The impact of individualised cardiovascular disease (CVD) risk estimates and lifestyle advice on physical activity in individuals at high risk of CVD: a pilot 2 x 2 factorial understanding risk trial.

BACKGROUND: There is currently much interest in encouraging individuals to increase physical activity in order to reduce CVD risk. This study has been designed to determine if personalised CVD risk appreciation can increase physical activity in adults at high risk of CVD. METHODS/DESIGN: In a 2 x 2 factorial design participants are allocated at random to a personalised 10-year CVD risk estimate or numerical CVD risk factor values (systolic blood pressure, LDL cholesterol and fasting glucose) and, simultaneously, to receive a brief lifestyle advice intervention targeting physical activity, diet and smoking cessation or not. We aim to recruit 200 participants from Oxfordshire primary care practices. Eligibility criteria include adults age 40-70 years, estimated 10-year CVD risk > or =20%, ability to read and write English, no known CVD and no physical disability or other condition reducing the ability to walk. Primary outcome is physical activity measured by ActiGraph accelerometer with biochemical, anthropometrical and psychological measures as additional outcomes. Primary analysis is between group physical activity differences at one month powered to detect a difference of 30,000 total counts per day of physical activity between the groups. Additional analyses will seek to further elucidate the relationship between the provision of risk information, and intention to change behaviour and to determine the impact of both interventions on clinical and anthropometrical measures including fasting and 2 hour plasma glucose, fructosamine, serum cotinine, plasma vitamin C, body fat percentage and blood pressure. DISCUSSION: This is a pilot trial seeking to demonstrate in a real world setting, proof of principal that provision of personalised risk information can contribute to behaviour changes aimed at reducing CVD risk. This study will increase our understanding of the links between the provision of risk information and behaviour change and if successful, could be used in clinical practice with little or no modification.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Health selection into neighborhoods among patients enrolled in a clinical trial

Health selection into neighborhoods may contribute to geographic health disparities. We demonstrate the potential for clinical trial data to help clarify the causal role of health on locational attainment. We used data from the 20-year United Kingdom Prospective Diabetes Study (UKPDS) to explore whether random assignment to intensive blood-glucose control therapy, which improved long-term health outcomes after median 10 years follow-up, subsequently affected what neighborhoods patients lived in. We extracted postcode-level deprivation indices for the 2710 surviving participants of UKPDS living in England at study end in 1996/1997. We observed small neighborhood advantages in the intensive versus conventional therapy group, although these differences were not statistically significant. This analysis failed to show conclusive evidence of health selection into neighborhoods, but data suggest the hypothesis may be worthy of exploration in other clinical trials or in a meta-analysis. Keywords: Neighborhoods, Self-selection, Health, Equity, Socioeconomic statu

International variation in outcomes among people with cardiovascular disease or cardiovascular risk factors and impaired glucose tolerance: insights from the NAVIGATOR Trial

Background: Regional differences in risk of diabetes mellitus and cardiovascular outcomes in people with impaired glucose tolerance are poorly characterized. Our objective was to evaluate regional variation in risk of new‐onset diabetes mellitus, cardiovascular outcomes, and treatment effects in participants from the NAVIGATOR (Nateglinide and Valsartan in Impaired Glucose Tolerance Outcomes Research) trial. Methods and Results: NAVIGATOR randomized people with impaired glucose tolerance and cardiovascular risk factors or with established cardiovascular disease to valsartan (or placebo) and to nateglinide (or placebo) with a median 5‐year follow‐up. Data from the 9306 participants were categorized by 5 regions: Asia (n=552); Europe (n=4909); Latin America (n=1406); North America (n=2146); and Australia, New Zealand, and South Africa (n=293). Analyzed outcomes included new‐onset diabetes mellitus; cardiovascular death; a composite cardiovascular outcome of cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke; and treatment effects of valsartan and nateglinide. Respective unadjusted 5‐year risks for new‐onset diabetes mellitus, cardiovascular death, and the composite cardiovascular outcome were 33%, 0.4%, and 4% for Asia; 34%, 2%, and 6% for Europe; 37%, 4%, and 8% for Latin America; 38%, 2%, and 6% for North America; and 32%, 4%, and 8% for Australia, New Zealand, and South Africa. After adjustment, compared with North America, European participants had a lower risk of new‐onset diabetes mellitus (hazard ratio 0.86, 95% CI 0.78–0.94; P=0.001), whereas Latin American participants had a higher risk of cardiovascular death (hazard ratio 2.68, 95% CI 1.82–3.96; P<0.0001) and the composite cardiovascular outcome (hazard ratio 1.48, 95% CI 1.15–1.92; P=0.003). No differential interactions between treatment and geographic location were identified. Conclusions: Major regional differences regarding the risk of new‐onset diabetes mellitus and cardiovascular outcomes in NAVIGATOR participants were identified. These differences should be taken into account when planning global trials

