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Diabetes care for south Asian patients: a special case, EDITORIAL
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The Lancet May 24, 2008
Tahseen A Chowdhury a and Graham A Hitman a
a. Department of Diabetes and Metabolism, Barts and the London NHS Trust and School of Medicine and Dentistry, London E1 1BB, UK
The prevalence of type 2 diabetes is rising rapidly worldwide, particularly for south Asian people living in urban areas.1,2 South Asian individuals have a four-fold to six-fold greater risk of developing type 2 diabetes, contract the disease at an earlier age, and have higher rates of renal and cardiovascular complications than do other ethnic groups .3,4 Although prevention of diabetes is a public-health priority, prevention of complications in patients with established diabetes is equally important. Evidence from randomised trials shows that this priority can be achieved by multifactorial interventions, reducing the risk of cardiovascular complications by up to 50%.5 The challenge remains how to implement such interventions cost-effectively, particularly in high-risk ethnic groups such as south Asian patients, to reduce the health inequalities that exist between people from south Asia and the indigenous UK population.
In today's Lancet, Srikanth Bellary and colleagues try to address this challenge.6 They report findings from the UK Asian Diabetes Study (UKADS)-a cluster randomised trial of enhanced versus standard diabetes care for south Asian patients with diabetes in a UK primary-care setting. The enhanced package consisted of an evidence-based protocol for cardiovascular risk factors, which was delivered by primary-care nurses. A key intervention was that of link workers, who were trained to undertake advocacy and offer culturally appropriate advice for patients during and between consultations with their health-care professionals. Additional educational support for health-care professionals was offered by community-based nurses specialising in diabetes.
The effect of the intervention was disappointingly modest-a difference of 1·91/1·36 mm_Hg in blood pressure, but no significant effect on the other primary endpoints of cholesterol or haemoglobin A1c. The trial was not powered to detect differences in mortality or cardiovascular outcomes, and the investigators noted no benefit for patients receiving the enhanced care package. Although the intervention proved not to be cost effective, no modelling was undertaken to account for the effect of reduction in blood pressure on cardiovascular events. What are the reasons for this costly intervention not being as effective as was hypothesised at the start of the study? Several explanations are plausible.
First, the intervention did not seem to include a substantial structured patient-education component. The mantra of diabetes care in recent years has been patient empowerment and encouragement to self manage, and UK south Asian patients with diabetes seem to have a poor understanding of the disease.7 Assessment of DESMOND (diabetes education for on-going and newly diagnosed)-a patients' structured education programme delivered in multiethnic populations-showed significant improvement over 1 year in biomedical outcomes such as weight loss and smoking cessation, although this improvement did not produce a change in glycaemic control.8 Although the link workers in UKADS could have had a useful advocacy role, was their potential for education fully realised? Second, significant improvements in diabetes care were achieved during the study through the pay for performance initiative (quality outcomes framework),9 and hence the intervention's effects might have been diluted.
Third, the intervention might not have addressed some of the cultural barriers to improvement in diabetes care. Health beliefs for diabetes in south Asian people have substantial cultural effects,10 and might need carefully designed, culturally appropriate interventions to overcome barriers. An example of this tenet is insulin initiation. In our population of predominantly Bangladeshi patients in east London, around one in five patients refuses insulin despite careful counselling, often because of myths and misconceptions about the use of insulin therapy.11 In UKADS, attainment of tight glycaemic control was rare, possibly because of insufficient insulin treatment. Was this finding due to clinical inertia on the part of health-care professionals, or due to poor acceptance of therapy by the patients? Overcoming these barriers clearly needs much greater attention than is currently given. This study also draws attention to the difficulty in attainment of good glycaemic control, which is partly because the drugs provided are not as effective as those used for cholesterol lowering.
