Thomas Lung

A meta-analysis of health state valuations for people with diabetes: explaining the variation across methods and implications for economic evaluation

PurposeTo review published studies on the effect of diabetes and its complications on utility scores to establish whether there is systematic variation across studies and to examine the implications for the estimation of quality-adjusted life years (QALYs).MethodsA systematic review was performed using studies reporting QALY measures elicited from people with diabetes including those with a history of complications. Meta-analysis was used to obtain the average utility, and meta-regression was employed to examine the impact of study characteristics and elicitation methods on these values. The effect of different utility scores on QALYs was examined using diabetes simulation models.ResultsIn the meta-analysis based on 45 studies reporting 66 values, the average utility score was 0.76 (95% CI 0.75–0.77). A meta-regression showed significant variation due to age, method of elicitation and the proportion of males. The average utility score for individual complications ranged from 0.48 (95% CI 0.25, 0.71) for chronic renal disease to 0.75 (95% CI 0.73, 0.78) for myocardial infarction, and these differences produced meaningful changes in simulated QALYs. There was significant heterogeneity between studies.ConclusionsWe provide summary utility scores for diabetes and its major complications that could help inform economic evaluation and policy analysis.

Severe Hypoglycemia and Mortality After Cardiovascular Events for Type 1 Diabetic Patients in Sweden

OBJECTIVE To examine whether previous severe hypoglycemic events were associated with the risk of all-cause mortality after major cardiovascular events (myocardial infarction [MI] or stroke) in patients with type 1 diabetes. RESEARCH DESIGN AND METHODS This study is based on data from the Swedish National Diabetes Register linked to patient-level hospital records, prescription data, and death records. We selected patients with type 1 diabetes who visited a clinic during 2002–2010 and experienced a major cardiovascular complication after their clinic visit. We estimated a two-part model for all-cause mortality after a major cardiovascular event: logistic regression for death within the first month and a Cox proportional hazards model conditional on 1-month survival. At age 60 years, 5-year cumulative mortality risk was estimated from the models for patients with and without prior diabetes complications. RESULTS A total of 1,839 patients experienced major cardiovascular events, of whom 403 had previously experienced severe hypoglycemic events and 703 died within our study period. A prior hypoglycemic event was associated with a significant increase in mortality after a cardiovascular event, with hazard ratios estimated at 1.79 (95% CI 1.37–2.35) within the first month and 1.25 (95% CI 1.02–1.53) after 1 month. Patients with prior hypoglycemia had an estimated 5-year cumulative mortality risk of 52.4% (95% CI 45.3–59.5) and 39.8% (95% CI 33.4–46.3) for MI and stroke, respectively. CONCLUSIONS We have found evidence that patients with type 1 diabetes in Sweden with prior severe hypoglycemic events have increased risk of mortality after a cardiovascular event.

Optimal strategies for identifying kidney disease in diabetes: Properties of screening tests, progression of renal dysfunction and impact of treatment - Systematic review and modelling of progression and cost-effectiveness

