forced vital capacity ratio and skin prick test responses.

RESULTS

Among the 141 participants with complete parent-reported data, 26 (18%) had an asthma diagnosis before age nine. Using general practitioner (GP)-recorded asthma as the gold standard, the question 'Has a doctor ever diagnosed your child with asthma?' was both sensitive (88.5%) and specific (95.7%). 'Ever wheezed' had the highest sensitivity (100%) but low specificity (60%). More specific definitions were obtained by restricting to those who had wheezed on more than one occasion, experienced frequent wheeze and/or wheezed after the age of 3, but these measures had low sensitivities. BHR only identified 50% of those with a GP-recorded diagnosis.

CONCLUSIONS

Parental reports of a doctor's diagnosis agree well with a GP-recorded diagnosis. High specificity for asthma can be achieved by using detailed wheezing questions, although these definitions are likely to exclude mild cases of asthma. Our study shows that linkage between observational studies and electronic patient records has the potential to enhance epidemiological research.

Exploiting the potential of large databases of electronic health records for research using rapid search algorithms and an intuitive query interface

Objective

UK primary care databases, which contain diagnostic, demographic and prescribing information for millions of patients geographically representative of the UK, represent a significant resource for health services and clinical research. They can be used to identify patients with a specified disease or condition (phenotyping) and to investigate patterns of diagnosis and symptoms. Currently, extracting such information manually is time-consuming and requires considerable expertise. In order to exploit more fully the potential of these large and complex databases, our interdisciplinary team developed generic methods allowing access to different types of user.

Materials and methods

Using the Clinical Practice Research Datalink database, we have developed an online user-focused system (TrialViz), which enables users interactively to select suitable medical general practices based on two criteria: suitability of the patient base for the intended study (phenotyping) and measures of data quality.

Results

An end-to-end system, underpinned by an innovative search algorithm, allows the user to extract information in near real-time via an intuitive query interface and to explore this information using interactive visualization tools. A usability evaluation of this system produced positive results.

Discussion

We present the challenges and results in the development of TrialViz and our plans for its extension for wider applications of clinical research.

Conclusions

Our fast search algorithms and simple query algorithms represent a significant advance for users of clinical research databases.

Socio-economic position and childhood multimorbidity: a study using linkage between the Avon Longitudinal Study of Parents and Children and the General Practice Research Database

INTRODUCTION

In adults, multimorbidity is associated with social position. Socially disadvantaged adults typically experience more chronic illness at a younger age than comparable individuals who are more advantaged. The relation between social position and multimorbidity amongst children and adolescents has not been as widely studied and is less clear.

METHODS

The NHS Information Centre (NHS IC) linked participants in the Avon Longitudinal Study of Parents and Children (ALSPAC) to the General Practice Research Database (GPRD). Multimorbidity was measured in three different ways: using a count of the number of drugs prescribed, a count of chronic diseases, and a person's predicted resource use score; the latter two measures were derived using the Johns Hopkins ACG system. A number of different socio-economic position variables measured as part of ALSPAC during pregnancy and early childhood were considered. Ordered logistic and negative binomial regression models were used to investigate associations between socio-economic variables and multimorbidity.

RESULTS

After mutually adjusting for the different markers of socio-economic position, there was evidence, albeit weak, that chronic condition counts among children aged from 0 to 9 years were higher among those whose mothers were less well educated (OR = 0.44; 95% confidence interval 0.18-1.10; p = 0.08). Conversely, children whose mothers were better educated had higher rates of chronic illness between 10 and 18 years (OR = 1.94; 95% CI 1.14-3.30). However, living in a more deprived area, as indicated by the Townsend score, was associated with a higher odds of chronic illness between 10 and 18 years (OR for each increasing decile of Townsend score = 1.09; 95% CI 1.00-1.19; p = 0.06).

CONCLUSIONS

We have found some evidence that, in younger children, multimorbidity may be higher amongst children whose parents are less well educated. In older children and adolescents this association is less clear. We have also demonstrated that linkage between prospective observational studies and electronic patient records can provide an effective way of obtaining objectively measured outcome variables.

Impact of clinical trial findings on Bell's palsy management in general practice in the UK 2001-2012: interrupted time series regression analysis

OBJECTIVES

To measure the incidence of Bell's palsy and determine the impact of clinical trial findings on Bell's palsy management in the UK.

DESIGN

Interrupted time series regression analysis and incidence measures.

SETTING

General practices in the UK contributing to the Clinical Practice Research Datalink (CPRD).

PARTICIPANTS

Patients ≥16 years with a diagnosis of Bell's palsy between 2001 and 2012.