The trial did show some optimistic signs for diabetes care in deprived, urban areas that are ethnically diverse. UK primary care seems to be grasping the nettle of cardiovascular risk reduction in patients with diabetes, as shown by the increase in treatment with statins and angiotensin-converting-enzyme inhibitors to more than two-thirds of the diabetic population, accompanied by a drop in blood pressure of 4·9/3·8 mm_Hg and a reduction in total cholesterol of 0·45 mmol/L.6 These findings should equate to substantial reductions in cardiovascular disease in this population over time. However, similar reductions in glycaemic control have not been achieved, emphasising that this challenge in diabetes care remains, particularly for south Asian patients.
Enhanced diabetes care to patients of south Asian ethnic origin (the United Kingdom Asian Diabetes Study): a cluster randomised controlled trial
The Lancet May 24, 2008; 371:1769-1776
S Bellary MRCP a c *, JP O'Hare FRCP b *, NT Raymond MSc b, A Gumber PhD b, S Mughal Dip Nursing a, Prof A Szczepura DPhil b, Prof S Kumar FRCP b and Prof AH Barnett FRCP a c , for UKADS Study Group
*Joint first authors
a. Heart of England NHS Foundation Trust, Birmingham, UK
b. Warwick Medical School, Coventry, UK
c. University of Birmingham, Birmingham, UK
Discussion
Our results confirm that the achievement of targets set by national and international advisory bodies poses a major challenge for south Asian ethnic groups in inner-city general practices.12-14,21 At baseline, many of our patients had haemoglobin A1c greater than 7%, blood pressure greater than 130/80 mm_Hg, and total cholesterol greater than 4 mmol/L, which are higher than targets recommended by international standards for diabetes care. After 2 years in which secular changes included the pay for performance initiative, we noted significant improvements in blood pressure and total cholesterol across the whole study population, but no change in haemoglobin A1c. A reduction in blood pressure has been associated with rapid reduction in cardiovascular risk in many studies.22-24 The relation between blood pressure and cardiovascular risk is such that a sustained reduction of 5 mm_Hg would confer substantial protection from cardiovascular events.25 The improvements in blood pressure and cholesterol that we recorded were associated with increased prescribing of antihypertensive agents and statins, and are consistent with improvements reported by several other investigators after the introduction of QOF initiatives.26
The mortality noted during our study, together with the frequency of cardiovascular events at baseline and follow-up, confirm that the south Asian group which we investigated has a high cardiovascular risk and that substantial benefits could be obtained by aggressive reduction in risk factors. The failure to prevent the increase in microalbuminuria despite a 5 mm_Hg decrease in blood pressure is surprising and suggests that lower targets could be needed for this group.
A comparison of intervention and control groups after 2 years showed significant differences for diastolic blood pressure and mean arterial pressure after adjustment for confounding and clustering. Although systolic blood pressure was lower in the intervention than in the control group, the result was not significant. The reductions seen in diastolic blood pressure were comparable with those recorded in our pilot study,11 but the reduction in systolic blood pressure was less than was previously achieved. The fairly young age of onset and ethnic origin might be a factor in this finding, and a more pronounced diastolic effect has been reported in some other studies.27 We noted a small but significant increase in BMI in the intervention group. This finding could be because of the increased use of insulin in the intervention group, but other factors such as poor adherence to lifestyle advice might have contributed.
The absence of significant improvement in haemoglobin A1c could be partly due to the natural disease progression that is commonly seen in type 2 diabetes;28 haemoglobin A1c tended to rise in the control group, whereas it remained stable over 2 years in the intervention group. In view of the health-care resources provided, we find it disappointing that neither the QOF incentives nor our culturally sensitive enhanced care package significantly effected glycaemic control.
Despite clear evidence of failure to reach target levels of haemoglobin A1c via diet and oral antidiabetic therapy, we recorded only a small increase in the percentage of patients given insulin in both groups. Even though the intervention was supported by nurses specialised in diabetes, who have experience of insulin initiation and patient education, this support seems to have had only a small effect in terms of behavioural change or patient acceptance of insulin.
