Age at initiation and frequency of screening to detect type 2 diabetes: a cost-effectiveness analysis

A Population-Based Study of Diabetes Incidence by Ethnicity and Age: Support for the Development of Ethnic-Specific Prevention Strategies

OBJECTIVE

Although national guidelines advocate for earlier diabetes screening in high-risk ethnic groups, little evidence exists to guide clinicians on the age at which screening should commence. The purpose of this study was to determine age equivalency thresholds for diabetes risk across a broad range of ethnic populations.

METHODS

This population-based, retrospective cohort study used linked administrative health and immigration records for 592,376 individuals in Ontario, Canada. Adjusted incidence rates by ethnicity, sex and age were used to derive ethnic-specific age thresholds for risk.

RESULTS

Diabetes incidence rates in South Asians reached an equivalent risk as that experienced by a 40-year-old Western European man (3.7 per 1,000 person-years) by 25 years of age. For all other non-European ethnic groups, the equivalent risk was experienced between 30 and 35 years of age. These risk differentials persisted despite controlling for covariates.

CONCLUSIONS

We found a 15-year difference in age equivalency of risk across ethnic groups.

Evaluation of the Diabetes Screening Component of a National Cardiovascular Risk Assessment Programme in England: a Retrospective Cohort Study

Type 2 Diabetes (T2D) is increasing but the effectiveness of large-scale diabetes screening programmes is debated. We assessed associations between coverage of a national cardiovascular and diabetes risk assessment programme in England (NHS Health Check) and detection and management of incident cases of non-diabetic hyperglycaemia (NDH) and T2D. Retrospective analysis employing propensity score covariate adjustment method of prospectively collected data of 348,987 individuals aged 40-74 years and registered with 455 general practices in England (January 2009-May 2016). We examined differences in diagnosis of NDH and T2D, and changes in blood glucose levels and cardiovascular risk score between individuals registered with general practices with different levels (tertiles) of programme coverage. Over the study period 7,126 cases of NDH and 12,171 cases of T2D were detected. Compared with low coverage practices, incidence rate of detection in medium and high coverage practices were 15% and 19% higher for NDH and 10% and 9% higher for T2D, respectively. Individuals with NDH in high coverage practices had 0.2 mmol/L lower mean fasting plasma glucose and 0.9% lower cardiovascular risk score at follow-up. General practices actively participating in the programme had higher detection of NDH and T2D and improved management of blood glucose and cardiovascular risk factors.

2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2020

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee (https://doi.org/10.2337/dc20-SPPC), a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc20-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Type 2 Diabetes

Type 2 diabetes is a prevalent illness that causes major vascular, renal, and neurologic complications. Prevention and treatment of diabetes and its complications are of paramount importance. Many new treatments have emerged over the past 5-10 years. Recent evidence shows that newer treatments may substantially reduce risk for cardiac and renal disease, suggesting that it may be necessary to change existing treatment paradigms. This review summarizes the evidence supporting diabetes prevention and treatment, focusing on aspects that are commonly in the purview of primary care physicians.

Metabolic syndrome and pre-eclampsia

OBJECTIVE

To evaluate the association between different pre-eclampsia (PE) phenotypes and the development of metabolic syndrome postpartum, in order to identify the subgroup of formerly pre-eclamptic women with a worse cardiovascular risk profile requiring tailored postpartum follow-up.

METHODS

This was a cohort study of 1102 formerly pre-eclamptic women in whom cardiovascular and cardiometabolic evaluation was performed at least 3 months postpartum. Women were divided into four subgroups based on PE resulting in delivery before 34 weeks (early-onset (EO)) or at or after 34 weeks (late onset (LO)) of gestation and whether they delivered a small-for-gestational-age (SGA) neonate. Metabolic syndrome was diagnosed as the presence of hyperinsulinemia along with two or more of: body mass index ≥ 30 kg/m² ; dyslipidemia; hypertension; and microalbuminuria or proteinuria. Data were compared between groups using ANOVA after Bonferroni correction. Odds ratios (OR) were calculated using logistic regression to determine the association between metabolic syndrome and the four subgroups. We constructed receiver-operating characteristics curves and computed the area under the curve (AUC) to quantify the ability of different obstetric variables to distinguish between women who developed metabolic syndrome and those who did not.

RESULTS

The prevalence of metabolic syndrome was higher in women with EO-PE and SGA (25.8%) than in those with EO-PE without SGA (14.7%) (OR 2.01 (95% CI, 1.34-3.03)) and approximately five-fold higher than in women with LO-PE with SGA (5.6%) (OR 5.85 (95% CI, 2.60-13.10)). In women with LO-PE, the prevalence of metabolic syndrome did not differ significantly between women with and those without SGA. Multivariate analysis revealed that a history of SGA, a history of EO-PE and systolic blood pressure at the time of screening are the best predictors of developing metabolic syndrome postpartum. The AUC of the model combining these three variables was 74.6% (95% CI, 70.7-78.5%). The probability of the presence of metabolic syndrome was calculated as: P = 1/(1 + e^-LP ), where LP is linear predictor = -8.693 + (0.312 × SGA (yes = 1)) + (0.507 × EO-PE (yes = 1)) + (0.053 × systolic blood pressure).

CONCLUSIONS

The incidence of metabolic syndrome postpartum was associated more strongly with EO-PE in combination with SGA as compared with LO-PE or EO-PE without SGA. Both time of onset of PE and fetal growth affect the risk of metabolic syndrome after a pre-eclamptic pregnancy. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.

A Markov decision process for modeling adverse drug reactions in medication treatment of type 2 diabetes

Type 2 diabetes has an increasing prevalence and high cost of treatment. The goal of type 2 diabetes treatment is to control patients' blood glucose level by pharmacological interventions and to prevent adverse disease-related complications. Therefore, it is important to optimize the medication treatment plans for type 2 diabetes patients to enhance the quality of their lives and to decrease the economic burden of this chronic disease. Since the treatment of type 2 diabetes relies on medication, it is vital to consider adverse drug reactions. Adverse drug reaction is undesired harmful reactions that may result from some certain medications. Therefore, a Markov decision process is developed in this article to model the medication treatment of type 2 diabetes, considering the possibility of adverse drug reaction occurring adverse drug reaction. The optimal policy of the proposed Markov decision process model is compared with clinical guidelines and existing models in the literature. Moreover, a sensitivity analysis is conducted to address the manner in which model behavior depends on model parameterization and then therapeutic insights are obtained based on the results. The satisfying results show that the model has the capability to offer an optimal treatment policy with an acceptable expected quality of life by utilizing fewer medications and provide significant implications in endocrinology and metabolism applications.

