Debate: Are surrogate end-point studies worth the effort?

Surrogate end-points of cardiovascular disease can provide useful information in cross-sectional, prospective and interventional studies. They provide information on association with risk factors, natural history and factors associated with disease progression. Because every participant can reach an end-point, sufficient power can be attained with much smaller numbers of subjects in surrogate end-point studies than in studies that use clinical endpoints, so that the costs are likely to be substantially less. Measures of carotid intima-media thickness (IMT) by B-mode ultrasonography and of coronary calcification by electron beam computed tomography (EBCT) appear to be the most promising surrogate end-points

Obesity as a risk factor for severe COVID-19: summary of the best evidence and implications for health care

Purpose of Review: To collate the best evidence from several strands—epidemiological, genetic, comparison with historical data and mechanistic information—and ask whether obesity is an important causal and potentially modifiable risk factor for severe COVID-19 outcomes. Recent Findings: Several hundred studies provide powerful evidence that body mass index (BMI) is a strong linear risk factor for severe COVID-19 outcomes, with recent studies suggesting ~5-10% higher risk for COVID-19 hospitalisation per every kg/m2 higher BMI. Genetic data concur with hazard ratios increasing by 14% per every kg/m2 higher BMI. BMI to COVID-19 links differ markedly from prior BMI-infection associations and are further supported as likely causal by multiple biologically plausible pathways. Summary: Excess adiposity appears to be an important, modifiable risk factor for adverse COVID-19 outcomes across all ethnicities. The pandemic is also worsening obesity levels. It is imperative that medical systems worldwide meet this challenge by upscaling investments in obesity prevention and treatments

Financial disincentives? A three-armed randomised controlled trial of the effect of financial Incentives in Diabetic Eye Assessment by Screening (IDEAS) trial

Objective Conflicting evidence exists regarding the impact of financial incentives on encouraging attendance at medical screening appointments. The primary aim was to determine whether financial incentives increase attendance at diabetic eye screening in persistent non-attenders. Methods and analysis A three-armed randomised controlled trial was conducted in London in 2015. 1051 participants aged over 16 years, who had not attended eye screening appointments for 2 years or more, were randomised (1.4:1:1 randomisation ratio) to receive the usual invitation letter (control), an offer of £10 cash for attending screening (fixed incentive) or a 1 in 100 chance of winning £1000 (lottery incentive) if they attend. The primary outcome was the proportion of invitees attending screening, and a comparative analysis was performed to assess group differences. Pairwise comparisons of attendance rates were performed, using a conservative Bonferroni correction for independent comparisons. Results 34/435 (7.8%) of control, 17/312 (5.5%) of fixed incentive and 10/304 (3.3%) of lottery incentive groups attended. Participants who received any incentive were significantly less likely to attend their appointment compared with controls (risk ratio (RR)=0.56; 95% CI 0.34 to 0.92). Those in the probabilistic incentive group (RR=0.42; 95% CI 0.18 to 0.98), but not the fixed incentive group (RR=1.66; 95% CI 0.65 to 4.21), were significantly less likely to attend than those in the control group. Conclusion Financial incentives, particularly lottery-based incentives, attract fewer patients to diabetic eye screening than standard invites in this population. Financial incentives should not be used to promote screening unless tested in context, as they may negatively affect attendance rates

Incentives in diabetic eye assessment by screening (IDEAS): study protocol of a three-arm randomized controlled trial using financial incentives to increase screening uptake in London

Background: Diabetes is an increasing public health problem in the UK and globally. Diabetic retinopathy is a microvascular complication of diabetes, and is one of the leading causes of blindness in the UK working age population. The diabetic eye screening programme in England aims to invite all people with diabetes aged 12 or over for retinal photography to screen for the presence of diabetic retinopathy. However, attendance rates are only 81 %, leaving many people at risk of preventable sight loss. Methods: This is a three arm randomized controlled trial to investigate the impact of different types of financial incentives (based on principles from behavioral economics) on increasing attendance at diabetic eye screening appointments in London. Eligible participants will be aged 16 or over, and are those who have been invited to screening appointments annually, but who have not attended, or telephoned to rearrange an appointment, within the last 24 months. Eligible participants will be randomized to one of three conditions: 1. Control condition (usual invitation letter) 2. Fixed incentive condition (usual invitation letter, including a voucher for £10 if they attend their appointment) 3. Probabilistic incentive condition (invitation letter, including a voucher for a 1 in 100 chance of winning £1000 if they attend their appointment). Participants will be sent invitation letters, and the primary outcome will be whether or not they attend their appointment. One thousand participants will be included in total, randomized with a ratio of 1.4:1:1. In order to test whether the incentive scheme has a differential impact on patients from different demographic or socio-economic groups, information will be recorded on age, gender, distance from screening center, socio-economic status and length of time since they were last screened. A cost-effectiveness analysis will also be performed. Discussion: This study will be the first trial of financial incentives for improving uptake of diabetic eye screening. If effective, the intervention may suggest a cost-effective way to increase screening rates, thus reducing unnecessary blindness