Initiation of insulin in many primary-care practices in the UK is fairly new, and building up confidence of both the health-care team and south Asian patients might be as important as any financial incentives that the health-care team receive. Changes in patient behaviour through motivation and patient education might take longer than the 2-year follow-up in this study. Alternative methods of motivation, including structured patient education29 and more aggressive insulin initiation, might be needed.
Significant improvements in performance indicators were noted across the UK general practice after the introduction of the QOF initiatives, and even the control practices in our study probably benefited from these changes. Many fewer patients achieved the study targets than did those meeting the QOF targets, suggesting adherence to treatment protocols was poor in both groups. Despite additional nursing resources, we recorded small improvements in the intervention group, which might have been due to reluctance of health professionals to intensify treatments and achieve tighter targets beyond those already set in the QOF initiative. Such factors will not be exclusive to south Asian patients receiving primary care in the UK and might apply to other racial groups and health-care settings.
The economic analysis shows that the financial investment needed over 2 years did not produce sufficient health-related gain in quality of life to make such a nurse-led intervention clearly cost effective. At 28_933 per QALY gained, compared with an indicative norm of 30_000 per QALY,30 wide-scale implementation is not suggested without improvement in effectiveness.
In our study, not all patients were receiving statins at the start of the trial. The proportion of patients receiving statins increased over 2 years and was comparable to other published reports in patients with diabetes.31 However, only two-thirds of patients were receiving statins despite our protocol stating that all patients should be prescribed them. The precise reason for this finding is unclear. One reason could be that target cholesterol concentrations in the QOF were 5 mmol/L. Therefore patients whose cholesterol concentrations achieved these targets did not receive statins.
We used the LOCF method in our analyses, which we acknowledge has its weaknesses. However, an analysis of complete data only, produced very similar results. A further limitation of our study is the inability to assess the relative contributions of individual components of the intervention; such challenges are inherent to the assessment of complex interventions.
Despite the modest clinical outcomes achieved in the study, evidence suggests that intensive management can improve outcomes in type 2 diabetes. Although the intervention might need development, the strength of the study is that it applies rigorous scientific evaluation to a socially deprived ethnic minority group.
Substantial difficulties in recruiting and retaining individuals of south Asian ethnic origin have been reported previously by several investigators,32,33 which might account for the scarcity of large-scale studies in this population.34 However, our experience suggests that recruitment and retention is possible in this hard-to-reach group. Our results suggest that small but sustained improvements in blood pressure can be achieved through the introduction of a culturally sensitive, enhanced care package for south Asian patients in addition to improvements from the QOF financial incentives. Improvement in glycaemic control remains a major challenge, and further work to enhance effectiveness of health-care delivery in general practice and to improve motivation is clearly needed for this group if health-care inequalities are to be reduced. Although progress has been made, a substantial challenge remains to achieve the more stringent targets that are recommended by national and international expert advisory bodies.
Summary
Background
Delivery of high-quality, evidence-based health care to deprived sectors of the community is a major goal for society. We investigated the effectiveness of a culturally sensitive, enhanced care package in UK general practices for improvement of cardiovascular risk factors in patients of south Asian origin with type 2 diabetes.
Methods
In this cluster randomised controlled trial, 21 inner-city practices in the UK were assigned by simple randomisation to intervention (enhanced care including additional time with practice nurse and support from a link worker and diabetes-specialist nurse [nine practices; n=868]) or control (standard care [12 practices; n=618]) groups. All adult patients of south Asian origin with type 2 diabetes were eligible. Prescribing algorithms with clearly defined targets were provided for all practices. Primary outcomes were changes in blood pressure, total cholesterol, and glycaemic control (haemoglobin A1c) after 2 years. Analysis was by intention to treat. This trial is registered, number ISRCTN 38297969.