Development and Validation of PREDICT-DM: A New Microsimulation Model to Project and Evaluate Complications and Treatments of Type 2 Diabetes Mellitus

Background: Type 2 diabetes mellitus (T2DM) affects ∼30 million people in the United States and ∼400 million people worldwide, numbers likely to increase due to the rising prevalence of obesity. We sought to design, develop, and validate PREDICT-DM (PRojection and Evaluation of Disease Interventions, Complications, and Treatments-Diabetes Mellitus), a state-transition microsimulation model of T2DM, incorporating recent data. Methods: PREDICT-DM is populated with natural history, risk factor, and outcome data from large-scale cohort studies and randomized clinical trials. The model projects diabetes-relevant outcomes, including cardiovascular and renal disease outcomes, and 5/10-year survival. We assessed the model validity against 62 endpoints from ACCORD (Action to Control Cardiovascular Risk in Diabetes), VADT (Veterans Affairs Diabetes Trial), and Look AHEAD trials via several comparative statistical methods, including mean absolute percentage error (MAPE), Bland-Altman graphs, and Kaplan-Meier curves. Results: For the comparison between simulated and observed outcomes of the intervention/control arms of the trial, the MAPE was 19%/25% (ACCORD), 29%/20% (VADT), and 42%/10% (Look AHEAD). The Bland-Altman's 95% limit of agreement was 0.02 (ACCORD), 0.03 (VADT), and 0.01 (Look AHEAD), and the mean difference (95% confidence interval) for the comparison between PREDICT-DM and trial endpoints was 0.0025 (-0.0018 to 0.0070) for ACCORD, -0.0067 (-0.0137 to 0.0002) for VADT, and -0.0033 (-0.0067 to 0.00002) for Look AHEAD, indicating an adequate model fit to the data. The model-driven Kaplan-Meier curves were similarly close to those previously published. Conclusions: PREDICT-DM can reasonably predict clinical outcomes from ACCORD and other clinical trials of U.S. patients with T2DM. This model may be leveraged to inform clinical strategy questions related to the management and care of T2DM in the United States.

Variation in health system performance for managing diabetes among states in India: a cross-sectional study of individuals aged 15 to 49 years

BACKGROUND

Understanding where adults with diabetes in India are lost in the diabetes care cascade is essential for the design of targeted health interventions and to monitor progress in health system performance for managing diabetes over time. This study aimed to determine (i) the proportion of adults with diabetes in India who have reached each step of the care cascade and (ii) the variation of these cascade indicators among states and socio-demographic groups.

METHODS

We used data from a population-based household survey carried out in 2015 and 2016 among women and men aged 15-49 years in all states of India. Diabetes was defined as a random blood glucose (RBG) ≥ 200 mg/dL or reporting to have diabetes. The care cascade-constructed among those with diabetes-consisted of the proportion who (i) reported having diabetes ("aware"), (ii) had sought treatment ("treated"), and (iii) had sought treatment and had a RBG < 200 mg/dL ("controlled"). The care cascade was disaggregated by state, rural-urban location, age, sex, household wealth quintile, education, and marital status.

RESULTS

This analysis included 729,829 participants. Among those with diabetes (19,453 participants), 52.5% (95% CI, 50.6-54.4%) were "aware", 40.5% (95% CI, 38.6-42.3%) "treated", and 24.8% (95% CI, 23.1-26.4%) "controlled". Living in a rural area, male sex, less household wealth, and lower education were associated with worse care cascade indicators. Adults with untreated diabetes constituted the highest percentage of the adult population (irrespective of diabetes status) aged 15 to 49 years in Goa (4.2%; 95% CI, 3.2-5.2%) and Tamil Nadu (3.8%; 95% CI, 3.4-4.1%). The highest absolute number of adults with untreated diabetes lived in Tamil Nadu (1,670,035; 95% CI, 1,519,130-1,812,278) and Uttar Pradesh (1,506,638; 95% CI, 1,419,466-1,589,832).

CONCLUSIONS

There are large losses to diabetes care at each step of the care cascade in India, with the greatest loss occurring at the awareness stage. While health system performance for managing diabetes varies greatly among India's states, improvements are particularly needed for rural areas, those with less household wealth and education, and men. Although such improvements will likely have the greatest benefits for population health in Goa and Tamil Nadu, large states with a low diabetes prevalence but a high absolute number of adults with untreated diabetes, such as Uttar Pradesh, should not be neglected.

2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2019

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

A Simple Model for Predicting Two-Year Risk of Diabetes Development in Individuals with Prediabetes

CONTEXT

Given the dramatic rise in the incidence of type 2 diabetes mellitus (T2DM) in recent decades, identifying individuals at increased risk of T2DM and validating methods to reduce their risk of disease progression is important. With more than one-third of US adults having prediabetes, a more precise stratification of absolute risk of T2DM incidence would help in prioritizing prevention efforts.

OBJECTIVE

To develop a simple and clinically useful schema to stratify short-term (2-year) absolute risk of T2DM.

DESIGN

Observational study of more than 77,000 adult members (age 18-75 years) from 3 Regions of the Kaiser Foundation Health Plan with prediabetes (hemoglobin A_1C [HbA_1C] = 5.7%-6.4%).

MAIN OUTCOME MEASURES

The 2-year probability for development of diabetes as a function of baseline HbA_1C and body mass index (BMI).

RESULTS

The 2-year risk of diabetes diagnosis varied widely by HbA_1C and BMI. A small subset (5.2%) had a very high risk of T2DM developing within 2 years. Another 13.3% had a moderate 2-year risk of T2DM, whereas most (81.5%) of the population was at much lower risk. Thus, most Kaiser Foundation Health Plan members with prediabetes have only modest risk of progression to T2DM within 2 years.

CONCLUSION

Using HbA_1C and BMI, we created a simple stratification scheme to more precisely estimate risk of T2DM incidence. This will enable more efficient assignment of prevention interventions and clinical and laboratory follow-up to the small subset at highest risk, while minimizing the potentially negative effects of overdiagnosis among the majority with prediabetes who are not at high short-term risk of T2DM.

Descriptive analysis of pharmacy services provided after community pharmacy screening

Background Community pharmacies are promising locations for opportunistic screening due to pharmacist accessibility and ability to perform various health and medication management services. Little is known as to the provision of pharmacy services following screening initiatives. Objective To describe provision of pharmacy services for participants following a community pharmacy stroke screening initiative. Setting The Program for the Identification of "Actionable Atrial" Fibrillation Pharmacy initiative took place in 30 pharmacies in Alberta and Ontario, Canada. 1149 participants ≥ 65 were screened for atrial fibrillation, type 2 diabetes, and hypertension. Method Retrospective, secondary analysis of data using participant case-report forms, pharmacy data, and pharmacy claims to describe pharmacy services received by participants post-screening. Main Outcome Measure Number and types of remunerated pharmacy services received by participants post-screening. Results A total of 535/1149 (46.6%) participants screened at their regular pharmacy were included in this analysis. Of these, 165 (30.8%) participants received 229 pharmacy services within 3 months post-screening, including 146 medication reviews, 57 influenza vaccinations, and 21 pharmaceutical opinions. A median (interquartile range, IQR) of 6 (2-11) pharmacy services were delivered, and median (IQR) reimbursement was $187.50 ($67.50-$342.50). Conclusions Approximately one-third of participants received a pharmacy service within 3 months post-screening. Relatively large numbers of annual and follow-up medication reviews were delivered despite low eligibility for annual-only reviews and despite many missed opportunities for pharmacy service provision in at-risk patients. In-pharmacy screening may facilitate provision of some services, namely medication reviews, by providing opportunities to identify patients at-risk.

