Search

BACKGROUND: Approximately 40% of cancers could be prevented if people lived healthier lifestyles. We have developed a theory-based brief intervention to share personalised cancer risk information and promote behaviour change within primary care. This study aimed to assess the feasibility and acceptability of incorporating this intervention into primary care consultations. METHOD: Patients eligible for an NHS Health Check or annual chronic disease review at five general practices were invited to participate in a non-randomised pilot study. In addition to the NHS Health Check or chronic disease review, those receiving the intervention were provided with their estimated risk of developing the most common preventable cancers alongside tailored behaviour change advice. Patients completed online questionnaires at baseline, immediately post-consultation and at 3-month follow-up. Consultations were audio/video recorded. Patients (n = 12) and healthcare professionals (HCPs) (n = 7) participated in post-intervention qualitative interviews that were analysed using thematic analysis. RESULTS: 62 patients took part. Thirty-four attended for an NHS Health Check plus the intervention; 7 for a standard NHS Health Check; 16 for a chronic disease review plus the intervention; and 5 for a standard chronic disease review. The mean time for delivery of the intervention was 9.6 min (SD 3) within NHS Health Checks and 9 min (SD 4) within chronic disease reviews. Fidelity of delivery of the intervention was high. Data from the questionnaires demonstrates potential improvements in health-related behaviours following the intervention. Patients receiving the intervention found the cancer risk information and lifestyle advice understandable, useful and motivating. HCPs felt that the intervention fitted well within NHS Health Checks and facilitated conversations around behaviour change. Integrating the intervention within chronic disease reviews was more challenging. CONCLUSIONS: Incorporating

OBJECTIVE: To assess the association between covid-19 vaccines and risk of thrombocytopenia and thromboembolic events in England among adults. DESIGN: Self-controlled case series study using national data on covid-19 vaccination and hospital admissions. SETTING: Patient level data were obtained for approximately 30 million people vaccinated in England between 1 December 2020 and 24 April 2021. Electronic health records were linked with death data from the Office for National Statistics, SARS-CoV-2 positive test data, and hospital admission data from the United Kingdom's health service (NHS). PARTICIPANTS: 29 121 633 people were vaccinated with first doses (19 608 008 with Oxford-AstraZeneca (ChAdOx1 nCoV-19) and 9 513 625 with Pfizer-BioNTech (BNT162b2 mRNA)) and 1 758 095 people had a positive SARS-CoV-2 test. People aged ≥16 years who had first doses of the ChAdOx1 nCoV-19 or BNT162b2 mRNA vaccines and any outcome of interest were included in the study. MAIN OUTCOME MEASURES: The primary outcomes were hospital admission or death associated with thrombocytopenia, venous thromboembolism, and arterial thromboembolism within 28 days of three exposures: first dose of the ChAdOx1 nCoV-19 vaccine; first dose of the BNT162b2 mRNA vaccine; and a SARS-CoV-2 positive test. Secondary outcomes were subsets of the primary outcomes: cerebral venous sinus thrombosis (CVST), ischaemic stroke, myocardial infarction, and other rare arterial thrombotic events. RESULTS: The study found increased risk of thrombocytopenia after ChAdOx1 nCoV-19 vaccination (incidence rate ratio 1.33, 95% confidence interval 1.19 to 1.47 at 8-14 days) and after a positive SARS-CoV-2 test (5.27, 4.34 to 6.40 at 8-14 days); increased risk of venous thromboembolism after ChAdOx1 nCoV-19 vaccination (1.10, 1.02 to 1.18 at 8-14 days) and after SARS-CoV-2 infection (13.86, 12.76 to 15.05 at 8-14 days); and increased risk of arterial thromboembolism after BNT162b2 mRNA vaccination (1.06, 1.01 to 1.10 at 15-21 da

INTRODUCTION: Recent evidence suggests that ethnic minority groups are disproportionately at increased risk of hospitalisation and death from SARS-CoV-2 infection. Population-based evidence on potential explanatory factors across minority groups and within subgroups is lacking. This study aims to quantify the association between ethnicity and the risk of hospitalisation and mortality due to COVID-19. METHODS AND ANALYSIS: This is a retrospective cohort study of adults registered across a representative and anonymised national primary care database (QResearch) that includes data on 10 million people in England. Sociodemographic, deprivation, clinical and domicile characteristics will be summarised and compared across ethnic subgroups (categorised as per 2011 census). Cox models will be used to calculate HR for hospitalisation and COVID-19 mortality associated with ethnic group. Potential confounding and explanatory factors (such as demographic, socioeconomic and clinical) will be adjusted for within regression models. The percentage contribution of distinct risk factor classes to the excess risks seen in ethnic groups/subgroups will be calculated. ETHICS AND DISSEMINATION: The study has undergone ethics review in accordance with the QResearch agreement (reference OX102). Findings will be disseminated through peer-reviewed manuscripts, presentations at scientific meetings and conferences with national and international stakeholders.