Uptake and impact of the English National Health Service digital diabetes prevention programme: observational study

INTRODUCTION: 'Healthier You', the National Health Service (NHS) diabetes prevention programme (DPP) offers adults in England at high risk of type 2 diabetes (T2DM) an evidence-based behavioral intervention to prevent or delay T2DM onset. This study assesses the impact of a pilot digital stream of the DPP (DDPP) on glycated hemoglobin (HbA1c) and weight. RESEARCH DESIGN AND METHODS: A service evaluation employing prospectively collected data in a prospective cohort design in nine NHS local pilot areas across England. Participants were adults with non-diabetic hyperglycemia (NDH) (HbA1c 42-47 mmol/mol or fasting plasma glucose 5.5-6.9 mmol/L) in the 12 months prior to referral. The DDPP comprised five digital health interventions (DHI). Joint primary outcomes were changes in HbA1c and weight between baseline and 12 months. HbA1c and weight readings were recorded at referral (baseline) by general practices, and then at 12-month postregistration. Demographic data and service variables were collected from the DHI providers. RESULTS: 3623 participants with NDH registered for the DDPP and of these, 2734 (75%) were eligible for inclusion in the analyses. Final (12-month) follow-up data for HbA1c were available for 1799 (50%) and for weight 1817 (50%) of registered participants. Mean change at 12 months was -3.1 (-3.4 to -2.8) kg, p<0.001 for weight and -1.6 (-1.8 to -1.4) mmol/mol, p<0.001 for HbA1c. Access to peer support and a website and telephone service was associated with significantly greater reductions in HbA1c and weight. CONCLUSIONS: Participation in the DDPP was associated with clinically significant reductions in weight and HbA1c. Digital diabetes prevention can be an effective and wide-reaching component of a population-based approach to addressing type 2 diabetes prevention

Care processes in people in remission from type 2 diabetes:A cohort study using the National Diabetes Audit

Aims: People with type 2 diabetes can enter remission but may relapse or develop legacy complications. This analysis assesses whether people with remission from type 2 diabetes continue receiving annual care processes recommended in national guidelines and the potential impacts of formal recognition of remission. Methods: People with type 2 diabetes with and without formal recognition (diagnostic code) of remission, and with and without evidence of remission (HbA1c &lt; 48 mmol/mol without prescription for glucose-lowering drugs in preceding 26 weeks), included in the 2018/19 National Diabetes Audit (NDA) for England and Wales were followed up to identify care processes received between 1 January 2019 and 31 March 2020. Results: Of the 2,822,145 people with type 2 diabetes in the cohort, 16,460 (0.58%) were coded with remission in the 2018/19 NDA. After adjustment for age, sex, socioeconomic deprivation and ethnicity, people coded with remission were less likely to receive each care process than those without such coding irrespective of HbA1c measurements (relative risk (RR) of receiving all 8 care processes 0.70 (95% CI 0.69–0.72)). For the 339,235 people with evidence of remission, irrespective of diagnostic coding compared to those without such evidence, the RR for receiving all 8 care processes was 0.94 (95% CI 0.93–0.94). Conclusions: People coded with remission of type 2 diabetes were less likely to receive diabetes care processes than those without such coding. People with evidence of remission had only a slightly reduced likelihood of receiving care processes. Formal recognition of remission may affect the provision or uptake of care processes

Comparative incidence of diabetes following hospital admission for COVID-19 and pneumonia: a cohort study

Objective: The incidence of diabetes may be elevated following coronavirus disease 2019 (COVID-19), but it is unclear whether this is specific to severe acute respiratory syndrome coronavirus 2 infection, associated with shared risk factors for severe COVID-19 and diabetes, and/or a generic risk following illness. Research Design and Methods: People admitted to the hospital for COVID-19 and/or pneumonia between 1 April 2020 and 31 August 2020 in England were linked with the National Diabetes Audit to identify incident diabetes after discharge up to 31 March 2021. Comparator cohorts admitted with pneumonia over the same dates in 2017, 2018, and 2019 were followed until 31 March 2018, 31 March 2019, and 31 March 2020, respectively. Poisson regression models were used to calculate adjusted diabetes incidence rates. Results: Using the cohort of people discharged from the hospital following a diagnosis of COVID-19 without pneumonia in 2020 as the standard population (incidence rate 16.4 [95% CI 12.8–20.7] per 1,000 person-years), adjusting for age, sex, ethnicity, and deprivation, gave incidence rates of 19.0 (95% CI 13.8–25.6) and 16.6 (95% CI 13.3–20.4) per 1,000 person-years for those admitted for COVID-19 with pneumonia and pneumonia without COVID-19, respectively, in 2020. These rates are not significantly different from those found after hospital admission for pneumonia in 2019, 2018, and 2017, at 13.7 (95% CI 10.8–17.3), 13.8 (95% CI 10.9–17.4), and 14.2 (95% CI 10.9–18.3) per 1,000 person-years, respectively. Conclusions: Our data do not support a clear impact of COVID-19 on the incidence of diabetes compared with risks in several comparator groups, including contemporaneously assessed risks in people hospitalized with pneumonia

