ORCID Profile
0000-0002-9258-4060
Current Organisation
University of Oxford
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Publisher: Springer Science and Business Media LLC
Date: 09-03-2001
Abstract: To estimate the economic efficiency of intensive blood-glucose control with metformin compared with conventional therapy primarily with diet in overweight patients with Type II (non-insulin-dependent) diabetes mellitus. Cost-effectiveness analysis based on patient level data from a randomised clinical controlled trial involving 753 overweight (> 120% ideal body weight) patients with newly diagnosed Type II diabetes conducted in 15 hospital-based clinics in England, Scotland and Northern Ireland as part of the UK Prospective Diabetes Study. Subjects were allocated at random to an intensive blood-glucose control policy with metformin (n = 342) or a conventional policy primarily with diet (n = 411). The analysis was based on the cost of health care resources associated with metformin and conventional therapy and the estimated effectiveness in terms of life expectancy gained from within-trial effects. Intensive blood-glucose control with metformin produced a net saving of 258 Pounds per patient (1997 United Kingdom prices) over the trial period (median duration of 10.7 years) due to lower complication costs, and increased life expectancy by 0.4 years (costs and benefits discounted at 6%). As metformin is both cost-saving in the United Kingdom and extends life expectancy when used as first line pharmacological therapy in overweight Type II diabetic patients, its use should be attractive to clinicians and health care managers alike.
Publisher: Springer Science and Business Media LLC
Date: 15-03-2013
Publisher: Public Library of Science (PLoS)
Date: 19-09-2017
Publisher: National Institute for Health and Care Research
Date: 02-2014
DOI: 10.3310/HTA18140
Publisher: National Institute for Health and Care Research
Date: 08-2021
DOI: 10.3310/PGFAR09100
Abstract: Long-term monitoring is important in chronic condition management. Despite considerable costs of monitoring, there is no or poor evidence on how, what and when to monitor. The aim of this study was to improve understanding, methods, evidence base and practice of clinical monitoring in primary care, focusing on two areas: chronic kidney disease and chronic heart failure. The research questions were as follows: does the choice of test affect better care while being affordable to the NHS? Can the number of tests used to manage in iduals with early-stage kidney disease, and hence the costs, be reduced? Is it possible to monitor heart failure using a simple blood test? Can this be done using a rapid test in a general practitioner consultation? Would changes in the management of these conditions be acceptable to patients and carers? Various study designs were employed, including cohort, feasibility study, Clinical Practice Research Datalink analysis, seven systematic reviews, two qualitative studies, one cost-effectiveness analysis and one cost recommendation. This study was set in UK primary care. Data were collected from study participants and sourced from UK general practice and hospital electronic health records, and worldwide literature. The participants were NHS patients (Clinical Practice Research Datalink: 4.5 million patients), chronic kidney disease and chronic heart failure patients managed in primary care (including 750 participants in the cohort study) and primary care health professionals. The interventions were monitoring with blood and urine tests (for chronic kidney disease) and monitoring with blood tests and weight measurement (for chronic heart failure). The main outcomes were the frequency, accuracy, utility, acceptability, costs and cost-effectiveness of monitoring. Chronic kidney disease: serum creatinine testing has increased steadily since 1997, with most results being normal (83% in 2013). Increases in tests of creatinine and proteinuria correspond to their introduction as indicators in the Quality and Outcomes Framework. The Chronic Kidney Disease Epidemiology Collaboration equation had 2.7% greater accuracy (95% confidence interval 1.6% to 3.8%) than the Modification of Diet in Renal Disease equation for estimating glomerular filtration rate. Estimated annual transition rates to the next chronic kidney disease stage are ≈ 2% for people with normal urine albumin, 3–5% for people with microalbuminuria (3–30 mg/mmol) and 3–12% for people with macroalbuminuria ( 30 mg/mmol). Variability in estimated glomerular filtration rate-creatinine leads to misclassification of chronic kidney disease stage in 12–15% of tests in primary care. Glycaemic-control and lipid-modifying drugs are associated with a 6% (95% confidence interval 2% to 10%) and 4% (95% confidence interval 0% to 8%) improvement in renal function, respectively. Neither estimated glomerular filtration rate-creatinine nor estimated glomerular filtration rate-Cystatin C have utility in predicting rate of kidney function change. Patients viewed phrases such as ‘kidney damage’ or ‘kidney failure’ as frightening, and the term ‘chronic’ was misinterpreted as serious. Diagnosis of asymptomatic conditions (chronic kidney disease) was difficult to understand, and primary care professionals