Background There is considerable heterogeneity in individuals’ risk of disease and thus the absolute benefits and harms of population-wide screening programmes. Using colorectal cancer (CRC) screening as an exemplar, we explored how people make decisions about screening when presented with information about absolute benefits and harms, and how those preferences vary with baseline risk, between screening tests and between individuals. Method We conducted two linked studies with members of the public: a think-aloud study exploring decision making in-depth and an online randomised experiment quantifying preferences. In both, participants completed a web-based survey including information about three screening tests (colonoscopy, sigmoidoscopy, and faecal immunochemical testing) and then up to nine scenarios comparing screening to no screening for three levels of baseline risk (1%, 3% and 5% over 15 years) and the three screening tests. Participants reported, after each scenario, whether they would opt for screening (yes/no). Results Of the 20 participants in the think-aloud study 13 did not consider absolute benefits or harms when making decisions concerning CRC screening. In the online experiment (n = 978), 60% expressed intention to attend at 1% risk of CRC, 70% at 3% and 77% at 5%, with no differences between screening tests. At an individual level, 535 (54.7%) would attend at all three risk levels and 178 (18.2%) at none. The 27% whose intention varied by baseline risk were more likely to be younger, without a family history of CRC, and without a prior history of screening. Conclusions Most people in our population were not influenced by the range of absolute benefits and harms associated with CRC screening presented. For an appreciable minority, however, magnitude of benefit was important.

BACKGROUND: The NHS Health Check programme is a prevention initiative offering cardiovascular risk assessment and management advice to adults aged 40-74 years across England. Its effectiveness depends on uptake. When it was introduced in 2009, it was anticipated that all those eligible would be invited over a 5-year cycle and 75% of those invited would attend. So far in the current cycle from 2013 to 2018, 33.8% of those eligible have attended, which is equal to 48.5% of those invited to attend. Understanding the reasons why some people do not attend is important to maximise the impact of the programmes. AIM: To review why people do not attend NHS Health Checks. DESIGN AND SETTING: A systematic review and thematic synthesis of qualitative studies. METHOD: An electronic literature search was carried out of MEDLINE, Embase, Health Management Information Consortium, Cumulative Index to Nursing and Allied Health Literature, Global Health, PsycINFO, Web of Science, OpenGrey, the Cochrane Library, NHS Evidence, Google Scholar, Google, ClinicalTrials.gov, and the ISRCTN registry from 1 January 1996 to 9 November 2016, and the reference lists of all included papers were also screened manually. Inclusion criteria were primary research studies that reported the views of people who were eligible for but had not attended an NHS Health Check. RESULTS: Nine studies met the inclusion criteria. Reasons for not attending included lack of awareness or knowledge, misunderstanding the purpose of the NHS Health Check, aversion to preventive medicine, time constraints, difficulties with access to general practices, and doubts regarding pharmacies as appropriate settings. CONCLUSION: The findings particularly highlight the need for improved communication and publicity around the purpose of the NHS Health Check programme and the personal health benefits of risk factor detection.

BACKGROUND: This study aimed to compare and externally validate risk scores developed to predict incident colorectal cancer (CRC) that include variables routinely available or easily obtainable via self-completed questionnaire. METHODS: External validation of fourteen risk models from a previous systematic review in 373 112 men and women within the UK Biobank cohort with 5-year follow-up, no prior history of CRC and data for incidence of CRC through linkage to national cancer registries. RESULTS: There were 1719 (0.46%) cases of incident CRC. The performance of the risk models varied substantially. In men, the QCancer10 model and models by Tao, Driver and Ma all had an area under the receiver operating characteristic curve (AUC) between 0.67 and 0.70. Discrimination was lower in women: the QCancer10, Wells, Tao, Guesmi and Ma models were the best performing with AUCs between 0.63 and 0.66. Assessment of calibration was possible for six models in men and women. All would require country-specific recalibration if estimates of absolute risks were to be given to individuals. CONCLUSIONS: Several risk models based on easily obtainable data have relatively good discrimination in a UK population. Modelling studies are now required to estimate the potential health benefits and cost-effectiveness of implementing stratified risk-based CRC screening.