Predicting the risk of developing type 2 diabetes in Chinese people who have coronary heart disease and impaired glucose tolerance

Aims Robust diabetes risk estimates in Asian patients with impaired glucose tolerance (IGT) and coronary heart disease (CHD) are lacking. We developed a Chinese type 2 diabetes risk calculator using Acarbose Cardiovascular Evaluation (ACE) trial data. Methods There were 3105 placebo-treated ACE participants with requisite data for model development. Clinically relevant variables, and those showing nominal univariate association with new-onset diabetes (P <.10), were entered into BASIC (clinical variables only), EXTENDED (clinical variables plus routinely available laboratory results), and FULL (all candidate variables) logistic regression models. External validation was performed using the Luzhou prospective cohort of 1088 Chinese patients with IGT. Results Over median 5.0 years, 493 (15.9%) ACE participants developed diabetes. Lower age, higher body mass index, and use of corticosteroids or thiazide diuretics were associated with higher diabetes risk. C-statistics for the BASIC (using these variables), EXTENDED (adding male sex, fasting plasma glucose, 2-hour glucose, and HbA1c), and FULL models were 0.610, 0.757, and 0.761 respectively. The EXTENDED model predicted a lower 13.9% 5-year diabetes risk in the Luzhou cohort than observed (35.2%, 95% confidence interval 31.3%-39.5%, C-statistic 0.643). Conclusion A risk prediction model using routinely available clinical variables can be used to estimate diabetes risk in Chinese people with CHD and IGT.Peer reviewe

Risk of anemia with metformin use in type 2 diabetes:A MASTERMIND study

Objective: To evaluate the association between metformin use and anemia risk in type 2 diabetes, and the time-course for this, in a randomized controlled trial (RCT) and real-world population data. Research Design and Methods: Anemia was defined as a hemoglobin measure of &lt;11 g/dL. In the RCTs A Diabetes Outcome Progression Trial (ADOPT; n = 3,967) and UK Prospective Diabetes Study (UKPDS; n = 1,473), logistic regression was used to model anemia risk and nonlinear mixed models for change in hematological parameters. In the observational Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) population (n = 3,485), discrete-time failure analysis was used to model the effect of cumulative metformin exposure on anemia risk. Results: In ADOPT, compared with sulfonylureas, the odds ratio (OR) (95% CI) for anemia was 1.93 (1.10, 3.38) for metformin and 4.18 (2.50, 7.00) for thiazolidinediones. In UKPDS, compared with diet, the OR (95% CI) was 3.40 (1.98, 5.83) for metformin, 0.96 (0.57, 1.62) for sulfonylureas, and 1.08 (0.62, 1.87) for insulin. In ADOPT, hemoglobin and hematocrit dropped after metformin initiation by 6 months, with no further decrease after 3 years. In UKPDS, hemoglobin fell by 3 years in the metformin group compared with other treatments. At years 6 and 9, hemoglobin was reduced in all treatment groups, with no greater difference seen in the metformin group. In GoDARTS, each 1 g/day of metformin use was associated with a 2% higher annual risk of anemia. Conclusions: Metformin use is associated with early risk of anemia in individuals with type 2 diabetes, a finding consistent across two RCTs and replicated in one real-world study. The mechanism for this early fall in hemoglobin is uncertain, but given the time course, is unlikely to be due to vitamin B12 deficiency alone

Are lower fasting plasma glucose levels at diagnosis of type 2 diabetes associated with improved outcomes? U.K. Prospective Diabetes Study 61