often did not use ‘chronic kidney disease’ when managing patients at early stages. General practitioners relied on Clinical Commissioning Group or Quality and Outcomes Framework alerts rather than National Institute for Health and Care Excellence guidance for information. Cost-effectiveness modelling did not demonstrate a tangible benefit of monitoring kidney function to guide preventative treatments, except for in iduals with an estimated glomerular filtration rate of 60–90 ml/minute/1.73 m 2 , aged 70 years and without cardiovascular disease, where monitoring every 3–4 years to guide cardiovascular prevention may be cost-effective. Chronic heart failure: natriuretic peptide-guided treatment could reduce all-cause mortality by 13% and heart failure admission by 20%. Implementing natriuretic peptide-guided treatment is likely to require predefined protocols, stringent natriuretic peptide targets, relative targets and being located in a specialist heart failure setting. Remote monitoring can reduce all-cause mortality and heart failure hospitalisation, and could improve quality of life. Diagnostic accuracy of point-of-care N-terminal prohormone of B-type natriuretic peptide (sensitivity, 0.99 specificity, 0.60) was better than point-of-care B-type natriuretic peptide (sensitivity, 0.95 specificity, 0.57). Within-person variation estimates for B-type natriuretic peptide and weight were as follows: coefficient of variation, 46% and coefficient of variation, 1.2%, respectively. Point-of-care N-terminal prohormone of B-type natriuretic peptide within-person variability over 12 months was 881 pg/ml (95% confidence interval 380 to 1382 pg/ml), whereas between-person variability was 1972 pg/ml (95% confidence interval 1525 to 2791 pg/ml). For in iduals, monitoring provided reassurance future changes, such as increased testing, would be acceptable. Point-of-care testing in general practice surgeries was perceived positively, reducing waiting time and anxiety. Community heart failure nurses had greater knowledge of National Institute for Health and Care Excellence guidance than general practitioners and practice nurses. Health-care professionals believed that the cost of natriuretic peptide tests in routine monitoring would outweigh potential benefits. The review of cost-effectiveness studies suggests that natriuretic peptide-guided treatment is cost-effective in specialist settings, but with no evidence for its value in primary care settings. No randomised controlled trial evidence was generated. The pathways to the benefit of monitoring chronic kidney disease were unclear. It is difficult to ascribe quantifiable benefits to monitoring chronic kidney disease, because monitoring is unlikely to change treatment, especially in chronic kidney disease stages G3 and G4. New approaches to monitoring chronic heart failure, such as point-of-care natriuretic peptide tests in general practice, show promise if high within-test variability can be overcome. The following future work is recommended: improve general practitioner–patient communication of early-stage renal function decline, and identify strategies to reduce the variability of natriuretic peptide. This study is registered as PROSPERO CRD42015017501, CRD42019134922 and CRD42016046902. This project was funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research programme and will be published in full in Programme Grants for Applied Research Vol. 9, No. 10. See the NIHR Journals Library website for further project information.
Publisher: Springer Science and Business Media LLC
Date: 15-04-2005
DOI: 10.1007/S00125-005-1717-3
Abstract: This study estimated the economic efficiency (1) of intensive blood glucose control and tight blood pressure control in patients with type 2 diabetes who also had hypertension, and (2) of metformin therapy in type 2 diabetic patients who were overweight. We conducted cost-utility analysis based on patient-level data from a randomised clinical controlled trial involving 4,209 patients with newly diagnosed type 2 diabetes conducted in 23 hospital-based clinics in England, Scotland and Northern Ireland as part of the UK Prospective Diabetes Study (UKPDS). Three different policies were evaluated: intensive blood glucose control with sulphonylurea/insulin intensive blood glucose control with metformin for overweight patients and tight blood pressure control of hypertensive patients. Incremental cost : effectiveness ratios were calculated based on the net cost of healthcare resources associated with these policies and on effectiveness in terms of quality-adjusted life years gained, estimated over a lifetime from within-trial effects using the UKPDS Outcomes Model. The incremental cost per quality-adjusted life years gained (in year 2004 UK prices) for intensive blood glucose control was 6,028 UK pounds, and for blood pressure control was 369 UK pounds. Metformin therapy was cost-saving and increased quality-adjusted life expectancy. Each of the three policies evaluated has a lower cost per quality-adjusted life year gained than that of many other accepted uses of healthcare resources. The results provide an economic rationale for ensuring that care of patients with type 2 diabetes corresponds at least to the levels of these interventions.
