What impact would pancreatic beta-cell preservation have on life expectancy, quality-adjusted life expectancy and costs of complications in patients with type 2 diabetes? A projection using the CORE Diabetes Model

Contemporary Risk Estimates of Three HbA1c Variables for Myocardial Infarction in 101,799 Patients Following Diagnosis of Type 2 Diabetes

OBJECTIVE

This study evaluated the risk of myocardial infarction (MI) by impaired glycemic control in a contemporary large cohort of patients with type 2 diabetes followed from diagnosis.

RESEARCH DESIGN AND METHODS

Patients with type 2 diabetes diagnosed between 1995 and 2011 were retrieved from the Clinical Practice Research Datalink in the U.K., and followed from diagnosis until event of MI or end of study in 2013. Two subcohorts were defined: an early cohort with those diagnosed from 1997 to 2004 and a recent cohort with those diagnosed from 2004 to 2011. Association between each of three HbA1c metrics and MI was estimated using adjusted proportional hazards models.

RESULTS

In the overall cohort (n = 101,799), the risk increase for MI per 1% (10 mmol/mol) increase in HbA(1c) was higher for updated latest and updated mean HbA(1c) of 1.11 (95% CI 1.09-1.13) and 1.15 (1.13-1.18) than for baseline HbA(1c) of 1.05 (1.03-1.06). In the early subcohort, the corresponding risk estimates were greater than those in the recent subcohort. When categorized, the updated latest variable showed an increased risk for HbA(1c) <6% (42 mmol/mol), relative category 6-7%, in the recent but not in the early subcohort, with hazard ratios of 1.23 (1.08-1.40) and 1.01 (0.84-1.22), respectively.

CONCLUSIONS

The two time-updated HbA(1c) variables show a stronger relation with MI than baseline HbA(1c). The risk association between HbA(1c) and MI has decreased over time. In recently diagnosed patients with type 2 diabetes, an increased risk of MI exists at a current HbA(1c) of <6.0% (42 mmol/mol).

Changes in HbA1c and frequency of measuring HbA1c and adjusting glucose-lowering medications in the 10 years following diagnosis of type 2 diabetes: a population-based study in the UK

AIMS/HYPOTHESIS

The aim of this work was to study levels of HbA1c and patterns of adjusting glucose-lowering drugs in patients with impaired glycaemic control over 10 years after diagnosis of type 2 diabetes.

METHODS

We studied 4,529 individuals in The Health Improvement Network Database newly diagnosed with type 2 diabetes in the year 2000.

RESULTS

From 6 months to 10 years after diagnosis, the HbA1c increased from 7.04% (53.4 mmol/mol) to 7.49% (58.3 mmol/mol) (average annual change: 0.047% [0.51 mmol/mol]). The greatest annual change occurred between 6 months and 2 years (0.21% [2.30 mmol/mol] increase per year, p < 0.001), followed by the 2-5 year time period (0.033% [0.36 mmol/mol] increase per year, p < 0.001). No significant increase in HbA1c occurred between 5 and 10 years (p = 0.20). In multivariable analyses, patients who were younger (p < 0.001), with higher BMI (p = 0.033) and who were current insulin users (p = 0.024) at diagnosis had greater increases in HbA1c between 6 months and 2 years. For individuals with HbA1c above 7.0% (53 mmol/mol) the mean time to next measurement of HbA1c was 0.53 years and increase in doses or changes to other glucose-lowering medications were performed in 26% of cases.

CONCLUSIONS/INTERPRETATION

HbA1c increases by approximately 0.5% (5 mmol/mol) over 10 years after diagnosis of type 2 diabetes, with the main increase appearing in the first years after diagnosis. More frequent monitoring of HbA1c and adjustments of glucose-lowering drugs may be essential to prevent the decline.

Levels of C-peptide, body mass index and age, and their usefulness in classification of diabetes in relation to autoimmunity, in adults with newly diagnosed diabetes in Kronoberg, Sweden

OBJECTIVE

C-peptide is a main outcome measure in treatment trials of diabetes. C-peptide also has a role in the classification of diabetes, which is often difficult in adults and this is also increasingly recognised in adolescents and elders.

AIM

We aimed to describe the levels of C-peptide in relation to age and body mass index (BMI) in a large population-based cohort of adults with newly diagnosed diabetes and compare the capabilities of C-peptide, age and BMI to discriminate between autoimmune and non-autoimmune diabetes.