WSTĘP. Cukrzyca typu 2 może się rozwijać przez wiele lat przed postawieniem diagnozy. W tym czasie u wielu osób dochodzi już do rozwoju jej powikłań. Wczesne wykrycie i leczenie cukrzycy może temu zapobiec, ale jak dotąd brakuje dowodów na poparcie tej tezy. MATERIAŁ I METODY. U 5088 spośród 5102 uczestników badania UKDPS (United Kingdom Prospective Diabetes Study) dokonano porównania kontroli glikemii oraz klinicznych i pośrednich kryteriów badania w zależności od glikemii na czczo (FPG, fasting plasma glucose) w momencie rozpoznania choroby. Grupy porównywane cechowały się niską ( 140 do < 180 mg/dl [7,8 do < 10,0 mmol/l]) lub wysoką (ł 180 mg/dl [ł 10,0 mmol/l]) glikemią. Porównano również grupy pacjentów różniące się objawami klinicznymi cukrzycy. WYNIKI. W grupie pacjentów z niższymi stężeniami glukozy na czczo stwierdzono rzadsze występowanie retinopatii cukrzycowej, nieprawidłowych wyników biotezjometrii oraz deklarowanych zaburzeń erekcji. Stopień wzrostu FPG i HbA1c podczas badania był identyczny we wszystkich trzech grupach, chociaż obserwowano przetrwanie pierwotnych różnic. U osób mieszczących się w grupie z najniższą glikemią na czczo ryzyko wystąpienia każdego z określonych wcześniej klinicznych kryteriów badania, wyłączywszy udar mózgu, było istotnie niższe. W grupie o średnich wartościach glikemii ryzyko wszystkich kryteriów badania, poza udarem i zawałem serca, było istotnie zmniejszone. Grupy o niskiej i średniej FPG charakteryzowało istotnie zmniejszone ryzyko progresji retinopatii, zmniejszenia czucia wibracji i rozwoju mikroalbuminurii. WNIOSKI. Chorzy, u których rozpoznaje się cukrzycę typu 2 z niższymi wartościami glikemii na czczo, znajdują się na wczesnym etapie rozwoju choroby i ryzyko rozwoju klinicznych kryteriów badania jest u nich mniejsze mimo progresji cukrzycy. Ponieważ większość pacjentów w momencie rozpoznania nie ma wyraźnych objawów klinicznych, do ich identyfikacji pożądane jest wprowadzenie programów aktywnego wykrywania cukrzycyINTRODUCTION. Type 2 diabetes may be present for several years before diagnosis, by which time many patients have already developed diabetic complications. Earlier detection and treatment may reduce this burden, but evidence to support this approach is lacking. MATERIAL AND METHODS. Glycemic control and clinical and surrogate outcomes were compared for 5,088 of 5,102 U.K. Diabetes Prospective Study participants according to whether they had low (< 140 mg/dl [< 7.8 mmol/l]), intermediate (140 to < 180 mg/dl [7.8 to < 10.0 mmol/l]), or high (&#8805; 180 mg/dl [&#8805; 10 mmol/l]) fasting plasma glucose (FPG) levels at diagnosis. Individuals who presented with and without diabetic symptoms were also compared. RESULTS. Fewer people with FPG in the lowest category had retinopathy, abnormal biothesiometer measurements, or reported erectile dysfunction. The rate of increase in FPG and HbA1c during the study was identical in all three groups, although absolute differences persisted. Individuals in the low FPG group had a significantly reduced risk for each predefined clinical outcome except stroke, whereas those in the intermediate group had significantly reduced risk for each outcome except stroke and myocardial infarction. The low and intermediate FPG groups had a significantly reduced risk for progression of retinopathy, reduction in vibration sensory threshold, or development of microalbuminuria. CONCLUSIONS. People presenting with type 2 diabetes with lower initial glycemia who may be earlier in the course of their disease had fewer adverse clinical outcomes despite similar glycemic progression. Since most such people are asymptomatic at diagnosis, active case detection programs would be required to identify them

Prospective relationships between body weight and physical activity: an observational analysis from the NAVIGATOR study

