Faculty Bibliography

BACKGROUND: Indian Asians, who make up a quarter of the world's population, are at high risk of developing type 2 diabetes. We investigated whether DNA methylation is associated with future type 2 diabetes incidence in Indian Asians and whether differences in methylation patterns between Indian Asians and Europeans are associated with, and could be used to predict, differences in the magnitude of risk of developing type 2 diabetes. METHODS: We did a nested case-control study of DNA methylation in Indian Asians and Europeans with incident type 2 diabetes who were identified from the 8-year follow-up of 25 372 participants in the London Life Sciences Prospective Population (LOLIPOP) study. Patients were recruited between May 1, 2002, and Sept 12, 2008. We did epigenome-wide association analysis using samples from Indian Asians with incident type 2 diabetes and age-matched and sex-matched Indian Asian controls, followed by replication testing of top-ranking signals in Europeans. For both discovery and replication, DNA methylation was measured in the baseline blood sample, which was collected before the onset of type 2 diabetes. Epigenome-wide significance was set at p<1 x 10(-7). We compared methylation levels between Indian Asian and European controls without type 2 diabetes at baseline to estimate the potential contribution of DNA methylation to increased risk of future type 2 diabetes incidence among Indian Asians. FINDINGS: 1608 (11.9%) of 13 535 Indian Asians and 306 (4.3%) of 7066 Europeans developed type 2 diabetes over a mean of 8.5 years (SD 1.8) of follow-up. The age-adjusted and sex-adjusted incidence of type 2 diabetes was 3.1 times (95% CI 2.8-3.6; p<0.0001) higher among Indian Asians than among Europeans, and remained 2.5 times (2.1-2.9; p<0.0001) higher after adjustment for adiposity, physical activity, family history of type 2 diabetes, and baseline glycaemic measures. The mean absolute difference in methylation level between type 2 diabetes cases and controls ranged from 0.5% (SD 0.1) to 1.1% (0.2). Methylation markers at five loci were associated with future type 2 diabetes incidence; the relative risk per 1% increase in methylation was 1.09 (95% CI 1.07-1.11; p=1.3 x 10(-17)) for ABCG1, 0.94 (0.92-0.95; p=4.2 x 10(-11)) for PHOSPHO1, 0.94 (0.92-0.96; p=1.4 x 10(-9)) for SOCS3, 1.07 (1.04-1.09; p=2.1 x 10(-10)) for SREBF1, and 0.92 (0.90-0.94; p=1.2 x 10(-17)) for TXNIP. A methylation score combining results for the five loci was associated with future type 2 diabetes incidence (relative risk quartile 4 vs quartile 1 3.51, 95% CI 2.79-4.42; p=1.3 x 10(-26)), and was independent of established risk factors. Methylation score was higher among Indian Asians than Europeans (p=1 x 10(-34)). INTERPRETATION: DNA methylation might provide new insights into the pathways underlying type 2 diabetes and offer new opportunities for risk stratification and prevention of type 2 diabetes among Indian Asians. FUNDING: The European Union, the UK National Institute for Health Research, the Wellcome Trust, the UK Medical Research Council, Action on Hearing Loss, the UK Biotechnology and Biological Sciences Research Council, the Oak Foundation, the Economic and Social Research Council, Helmholtz Zentrum Munchen, the German Research Center for Environmental Health, the German Federal Ministry of Education and Research, the German Center for Diabetes Research, the Munich Center for Health Sciences, the Ministry of Science and Research of the State of North Rhine-Westphalia, and the German Federal Ministry of Health.