OBJECTIVE: To synthesise data concerning the views of commissioners, managers and healthcare professionals towards the National Health Service (NHS) Health Check programme in general and the challenges faced when implementing it in practice. DESIGN: A systematic review of surveys and interview studies with a descriptive analysis of quantitative data and thematic synthesis of qualitative data. DATA SOURCES: An electronic literature search of MEDLINE, Embase, Health Management Information Consortium, Cumulative Index of Nursing and Allied Health Literature, Global Health, PsycInfo, Web of Science, OpenGrey, the Cochrane Library, NHS Evidence, Google Scholar, Google, ClinicalTrials.gov and the International Standard Randomised Controlled Trial Number registry from 1 January 1996 to 9 November 2016 with no language restriction and manual screening of reference lists of all included papers. INCLUSION CRITERIA: Primary research reporting views of commissioners, managers or healthcare professionals on the NHS Health Check programme and its implementation in practice. RESULTS: Of 18 524 citations, 15 articles met the inclusion criteria. There was evidence from both quantitative and qualitative studies that some commissioners and general practice (GP) healthcare professionals were enthusiastic about the programme, whereas others raised concerns around inequality of uptake, the evidence base and cost-effectiveness. In contrast, those working in pharmacies were all positive about programme benefits, citing opportunities for their business and staff. The main challenges to implementation were: difficulties with information technology and computer software, resistance to the programme from some GPs, the impact on workload and staffing, funding and training needs. Inadequate privacy was also a challenge in pharmacy and community settings, along with difficulty recruiting people eligible for Health Checks and poor public access to some venues. CONCLUSIONS: The success of the NHS H

OBJECTIVE: To review the experiences of patients attending NHS Health Checks in England. DESIGN: A systematic review of quantitative and qualitative studies with a thematic synthesis of qualitative studies. DATA SOURCES: An electronic literature search of Medline, Embase, Health Management Information Consortium, Cumulative Index of Nursing and Allied Health Literature, Global Health, PsycInfo, Web of Science, OpenGrey, the Cochrane Library, National Health Service (NHS) Evidence, Google Scholar, Google, Clinical Trials.gov and the ISRCTN registry to 09/11/16 with no language restriction and manual screening of reference lists of all included papers. INCLUSION CRITERIA: Primary research reporting experiences of patients who have attended NHS Health Checks. RESULTS: 20 studies met the inclusion criteria, 9 reporting quantitative data and 15 qualitative data. There were consistently high levels of reported satisfaction in surveys, with over 80% feeling that they had benefited from an NHS Health Check. Data from qualitative studies showed that the NHS Health Check had been perceived to act as a wake-up call for many who reported having gone on to make substantial lifestyle changes which they attributed to the NHS Health Check. However, some had been left with a feeling of unmet expectations, were confused about or unable to remember their risk scores, found the lifestyle advice too simplistic and non-personalised or were confused about follow-up. CONCLUSIONS: While participants were generally very supportive of the NHS Health Check programme and examples of behaviour change were reported, there are a number of areas where improvements could be made. These include greater clarity around the aims of the programme within the promotional material, more proactive support for lifestyle change and greater appreciation of the challenges of communicating risk and the limitations of relying on the risk score alone as a trigger for facilitating behaviour change.