INTERVENTIONS

(1) Publication of the 2004 Cochrane reviews of clinical trials on corticosteroids and antivirals for Bell's palsy, which made no clear recommendation on their use and (2) publication of the 2007 Scottish Bell's Palsy Study (SBPS), which made a clear recommendation that treatment with prednisolone alone improves chances for complete recovery.

MAIN OUTCOME MEASURES

Incidence of Bell's palsy per 100 000 person-years. Changes in the management of Bell's palsy with either prednisolone therapy, antiviral therapy, combination therapy (prednisolone with antiviral therapy) or untreated cases.

RESULTS

During the 12-year period, 14 460 cases of Bell's palsy were identified with an overall incidence of 37.7/100 000 person-years. The 2004 Cochrane reviews were associated with immediate falls in prednisolone therapy (-6.3% (-11.0 to -1.6)), rising trends in combination therapy (1.1% per quarter (0.5 to 1.7)) and falling trends for untreated cases (-0.8% per quarter (-1.4 to -0.3)). SBPS was associated with immediate increases in prednisolone therapy (5.1% (0.9 to 9.3)) and rising trends in prednisolone therapy (0.7% per quarter (0.4 to 1.2)); falling trends in combination therapy (-1.7% per quarter (-2.2 to -1.3)); and rising trends for untreated cases (1.2% per quarter (0.8 to 1.6)). Despite improvements, 44% still remain untreated.

CONCLUSIONS

SBPS was clearly associated with change in management, but a significant proportion of patients failed to receive effective treatment, which cannot be fully explained. Clarity and uncertainty in clinical trial recommendations may change clinical practice. However, better ways are needed to understand and circumvent barriers in implementing clinical trial findings.

Construction and validation of a scoring system for the selection of high-quality data in a Spanish population primary care database (SIDIAP)

BACKGROUND

Computerised databases of primary care clinical records are widely used for epidemiological research. In Catalonia, the Information System for the Development of Research in Primary Care (SIDIAP) aims to promote the development of research based on high-quality validated data from primary care electronic medical records.

OBJECTIVE

The purpose of this study is to create and validate a scoring system (Registry Quality Score, RQS) that will enable all primary care practices (PCPs) to be selected as providers of researchusable data based on the completeness of their registers.

METHODS

Diseases that were likely to be representative of common diagnoses seen in primary care were selected for RQS calculations. The observed/expected cases ratio was calculated for each disease. Once we had obtained an estimated value for this ratio for each of the selected conditions we added up the ratios calculated for each condition to obtain a final RQS. Rate comparisons between observed and published prevalences of diseases not included in the RQS calculations (atrial fibrillation, diabetes, obesity, schizophrenia, stroke, urinary incontinence and Crohn's disease) were used to set the RQS cutoff which will enable researchers to select PCPs with research-usable data.

RESULTS

Apart from Crohn's disease, all prevalences were the same as those published from the RQS fourth quintile (60th percentile) onwards. This RQS cut-off provided a total population of 1 936 443 (39.6% of the total SIDIAP population).

CONCLUSIONS

SIDIAP is highly representative of the population of Catalonia in terms of geographical, age and sex distributions. We report the usefulness of rate comparison as a valid method to establish research-usable data within primary care electronic medical records.

Good research practices for comparative effectiveness research: approaches to mitigate bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: the International Society for Pharmacoeconomics and Outcomes Research Good Research Practices for Retrospective Database Analysis Task Force Report--Part II

OBJECTIVES

The goal of comparative effectiveness analysis is to examine the relationship between two variables, treatment, or exposure and effectiveness or outcome. Unlike data obtained through randomized controlled trials, researchers face greater challenges with causal inference with observational studies. Recognizing these challenges, a task force was formed to develop a guidance document on methodological approaches to addresses these biases.

METHODS

The task force was commissioned and a Chair was selected by the International Society for Pharmacoeconomics and Outcomes Research Board of Directors in October 2007. This report, the second of three reported in this issue of the Journal, discusses the inherent biases when using secondary data sources for comparative effectiveness analysis and provides methodological recommendations to help mitigate these biases.

RESULTS

The task force report provides recommendations and tools for researchers to mitigate threats to validity from bias and confounding in measurement of exposure and outcome. Recommendations on design of study included: the need for data analysis plan with causal diagrams; detailed attention to classification bias in definition of exposure and clinical outcome; careful and appropriate use of restriction; extreme care to identify and control for confounding factors, including time-dependent confounding.

CONCLUSIONS

Design of nonrandomized studies of comparative effectiveness face several daunting issues, including measurement of exposure and outcome challenged by misclassification and confounding. Use of causal diagrams and restriction are two techniques that can improve the theoretical basis for analyzing treatment effects in study populations of more homogeneity, with reduced loss of generalizability.