Changing the housing environment to reduce obesity in public housing residents: a cluster randomized trial

BACKGROUND

Public housing residents face significant social, economic, and physical barriers to the practice of health behaviors for prevention of chronic disease. Research shows that public housing residents are more likely to report higher rates of obesity, current smoking, disability, and insufficient physical activity compared to individuals not living in public housing. Because these behaviors and conditions may be shaped by the built and social environments in which they live, we conducted a study to test an environmental level diet and physical activity intervention targeting obesity among urban public housing developments.

METHODS

This study was a cluster randomized controlled trial of public housing developments, the unit of analysis and randomization. A total of 10 public housing developments were recruited and subsequently randomized to either receive the intervention package or to serve as comparison sites. The year-long intervention included components to change the dietary and physical activity-related environments of the developments. Surveys at baseline and one-year follow-up provided data on changes in behaviors and weight from participants in both intervention and control developments.

RESULTS

Intervention participants significantly changed their eating and activity behaviors and body weight from baseline to one-year follow-up (p's < .05) while comparison participants reported no significant changes in any study variable.

CONCLUSIONS

These data provide initial support for the idea that interventions targeting the environment of public housing developments can assist residents to change unhealthy behaviors and can possibly reduce the high levels of chronic disease among public housing residents.

A systematic review of economic evaluations of screening programmes for cardiometabolic diseases

Background

The early detection and adequate management of cardiometabolic diseases (CMD) is becoming a priority to prevent future health problems and related healthcare costs.

Aim

This study systematically reviewed the economic evaluations of screening programmes for the early detection of persons at risk for CMD.

Methods

A systematic review was conducted using MEDLINE, Web of Science, NHSEED and the CEA registry to identify relevant articles published between 1 January 2005 and 1 May 2015. Two reviewers independently selected articles, systematically extracted data and critically appraised the study quality using the Extended Consensus on Health Economic Criteria (CHEC) List.

Results

From the initial 2820 studies identified, 17 were included. Six studies assessed whether screening would be cost-effective, seven aimed to determine the most efficient screening programme and four assessed the cost-effectiveness of existing programmes. There were 11 cost-utility analyses using quality-adjusted life years (QALYs) or disability-adjusted life years. Decision-analytic modelling (e.g. Markov model) was most frequently used (n = 10), followed by simulation models (n = 4), observational (n = 2) and trial-based (n = 1) studies. All studies assessing the cost per QALY gained of screening for cardiovascular diseases and diabetes mellitus (n = 8) were below a threshold of £30 000, while those assessing chronic kidney diseases (n = 2) were above the threshold. Conclusions: In view of the heterogeneity in study objectives, country setting, screening programmes, comparators, methodology and outcomes, it is not possible to make clear recommendations about the economic value of screening programmes for CMD. Developing further screening programmes and conducting thorough economic analysis, including usual care, is needed.

Effect of screening for type 2 diabetes on healthcare costs: a register-based study among 139,075 individuals diagnosed with diabetes in Denmark between 2001 and 2009

AIMS/HYPOTHESIS

Trials have not demonstrated benefits to the population of screening for type 2 diabetes. However, there may be cost savings for those found to have diabetes. We therefore aimed to compare healthcare costs among individuals with incident type 2 diabetes in a screened group with those in an unscreened group.

METHODS

In this register-based, non-randomised controlled trial, eligible individuals were men and women aged 40-69 years without known diabetes who were registered with a general practice in Denmark (n = 1,912,392). Between 2001 and 2006, 153,107 individuals registered with 181 practices participating in the Anglo-Danish-Dutch Study of Intensive Treatment in People with Screen Detected Diabetes in Primary Care (ADDITION)-Denmark study were sent a diabetes risk-score questionnaire. Individuals with a moderate-to-high risk were invited to visit their family doctor for assessment of diabetes status and cardiovascular risk (screening group). The 1,759,285 individuals registered with all other practices in Denmark constituted the retrospectively constructed no-screening (control) group. In this post hoc analysis, we identified individuals from the screening and no-screening groups who were diagnosed with diabetes between 2001 and 2009 (n = 139,075). Using national registry data, we quantified the cost of healthcare services in these two groups between 2001 and 2012. From a healthcare sector perspective, we estimated the potential healthcare cost savings for individuals with diabetes that were attributable to the screening programme.

RESULTS

In the screening group, 27,177 of 153,107 individuals (18% of those sent a risk-score questionnaire) attended for screening, 1533 of whom were diagnosed with diabetes. Between 2001 and 2009, 13,992 people were newly diagnosed with diabetes in the screening group (including those diagnosed by screening) and 125,083 in the no-screening group. Healthcare costs were significantly lower in the screening group compared with the no-screening group (difference in mean total annual healthcare costs -€889 per individual with incident diabetes; 95% CI -€1196, -€581). The screening programme was associated with a cost saving per person with incident diabetes over a 5-year period of €2688 (95% CI €1421, €3995).

CONCLUSIONS/INTERPRETATION

Healthcare costs were lower among individuals with incident type 2 diabetes in the screened group compared with the unscreened group. The relatively modest cost of screening per person discovered to have developed diabetes was offset within 2 years by savings in the healthcare system.

Prediabetes and Cardiovascular Disease: Pathophysiology and Interventions for Prevention and Risk Reduction

Prediabetes is a state characterized by impaired fasting glucose or impaired glucose tolerance. This review discusses the pathophysiology and macrovascular complications of prediabetes. The pathophysiologic defects underlying prediabetes include insulin resistance, alpha- and beta-cell dysfunction, increased lipolysis, inflammation, and suboptimal incretin effect. Recent studies have revealed that the long-term complications of diabetes manifest in some people with prediabetes; these complications include microvascular and macrovascular disorders. Finally, we present an overview of randomized control trials aimed at preventing progression from prediabetes to type 2 diabetes and discuss their implications for macrovascular risk reduction.

2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2018

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Determining the optimal screening interval for type 2 diabetes mellitus using a risk prediction model

Background

Progression to diabetes mellitus (DM) is variable and the screening time interval not well defined. The American Diabetes Association and US Preventive Services Task Force suggest screening every 3 years, but evidence is limited.

The objective of the study was to develop a model to predict the probability of developing DM and suggest a risk-based screening interval.

Methods

We included non-diabetic adult patients screened for DM in the Cleveland Clinic Health System if they had at least two measurements of glycated hemoglobin (HbA1c), an initial one less than 6.5% (48 mmol/mol) in 2008, and another between January, 2009 and December, 2013. Cox proportional hazards models were created.

The primary outcome was DM defined as HbA1C greater than 6.4% (46 mmol/mol). The optimal rescreening interval was chosen based on the predicted probability of developing DM.

Results

Of 5084 participants, 100 (4.4%) of the 2281 patients with normal HbA1c and 772 (27.5%) of the 2803 patients with prediabetes developed DM within 5 years. Factors associated with developing DM included HbA1c (HR per 0.1 units increase 1.20; 95%CI, 1.13–1.27), family history (HR 1.31; 95%CI, 1.13–1.51), smoking (HR 1.18; 95%CI, 1.03–1.35), triglycerides (HR 1.01; 95%CI, 1.00–1.03), alanine aminotransferase (HR 1.07; 95%CI, 1.03–1.11), body mass index (HR 1.06; 95%CI, 1.01–1.11), age (HR 0.95; 95%CI, 0.91–0.99) and high-density lipoproteins (HR 0.93; 95% CI, 0.90–0.95). Five percent of patients in the highest risk tertile developed DM within 8 months, while it took 35 months for 5% of the middle tertile to develop DM. Only 2.4% percent of the patients in the lowest tertile developed DM within 5 years.