It is widely accepted that dietary sugars promote adverse metabolic outcomes via weight-gain through their contribution to energy intake. Emerging evidence suggests that dietary sugars are associated with adverse metabolic outcomes including increased blood pressure and serum lipids, independently of energy intake and body-weight1. However, dietary sugars are a complex component of the diet and their effects on health outcomes are likely to differ depending on the properties of the consumed sugars. Therefore, associations between dietary sugars and metabolic and inflammatory markers may vary according to whether sugars are from beverage or food sources and, extrinsic or intrinsic. The aim of this study was to examine the association between intakes of dietary sugars from different sources and metabolic and inflammatory markers using a population-based cross-sectional study of adults in the East of England. Sugar intakes from beverages (liquids), foods (solids), extrinsic (free sugars) or intrinsic (non-free sugars) were estimated using food frequency questionnaires. Glycated haemoglobin, glucose, insulin, and C-Reactive Protein (CRP) were measured in fasting blood samples and insulin resistance (HOMA-IR) and a continuous metabolic risk z-score were derived. The contributions to total energy intake (TEI) of sugars from liquids, solids, free sugars and non-free sugars contributed 2.9%, 20.0%, 12.0% and 11.6% respectively. In multiple linear regression analyses adjusted for age, sex, socio-economic status, smoking status, alcohol consumption, physical activity, clinical history, BMI, TEI, dietary quality, fat intake and sugars from other sources, and corrected for multiple testing, sugars from liquids (per 10%TEI) were positively associated with ln-CRP [β-coefficient(95%CI), 0.14(0.05,0.22)] and the metabolic risk z-score [0.13(0.07,0.18)]. Free sugars were positively associated with ln-HOMA-IR [0.05(0.03,0.08)] and the metabolic risk z-score [0.09(0.06,0.12)]. Sugars

BACKGROUND: Colorectal cancer (CRC) is the fourth leading cause of cancer-related death in Europe and the United States. Detecting the disease at an early stage improves outcomes. Risk prediction models which combine multiple risk factors and symptoms have the potential to improve timely diagnosis. The aim of this review is to systematically identify and compare the performance of models that predict the risk of primary CRC among symptomatic individuals. METHODS: We searched Medline and EMBASE to identify primary research studies reporting, validating or assessing the impact of models. For inclusion, models needed to assess a combination of risk factors that included symptoms, present data on model performance, and be applicable to the general population. Screening of studies for inclusion and data extraction were completed independently by at least two researchers. RESULTS: Twelve thousand eight hundred eight papers were identified from the literature search and three through citation searching. 18 papers describing 15 risk models were included. Nine were developed in primary care populations and six in secondary care. Four had good discrimination (AUROC > 0.8) in external validation studies, and sensitivity and specificity ranged from 0.25 and 0.99 to 0.99 and 0.46 depending on the cut-off chosen. CONCLUSIONS: Models with good discrimination have been developed in both primary and secondary care populations. Most contain variables that are easily obtainable in a single consultation, but further research is needed to assess clinical utility before they are incorporated into practice.

Colorectal cancer is the second leading cause of cancer-related death in Europe and the United States. Survival is strongly related to stage at diagnosis and population-based screening reduces colorectal cancer incidence and mortality. Stratifying the population by risk offers the potential to improve the efficiency of screening. In this systematic review we searched Medline, EMBASE, and the Cochrane Library for primary research studies reporting or validating models to predict future risk of primary colorectal cancer for asymptomatic individuals. A total of 12,808 papers were identified from the literature search and nine through citation searching. Fifty-two risk models were included. Where reported (n = 37), half the models had acceptable-to-good discrimination (the area under the receiver operating characteristic curve, AUROC >0.7) in the derivation sample. Calibration was less commonly assessed (n = 21), but overall acceptable. In external validation studies, 10 models showed acceptable discrimination (AUROC 0.71-0.78). These include two with only three variables (age, gender, and BMI; age, gender, and family history of colorectal cancer). A small number of prediction models developed from case-control studies of genetic biomarkers also show some promise but require further external validation using population-based samples. Further research should focus on the feasibility and impact of incorporating such models into stratified screening programmes.

INTRODUCTION: Individuals with screen-detected diabetes are likely to receive intensified pharmacotherapy to improve glycaemic control and general cardiometabolic health. Individuals are often asymptomatic, and little is known about the degree to which polypharmacy is present both before, and after diagnosis. We aimed to describe and characterize the pharmacotherapy burden of individuals with screen-detected diabetes at diagnosis, 1 and 5 years post-diagnosis. METHODS: The prescription histories of 1026 individuals with screen-detected diabetes enrolled in the ADDITION-UK trial of the promotion of intensive treatment were coded into general medication types at diagnosis, 1 and 5 years post-diagnosis. The association between change in the count of several medication types and age, baseline 10-year UK Prospective Diabetes Study (UKPDS) cardiovascular disease (CVD risk), sex, intensive treatment group and number of medications was explored. RESULTS: Just under half of individuals were on drugs unrelated to cardioprotection before diagnosis (42%), and this increased along with a rise in the number of prescribed diabetes-related and cardioprotective drugs. The medication profile over the first 5 years suggests multimorbidity and polypharmacy is present in individuals with screen-detected diabetes. Higher modeled CVD risk at baseline was associated with a greater increase in cardioprotective and diabetes-related medication, but not an increase in other medications. CONCLUSION: As recommended in national guidelines, our results suggest that treatment of diabetes was influenced by the underlying risk of CVD. While many individuals did not start glucose lowering and cardioprotective therapies in the first 5 years after diagnosis, more information is required to understand whether this represents unmet need, or patient-centered care. TRIAL REGISTRATION NUMBER: CNT00237549.