BACKGROUND Annual screening for adults with type 2 diabetes to detect the early onset of kidney disease is widely recommended, but the recommendations are based on a limited methodological approach. In addition, there are continuing uncertainties about underlying rates of progression of the condition and the benefits of treatments with angiotensin-converting enzyme inhibitors and angiotensin receptor blockers. OBJECTIVES We aimed to estimate the clinical value and cost-effectiveness of different screening intervals to diagnose early diabetic kidney disease. DATA SOURCES We used the following databases for the literature review (searched January 2005 to August 2010): MEDLINE, EMBASE and the Cochrane Database of Systematic Reviews. Individual patient data were obtained from the Oxford Regional Prospective Diabetes Study and the Collaborative Atorvastatin Diabetes Study. METHODS Data from systematically identified randomised trials reporting the impact on renal outcomes of angiotensin-converting enzyme inhibitors and angiotensin 2 receptor blockers for type 1 and type 2 diabetes patients with normoalbuminuria and microalbuminuria were pooled to derive estimates of effect. Individual patient data for type 1 and type 2 diabetes patients were used to obtain parameters describing progression and variability of measurement over time for the albumin-to-creatinine ratio (ACR) and estimated glomerular filtration rate. Based on accepted diagnostic thresholds, we modelled whether these tests accurately identified patients who were developing early diabetic kidney disease and required intensification of treatment. Cost-effectiveness analyses were carried out using simulation outcome models to estimate the incremental costs per quality-adjusted life-year (QALY) for different screening intervals. RESULTS In total, 49 trials (n = 34,082 patients) were eligible for inclusion in the systematic review. For type 1 diabetes, pooled estimates of urinary albumin excretion (UAE) for treated patients with microalbuminuria were on average 67% [95% confidence interval (CI) 54% to 77%] lower at the end of the trial than for untreated patients. There was no significant treatment effect for patients with normoalbuminuria (p interaction = 0.006). For treated patients with type 2 diabetes and normoalbuminuria or microalbuminuria, UAE was lower by, on average, 21% (95% CI 97% to 32%) or 27% (95% CI 15% to 38%), respectively. The proportion (95% CI) of men and women with type 1 diabetes screened annually for microalbuminuria over 6 years and inaccurately identified as having microalbuminuria would be 48% (43% to 53%) and 55% (48% to 61%), respectively. The corresponding proportions for type 2 diabetes are 36% (32% to 42%) and 48% (41% to 55%). Decreasing the screening interval to 3-yearly would reduce this for men with type 1 diabetes to 38% (33% to 44%), with an increase in those not identified over 6 years from 1.5% (95% CI 1% to 2%) to 4% (95% CI 3% to 5%). For type 1 diabetes, incremental cost per QALY [standard deviation (SD)] of a 5-yearly compared with a 4-yearly screening interval was £3612 (£6586), increasing to £9601 (£34,112) for annual compared with 2-yearly screening. The probability that the intervention is cost saving is around 25%, and it has around an 80% chance of being below a cost-effectiveness threshold of £30,000. For type 2 diabetes, incremental cost per QALY (SD) of a yearly compared with a 2-yearly screening interval was £606 (£1782). The intervention is almost certainly below a cost-effectiveness threshold of £5000. CONCLUSIONS These results support current UK guidance, which recommends annual screening with ACR to identify early kidney disease in patients with diabetes, despite a high false-positive rate leading to, at worst, unnecessary or, at best, early therapeutic intervention. For type 1 diabetes, screening costs for annual compared with 2-yearly screening are well within the bounds of accepted cost-effectiveness. Annual screening is even more cost-effective in type 2 diabetes than in type 1 diabetes. Identification of alternative markers for developing diabetic nephropathy may improve targeting of treatment for those at high risk. FUNDING The National Institute for Health Research Health Technology Assessment programme.

Optimal strategies for monitoring lipid levels in patients at risk or with cardiovascular disease: a systematic review with statistical and cost-effectiveness modelling

BACKGROUND 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. OBJECTIVE To determine clinical value and cost-effectiveness of different monitoring intervals and different lipid measures for primary and secondary prevention of CVD. DATA SOURCES 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 Lukes Hospital, Japan, were used in statistical modelling. Utilities and health-care costs were drawn from the literature. METHODS 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. RESULTS 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. LIMITATION Heterogeneity in meta-analyses. CONCLUSIONS 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. STUDY REGISTRATION This study is registered as PROSPERO CRD42013003727. FUNDING The National Institute for Health Research Health Technology Assessment programme.

A Meta-Analysis of the Relative Risk of Mortality for Type 1 Diabetes Patients Compared to the General Population: Exploring Temporal Changes in Relative Mortality

Aims Type 1 diabetes has been associated with an elevated relative risk (RR) of mortality compared to the general population. To review published studies on the RR of mortality of Type 1 diabetes patients compared to the general population, we conducted a meta-analysis and examined the temporal changes in the RR of mortality over time. Methods Systematic review of studies reporting RR of mortality for Type 1 diabetes compared to the general population. We conducted meta-analyses using a DerSimonian and Laird random effects model to obtain the average effect and the distribution of RR estimates. Sub-group meta-analyses and multivariate meta-regression analysis was performed to examine heterogeneity. Summary RR with 95% CIs was calculated using a random-effects model. Results 26 studies with a total of 88 subpopulations were included in the meta-analysis and overall RR of mortality was 3.82 (95% CI 3.41, 3.4.29) compared to the general population. Observations using data prior to 1971 had a much larger estimated RR (5.80 (95% CI 4.20, 8.01)) when compared to: data between; 1971 and 1980 (5.06 (95% CI 3.44, 7.45)); 1981–90 (3.59 (95% CI 3.15, 4.09)); and those after 1990 (3.11 (95% CI 2.47, 3.91)); suggesting mortality of Type 1 diabetes patients when compared to the general population have been improving over time. Similarly, females (4.54 (95% CI 3.79–5.45)) had a larger RR estimate when compared to males (3.25 (95% CI 2.82–3.73) and the meta-regression found evidence for temporal trends and sex (p<0.01) accounting for heterogeneity between studies. Conclusions Type 1 diabetes patients’ mortality has declined at a faster rate than the general population. However, the largest relative improvements have occurred prior to 1990. Emphasis on intensive blood glucose control alongside blood pressure control and statin therapy may translate into further reductions in mortality in coming years.