BACKGROUND: An algorithm that detects errors in diagnosis, classification or coding of diabetes in primary care computerised medial record (CMR) systems is currently available. However, this was developed on CMR systems that are episode orientated medical records (EOMR); and do not force the user to always code a problem or link data to an existing one. More strictly problem orientated medical record (POMR) systems mandate recording a problem and linking consultation data to them. OBJECTIVE: To compare the rates of detection of diagnostic accuracy using an algorithm developed in EOMR with a new POMR specific algorithm. METHOD: We used data from The Health Improvement Network (THIN) database (N = 2,466,364) to identify a population of 100,513 (4.08%) patients considered likely to have diabetes. We recalibrated algorithms designed to classify cases of diabetes to take account of that POMR enforced coding consistency in the computerised medical record systems [In Practice Systems (InPS) Vision] that contribute data to THIN. We explored the different proportions of people classified as having type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM) and with diabetes unclassifiable as either T1DM or T2DM. We compared proportions using chi-square tests and used Tukey's test to compare the characteristics of the people in each group. RESULTS: The prevalence of T1DM using the original EOMR algorithm was 0.38% (9,264/2,466,364), and for T2DM 3.22% (79,417/2,466,364). The prevalence using the new POMR algorithm was 0.31% (7,750/2,466,364) T1DM and 3.65% (89,990/2,466,364) T2DM. The EOMR algorithms also left more people unclassified 11,439 (12%), as to their type of diabetes compared with 2,380 (2.4%), for the new algorithm. Those people who were only classified by the EOMR system differed in terms of older age, and apparently better glycaemic control, despite not being prescribed medication for their diabetes (p < 0.005). CONCLUSION: Increasing the degree of problem orientation of the medical record system can improve the accuracy of recording of diagnoses and, therefore, the accuracy of using routinely collected data from CMRs to determine the prevalence of diabetes mellitus; data processing strategies should reflect the degree of problem orientation.

The aims of supervised machine learning (ML) applications fall into three broad categories: classification, ranking, and calibration/probability estimation. Many ML methods and evaluation techniques relate to the first two. Nevertheless, there are many applications where having an accurate probability estimate is of great importance. Deriving accurate probabilities from the output of a ML method is therefore an active area of research, resulting in several methods to turn a ranking into class probability estimates. In this manuscript we present a method, splined empirical probabilities, based on the receiver operating characteristic (ROC) to complement existing algorithms such as isotonic regression. Unlike most other methods it works with a cumulative quantity, the ROC curve, and as such can be tagged onto an ROC analysis with minor effort. On a diverse set of measures of the quality of probability estimates (Hosmer-Lemeshow, Kullback-Leibler divergence, differences in the cumulative distribution function) using simulated and real health care data, our approach compares favourably with the standard calibration method, the pool adjacent violators algorithm used to perform isotonic regression.

BACKGROUND: Antibiotic prophylaxis given before invasive dental procedures in patients at risk of developing infective endocarditis has historically been the focus of infective endocarditis prevention. Recent changes in antibiotic prophylaxis guidelines in the USA and Europe have substantially reduced the number of patients for whom antibiotic prophylaxis is recommended. In the UK, guidelines from the National Institute for Health and Clinical Excellence (NICE) recommended complete cessation of antibiotic prophylaxis for prevention of infective endocarditis in March, 2008. We aimed to investigate changes in the prescribing of antibiotic prophylaxis and the incidence of infective endocarditis since the introduction of these guidelines. METHODS: We did a retrospective secular trend study, analysed as an interrupted time series, to investigate the effect of antibiotic prophylaxis versus no prophylaxis on the incidence of infective endocarditis in England. We analysed data for the prescription of antibiotic prophylaxis from Jan 1, 2004, to March 31, 2013, and hospital discharge episode statistics for patients with a primary diagnosis of infective endocarditis from Jan 1, 2000, to March 31, 2013. We compared the incidence of infective endocarditis before and after the introduction of the NICE guidelines using segmented regression analysis of the interrupted time series. FINDINGS: Prescriptions of antibiotic prophylaxis for the prevention of infective endocarditis fell substantially after introduction of the NICE guidance (mean 10,900 prescriptions per month [Jan 1, 2004, to March 31, 2008] vs 2236 prescriptions per month [April 1, 2008, to March 31, 2013], p<0.0001). Starting in March, 2008, the number of cases of infective endocarditis increased significantly above the projected historical trend, by 0.11 cases per 10 million people per month (95% CI 0.05-0.16, p<0.0001). By March, 2013, 35 more cases per month were reported than would have been expected had the previous trend continued. This increase in the incidence of infective endocarditis was significant for both individuals at high risk of infective endocarditis and those at lower risk. INTERPRETATION: Although our data do not establish a causal association, prescriptions of antibiotic prophylaxis have fallen substantially and the incidence of infective endocarditis has increased significantly in England since introduction of the 2008 NICE guidelines. FUNDING: Heart Research UK, Simplyhealth, and US National Institutes of Health.