SUBJECTS AND METHODS

Blood samples from 1180 patients were analysed regarding islet cell antibody, glutamic acid decarboxylase antibody and fasting C-peptide (FCP). Receiver operating characteristics (ROC) curves were analysed to check the ability of age, BMI and C-peptide to discriminate between autoantibody-positive (Ab(+)) and -negative (Ab(-)) diabetes.

RESULTS

Mean FCP was 0.73±0.5 (range 0.13-1.80) nmol/l in the Ab(+) and 1.42±0.9 (range 0.13-8.30) nmol/l in the Ab(-). FCP was 0.02 nmol/l higher per year increase in age at diagnosis of diabetes. Mean BMI was 26.0±4.8 (range 18.0-39.0) kg/m(2) in the Ab(+) and 28.9±5.3 (range 15.5-62.6) kg/m(2) in the Ab(-). FCP increased with age also within each BMI group. The highest area under the curve (AUC) in the ROC analysis was found for C-peptide, followed by age and BMI (0.78, 0.68 and 0.66 respectively).

CONCLUSIONS

At diagnosis of diabetes, C-peptide was superior to age and BMI in discriminating between autoimmune and non-autoimmune diabetes. C-peptide increased significantly with BMI and age, latter also within each BMI group. Most of the adults had normal or high levels of C-peptide at presentation of diabetes among the autoimmune patients.

Model-based decision support in diabetes care

The model-based Karlsburg Diabetes Management System (KADIS®) has been developed as a patient-focused decision-support tool to provide evidence-based advice for physicians in their daily efforts to optimize metabolic control in diabetes care of their patients on an individualized basis. For this purpose, KADIS® was established in terms of a personalized, interactive in silico simulation procedure, implemented into a problem-related diabetes health care network and evaluated under different conditions by conducting open-label mono- and polycentric trials, and a case-control study, and last but not least, by application in routine diabetes outpatient care. The trial outcomes clearly show that the recommendations provided to the physicians by KADIS® lead to significant improvement of metabolic control. This model-based decision-support system provides an excellent tool to effectively guide physicians in personalized decision-making to achieve optimal metabolic control for their patients.

Economic models in type 2 diabetes

OBJECTIVE

To identify and critically appraise cost-effectiveness models developed to evaluate type 2 diabetes (T2D) treatments and to assess which types of treatment effects they capture.

RESEARCH DESIGN AND METHODS

A systematic search was performed in MEDLINE, EMBASE, Centre for Reviews and Dissemination databases at the University of York, and Health Economic Evaluation Database for the period to September 2008. The websites of Health Technology Assessment (HTA) bodies in different countries were also screened for relevant models. For each of the identified original models, details of the structure, data in- and outputs were extracted and the overall quality of the model in terms of the combination of structure, assumptions and data inputs were appraised using published criteria.

RESULTS

Seventy-eight articles and 41 HTAs reporting relevant economic evaluations were identified. There were ten models with multiple publications, and a further ten models with one associated publication. The critical review demonstrated that most had the same fundamental structure, used similar micro-simulation techniques and were based on the same key data sources. However, the process for identification of relevant data and their synthesis, and the selection of outcomes lacked transparency. The models differed according to the extent and type of interventions they evaluated and which diabetes complications and treatment-related adverse events were captured. For example, just one model incorporated changes in patient weight, despite the fact that weight gain can be a side-effect of some treatments, and weight loss a potential benefit of others.

CONCLUSIONS

Whilst many economic models exist in T2D, most share common features such as the model type. Identified shortcomings are lack of transparency in data identification and evidence synthesis as well as the selection of the modelled outcomes. Future models should aim to include all relevant treatment outcomes, whether these relate to effects on underlying diabetes and its complications or to short- or long-term side effects of treatment.

A simulation of the comparative long-term effectiveness of liraglutide and glimepiride monotherapies in patients with type 2 diabetes mellitus

STUDY OBJECTIVE

To project and compare long-term outcomes of morbidity and mortality, and costs of complications of type 2 diabetes mellitus from a randomized controlled trial of patients receiving liraglutide versus glimepiride monotherapy.

DESIGN

Mathematic simulation using the validated Center for Outcomes Research (CORE) Diabetes Model, calibrated to baseline patient characteristics from a short-term, randomized, controlled trial of liraglutide and glimepiride monotherapies (Liraglutide Effect and Action in Diabetes [LEAD]-3 trial) and using data from long-term outcomes studies.

SETTING

Simulated routine clinical practice.