Findings
We recorded significant differences between treatment groups in diastolic blood pressure (1·91 [95% CI _2·88 to _0·94] mm_Hg, p=0·0001) and mean arterial pressure (1·36 [_2·49 to _0·23] mm_Hg, p=0·0180), after adjustment for confounders and clustering. We noted no significant differences between groups for total cholesterol (0·03 [_0·04 to 0·11] mmol/L), systolic blood pressure (_0·33 [_2·41 to 1·75] mm_Hg), or HbA1c (_0·15% [_0·33 to 0·03]). Economic analysis suggests that the nurse-led intervention was not cost effective (incremental cost-effectiveness ratio 28_933 per QALY gained). Across the whole study population over the 2 years of the trial, systolic blood pressure, diastolic blood pressure, and cholesterol decreased significantly by 4·9 (95% CI 4·0-5·9) mm_Hg, 3·8 (3·2-4·4) mm_Hg, and 0·45 (0·40-0·51) mmol/L, respectively, and we recorded a small and non-significant increase for haemoglobin A1c (0·04% [_0·04 to 0·13]), p=0·290).
Interpretation
We recorded additional, although small, benefits from our culturally tailored care package that were greater than the secular changes achieved in the UK in recent years. Stricter targets in general practice and further measures to motivate patients are needed to achieve best possible health-care outcomes in south Asian patients with diabetes.
Funding
Pfizer, Sanofi-Aventis, Servier Laboratories UK, Merck Sharp & Dohme/Schering-Plough, Takeda UK, Roche, Merck Pharma, Daiichi-Sankyo UK, Boehringer Ingelheim, Eli Lilly, Novo Nordisk, Bristol-Myers Squibb, Solvay Health Care, and Assurance Medical Society UK.
Introduction
Patients of south Asian ethnic background (UK decennial census categories Indian, Pakistani, Bangladeshi, and other Asians) with type 2 diabetes present special management challenges.1,2 In the UK, prevalence of type 2 diabetes is four-fold to six-fold higher in people from south Asia than in white Europeans.3 Furthermore, onset can be more than a decade earlier and the risk of cardiovascular and renal complications greater in patients from south Asia, with higher morbidity and 50% higher mortality.4 Health-care delivery in this population is more challenging because of cultural, communication, and comprehension difficulties, which along with social deprivation further complicate the achievement of defined targets.5,6 Payments for UK general practices based on their achievement of quality (quality and outcomes framework [QOF])7 targets do not distinguish different ethnic groups.
Enhanced care packages based in the community have been associated with improved metabolic outcomes in some ethnic groups8 but have not been fully assessed in large randomised controlled trials. Such trials are scarce in people of south Asian ethnic origin.9 The United Kingdom Asian Diabetes Study (UKADS) assessed a community-based complex intervention that aimed to reduce cardiovascular risk in south Asian people with type 2 diabetes. The intervention package was tailored to the needs of the south Asian community and consisted of additional time with a practice nurse, Asian link workers, and input from diabetes-specialist nurses, who were working to protocols to achieve clearly defined targets. The UKADS study hypothesis was that an enhanced care package for diabetes would improve cardiovascular risk profile in patients of south Asian origin, with established type 2 diabetes.
Methods
Study design and patients
In line with recognised complex intervention evaluations10 and following a protocol informed by a pilot study,11 we undertook a large cluster randomised controlled trial from March, 2004 to April, 2007. 21 general practices (seven in Coventry [500 patients] and 14 in Birmingham, UK [986 patients]) with a very high proportion (more than 80%) of south Asian patients were included in this cluster randomised controlled trial. Between March 2004 and April 2005, nine practices were randomised to enhanced (intervention) and 12 to conventional (control) care. We used simple randomisation in both areas to achieve reasonable balance between groups. A common treatment algorithm was provided for control of blood pressure (webfigure 1), type 2 diabetes (webfigure 2), and lipid control (webfigure 3). All adult patients of south Asian origin with type 2 diabetes were eligible for inclusion in the study. There were no exclusion criteria.