Numerous risk tools are now available, which predict either current or future risk of a cancer diagnosis. In theory, these tools have the potential to improve patient outcomes through enhancing the consistency and quality of clinical decision-making, facilitating equitable and cost-effective distribution of finite resources such as screening tests or preventive interventions, and encouraging behaviour change. These potential uses have been recognised by the National Cancer Institute as an 'area of extraordinary opportunity' and an increasing number of risk prediction models continue to be developed. The data on predictive utility (discrimination and calibration) of these models suggest that some have potential for clinical application; however, the focus on implementation and impact is much more recent and there remains considerable uncertainty about their clinical utility and how to implement them in order to maximise benefits and minimise harms such as over-medicalisation, anxiety and false reassurance. If the potential benefits of risk prediction models are to be realised in clinical practice, further validation of the underlying risk models and research to assess the acceptability, clinical impact and economic implications of incorporating them in practice are needed.

AIMS: To examine the short- and long-term cost-effectiveness of intensive multifactorial treatment compared with routine care among people with screen-detected Type 2 diabetes. METHODS: Cost-utility analysis in ADDITION-UK, a cluster-randomized controlled trial of early intensive treatment in people with screen-detected diabetes in 69 UK general practices. Unit treatment costs and utility decrement data were taken from published literature. Accumulated costs and quality-adjusted life years (QALYs) were calculated using ADDITION-UK data from 1 to 5 years (short-term analysis, n = 1024); trial data were extrapolated to 30 years using the UKPDS outcomes model (version 1.3) (long-term analysis; n = 999). All costs were transformed to the UK 2009/10 price level. RESULTS: Adjusted incremental costs to the NHS were £285, £935, £1190 and £1745 over a 1-, 5-, 10- and 30-year time horizon, respectively (discounted at 3.5%). Adjusted incremental QALYs were 0.0000, - 0.0040, 0.0140 and 0.0465 over the same time horizons. Point estimate incremental cost-effectiveness ratios (ICERs) suggested that the intervention was not cost-effective although the ratio improved over time: the ICER over 10 years was £82,250, falling to £37,500 over 30 years. The ICER fell below £30 000 only when the intervention cost was below £631 per patient: we estimated the cost at £981. CONCLUSION: Given conventional thresholds of cost-effectiveness, the intensive treatment delivered in ADDITION was not cost-effective compared with routine care for individuals with screen-detected diabetes in the UK. The intervention may be cost-effective if it can be delivered at reduced cost.

BACKGROUND: There is little evidence to inform the targeted treatment of individuals found early in the diabetes disease trajectory. AIM: To describe cardiovascular disease (CVD) risk profiles and treatment of individual CVD risk factors by modelled CVD risk at diagnosis; changes in treatment, modelled CVD risk, and CVD risk factors in the 5 years following diagnosis; and how these are patterned by socioeconomic status. DESIGN AND SETTING: Cohort analysis of a cluster-randomised trial (ADDITION-Europe) in general practices in Denmark, England, and the Netherlands. METHOD: A total of 2418 individuals with screen-detected diabetes were divided into quartiles of modelled 10-year CVD risk at diagnosis. Changes in treatment, modelled CVD risk, and CVD risk factors were assessed at 5 years. RESULTS: The largest reductions in risk factors and modelled CVD risk were seen in participants who were in the highest quartile of modelled risk at baseline, suggesting that treatment was offered appropriately. Participants in the lowest quartile of risk at baseline had very similar levels of modelled CVD risk at 5 years and showed the least variation in change in modelled risk. No association was found between socioeconomic status and changes in CVD risk factors, suggesting that treatment was equitable. CONCLUSION: Diabetes management requires setting of individualised attainable targets. This analysis provides a reference point for patients, clinicians, and policymakers when considering goals for changes in risk factors early in the course of the disease that account for the diverse cardiometabolic profile present in individuals who are newly diagnosed with type 2 diabetes.