Conclusion

A risk prediction model employing commonly available data can be used to guide screening intervals. Based on equal intervals for equal risk, patients in the highest risk category could be rescreened after 8 months, while those in the intermediate and lowest risk categories could be rescreened after 3 and 5 years respectively.

Variation in Point-of-Care Testing of HbA1c in Diabetes Care in General Practice

Background: Point-of-care testing (POCT) of HbA1c may result in improved diabetic control, better patient outcomes, and enhanced clinical efficiency with fewer patient visits and subsequent reductions in costs. In 2008, the Danish regulators created a framework agreement regarding a new fee-for-service fee for the remuneration of POCT of HbA1c in general practice. According to secondary research, only the Capital Region of Denmark has allowed GPs to use this new incentive for POCT. The aim of this study is to use patient data to characterize patients with diabetes who have received POCT of HbA1c and analyze the variation in the use of POCT of HbA1c among patients with diabetes in Danish general practice. Methods: We use register data from the Danish Drug Register, the Danish Health Service Register and the National Patient Register from the year 2011 to define a population of 44,981 patients with diabetes (type 1 and type 2 but not patients with gestational diabetes) from the Capital Region. The POCT fee is used to measure the amount of POCT of HbA1c among patients with diabetes. Next, we apply descriptive statistics and multilevel logistic regression to analyze variation in the prevalence of POCT at the patient and clinic level. We include patient characteristics such as gender, age, socioeconomic markers, health care utilization, case mix markers, and municipality classifications. Results: The proportion of patients who received POCT was 14.1% and the proportion of clinics which were “POCT clinics” was 26.9%. There were variations in the use of POCT across clinics and patients. A part of the described variation can be explained by patient characteristics. Male gender, age differences (older age), short education, and other ethnicity imply significantly higher odds for POCT. High patient costs in general practice and other parts of primary care also imply higher odds for POCT. In contrast, high patient costs for drugs and/or morbidity in terms of the Charlson Comorbidity index mean lower odds for POCT. The frequency of patients with diabetes per 1000 patients was larger in POCT clinics than Non-POCT clinics. A total of 22.5% of the unexplained variability was related to GP clinics. Conclusions: This study demonstrates variation in the use of POCT which can be explained by patient characteristics such as demographic, socioeconomic, and case mix markers. However, it appears relevant to reassess the system for POCT. Further studies are warranted in order to assess the impacts of POCT of HbA1c on health care outcomes.

Effect of screening for type 2 diabetes on risk of cardiovascular disease and mortality: a controlled trial among 139,075 individuals diagnosed with diabetes in Denmark between 2001 and 2009

AIMS/HYPOTHESIS

There is continuing debate about the net benefits of population screening for type 2 diabetes. We compared the risk of cardiovascular disease (CVD) and mortality among incident cases of type 2 diabetes in a screened group with those in an unscreened group.

METHODS

In this register-based non-randomised controlled trial, eligible individuals were all men and women aged 40-69 years without known diabetes, registered with a general practice in Denmark (n = 1,912,392). Between 2001 and 2006, 153,107 individuals registered with 181 practices participating in the Anglo-Danish-Dutch Study of Intensive Treatment in People with Screen-Detected Diabetes in Primary Care (ADDITION)-Denmark study were sent a diabetes-risk-score questionnaire. Individuals at moderate-to-high risk were invited to visit their family doctor for assessment of diabetes status and cardiovascular risk (screening group). The 1,759,285 individuals registered with all other practices in Denmark constituted the retrospectively constructed no-screening (control) group. In this post hoc analysis, we identified individuals from the screening and no-screening groups who were diagnosed with diabetes between 2001 and 2009 (n = 139,075), and compared risk of CVD and mortality in these groups between 2001 and 2012.

RESULTS

In the screening group, 27,177/153,107 (18%) individuals attended for screening, of whom 1533 were diagnosed with diabetes. Between 2001 and 2009, 13,992 people were newly diagnosed with diabetes in the screening group (including those diagnosed by screening) and 125,083 in the no-screening group. Between 2001 and 2012, the risks of CVD and mortality were lower among individuals with diabetes in the screening group compared with individuals with diabetes in the no-screening (control) group (CVD HR 0.84, 95% CI 0.80, 0.89; mortality HR 0.79, 95% CI 0.74, 0.84).

CONCLUSIONS/INTERPRETATION

A single round of diabetes screening and cardiovascular risk assessment in middle-aged Danish adults in general practice was associated with a significant reduction in risk of all-cause mortality and CVD events in those diagnosed with diabetes.

Effect of population screening for type 2 diabetes and cardiovascular risk factors on mortality rate and cardiovascular events: a controlled trial among 1,912,392 Danish adults

AIMS/HYPOTHESIS

Health check programmes for chronic disease have been introduced in a number of countries. However, there are few trials assessing the benefits and harms of these screening programmes at the population level. In a post hoc analysis, we evaluated the effect of population-based screening for type 2 diabetes and cardiovascular risk factors on mortality rates and cardiovascular events.

METHODS

This register-based, non-randomised, controlled trial included men and women aged 40-69 years without known diabetes who were registered with a general practice in Denmark (n = 1,912,392). Between 2001 and 2006, 153,107 individuals registered with 181 practices participating in the Anglo-Danish-Dutch Study of Intensive Treatment in People with Screen-Detected Diabetes in Primary Care (ADDITION)-Denmark study were sent a diabetes risk score questionnaire. Individuals at moderate-to-high risk were invited to visit their GP for assessment of diabetes status and cardiovascular risk (screening group). The 1,759,285 individuals registered with all other general practices in Denmark constituted the retrospectively constructed no-screening (control) group. Outcomes were mortality rate and cardiovascular events (cardiovascular disease death, non-fatal ischaemic heart disease or stroke). The analysis was performed according to the intention-to-screen principle.

RESULTS

Among the screening group, 27,177 (18%) individuals attended for assessment of diabetes status and cardiovascular risk. Of these, 1,533 were diagnosed with diabetes. During a median follow-up of 9.5 years, there were 11,826 deaths in the screening group and 141,719 in the no-screening group (HR 0.99 [95% CI 0.96, 1.02], p = 0.66). There were 17,941 cardiovascular events in the screening group and 208,476 in the no-screening group (HR 0.99 [0.96, 1.02], p = 0.49).

CONCLUSIONS/INTERPRETATION

A population-based stepwise screening programme for type 2 diabetes and cardiovascular risk factors among all middle-aged adults in Denmark was not associated with a reduction in rate of mortality or cardiovascular events between 2001 and 2012.