Early outcomes of referrals to the English National Health Service Digital Weight Management Programme

Objective The study objective was to assess participant weight change for the English National Health Service (NHS) Digital Weight Management Programme, the first such digital intervention to achieve population coverage. Methods A service evaluation was used to assess intervention effectiveness for adults with obesity and a diagnosis of hypertension and/or diabetes, between April 2021 and March 2022, using prospectively collected, national service–level data in England. Results Of the 63,937 referrals made from general practices, within the time period, 31,861 (50%) chose to take up the 12-week Programme. There were 31,718 participants who had time to finish the Programme; of those, 14,268 completed the Programme (defined as attending ≥60%), a 45% completion rate. The mean weight change for those who had time to finish the Programme was −2.2 kg (95% CI: −2.25 to −2.16), for those who completed it was −3.9 kg (95% CI: −3.99 to −3.84), and for those who had time to finish the Programme but did not complete it was −0.74 kg (95% CI: −0.79 to −0.70). Conclusions The NHS Digital Weight Management Programme is effective at achieving clinically meaningful weight loss. The outcomes compare favorably to web-based weight management interventions tested in randomized trials and those delivered as face-to-face interventions, and results suggest that the approach may, with increased participation, bring population-level benefits

Comparison of mortality in people with type 1 and type 2 diabetes by age of diagnosis: an incident population-based study in England and Wales

No abstract available

Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort study

Objectives To derive and validate risk prediction algorithms to estimate the risk of covid-19 related mortality and hospital admission in UK adults after one or two doses of covid-19 vaccination.Design Prospective, population based cohort study using the QResearch database linked to data on covid-19 vaccination, SARS-CoV-2 results, hospital admissions, systemic anticancer treatment, radiotherapy, and the national death and cancer registries.Settings Adults aged 19-100 years with one or two doses of covid-19 vaccination between 8 December 2020 and 15 June 2021.Main outcome measures Primary outcome was covid-19 related death. Secondary outcome was covid-19 related hospital admission. Outcomes were assessed from 14 days after each vaccination dose. Models were fitted in the derivation cohort to derive risk equations using a range of predictor variables. Performance was evaluated in a separate validation cohort of general practices.Results Of 6 952 440 vaccinated patients in the derivation cohort, 5 150 310 (74.1%) had two vaccine doses. Of 2031 covid-19 deaths and 1929 covid-19 hospital admissions, 81 deaths (4.0%) and 71 admissions (3.7%) occurred 14 days or more after the second vaccine dose. The risk algorithms included age, sex, ethnic origin, deprivation, body mass index, a range of comorbidities, and SARS-CoV-2 infection rate. Incidence of covid-19 mortality increased with age and deprivation, male sex, and Indian and Pakistani ethnic origin. Cause specific hazard ratios were highest for patients with Down’s syndrome (12.7-fold increase), kidney transplantation (8.1-fold), sickle cell disease (7.7-fold), care home residency (4.1-fold), chemotherapy (4.3-fold), HIV/AIDS (3.3-fold), liver cirrhosis (3.0-fold), neurological conditions (2.6-fold), recent bone marrow transplantation or a solid organ transplantation ever (2.5-fold), dementia (2.2-fold), and Parkinson’s disease (2.2-fold). Other conditions with increased risk (ranging from 1.2-fold to 2.0-fold increases) included chronic kidney disease, blood cancer, epilepsy, chronic obstructive pulmonary disease, coronary heart disease, stroke, atrial fibrillation, heart failure, thromboembolism, peripheral vascular disease, and type 2 diabetes. A similar pattern of associations was seen for covid-19 related hospital admissions. No evidence indicated that associations differed after the second dose, although absolute risks were reduced. The risk algorithm explained 74.1% (95% confidence interval 71.1% to 77.0%) of the variation in time to covid-19 death in the validation cohort. Discrimination was high, with a D statistic of 3.46 (95% confidence interval 3.19 to 3.73) and C statistic of 92.5. Performance was similar after each vaccine dose. In the top 5% of patients with the highest predicted covid-19 mortality risk, sensitivity for identifying covid-19 deaths within 70 days was 78.7%.Conclusion This population based risk algorithm performed well showing high levels of discrimination for identifying those patients at highest risk of covid-19 related death and hospital admission after vaccination