Publisher: Springer Science and Business Media LLC
Date: 13-04-2013
DOI: 10.1007/S40273-013-0047-4
Abstract: The aim of this study was to develop a discrete-time simulation model for people with type 1 diabetes mellitus, to estimate and compare mean life expectancy and quality-adjusted life-years (QALYs) over a lifetime between intensive and conventional blood glucose treatment groups. We synthesized evidence on type 1 diabetes patients using several published sources. The simulation model was based on 13 equations to estimate risks of events and mortality. Cardiovascular disease (CVD) risk was obtained from results of the DCCT (diabetes control and complications trial). Mortality post-CVD event was based on a study using linked administrative data on people with diabetes from Western Australia. Information on incidence of renal disease and the progression to CVD was obtained from studies in Finland and Italy. Lower-extremity utation (LEA) risk was based on the type 1 diabetes Swedish inpatient registry, and the risk of blindness was obtained from results of a German-based study. Where diabetes-specific data were unavailable, information from other populations was used. We examine the degree and source of parameter uncertainty and illustrate an application of the model in estimating lifetime outcomes of using intensive and conventional treatments for blood glucose control. From 15 years of age, male and female patients had an estimated life expectancy of 47.2 (95 % CI 35.2-59.2) and 52.7 (95 % CI 41.7-63.6) years in the intensive treatment group. The model produced estimates of the lifetime benefits of intensive treatment for blood glucose from the DCCT of 4.0 (95 % CI 1.2-6.8) QALYs for women and 4.6 (95 % CI 2.7-6.9) QALYs for men. Absolute risk per 1,000 person-years for fatal CVD events was simulated to be 1.37 and 2.51 in intensive and conventional treatment groups, respectively. The model incorporates diabetic complications risk data from a type 1 diabetes population and synthesizes other type 1-specific data to estimate long-term outcomes of CVD, end-stage renal disease, LEA and risk of blindness, along with life expectancy and QALYs. External validation was carried out using life expectancy and absolute risk for fatal CVD events. Because of the flexible and transparent nature of the model, it has many potential future applications.
Publisher: Wiley
Date: 06-2001
DOI: 10.1046/J.1464-5491.2001.00485.X
Abstract: To compare the net cost of a tight blood pressure control policy with an angiotensin converting enzyme inhibitor (captopril) or beta blocker (atenolol) in patients with Type 2 diabetes. A cost-effectiveness analysis based on outcomes and resources used in a randomized controlled trial and assumptions regarding the use of these therapies in a general practice setting. Twenty United Kingdom Prospective Diabetes Study Hospital-based clinics in England, Scotland and Northern Ireland. Hypertensive patients (n = 758) with Type 2 diabetes (mean age 56 years, mean blood pressure 159/94 mmHg), 400 of whom were allocated to the angiotensin converting enzyme inhibitor captopril and 358 to the beta blocker atenolol. Life expectancy and mean cost per patient. There was no statistically significant difference in life expectancy between groups. The cost per patient over the trial period was 6485 UK pounds in the captopril group, compared with 5550 UK pounds in the atenolol group, an average cost difference of 935 UK pounds (95% confidence interval 188 UK pounds, 1682 UK pounds). This 14% reduction arose partly because of lower drug prices, and also because of significantly fewer and shorter hospitalizations in the atenolol group, and despite higher antidiabetic drug costs in the atenolol group. Treatment of hypertensive patients with Type 2 diabetes using atenolol or captopril was equally effective. However, total costs were significantly lower in the atenolol group. Diabet. Med. 18, 438-444 (2001)
Publisher: BMJ
Date: 09-08-2016
DOI: 10.1136/BMJ.I4098
Abstract: To systematically review studies quantifying the associations of long term (clinic), mid-term (home), and short term (ambulatory) variability in blood pressure, independent of mean blood pressure, with cardiovascular disease events and mortality. Medline, Embase, Cinahl, and Web of Science, searched to 15 February 2016 for full text articles in English. Prospective cohort studies or clinical trials in adults, except those in patients receiving haemodialysis, where the condition may directly impact blood pressure variability. Standardised hazard ratios were extracted and, if there was little risk of confounding, combined using random effects meta-analysis in main analyses. Outcomes included all cause and cardiovascular disease mortality and cardiovascular disease events. Measures of variability included standard deviation, coefficient of variation, variation independent of mean, and average real variability, but not night dipping or day-night variation. 41 papers representing 19 observational cohort studies and 17 clinical trial cohorts, comprising 46 separate analyses were identified. Long term variability in blood pressure was studied in 24 papers, mid-term in four, and short-term in 15 (two studied both long term and short term variability). Results from 23 analyses were excluded from main analyses owing to high risks of confounding. Increased long term variability in systolic blood pressure was associated with risk of all cause mortality (hazard ratio 1.15, 95% confidence interval 1.09 to 1.22), cardiovascular disease mortality (1.18, 1.09 to 1.28), cardiovascular disease events (1.18, 1.07 to 1.30), coronary heart disease (1.10, 1.04 to 1.16), and stroke (1.15, 1.04 to 1.27). Increased mid-term and short term variability in daytime systolic blood pressure were also associated with all cause mortality (1.15, 1.06 to 1.26 and 1.10, 1.04 to 1.16, respectively). Long term variability in blood pressure is associated with cardiovascular and mortality outcomes, over and above the effect of mean blood pressure. Associations are similar in magnitude to those of cholesterol measures with cardiovascular disease. Limited data for mid-term and short term variability showed similar associations. Future work should focus on the clinical implications of assessment of variability in blood pressure and avoid the common confounding pitfalls observed to date. PROSPERO CRD42014015695.