Estimating Disease Onset Time by Modeling Lab Result Trajectories via Bayes Networks

The true onset time of a disease, particularly slow-onset diseases like Type 2 diabetes mellitus (T2DM), is rarely observable in electronic health records (EHRs). However, it is critical for analysis of time to events and for studying sequences of diseases. The aim of this study is to demonstrate a method for estimating the onset time of such diseases from intermittently observable laboratory results in the specific context of T2DM. A retrospective observational study design is used. A cohort of 5,874 non-diabetic patients from a large healthcare system in the Upper Midwest United States was constructed with a three-year follow-up period. The HbA1c level of each patient was collected from earliest and the latest follow-up. We modeled the patients' HbA1c trajectories through Bayesian networks to estimate the onset time of diabetes. Due to non-random censoring and interventions unobservable from EHR data (such as lifestyle changes), naïve modeling of HbA1c through linear regression or modeling time-to-event through proportional hazard model leads to a clinically infeasible model with no or limited ability to predict the onset time of diabetes. Our model is consistent with clinical knowledge and estimated the onset of diabetes with less than a six-month error for almost half the patients for whom the onset time could be clinically ascertained. To our knowledge, this is the first study of modeling long-term HbA1c progression in non-diabetic patients and estimating the onset time of diabetes.

Delays in treatment intensification with oral antidiabetic drugs and risk of microvascular and macrovascular events in patients with poor glycaemic control: An individual patient simulation study

AIMS

To use the Archimedes model to estimate the consequences of delays in oral antidiabetic drug (OAD) treatment intensification on glycaemic control and long-term outcomes at 5 and 20 years.

MATERIALS AND METHODS

Using real-world data, we modelled a cohort of hypothetical patients with glycated haemoglobin (HbA1c) ≥8%, on metformin, with no history of insulin use. The cohort included 3 strata based on the number of OADs taken at baseline. The first add-on in the intensification sequence was a sulphonylurea, next was a dipeptidyl peptidase-4 inhibitor, and last, a thiazolidinedione. The scenarios included either no delay or delay, based on observed and extrapolated times to intensification.

RESULTS

At 1 year, HbA1c was 6.8% for patients intensifying without delay, and 8.2% for those delaying intensification. For no delay vs delay, risks of major adverse cardiac events, myocardial infarction, heart failure and amputations were reduced by 18.0%, 25.0%, 13.7%, and 20.4%, respectively, at 5 years; severe hypoglycaemia risk, however, increased to 19% for the no delay scenario vs 12.5% for delay. At 20 years, the results showed similar trends to those at 5 years.

CONCLUSIONS

Timing of intensification of OAD therapy according to guideline recommendations led to greater reductions in HbA1c and lower risks of complications, but higher risks of hypoglycaemia than delaying intensification. These results highlight the potential impact of timely treatment intensification on long-term outcomes.

Point-of-care testing improves diabetes management in a primary care clinic in South Africa

INTRODUCTION

Diabetes is a major health problem in South Africa. DiabCare Africa found just 47% of diabetes patients had a hemoglobin A1c (HbA1c) test for their management in the previous year.

METHODS

Patients attending an urban diabetes clinic near Johannesburg, run by Project HOPE, accessed HbA1c (and urine albumin:creatinine ratio) point-of-care testing (POCT) as part of a quality-assured international program called ACE (Analytical and Clinical Excellence). Patients who had two or more HbA1c POC tests from 2012 to 2014 were assessed to determine their change in glycaemic control.

RESULTS

The mean (±SD) HbA1c in this group of diabetes patients (n=131) fell significantly from 9.7%±2.4 (83mmol/mol) at their first POCT measurement to 8.4%±2.4 (68mmol/mmol/mol) at their most recent POCT measurement (paired t-test p<0.01). The average time between first and most recent HbA1c test was 15 months. The number of diabetes patients achieving optimal glycaemic control (HbA1c≤6.5-7.5% [48-58mmol/mol) increased by 125%, while the number with very poor glycaemic control (HbA1c>10% [86mmol/mol]) halved. An association was observed between degree of glycaemic control and increasing albuminuria in this cohort.

DISCUSSION

POCT has promoted change in clinical practice by facilitating greater accessibility to HbA1c testing.

Cardiovascular risk factors and incident albuminuria in screen-detected type 2 diabetes

BACKGROUND

It is unclear whether cardiovascular risk factor modification influences the development of renal disease in people with type 2 diabetes identified through screening. We determined predictors of albuminuria 5 years after a diagnosis of screen-detected diabetes within the ADDITION-Europe study, a pragmatic cardiovascular outcome trial of multifactorial cardiovascular risk management.

METHODS

In 1826 participants with newly diagnosed, screen-detected diabetes without albuminuria, we explored associations between risk of new albuminuria (≥2.5 mg mmol-1 for males and ≥3.5 mg mmol-1 for females) and (1) baseline cardio-metabolic risk factors and (2) changes from baseline to 1 year in systolic blood pressure (ΔSBP) and glycated haemoglobin (ΔHbA1c ) using logistic regression.

RESULTS

Albuminuria developed in 268 (15%) participants; baseline body mass index and active smoking were independently associated with new onset albuminuria in 5 years after detection of diabetes. In a model adjusted for age, gender, baseline HbA1c and blood pressure, a 1% decrease in HbA1c and 5-mm Hg decrease in SBP during the first year were independently associated with lower risks of albuminuria (odds ratio), 95% confidence interval: 0.76, 0.62 to 0.91 and 0.94, 0.88 to 1.01, respectively. Further adjustment did not materially change these estimates. There was no interaction between ΔSBP and ΔHbA1c in relation to albuminuria risk, suggesting likely additive effects on renal microvascular disease.

CONCLUSIONS

Baseline measurements and changes in HbA1c and SBP a year after diagnosis of diabetes through screening independently associate with new onset albuminuria 4 years later. Established multifactorial treatment for diabetes applies to cases identified through screening.

How to improve opportunistic screening by using EMRs and other data. The prevalence of undetected diabetes mellitus in target population in Croatia

OBJECTIVES

Opportunistic screening for type 2 diabetes (T2D) has not been adopted as part of routine practice. The aim of the study was to investigate the yield of opportunistic target screening for T2D in Croatia and to evaluate the process of screening by using data from electronic medical record.

STUDY DESIGN

We conducted opportunistic screening in 23 general practitioners (GPs) in a population of 13,344 patients aged 45-70 years.

METHODS

First, after excluding patients with T2D, patients with risk factors for T2D were derived from the electronic medical record and GP's assessment during the preconsultation phase. Second, those with data about normoglycemia in past three years were excluded. Remaining patients started the consultation phase during their usual visit, when they were offered capillary fasting plasma glucose testing in the next consultation.

RESULTS

Prevalence of T2D was 10.9% (new 1.4%). A total of 5568 (46.1%) patients had risks and 2849 (51.2%) had data about normoglycemia in the last three years. Using those data, number needed to invite to screening (NNI) was reduced to half: from 46.1% to 22.5%. One hundred eighty-four patients were screened positive for T2D in two capillary fasting plasma glucose tests (yield 9.8%). Number needed to screen (NNS) in order to detect one T2D was 10.3 patients. Among risks for T2D, overweight was the best predictive factor for undiagnosed T2D (odds ratio [OR]: 2.11, confidence interval [CI]:1.41-3.15, P < .001). Logistic regression showed that in targeted population, overweight patients with a family history in fold were 2.5 times more likely to have T2D (OR: 2.54, CI 1.78-.61, P < .001).