This article revolves around the assessment of corporate social responsibility in relation to pharmaceutical firms. Corporate social responsibility (CSR) is becoming an increasingly important dimension in the corporate landscape. The rise of ethical awareness of stakeholders has prompted many global corporations to adopt CSR policies. This study shines the light on pharmaceutical firms to gauge the level of CSR in this industry. Five of the largest pharmaceutical firms were evaluated using the global reporting initiative (GRI) guidelines as a benchmark. The results showed an unexpectedly large variety in the performance of the companies, with some areas of CSR being emphasised, while others were largely ignored. This is partly due to lack of relevance of certain GRI performance metrics to the pharmaceutical industry. We conclude that the pharmaceutical industry's CSR initiatives require much improvement to be deemed comprehensive. Current major CSR guidelines, including GRI, are largely not industry specific so there needs to be a move to construct relevant CSR guidelines that target issues pertaining to the pharmaceutical industry. There should also be a focus on impact-orientated CSR guidelines, as opposed to simple reportability, in order to promote more meaningful CSR initiatives

BACKGROUND: Recording concerns about child maltreatment, including minor concerns, is recommended by the General Medical Council (GMC) and National Institute for Health and Clinical Excellence (NICE) but there is evidence of substantial under-recording. AIM: To determine whether a simple coding strategy improved recording of maltreatment-related concerns in electronic primary care records. DESIGN AND SETTING: Clinical audit of rates of maltreatment-related coding before January 2010-December 2011 and after January-December 2012 implementation of a simple coding strategy in 11 English family practices. The strategy included encouraging general practitioners to use, always and as a minimum, the Read code 'Child is cause for concern'. A total of 25,106 children aged 0-18 years were registered with these practices. We also undertook a qualitative service evaluation to investigate barriers to recording. METHOD: Outcomes were recording of 1) any maltreatment-related codes, 2) child protection proceedings and 3) child was a cause for concern. RESULTS: We found increased recording of any maltreatment-related code (rate ratio 1.4; 95% CI 1.1-1.6), child protection procedures (RR 1.4; 95% CI 1.1-1.6) and cause for concern (RR 2.5; 95% CI 1.8-3.4) after implementation of the coding strategy. Clinicians cited the simplicity of the coding strategy as the most important factor assisting implementation. CONCLUSION: This simple coding strategy improved clinician's recording of maltreatment-related concerns in a small sample of practices with some 'buy-in'. Further research should investigate how recording can best support the doctor-patient relationship. HOW THIS FITS IN: Recording concerns about child maltreatment, including minor concerns, is recommended by the General Medical Council (GMC) and National Institute for Health and Clinical Excellence (NICE), but there is evidence of substantial under-recording. We describe a simple clinical coding strategy that helped general practitioners to improve recording of maltreatment-related concerns. These improvements could improve case finding of children at risk and information sharing.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) causes progressive renal damage and is a leading cause of end-stage renal failure. With emerging therapies it is important to devise a method for early detection. We aimed to identify factors from routine clinical data which can be used to distinguish people with a high likelihood of having ADPKD in a primary health care setting. METHOD: A cross-sectional study was undertaken using data from the Quality Intervention in Chronic Kidney Disease trial extracted from 127 primary care practices in England. The health records of 255 people with ADPKD were compared to the general population. Logistic regression was used to identify clinical features which distinguish ADPKD. These clinical features were used to stratify individual risk using a risk score tool. RESULTS: Renal impairment, proteinuria, haematuria, a diastolic blood pressure over 90 mmHg and multiple antihypertensive medications were more common in ADPKD than the general population and were used to build a regression model (area under the receiver operating characteristic curve; 0.79). Age, gender, haemoglobin and urinary tract infections were not associated with ADPKD. A risk score (range -3 to +10) of >/=0 gave a sensitivity of 70.2% and specificity 74.9% of for detection. CONCLUSIONS: Stratification of ADPKD likelihood from routine data may be possible. This approach could be a valuable component of future screening programs although further longitudinal analyses are needed.

We report trends in type 2 diabetes mellitus and obesity in adults residing in the Arabian Gulf States. Among the Saudi population, the prevalence of diabetes increased from 10.6% in 1989 to 32.1% in 2009. Prevalence of the disease increased faster among Saudi men than women, with growth rates of 0.8% and 0.6% per year, respectively.