PATIENTS

Seven hundred forty-six patients with type 2 diabetes who participated in the LEAD-3 trial, and three hypothetical cohorts of 5000 patients each that were based on the baseline characteristics of the patients in the LEAD-3 trial. The patients in the LEAD-3 trial were randomly assigned to monotherapy with liraglutide 1.2 mg/day (251 patients), liraglutide 1.8 mg/day (247 patients), or glimepiride 8 mg/day (248 patients).

MEASUREMENTS AND MAIN RESULTS

The impact of the three treatments for type 2 diabetes on survival and cumulative incidence of cardiovascular, ocular, or renal events and costs were estimated at three time periods: 10, 20, and 30 years. Simulations predicted improved survival for liraglutide 1.8 and 1.2 mg at all three time points compared with glimepiride. Survival benefits were greatest after 30 years of follow-up: 16.5%, 13.6%, and 7.3%, respectively. The frequency of nonfatal renal and ocular events was lower for both liraglutide doses than for glimepiride. The rate of neuropathies leading to first or recurrent amputation was higher for glimepiride compared with both liraglutide doses. The average cumulative cost/patient was higher for glimepiride compared with liraglutide 1.2 mg and liraglutide 1.8 mg.

CONCLUSION

With use of the CORE Diabetes Model and data from the LEAD-3 trial, long-term projected survival, diabetes complications, and costs favored liraglutide 1.2- and 1.8-mg monotherapies compared with glimepiride in the treatment of type 2 diabetes.

Pharmacoeconomic simulation of delayed results of the treatment of type 2 diabetes mellitus with modern insulin analogsin comparison with oral hypoglycemic agents

Aim. To carry out cost-effectiveness analysis of treatment options for type 2 diabetes using different groups of medicines, to prognosticate late diabeticcomplications and the cost of their management. Materials and methods. A total of 3678 DM2 patients (with mean HbAc1 level 9.3%) were examined in 23 regionsin the framework of the Diabetesmellitus subprogram of the Federal target program "Prevention and control of socially significant diseases". Two hypothetical therapeutic modalitieswere considered: treatment with NovoMix 30 and oral hypoglycemic (OHG) agents. The CORE model was used to analyse anticipated expendituresand DM outcomes. Results. Simulation revealed a greater decrease of HbA1c levels (-1.7%), reduction of total cholesterol, LDL, systolic AP (-4.1%) and risk of cardiovasculardiseases coupled to increase of HDL in patients treated with NovoMix 30. Maximum life expectancy was 17.2 yr compared with 16.5 yrin the OHG group and overall cost of the treatment 1,650,725 and 1,586,234 rubles respectively. Savings for the treatment of diabetes using NovoMix30 amounted to 19,832 rubles per patients due to reduced indirect expenditures including management of renal, cardiac, ophthalmologic , and cerebrovascularcomplications. Conclusion. Simulation of late results of DM2 treatment demonstrated enhanced pharmacoeconomic efficiency of modern insulin analogs comparedwith OHG agents.

Long-term outcomes in patients with type 2 diabetes receiving glimepiride combined with liraglutide or rosiglitazone

Background

Poor control of type 2 diabetes results in substantial long-term consequences. Studies of new diabetes treatments are rarely designed to assess mortality, complication rates and costs. We sought to estimate the long-term consequences of liraglutide and rosiglitazone both added to glimepiride.

Methods

To estimate long-term clinical and economic consequences, we used the CORE diabetes model, a validated cohort model that uses epidemiologic data from long-term clinical trials to simulate morbidity, mortality and costs of diabetes. Clinical data were extracted from the LEAD-1 trial evaluating two doses (1.2 mg and 1.8 mg) of a once daily GLP-1 analog liraglutide, or rosiglitazone 4 mg, on a background of glimepiride in type 2 diabetes. CORE was calibrated to the LEAD-1 baseline patient characteristics. Survival, cumulative incidence of cardiovascular, ocular and renal events and healthcare costs were estimated over three periods: 10, 20 and 30 years.

Results

In a hypothetical cohort of 5000 patients per treatment followed for 30 years, liraglutide 1.2 mg and 1.8 mg had higher survival rates compared to the group treated with rosiglitazone (15.0% and 16.0% vs. 12.6% after 30 years), and fewer cardiovascular, renal, and ocular events. Cardiovascular death rates after 30 years were 69.7%, 68.4% and 72.5%, for liraglutide 1.2 mg, 1.8 mg, and rosiglitazone, respectively. First and recurrent amputations were lower in the rosiglitazone group, probably due to a 'survival paradox' in the liraglutide arms (number of events: 565, 529, and 507, respectively). Overall cumulative costs per patient, were lower in both liraglutide groups compared to rosiglitazone (US$38,963, $39,239, and $40,401 for liraglutide 1.2 mg, 1.8 mg, and rosiglitazone, respectively), mainly driven by the costs of cardiovascular events in all groups.