CONCLUSIONS

Total yield in targeted population was 1,4%. By using data about normoglycemia from EMRs, NNI was reduced by half and NNS was 10.3 patients. Our findings suggest the model for improvement in opportunistic screening.

Performance of Indian Diabetes Risk Score (IDRS) as screening tool for diabetes in an urban slum

BACKGROUND

India is diabetic capital of world, with maximum number of diabetic patients. There is large burden of undetected diabetic cases in community. There is increasing risk of diabetes in urban slum, because of illiteracy, lack of awareness, low socioeconomic status and unhealthy life style. Madras Diabetes Research Foundation (MDRF) has developed Indian Diabetes Risk Score (IDRS) to detect undiagnosed Type 2 diabetes. The aim of this article is to study the performance of IDRS as screening tool for undiagnosed cases of Type 2 diabetes and to find the prevalence of undiagnosed Type 2 diabetes in an urban slum.

METHODS

Screening for diabetes was carried out in an urban slum. The sample size was 155 (assumed prevalence of undiagnosed diabetes 9%). IDRS tool comprising of two modifiable (waist circumference, physical activity) and two non-modifiable risk factors (age, family history) for diabetes was used to assess the risk of diabetes anthropometry data was obtained. Conformation of diabetes was done using blood sugar levels on fasting venous sample.

RESULTS

Mean and SD for age of study subjects were 49.68 ± 14.80 years, BMI 26.60 ± 8.51 kg/m2, waist hip ratio (females) 0.87 ± 0.06 cm, waist hip ratio (males) 0.95 ± 0.06 cm, waist circumference (females) 89.99 ± 10.95 cm, waist circumference (males) 89.44 ± 10.9 cm. IDRS predicted the risk of diabetes mellitus with sensitivity of 95.12% and specificity of 28.95% in individuals with score >60.

CONCLUSION

IDRS can be used as an effective tool for screening undiagnosed diabetes in the community.

Cost-effectiveness of diabetes screening initiated through a dental visit

OBJECTIVE

To analyse the cost-effectiveness of a screening programme and follow-up interventions for persons with dysglycemia who are identified during a dental visit.

METHODS

This study is a secondary analysis utilizing data from two relevant publications. Those studies identified persons with dysglycemia who were seen in a dental school clinic for routine dental care and determined compliance with a recommendation to seek medical care. The response site was 59.4%. The Archimedes disease simulation model was utilized to simulate the effect of a weight loss programme for identified subjects on several outcomes.

RESULTS

Two scenarios for weight loss programmes were considered: a 10% permanent loss in body weight and a 10% loss that decays over time. Both diabetes and prediabetes were analysed. The decay path costs $21 243 per quality adjusted life year (QALY) with 3 years required to achieve the weight reduction. This cost decreases to $6655 if only 1 year is needed to achieve the weight goal. Without decay, the cost per QALY is $15 873 with 20 years of intervention, vs $647 per QALY with 10 years of intervention. For individuals with type 2 diabetes mellitus, the cost per QALY is $48 604 to $56 207 depending on adherence. With the addition of oral medication (a sulfonylurea), the cost is three times higher.

CONCLUSIONS

Under the conditions described here, identification of persons with dysglycemia in the dental office for initiating prediabetic care is a cost-effective means of identifying and treating affected individuals.

Systematic literature review of the health economic implications of early detection by screening populations at risk for type 2 diabetes

BACKGROUND

Undetected/uncontrolled diabetes is associated with substantial morbidity and mortality and consequent costs. Early detection through screening identifies patients at risk, allowing for earlier treatment initiation.

OBJECTIVES

To determine the economic impact of screening for type 2 diabetes (T2DM).

DATA SOURCES

We systematically reviewed health economic analyses of screening programs for T2DM/pre-diabetes.

STUDY ELIGIBILITY CRITERIA

Published between 2000 and 2015 in any language. Articles must have reported costs of screening, test/patient outcomes and cost-effectiveness.

PARTICIPANTS AND INTERVENTIONS

Any type of screening (universal, targeted, opportunistic) was accepted.

METHODS

Data were extracted from Scopus/Medline/Embase, then tabulated.

RESULTS

There were 137 studies identified, 108 rejected; 29 were analyzed. Screening types included 18 universal, 8 targeted and 8 opportunistic. One study screened for pre-diabetes, 16 for T2DM and 12 examined both. Fourteen (48%) reported costs of screening only, 9 (31%) costs of screening combined with interventions and 6 (21%) presented all costs separately. Screening was compared to no screening in 13 studies (45%); screening was cost-effective in 8 (62%), not cost-effective in 4 (31%) and neither in 1 (8%). When comparing different screening methods, 6 found targeted screening was cost-effective compared with universal screening (none found the opposite), 2 found opportunistic superior to universal. Sensitivity analyses generally confirmed primary findings. Cost drivers included prevalence of T2DM/pre-diabetes, type of blood test used and uptake of testing. For optimal cost-effectiveness, screening for both T2DM and pre-diabetes should be initiated around age 45-50, with repeated testing every 5 years.

CONCLUSIONS/IMPLICATIONS

Targeted screening appears to be cost-effective compared to universal screening.

Use of Biomarkers in Predicting the Onset, Monitoring the Progression, and Risk Stratification for Patients with Type 2 Diabetes Mellitus

BACKGROUND

As the worldwide prevalence of type 2 diabetes mellitus (T2DM) increases, it is even more important to develop cost-effective methods to predict and diagnose the onset of diabetes, monitor progression, and risk stratify patients in terms of subsequent cardiovascular and diabetes complications.

CONTENT

Nonlaboratory clinical risk scores based on risk factors and anthropomorphic data can help identify patients at greatest risk of developing diabetes, but glycemic indices (hemoglobin A1c, fasting plasma glucose, and oral glucose tolerance tests) are the cornerstones for diagnosis, and the basis for monitoring therapy. Although family history is a strong predictor of T2DM, only small populations of patients carry clearly identifiable genetic mutations. Better modalities for detection of insulin resistance would improve earlier identification of dysglycemia and guide effective therapy based on therapeutic mechanisms of action, but improved standardization of insulin assays will be required. Although clinical risk models can stratify patients for subsequent cardiovascular risk, the addition of cardiac biomarkers, in particular, high-sensitivity troponin and natriuretic peptide provide, significantly improves model performance and risk stratification.

CONCLUSIONS

Much more research, prospectively planned and with clear treatment implications, is needed to define novel biomarkers that better identify the underlying pathogenic etiologies of dysglycemia. When compared with traditional risk features, biomarkers provide greater discrimination of future risk, and the integration of cardiac biomarkers should be considered part of standard risk stratification in patients with T2DM.

Cost-Effectiveness of Behavior Activation Versus Supportive Therapy on Adherence to Eye Exams in Older African Americans With Diabetes

Although the importance of ophthalmologic screening in diabetic patients is widely recognized by clinicians, the cost-effectiveness of strategies aimed at improving eye care utilization in this population is not well established. A cost-effectiveness analysis was performed comparing behavior activation (BA) to supportive therapy (ST) in activating patients to receive a dilated fundus exam (DFE) and promoting healthy management of diabetes. Two hundred six subjects were randomized to receive either BA or ST between 2009 and 2013. Cost-effectiveness was calculated as incremental cost-effectiveness ratio (ICER) of BA versus ST. Total costs for BA and ST per participant were $259.02 and $216.12, respectively. At the 6-month follow-up, 87.91% of BA subjects received a DFE compared to 34.48% of ST subjects. The ICER for BA versus ST was $80.29/percent increase in DFE rate. In terms of improving DFE rates, BA was found to be more cost-effective than ST.