Publisher: Royal College of General Practitioners
Date: 31-03-2014
Publisher: Springer Science and Business Media LLC
Date: 18-10-2012
Publisher: Elsevier BV
Date: 2015
Publisher: American Diabetes Association
Date: 06-2007
DOI: 10.2337/DC07-9919
Abstract: Computer simulation models are mathematical equations combined in a structured framework to represent some real or hypothetical system. One of their uses is to allow the projection of short-term data from clinical trials to evaluate clinical outcomes and costs over a long-term period. This technology is becoming increasingly important to assist decision making in modern medicine in situations where there is a paucity of long-term clinical trial data, as recently acknowledged in the American Diabetes Association Consensus Panel Guidelines for Computer Modeling of Diabetes and its Complications. The Mount Hood Challenge Meetings provide a forum for computer modelers of diabetes to discuss and compare models and identify key areas of future development to advance the field. The Fourth Mount Hood Challenge in 2004 was the first meeting of its kind to ask modelers to perform simulations of outcomes for patients in published clinical trials, allowing comparison against “real life” data. Eight modeling groups participated in the challenge. Each group was given three of the following challenges: to simulate a trial of type 2 diabetes (CARDS [Collaborative Atorvastatin Diabetes Study]) to simulate a trial of type 1 diabetes (DCCT [Diabetes Control and Complications Trial]) and to calculate outcomes for a hypothetical, precisely specified patient (cross-model validation). The results of the models varied from each other and for methodological reasons, in some cases, from the published trial data in important ways. This approach of performing systematic comparisons and validation exercises has enabled the identification of key differences among the models, as well as their possible causes and directions for improvement in the future.
Publisher: Springer Science and Business Media LLC
Date: 10-2004
DOI: 10.1007/S00125-004-1527-Z
Abstract: The aim of this study was to develop a simulation model for type 2 diabetes that can be used to estimate the likely occurrence of major diabetes-related complications over a lifetime, in order to calculate health economic outcomes such as quality-adjusted life expectancy. Equations for forecasting the occurrence of seven diabetes-related complications and death were estimated using data on 3642 patients from the United Kingdom Prospective Diabetes Study (UKPDS). After examining the internal validity, the UKPDS Outcomes Model was used to simulate the mean difference in expected quality-adjusted life years between the UKPDS regimens of intensive and conventional blood glucose control. The model's forecasts fell within the 95% confidence interval for the occurrence of observed events during the UKPDS follow-up period. When the model was used to simulate event history over patients' lifetimes, those treated with a regimen of conventional glucose control could expect 16.35 undiscounted quality-adjusted life years, and those receiving treatment with intensive glucose control could expect 16.62 quality-adjusted life years, a difference of 0.27 (95% CI: -0.48 to 1.03). The UKPDS Outcomes Model is able to simulate event histories that closely match observed outcomes in the UKPDS and that can be extrapolated over patients' lifetimes. Its validity in estimating outcomes in other groups of patients, however, remains to be evaluated. The model allows simulation of a range of long-term outcomes, which should assist in informing future economic evaluations of interventions in type 2 diabetes.