Procedures
Enhanced care included an additional practice nurse time (4 h per practice per week), supported by link workers and a community nurse specialising in diabetes. Patients in the intervention group were followed up on average every 2 months in clinics held every week by the practice nurses. Practice nurses had protected time to run a research diabetes clinic in intervention practices, and they worked with primary-care physicians to implement the protocol and encourage appropriate prescribing, provide face-to-face patient education in clinic setting, and achieve targets for blood pressure, lipid, and glycaemic control. Practice nurses were formally trained in diabetes and had 1:1 observed sessions with a diabetes-specialist nurse.
All patients were contacted by a link worker before and between appointments to encourage clinic attendance. Additionally, link workers provided interpretation and additional educational input in local languages (Punjabi, Urdu, and Mirpuri) to patients in the community setting to improve compliance and understanding and to encourage dietary and lifestyle changes. Link workers attended research clinics in intervention practices. A total of five link workers were employed-three in Birmingham (14 practices) and two in Coventry (seven practices), with each one responsible for three or more practices. All link workers had attended a foundation course (equivalent to diploma) in diabetes management and care.
The two community diabetes-specialist nurses covered the nine intervention practices and attended some research clinics every 6-8 weeks, providing additional educational and clinical support including insulin initiation, to the practice teams. Two specialist nurses were responsible for all 21 practices in the trial, one based in Coventry and one in Birmingham. All staff had formal training and experience in delivering diabetes care in the practice setting. The standard of care provided by the practice nurse and the link worker was monitored by the specialist nurse in observed sessions once every 3 months. General practitioners had overall responsibility for implementation of the study protocol within their practice and were involved in changing prescribing processes.
Practices were encouraged to adhere to treatment protocols and to achieve targets. The study targets followed internationally accepted norms and were haemoglobin A1c of 7·0% (accepted target at the time of commencement of study), total cholesterol of 4·0 mmol/L, and blood pressure 130/80 mm_Hg if no microvascular complications (as recommended by the Joint British Societies and international bodies)12-14 and 125/75 mm_Hg if microalbuminuria or proteinuria was present. Control practices received the same treatment protocols, and practices managed patients with their existing resources. The study protocol was approved by East Birmingham and Coventry Primary Care Trust Ethics Committees. All patients provided written informed consent. Table 1 shows the components and timings of the complex intervention.
Primary outcomes were follow-up measurements at 2 years for blood pressure, total cholesterol, and haemoglobin A1c, with secondary outcomes of waist circumference, body-mass index (BMI), Framingham 10 years coronary heart disease (CHD) risk score,15 microalbuminuria, and plasma creatinine.
We passively monitored adverse events, and practices were encouraged to report any incidents related to the intervention.
Statistical analysis
Estimations of sample size were made on the basis of the observed differences and intraclass correlations ([ICC] defined as variance between groups/within groups) from the pilot study or an ICC=0·05, which is derived from published estimates for primary care studies.16,17 In all estimations, power was set to 80%, and the two-sided probability value to p=0·05. Estimates were made for differences in changes in systolic blood pressure (7 [SD 21·25] mm_Hg, ICC=0·035), total cholesterol (0·45 [1·1] mmol/L, ICC=0·05), and haemoglobin A1c (0·75 [2·1], ICC=0·05). All estimates from these data values resulted in 16-18 clusters of 80-100 patients being needed, allowing for 10% drop-out rate. We selected these effect sizes since they were similar to those recorded in the pilot study, changes of this magnitude would be clinically significant, and they reflected prescribing algorithm targets.
We analysed data with the SAS software package (version 9.1.3). We compared baseline variables between groups with _2 tests of independence, with t tests for continuous variables, which were first assessed for normality.