PURPOSE: The objective of this study is to examine test-retest reliability, criterion validity, and absolute agreement of a self-report, last 7-d sedentary behavior questionnaire (SIT-Q-7d), which assesses total daily sedentary time as an aggregate of sitting/lying down in five domains (meals, transportation, occupation, nonoccupational screen time, and other sedentary time). Dutch (DQ) and English (EQ) versions of the questionnaire were examined. METHODS: Fifty-one Flemish adults (ages 39.4 ± 11.1 yr) wore a thigh accelerometer (activPAL3™) and simultaneously kept a domain log for 7 d. The DQ was subsequently completed twice (median test-retest interval: 3.3 wk). Thigh-acceleration sedentary time was log annotated to create comparable domain-specific and total sedentary time variables. Four hundred two English adults (ages 49.6 ± 7.3 yr) wore a combined accelerometer and HR monitor (Actiheart) for 6 d to objectively measure total sedentary time. The EQ was subsequently completed twice (median test-retest interval: 3.4 wk). In both samples, the questionnaire reference frame overlapped with the criterion measure administration period. All participants had five or more valid days of criterion data, including one or more weekend day. RESULTS: Test-retest reliability (intraclass correlation coefficient (95% CI)) was fair to good for total sedentary time (DQ: 0.68 (0.50-0.81); EQ: 0.53 (0.44-0.62)) and poor to excellent for domain-specific sedentary time (DQ: from 0.36 (0.10-0.57) (meals) to 0.66 (0.46-0.79) (occupation); EQ: from 0.45 (0.35-0.54) (other sedentary time) to 0.76 (0.71-0.81) (meals)). For criterion validity (Spearman rho), significant correlations were found for total sedentary time (DQ: 0.52; EQ: 0.22; all P <0.001). Compared with domain-specific criterion variables (DQ), modest-to-strong correlations were found for domain-specific sedentary time (from 0.21 (meals) to 0.76 (P < 0.001) (screen time)). The questionnaire generally overestimated sedentary tim

AIMS/HYPOTHESIS: The study aimed to examine the effects of intensive treatment (IT) vs routine care (RC) on patient-reported outcomes after 5 years in screen-detected diabetic patients. METHODS: In a pragmatic, cluster-randomised, parallel-group trial, 343 general practices in Denmark, Cambridge and Leicester (UK) and the Netherlands were randomised to screening for type 2 diabetes mellitus plus IT of multiple risk factors in people 40-69 years without known diabetes (n = 1,678 patients) or screening plus RC (n = 1,379 patients). Practices were randomised in a 1:1 ratio according to a computer-generated list. Diabetes mellitus was diagnosed according to WHO criteria. Exclusions were: life expectancy <1 year, housebound, pregnant or lactating, or psychological or psychiatric problems. Treatment targets for IT were: HbA1c <7.0% (53 mmol/mol), BP ≤135/85 mmHg, cholesterol <5 mmol/l in the absence of a history of coronary heart disease and <4.5 mmol/l in patients with cardiovascular (CV) disease; prescription of aspirin to people taking antihypertensive medication and, in cases of CV disease or BP >120/80 mmHg, ACE inhibitors were recommended. After 2003, the treatment algorithm recommended statins to all patients with cholesterol of ≥3.5 mmol/l. Outcome measures were: health status (Euroqol 5 Dimensions [EQ-5D]) at baseline and at follow-up; and health status (36-item Short Form Health Survey [SF-36] and Euroquol Visual Analogue Scale [EQ-VAS]), well-being (12-item Short Form of the Well-Being Questionnaire), diabetes-specific quality of life (Audit of Diabetes-Dependent Quality of Life) and satisfaction with diabetes treatment (Diabetes Treatment Satisfaction Questionnaire) at follow-up. At baseline, standardised self-report questionnaires were used to collect information. Questionnaires were completed at the same health assessment visit as the anthropometric and biochemical measurements. The patients and the staff assessing the outcomes were unaware of the group assi