Publisher: Springer Science and Business Media LLC
Date: 10-08-2012
DOI: 10.1007/S00125-012-2653-7
Abstract: Observational studies suggest that metformin may reduce cancer risk by approximately one-third. We examined cancer outcomes and all-cause mortality in published randomised controlled trials (RCTs). RCTs comparing metformin with active glucose-lowering therapy or placebo/usual care, with minimum 500 participants and 1-year follow-up, were identified by systematic review. Data on cancer incidence and all-cause mortality were obtained from publications or by contacting investigators. For two trials, cancer incidence data were not available cancer mortality was used as a surrogate. Summary RRs, 95% CIs and I (2)statistics for heterogeneity were calculated by fixed effects meta-analysis. Of 4,039 abstracts identified, 94 publications described 14 eligible studies. RRs for cancer were available from 11 RCTs with 398 cancers during 51,681 person-years. RRs for all-cause mortality were available from 13 RCTs with 552 deaths during 66,447 person-years. Summary RRs for cancer outcomes in people randomised to metformin compared with any comparator were 1.02 (95% CI 0.82, 1.26) across all trials, 0.98 (95% CI 0.77, 1.23) in a subgroup analysis of active-comparator trials and 1.36 (95% CI 0.74, 2.49) in a subgroup analysis of placebo/usual care comparator trials. The summary RR for all-cause mortality was 0.94 (95% CI 0.79, 1.12) across all trials. Meta-analysis of currently available RCT data does not support the hypothesis that metformin lowers cancer risk by one-third. Eligible trials also showed no significant effect of metformin on all-cause mortality. However, limitations include heterogeneous comparator types, absent cancer data from two trials, and short follow-up, especially for mortality.
Publisher: National Institute for Health and Care Research
Date: 12-2015
DOI: 10.3310/HTA191000
Abstract: Various lipid measurements in monitoring/screening programmes can be used, alone or in cardiovascular risk scores, to guide treatment for prevention of cardiovascular disease (CVD). Because some changes in lipids are due to variability rather than true change, the value of lipid-monitoring strategies needs evaluation. To determine clinical value and cost-effectiveness of different monitoring intervals and different lipid measures for primary and secondary prevention of CVD. We searched databases and clinical trials registers from 2007 (including the Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, the Clinical Trials Register, the Current Controlled Trials register, and the Cumulative Index to Nursing and Allied Health Literature) to update and extend previous systematic reviews. Patient-level data from the Clinical Practice Research Datalink and St Luke’s Hospital, Japan, were used in statistical modelling. Utilities and health-care costs were drawn from the literature. In two meta-analyses, we used prospective studies to examine associations of lipids with CVD and mortality, and randomised controlled trials to estimate lipid-lowering effects of atorvastatin doses. Patient-level data were used to estimate progression and variability of lipid measurements over time, and hence to model lipid-monitoring strategies. Results are expressed as rates of true-/false-positive and true-/false-negative tests for high lipid or high CVD risk. We estimated incremental costs per quality-adjusted life-year. A total of 115 publications reported strength of association between different lipid measures and CVD events in 138 data sets. The summary adjusted hazard ratio per standard deviation of total cholesterol (TC) to high-density lipoprotein (HDL) cholesterol ratio was 1.25 (95% confidence interval 1.15 to 1.35) for CVD in a primary prevention population but heterogeneity was high ( I 2 = 98%) similar results were observed for non-HDL cholesterol, apolipoprotein B and other ratio measures. Associations were smaller for other single lipid measures. Across 10 trials, low-dose atorvastatin (10 and 20 mg) effects ranged from a TC reduction of 0.92 mmol/l to 2.07 mmol/l, and low-density lipoprotein reduction of between 0.88 mmol/l and 1.86 mmol/l. Effects of 40 mg and 80 mg were reported by one trial each. For primary prevention, over a 3-year period, we estimate annual monitoring would unnecessarily treat 9 per 1000 more men (28 vs. 19 per 1000) and 5 per 1000 more women (17 vs. 12 per 1000) than monitoring every 3 years. However, annual monitoring would also undertreat 9 per 1000 fewer men (7 vs. 16 per 1000) and 4 per 1000 fewer women (7 vs. 11 per 1000) than monitoring at 3-year intervals. For secondary prevention, over a 3-year period, annual monitoring would increase unnecessary treatment changes by 66 per 1000 men and 31 per 1000 women, and decrease undertreatment by 29 per 1000 men and 28 per 1000 men, compared with monitoring every 3 years. In cost-effectiveness, strategies with increased screening/monitoring dominate. Exploratory analyses found that any unknown harms of statins would need utility decrements as large as 0.08 (men) to 0.11 (women) per statin user to reverse this finding in primary prevention. Heterogeneity in meta-analyses. While acknowledging known and potential unknown harms of statins, we find that more frequent monitoring strategies are cost-effective compared with others. Regular lipid monitoring in those with and without CVD is likely to be beneficial to patients and to the health service. Future research should include trials of the benefits and harms of atorvastatin 40 and 80 mg, large-scale surveillance of statin safety, and investigation of the effect of monitoring on medication adherence. This study is registered as PROSPERO CRD42013003727. The National Institute for Health Research Health Technology Assessment programme.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Richard Stevens.