Primary and secondary outcomes were continuous. In the main intervention assessment, final measured outcomes were modelled, with grand mean-centred baseline measures included as covariates. To adjust for clustering and potential confounding effects, the SAS PROC MIXED procedure was used to fit hierarchical, combined fixed and random effects models.18,19 In all cases, mixed models included fixed effects for area (Birmingham vs Coventry), sex, age at diagnosis of diabetes, duration of diabetes, and corresponding grand mean-centred baseline measurement. For haemoglobin A1c, treatment with insulin at baseline was included in final models. We included terms for antihypertensive treatments, angiotensin-converting enzyme inhibitors (ACE), or angiotensin-receptor blockers (ARB) at baseline in models of blood pressure. For total cholesterol, statins and fibrates were included. Random effects were fitted, within a subject term for general practice, allowing for different intercepts and regression slopes for all individual practices (random coefficients models).
We used restricted maximum likelihood (REML) models to analyse data. The correlation structure used in reported results was unstructured in all cases; variance components structures were considered. We used SAS graphics options to plot and assess residuals and influential data points, which were then removed and models re-run; results presented do not exclude outliers.
For the main intention-to-treat analysis comparing outcomes, all patients were included. We analysed baseline and 2-year follow-up data measurements; for patients whose follow-up data were not available (figure), we inputted data with last observation carried forward (LOCF) method. Data were an interim value measured after 1 year, for around 50% of patients, or the baseline value. We undertook analyses with the same final models only for patients with complete data and only with those who had not died; although estimates of effect differed slightly, results and their interpretation were essentially the same.
We gathered detailed data for staff salaries, travel and subsistence, equipment costs, payment to practices, and prescribing to estimate the net intervention cost over 2 years. Changes in quality-adjusted life years (QALY) between intervention and control groups were measured with the EQ5D (EuroQol Five Dimensions) questionnaire.20
This study is registered, number ISRCTN 38297969.
Role of the funding source
The sponsors of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. NTR, SB, JPO'H, AHB, AS, SK, and AG had full access to all the data in the study. All investigators and the UKADS Study Group had final responsibility for the decision to submit for publication.
Results
The figure shows the trial profile. 1486 patients of south Asian ethnic origin, with established type 2 diabetes, consented to take part and were included in the study; 500 (34%) from Coventry and 986 (66%) from Birmingham.
Table 2 shows the baseline risk-factor profile for the intervention and control groups. Mean age for the whole group was 57·0 (SD 11·9) years. Differences observed between groups for sex, age, duration of diabetes, and treatment for diabetes were not significant. The proportion of current smokers was much the same in both groups, but more patients in the control group than in the intervention group were ex-smokers. We recorded no differences in weight, BMI, or waist circumference measurements. More intervention than control patients were treated with statins.
At baseline, 268 (18%) patients (150 [17%] in the intervention group and 118 [19%] in the control group) had evidence of existing coronary heart disease or previous cardiovascular events, angina, myocardial infarction, cardiovascular accident, coronary artery bypass graft, or other heart problems.
At baseline we measured urinary albumin to creatinine ratio for 1389 (93%) patients (807 [93%] in the intervention and 582 [94%] in the control group) and noted that microalbuminuria (defined as a ratio >2·5 in men and >3·5 in women) was present in 268 (19%) patients (161 [20%] vs 107 [18%]). We detected significant proteinuria, defined as albumin to creatinine ratio of more than 25·0, in 114 (8%) patients (61 [8%] vs 53 [9%]). The prevalence of combined microalbuminuria or proteinuria was 28%, with no difference between intervention and control groups (222 [28%] vs 160 [27%]). With the Framingham equation, mean 10-year risk score for coronary heart disease was 10·6 (SD 8·8), with no difference between treatment groups (table 2).
During 2 years of follow-up, 48 (3%) patients died-24 (3%) in the intervention group and 24 (4%) in the control group. New cardiovascular events were recorded for 97 (7%) patients-62 (7%) in the intervention group and 35 (6%) in the control group. None of these small differences between intervention and control groups was significant. In a post-hoc analyses, patients with coronary heart disease at baseline were more likely to die (18 [7%] vs 30 [2%]) or to have events of coronary heart disease during follow-up (34 [13%] vs 63 [5%]) than were those with no evidence of this disease, irrespective of treatment group. We recorded no adverse events related to intervention during the study period.