Diabetes screening intervals based on risk stratification

BACKGROUND

Guidelines for frequency of Type 2 diabetes mellitus (DM) screening remain unclear, with proposed screening intervals typically based on expert opinion. This study aims to demonstrate that HbA1c screening intervals may differ substantially when considering individual risk for diabetes.

METHODS

This was a multi-institutional retrospective open cohort study. Data were collected between April 1999 to March 2014 from one urban and one rural cohort in Japan. After categorization by age, we stratified individuals based on cardiovascular disease risk (Framingham 10-year cardiovascular risk score) and body mass index (BMI). We adapted a signal-to-noise method for distinguishing true HbA1c change from measurement error by constructing a linear random effect model to calculate signal and noise of HbA1c. Screening interval for HbA1c was defined as informative when the signal-to-noise ratio exceeded 1.

RESULTS

Among 96,456 healthy adults, 46,284 (48.0%) were male; age (range) and mean HbA1c (SD) were 48 (30-74) years old and 5.4 (0.4)%, respectively. As risk increased among those 30-44 years old, HbA1c screening intervals for detecting Type 2 DM consistently decreased: from 10.5 (BMI <18.5) to 2.4 (BMI > 30) years, and from 8.0 (Framingham Risk Score <10%) to 2.0 (Framingham Risk Score ≥20%) years. This trend was consistent in other age and risk groups as well; among obese 30-44 year olds, we found substantially shorter intervals compared to other groups.

CONCLUSION

HbA1c screening intervals for identification of DM vary substantially by risk factors. Risk stratification should be applied when deciding an optimal HbA1c screening interval in the general population to minimize overdiagnosis and overtreatment.

Risk of Cause-Specific Death in Individuals With Diabetes: A Competing Risks Analysis

OBJECTIVE

Diabetes is a common cause of shortened life expectancy. We aimed to assess the association between diabetes and cause-specific death.

RESEARCH DESIGN AND METHODS

We used the pooled analysis of individual data from 12 Spanish population cohorts with 10-year follow-up. Participants had no previous history of cardiovascular diseases and were 35-79 years old. Diabetes status was self-reported or defined as glycemia >125 mg/dL at baseline. Vital status and causes of death were ascertained by medical records review and linkage with the official death registry. The hazard ratios and cumulative mortality function were assessed with two approaches, with and without competing risks: proportional subdistribution hazard (PSH) and cause-specific hazard (CSH), respectively. Multivariate analyses were fitted for cardiovascular, cancer, and noncardiovascular noncancer deaths.

RESULTS

We included 55,292 individuals (15.6% with diabetes and overall mortality of 9.1%). The adjusted hazard ratios showed that diabetes increased mortality risk: 1) cardiovascular death, CSH = 2.03 (95% CI 1.63-2.52) and PSH = 1.99 (1.60-2.49) in men; and CSH = 2.28 (1.75-2.97) and PSH = 2.23 (1.70-2.91) in women; 2) cancer death, CSH = 1.37 (1.13-1.67) and PSH = 1.35 (1.10-1.65) in men; and CSH = 1.68 (1.29-2.20) and PSH = 1.66 (1.25-2.19) in women; and 3) noncardiovascular noncancer death, CSH = 1.53 (1.23-1.91) and PSH = 1.50 (1.20-1.89) in men; and CSH = 1.89 (1.43-2.48) and PSH = 1.84 (1.39-2.45) in women. In all instances, the cumulative mortality function was significantly higher in individuals with diabetes.

CONCLUSIONS

Diabetes is associated with premature death from cardiovascular disease, cancer, and noncardiovascular noncancer causes. The use of CSH and PSH provides a comprehensive view of mortality dynamics in a population with diabetes.

Cost-effectiveness of a risk-based secondary screening programme of type 2 diabetes

OBJECTIVE

The objective of this study was to develop a long-term economic model for type 2 diabetes to describe the entire spectrum of the disease over a wide range of healthcare programmes. The model evaluates a public health, risk-based screening programme in a country specific setting.

METHODS

The lifespan of persons and important phases of the disease and related interventions are recorded in a Markov model, which first simulates the effect of screening, then replicates important complications of diabetes, follows the progression of individuals through physiological variables and finally calculates outcomes in monetary and naturalistic units.

RESULTS

The introduction of the screening programme nearly doubled the proportion of diagnosed patients at the age of 50 and prolonged life expectancy. Three-yearly screening gained 0.0229 quality adjusted life years for an additional €83 per person compared with no screening and resulted an incremental cost-effectiveness ratio of €3630/quality adjusted life years.

CONCLUSION

From the economic perspective introduction of the 3-yearly screening programme is justifiable and it provides a good value for money. Copyright © 2016 John Wiley & Sons, Ltd.

A randomised trial of the effect and cost-effectiveness of early intensive multifactorial therapy on 5-year cardiovascular outcomes in individuals with screen-detected type 2 diabetes: the Anglo-Danish-Dutch Study of Intensive Treatment in People with Screen-Detected Diabetes in Primary Care (ADDITION-Europe) study

BACKGROUND

Intensive treatment (IT) of cardiovascular risk factors can halve mortality among people with established type 2 diabetes but the effects of treatment earlier in the disease trajectory are uncertain.

OBJECTIVE

To quantify the cost-effectiveness of intensive multifactorial treatment of screen-detected diabetes.

DESIGN

Pragmatic, multicentre, cluster-randomised, parallel-group trial.

SETTING

Three hundred and forty-three general practices in Denmark, the Netherlands, and Cambridge and Leicester, UK.

PARTICIPANTS

Individuals aged 40-69 years with screen-detected diabetes.

INTERVENTIONS

Screening plus routine care (RC) according to national guidelines or IT comprising screening and promotion of target-driven intensive management (medication and promotion of healthy lifestyles) of hyperglycaemia, blood pressure and cholesterol.

MAIN OUTCOME MEASURES

The primary end point was a composite of first cardiovascular event (cardiovascular mortality/morbidity, revascularisation and non-traumatic amputation) during a mean [standard deviation (SD)] follow-up of 5.3 (1.6) years. Secondary end points were (1) all-cause mortality; (2) microvascular outcomes (kidney function, retinopathy and peripheral neuropathy); and (3) patient-reported outcomes (health status, well-being, quality of life, treatment satisfaction). Economic analyses estimated mean costs (UK 2009/10 prices) and quality-adjusted life-years from an NHS perspective. We extrapolated data to 30 years using the UK Prospective Diabetes Study outcomes model [version 1.3; (©) Isis Innovation Ltd 2010; see www.dtu.ox.ac.uk/outcomesmodel (accessed 27 January 2016)].