AIMS: To describe the total cardiovascular burden (cardiovascular morbidity or mortality, revascularization or non-traumatic amputation) in individuals with screen-detected diabetes in the ADDITION-Europe trial and to quantify the impact of the intervention on multiple cardiovascular events over 5 years. METHODS: In a pragmatic, cluster-randomized, parallel-group trial in four centres (Denmark; Cambridge, UK; the Netherlands; and Leicester, UK), 343 general practices were randomized to screening plus routine care (n = 1379 patients), or screening and promotion of target-driven, intensive treatment of multiple risk factors (n = 1678). We estimated the effect of the intervention on multiple cardiovascular events after diagnosis of diabetes using the Wei, Lin and Weissfeld method. RESULTS: Over 5.3 years, 167 individuals had exactly one cardiovascular event, 53 exactly two events, and 18 three or more events. The incidence rates (95% CI) of first events and any event per 1000 person-years were 14.6 (12.8-16.6) and 20.4 (18.2-22.6), respectively. There were non-significant reductions in the risk of a first (hazard ratio 0.83, 95% CI 0.65-1.05) and second primary endpoint (hazard ratio 0.70, 95% CI 0.43-1.12). The overall average hazard ratio for any event was 0.77 (95% CI 0.58-1.02). CONCLUSIONS: Early intensive multifactorial treatment was not associated with a significant reduction in total cardiovascular burden at 5 years. Focusing on first events in cardiovascular disease prevention trials underestimates the total cardiovascular burden to patients and the health service.

BACKGROUND: Earlier diagnosis followed by multi-factorial cardiovascular risk intervention may improve outcomes in type 2 diabetes mellitus (T2DM). Latent phase identification through screening requires structured, appropriately targeted population-based approaches. Providers responsible for implementing screening policy await evidence of clinical and cost effectiveness from randomised intervention trials in screen-detected T2DM cases. UK South Asians are at particularly high risk of abnormal glucose tolerance and T2DM. To be effective national screening programmes must achieve good coverage across the population by identifying barriers to the detection of disease and adapting to the delivery of earlier care. Here we describe the rationale and methods of a systematic community screening programme and randomised controlled trial of cardiovascular risk management within a UK multiethnic setting (ADDITION-Leicester). DESIGN: A single-blind cluster randomised, parallel group trial among people with screen-detected T2DM comparing a protocol driven intensive multi-factorial treatment with conventional care. METHODS: ADDITION-Leicester consists of community-based screening and intervention phases within 20 general practices coordinated from a single academic research centre. Screening adopts a universal diagnostic approach via repeated 75g-oral glucose tolerance tests within an eligible non-diabetic population of 66,320 individuals aged 40-75 years (25-75 years South Asian). Volunteers also provide detailed medical and family histories; complete health questionnaires, undergo anthropometric measures, lipid profiling and a proteinuria assessment. Primary outcome is reduction in modelled Coronary Heart Disease (UKPDS CHD) risk at five years. Seven thousand (30% of South Asian ethnic origin) volunteers over three years will be recruited to identify a screen-detected T2DM cohort (n = 285) powered to detected a 6% relative difference (80% power, alpha 0.05) between treatment gr

AIMS/HYPOTHESIS: The Anglo-Danish-Dutch study of intensive treatment in people with screen-detected diabetes in primary care (ADDITION) is a pragmatic randomised controlled trial of the effectiveness of intensified multi-factorial treatment on 5 year cardiovascular morbidity and mortality rates in people with screen-detected type 2 diabetes in the Netherlands, UK and Denmark. This paper describes the baseline characteristics of the study population, their estimated risk of coronary heart disease and the extent to which that risk is potentially modifiable. METHODS: Stepwise screening strategies were performed using risk questionnaires and routine general practice data plus random blood glucose, HbA(1c) and fasting blood glucose measurement. Diabetes was diagnosed using the 1999 World Health Organization criteria and estimated 10 year coronary heart disease risk was calculated using the UK Prospective Diabetes Study risk engine. RESULTS: Between April 2001 and December 2006, 3,057 people with screen-detected diabetes were recruited to the study (mean age 59.7 years, 58% men) after a stepwise screening programme involving 76,308 people screened in 334 general practices in three countries. Their median estimated 10 year risk of coronary heart disease was 11% in women (interquartile range 7-16%) and 21% (15-30%) in men. There were differences in the distribution of risk factors by country, linked to differences in approaches to screening and the extent to which risk factors had already been detected and treated. The mean HbA(1c) at recruitment was 7.0% (SD 1.6%). Of the people recruited, 73% had a blood pressure > or =140/90 and of these 58% were not on antihypertensive medication. Cholesterol levels were above 5.0 mmol/l in 70% of participants, 91% of whom were not being treated with lipid-lowering drugs. CONCLUSIONS/INTERPRETATION: People with type 2 diabetes detected by screening and included in the ADDITION study have a raised and potentially modifiable risk of CHD.