Objectives: While bidirectional relationships exist between body weight and physical activity, direction of causality remains uncertain and previous studies have been limited by self-reported activity or weight and small sample size. We investigated the prospective relationships between weight and physical activity. Design: Observational analysis of data from the Nateglinide And Valsartan in Impaired Glucose Tolerance Outcomes Research (NAVIGATOR) study, a double-blinded randomised clinical trial of nateglinide and valsartan, respectively. Setting Multinational study of 9306 participants. Participants: Participants with biochemically confirmed impaired glucose tolerance had annual measurements of both weight and step count using research grade pedometers, worn for 7 days consecutively. Along with randomisation to valsartan or placebo plus nateglinide or placebo, participants took part in a lifestyle modification programme. Outcome measures: Longitudinal regression using weight as response value and physical activity as predictor value was conducted, adjusted for baseline covariates. Analysis was then repeated with physical activity as response value and weight as predictor value. Only participants with a response value preceded by at least three annual response values were included. Results: Adequate data were available for 2811 (30%) of NAVIGATOR participants. Previous weight (χ2=16.8; p&lt;0.0001), but not change in weight (χ2=0.1; p=0.71) was inversely associated with subsequent step count, indicating lower subsequent levels of physical activity in heavier individuals. Change in step count (χ2=5.9; p=0.02) but not previous step count (χ2=0.9; p=0.34) was inversely associated with subsequent weight. However, in the context of trajectories already established for weight (χ2 for previous weight measurements 747.3; p&lt;0.0001) and physical activity (χ2 for previous step count 432.6; p&lt;0.0001), these effects were of limited clinical importance. Conclusions: While a prospective bidirectional relationship was observed between weight and physical activity, the magnitude of any effect was very small in the context of natural trajectories already established for these variables

Accurately Reflecting Uncertainty When Using Patient-Level Simulation Models to Extrapolate Clinical Trial Data.

Introduction. Patient-level simulation models facilitate extrapolation of clinical trial data while allowing for heterogeneity, prior history, and nonlinearity. However, combining different types of uncertainty around within-trial and extrapolated results remains challenging. Methods. We tested 4 methods to combine parameter uncertainty (around the regression coefficients used to predict future events) with sampling uncertainty (uncertainty around mean risk factors within the finite sample whose outcomes are being predicted and the effect of treatment on these risk factors). We compared these 4 methods using a simulation study based on an economic evaluation extrapolating the AFORRD randomized controlled trial using the UK Prospective Diabetes Study Outcomes Model version 2. This established type 2 diabetes model predicts patient-level health outcomes and costs. Results. The 95% confidence intervals around life years gained gave 25% coverage when sampling uncertainty was excluded (i.e., 25% of 95% confidence intervals contained the "true" value). Allowing for sampling uncertainty as well as parameter uncertainty widened confidence intervals by 6.3-fold and gave 96.3% coverage. Methods adjusting for baseline risk factors that combine sampling and parameter uncertainty overcame the bias that can result from between-group baseline imbalance and gave confidence intervals around 50% wider than those just considering parameter uncertainty, with 99.8% coverage. Conclusions. Analyses extrapolating data for individual trial participants should include both sampling uncertainty and parameter uncertainty and should adjust for any imbalance in baseline covariates

Patient preference for second- and third-line therapies in type 2 diabetes:a prespecified secondary endpoint of the TriMaster study

Patient preference is very important for medication selection in chronic medical conditions, like type 2 diabetes, where there are many different drugs available. Patient preference balances potential efficacy with potential side effects. As both aspects of drug response can vary markedly between individuals, this decision could be informed by the patient personally experiencing the alternative medications, as occurs in a crossover trial. In the TriMaster (NCT02653209, ISRCTN12039221), randomized double-blind, three-way crossover trial patients received three different second- or third-line once-daily type 2 diabetes glucose-lowering drugs (pioglitazone 30 mg, sitagliptin 100 mg and canagliflozin 100 mg). As part of a prespecified secondary endpoint, we examined patients’ drug preference after they had tried all three drugs. In total, 448 participants were treated with all three drugs which overall showed similar glycemic control (HbA1c on pioglitazone 59.5 sitagliptin 59.9, canagliflozin 60.5 mmol mol−1, P = 0.19). In total, 115 patients (25%) preferred pioglitazone, 158 patients (35%) sitagliptin and 175 patients (38%) canagliflozin. The drug preferred by individual patients was associated with a lower HbA1c (mean: 4.6; 95% CI: 3.9, 5.3) mmol mol−1 lower versus nonpreferred) and fewer side effects (mean: 0.50; 95% CI: 0.35, 0.64) fewer side effects versus nonpreferred). Allocating therapy based on the individually preferred drugs, rather than allocating all patients the overall most preferred drug (canagliflozin), would result in more patients achieving the lowest HbA1c for them (70% versus 30%) and the fewest side effects (67% versus 50%). When precision approaches do not predict a clear optimal therapy for an individual, allowing patients to try potential suitable medications before they choose long-term therapy could be a practical alternative to optimizing treatment for type 2 diabetes