Table 3 shows the results for comparison of outcomes between intervention and control groups. After 2 years we recorded a reduction of 5·1 (from 139·4 to 134·3) mm_Hg in systolic blood pressure and 4·5 (from 82·9 to 78·4) mm_Hg in diastolic blood pressure for patients in the intervention group compared with 4·7 (from 141·1 to 136·4) mm_Hg and 2·9 (from 83·8 to 81·0) mm_Hg, respectively, in the control group. Results from t tests showed significant differences in favour of the intervention group for diastolic blood pressure (p=0·0065) and haemoglobin A1c (p=0·0371) (table 3). After adjustment for potential confounders, we noted significant advantages for the intervention group for diastolic blood pressure (p<0·0001) and mean arterial pressure (p=0·0003) (table 3). In final models taking clustering effects into account, significant effects persisted for the intervention group for both mean arterial pressure (p=0·018) and diastolic blood pressure (p=0·0001) (table 3). BMI was significantly increased in the intervention group (p<0·0001; table 3). Other differences in primary and secondary outcomes were small and not significant after adjustment for confounding and clustering (table 3).
The number of patients with microalbuminuria or proteinuria increased from 382 (28%) at baseline to 474 (32%) after 2 years, with no significant difference between the intervention and control groups. Patients at high renal risk, defined by plasma creatinine greater than 120 _mol/L for women and greater than 150 _mol/L for men, increased from 61 (4%) at baseline to 83 (6%) after 2 years, with no difference between treatment groups.
When we combined all patients from both groups after 2 years, we noted an overall decrease of 4·9 (95% CI 4·0-5·9) mm_Hg in systolic blood pressure (p<0·0001), 3·8 (3·2-4·4) mm_Hg in diastolic blood pressure (p<0·0001), and 4·2 (3·6-4·8) mm_Hg in mean arterial pressure (p<0·0001). Total cholesterol decreased by 0·45 (0·40-0·51) mmol/L (p<0·0001). We recorded a small and non-significant increase for haemoglobin A1c (0·04% [_0·04 to 0·13], p=0·290).
After 2 years of follow-up in post-hoc analyses, the number of patients given antihypertensive drugs had increased to 1119 (75%) overall, with no difference between groups (660 [76%] in the intervention and 459 [74%] in the control group). Treatment with statins had increased, with 540 (64%) patients being treated in the intervention group compared with 389 (65%) in the control group. The use of ACE inhibitors or ARBs increased substantially from 321 (37%) to 569 (66%) in the intervention and from 246 (40%) to 389 (62%) in the control group; the groups did not differ significantly.
A similar proportion of patients were treated with insulin at baseline (table 2). After 2 years, more patients in the intervention group than in the control group had started insulin therapy (47 [8%] vs 23 [5%]), but this finding was not significant (relative risk 1·44 [95% CI 0·89-2·34]).
In post-hoc analyses, the number of patients achieving the study targets for blood pressure was 310 (36%) of 868 in the intervention group versus 191 (31%) of 618 in the control group, for cholesterol 411 (47%) of 867 versus 311 (50%) of 617, and for haemoglobin A1c 275 (32%) of 858 versus 165 (27%) of 615. For the QOF targets, the corresponding number for blood pressure of less than 145/85 mm_Hg was 575 (66%) versus 346 (56%), for cholesterol less than 5 mmol/L 700 (81%) versus 509 (83%), and for haemoglobin A1c less than 7·5% 377 (44%) versus 240 (39%).
Table 4 provides a detailed cost breakdown for the intervention. Over 2 years, the cost of intervention per patient was GB 434 ( 406 net service and 28 net prescribing costs). Despite patients' overall quality of life deteriorating over 2 years, the resultant net change in quality of life in the intervention group compared with control group was positive, although small (0·015). Thus, we calculated the incremental cost-effectiveness ratio to be 28_933 per QALY gained.
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