Modelling obesity trends in Australia: unravelling the past and predicting the future

Background/Objectives:Modelling is increasingly being used to predict the epidemiology of obesity progression and its consequences. The aims of this study were: (a) to present and validate a model for prediction of obesity among Australian adults and (b) to use the model to project the prevalence of obesity and severe obesity by 2025.Subjects/Methods:Individual level simulation combined with survey estimation techniques to model changing population body mass index (BMI) distribution over time. The model input population was derived from a nationally representative survey in 1995, representing over 12 million adults. Simulations were run for 30 years. The model was validated retrospectively and then used to predict obesity and severe obesity by 2025 among different aged cohorts and at a whole population level.Results:The changing BMI distribution over time was well predicted by the model and projected prevalence of weight status groups agreed with population level data in 2008, 2012 and 2014.The model predicts more growth in obesity among younger than older adult cohorts. Projections at a whole population level, were that healthy weight will decline, overweight will remain steady, but obesity and severe obesity prevalence will continue to increase beyond 2016. Adult obesity prevalence was projected to increase from 19% in 1995 to 35% by 2025. Severe obesity (BMI>35), which was only around 5% in 1995, was projected to be 13% by 2025, two to three times the 1995 levels.Conclusions:The projected rise in obesity severe obesity will have more substantial cost and healthcare system implications than in previous decades. Having a robust epidemiological model is key to predicting these long-term costs and health outcomes into the future.

Economic evaluation of "healthy beginnings" an early childhood intervention to prevent obesity.

To determine the costs and cost‐effectiveness of an early childhood home visiting program delivered to families in socio‐economically disadvantaged areas of Sydney, Australia during 2007‐2010.

Application of the 2014 NICE cholesterol guidelines in the English population: a cross-sectional analysis.

BACKGROUND The 2014 guidelines on cardiovascular risk assessment and lipid modification from the National Institute for Health and Care Excellence (NICE) recommend statin therapy for adults with prevalent cardiovascular disease (CVD), and for adults with a 10-year CVD risk of ≥10%, estimated using the QRISK2 algorithm. AIM To determine risk factor levels required to exceed the risk threshold for statin therapy, and to estimate the number of adults in England who would require statin therapy under the guidelines. DESIGN AND SETTING Cross-sectional study using a sample representative of the English population aged 30-84 years. METHOD To estimate 10-year CVD risk different combinations of risk factor levels were entered into the QRISK2 algorithm. The NICE guidelines were applied to the sample using data from the Health Survey for England 2011. RESULTS Even with optimal risk factor levels, males of different ethnicities would exceed the 10% risk threshold between the ages of 60 and 70 years, and females would exceed the threshold between 65 and 75 years. Under the NICE guidelines, 11.8 million males and females (37% of the adults aged 30-84 years) would require statin therapy, most of them (9.8 million) for primary prevention. When analysed by age, 95% of males and 66% of females without CVD in ages 60-74 years, including all males and females in ages 75-84 years, would require statin therapy. CONCLUSION Under the 2014 NICE guidelines, 11.8 million (37%) adults in England aged 30-84 years, including almost all males >60 years in all females >75 years, require statin therapy.

Making guidelines for economic evaluations relevant to public health in Australia

Australian and New Zealand Journal of Public Health 115

Treatment gaps and potential cardiovascular risk reduction from expanded statin use in the US and England.

Background The updated national guidelines for cardiovascular risk assessment and lipid modification in the UK and US expand the indications for statin therapy in primary prevention to adults with moderate risk of cardiovascular disease (CVD) but many adults at high CVD risk remain untreated in both countries. We set out to identify treatment gaps in English and American adults at moderate and high risk of cardiovascular disease (CVD), and to estimate the number of CVD events that would be prevented from expanding statin therapy to those who are currently untreated. Methods We used nationally representative samples of 10,375 English adults and 7,687 US adults aged 40–75 years and free of existing CVD from the Health Survey for England 2009–2013, and the National Health and Nutrition Examination Survey 2007–2012 in the US. We used the risk algorithms and the risk thresholds for statin therapy recommended by each country’s national guideline to categorize the survey participants into moderate-risk (≥10% to <20% 10-year risk of CVD in England and ≥7.5% to <20% risk in the US) or high-risk (≥20%risk) and simulated the number of events that would be prevented from expansion of statin therapy to those currently untreated. Results Close to half of adults at high CVD risk in England (46.0%) and the US (49.7%) were not receiving statins. Expanding statin use to 1.45 million high-risk adults in England would save 101,000 (95% CI = 81,000–120,000) CVD events in the next 10 years compared with 128,000 (103,000–154,000) CVD events that would be prevented from expanding treatment to 3.64 million untreated moderate-risk adults. In the US, expanding statin use to 5.27 million untreated high-risk adults would save 384,000 (305,000–461,000) CVD events over 10 years compared with 616,000 (493,000–738,000) CVD events that would be prevented from treating 20.29 million untreated moderate-risk adults. Conclusions In both England and the US, expanding statin therapy to untreated moderate-risk adults would prevent a comparable number of events as expanding statin use to a much smaller number of currently untreated high-risk adults. A large potential for CVD prevention remains from improving coverage of statin therapy among high-risk adults.