Conclusion

Using data from LEAD-1 and epidemiologic evidence from the CORE diabetes model, projected rates of mortality, diabetes complications and healthcare costs over the long term favor liraglutide plus glimepiride over rosiglitazone plus glimepiride.

Trial registration

LEAD-1 NCT00318422; LEAD-2 NCT00318461; LEAD-3 NCT 00294723; LEAD-4 NCT00333151; LEAD-5 NCT00331851; LEAD-6 NCT00518882.

Direct medical costs for type 2 diabetes mellitus complications in the US commercial payer setting: a resource for economic research

BACKGROUND

Medical complications are the key drivers of the direct medical costs of treating patients with type 2 diabetes mellitus. However, the published literature shows great variability across studies in the number and type of sources from which these costs for diabetes are obtained.

OBJECTIVE

To provide to researchers a set of costs for type 2 diabetes complications, originally developed for input into an established diabetes model, that are empirically based, clearly and consistently defined and applicable to a large segment of managed care patients in the US.

METHODS

Patients with 1 of 24 diabetes-related complications between 1 January 2003 and 31 December 2004 and with evidence of type 2 diabetes were identified using a nationally representative US commercial insurance claims database. Therapy utilization and complication cost data were extracted for all patients for the 12 months following the first identified complication; data for months 13-24 were obtained for a subset of patients with at least 24 months of follow-up enrollment. Medical costs included both the amounts charged by medical providers and the health plan contracted allowed amounts. Costs were expressed as $US, year 2007 values.

RESULTS

A total of 44 021 patients with a minimum of 12 months of continuous follow-up enrollment were identified, with a mean age of 56 years; a subset of 32 991 patients with at least 24 months of continuous health-plan enrollment was also identified. Among the aggregate sample, 74% of patients were receiving oral antidiabetics, 26% were receiving insulin, 43% were receiving ACE inhibitors and 50% were receiving antihyperlipidaemics/HMG-CoA reductase inhibitors (statins) during the first 12 months following the index complication. The majority of patients had at least one physician office visit (99.8%), laboratory diagnostic test (96.2%) and other outpatient visit (97.5%). Six complications (angina pectoris, heart failure, peripheral vascular disease, renal disease, nonproliferative retinopathy and neuropathy) had a prevalence of at least 10%. Allowed amounts for most complications were 30-45% of charges. Myocardial infarction, heart failure and renal disease had the greatest fiscal impact because of the total number of patients experiencing them (7.2%, 14.0% and 11.0%, respectively) and their associated costs; 12-month mean allowed amounts were $US 14,853, $US 11,257 and $US 13,876, respectively, and 12-month mean charged amounts were $US 41,695, $US 30, 066 and $US 34,987, respectively. Similarly, in the subset of 32 991 patients, these three complications had higher allowed and charged amounts over months 13-24 compared with the majority of other complications of interest.

CONCLUSION

These costing results provide an important resource for economic modelling and other types of costing research related to treating diabetes-related complications within the US managed care system.

Beta-cell preservation with thiazolidinediones

Progressive beta-cell dysfunction and beta-cell failure are fundamental pathogenic features of type 2 diabetes. Ultimately, the development and continued progression of diabetes is a consequence of the failure of the beta-cell to overcome insulin resistance. Strategies that aim to prevent diabetes must, therefore, ultimately aim to stabilize the progressive decline of the beta-cell. Clinical study evidence from several sources now suggests that thiazolidinediones (TZDs) have profound effects on the beta-cell, such as improving insulin secretory capacity, preserving beta-cell mass and islet structure and protecting beta-cells from oxidative stress, as well as improving measures of beta-cell function, such as insulinogenic index and homeostasis model assessment of beta-cell function (HOMA-%B). Furthermore, intervention studies suggest that TZDs have the potential to delay, stabilize and possibly even prevent the onset on diabetes in high-risk individuals, and these effects appear to accompany improvements in beta-cell function. Here, we review the evidence, from in vitro studies to large intervention trials, for the effects of TZDs on beta-cell function and the consequences for glucose-lowering therapy.