RESULTS

We included 3055 (RC, n = 1377; IT, n = 1678) of the 3057 recruited patients [mean (SD) age 60.3 (6.9) years] in intention-to-treat analyses. Prescription of glucose-lowering, antihypertensive and lipid-lowering medication increased in both groups, more so in the IT group than in the RC group. There were clinically important improvements in cardiovascular risk factors in both study groups. Modest but statistically significant differences between groups in reduction in glycated haemoglobin (HbA1c) levels, blood pressure and cholesterol favoured the IT group. The incidence of first cardiovascular event [IT 7.2%, 13.5 per 1000 person-years; RC 8.5%, 15.9 per 1000 person-years; hazard ratio 0.83, 95% confidence interval (CI) 0.65 to 1.05] and all-cause mortality (IT 6.2%, 11.6 per 1000 person-years; RC 6.7%, 12.5 per 1000 person-years; hazard ratio 0.91, 95% CI 0.69 to 1.21) did not differ between groups. At 5 years, albuminuria was present in 22.7% and 24.4% of participants in the IT and RC groups, respectively [odds ratio (OR) 0.87, 95% CI 0.72 to 1.07), retinopathy in 10.2% and 12.1%, respectively (OR 0.84, 95% CI 0.64 to 1.10), and neuropathy in 4.9% and 5.9% (OR 0.95, 95% CI 0.68 to 1.34), respectively. The estimated glomerular filtration rate increased between baseline and follow-up in both groups (IT 4.31 ml/minute; RC 6.44 ml/minute). Health status, well-being, diabetes-specific quality of life and treatment satisfaction did not differ between the groups. The intervention cost £981 per patient and was not cost-effective at costs ≥ £631 per patient.

CONCLUSIONS

Compared with RC, IT was associated with modest increases in prescribed treatment, reduced levels of risk factors and non-significant reductions in cardiovascular events, microvascular complications and death over 5 years. IT did not adversely affect patient-reported outcomes. IT was not cost-effective but might be if delivered at a reduced cost. The lower than expected event rate, heterogeneity of intervention delivery between centres and improvements in general practice diabetes care limited the achievable differences in treatment between groups. Further follow-up to assess the legacy effects of early IT is warranted.

TRIAL REGISTRATION

ClinicalTrials.gov NCT00237549.

FUNDING DETAILS

This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 20, No. 64. See the NIHR Journals Library website for further project information.

Determinants of individuals' participation in integrated chronic disease screening in Singapore

BACKGROUND

A large pool of patients with chronic diseases remains undiagnosed globally and in Singapore. We explored factors associated with participation in a health screening exercise, using revealed preference, that is, actual attendance, to understand why people remain undiagnosed with chronic diseases.

METHODS

A cross-sectional, community-based sample of Singapore residents was invited to participate in home interviews, and subsequently to attend centre-based health screening, between 2004 and 2007. Determinants of health screening participation were identified using logistic regression models based on Andersen's Behavioral Model.

RESULTS

Of the 6366 participants who completed health interview, 4092 attended the health screening, while 2274 did not. Older age, Chinese or Indian ethnicity, higher education levels, greater intake of monounsaturated fat, greater transport and leisure-time physical activity were the key predisposing factors associated with greater health screening participation. Greater family cohesion was the key associated enabling factor, while previous diagnosis of dyslipidaemia or musculoskeletal conditions, absence of previously diagnosed diabetes or hypertension and lower perceived physical health were the associated need factors.

CONCLUSIONS

Our study suggests that ethnicity, education, family cohesion, healthy behaviour patterns and perceived physical health status were key determinants of health screening participation. Enhancing the cultural competence of preventive health services may help increase participation of these groups in screening efforts and reduce the proportions of undiagnosed chronic disease in the community.

A novel approach to population-based risk stratification, comprising individualized lifestyle intervention in Danish general practice to prevent chronic diseases: Results from a feasibility study

Early detection of patients at risk seems to be effective for reducing the prevalence of lifestyle-related chronic diseases. We aim to test the feasibility of a novel intervention for early detection of lifestyle-related chronic diseases based on a population-based stratification using a combination of questionnaire and electronic patient record data. The intervention comprises four elements: (1) collection of information on lifestyle risk factors using a short 15-item questionnaire, (2) electronic transfer of questionnaire data to the general practitioners' electronic patient records, (3) identification of patients already diagnosed with a lifestyle-related chronic disease, and (4) risk estimation and stratification of apparently healthy patients using questionnaire and electronic patient record data on validated risk estimation models. We show that it is feasible to implement a novel intervention that identifies and stratifies patients for further examinations in general practice or behaviour change interventions at the municipal level without any additional workload for the general practitioner.

Situation of Diabetes and Related Disease Surveillance in Rural Areas of Jilin Province, Northeast China

Background: Several studies have investigated the prevalence and awareness of diabetes mellitus (DM) in China, but little is known about the situation of DM in the northeastern rural areas. Our present study investigated the prevalence, awareness and associated characteristics of DM in rural areas of Jilin Province, aiming to suggest more efforts for the prevention and control of DM. Methods: A multistage stratified random cluster sampling design was used in this cross-sectional study which took place in 2012. Data were collected by face-to-face interviews and physical examinations. Rao-Scott Chi-square test, t test and multivariate logistic regression analysis were used. Results: The estimated prevalence of DM in rural areas of Jilin province was 7.2%. DM was positively associated with age, Body mass index (BMI), hypotension, dyslipidemia and was high in participants with a family history of diabetes and those who exercise frequently, but low for high education level and married participants. 69.0% participants with DM were aware of their diabetes status, 88.2% of whom received treatment and 34.4% of whom had received treatment controlled their DM status. Conclusions: We observed a high prevalence and low awareness status of DM among the rural residents in Jilin Province, but the rate of effective control in those who have received treatment was considerable. The low rate of disease surveillance should draw health authority’s attention.

Early detection of type 2 diabetes mellitus and screening for retinopathy are associated with reduced prevalence and severity of retinopathy

PURPOSE

To explore whether the prevalence and severity of retinopathy differ in diabetes cohorts diagnosed through screening as compared with conventional health care.

METHODS

A total of 257 diabetes patients, 151 detected through screening and 106 through conventional clinical care, were included. Retinopathy was evaluated by fundus photography. The modified Airlie House adaptation of the Early Treatment Retinopathy Study protocol was used to grade the photographs. Averages of clinically collected fasting blood glucose (FBG), blood pressure and body mass index values were compiled from diabetes diagnosis until the eye examination. Blood chemistry, smoking habits and peripheral neuropathy were assessed at the time of the eye examination.

RESULTS

Among the screening-detected patients, 22% had retinopathy as compared to 51% among those clinically detected (p < 0.0001). In a multivariate analysis, patients with retinopathy were more likely to have increased average FBG (OR 1.42, 95% CI 1.19-1.70 per mmol/l) and peripheral neuropathy (OR 2.75, 95% CI 1.40-5.43), but less likely to have screening-detected diabetes (OR 0.31, 95% CI 0.17-0.57). Similar results were found using increasing severity grade of retinopathy as outcome. The cumulative retinopathy prevalence for the screening-detected diabetes cohort as compared with the clinically diagnosed cohort was significantly lower from 10 years' follow-up and onwards (p = 0.0002).

CONCLUSIONS

Among patients with screening-detected diabetes, the prevalence of retinopathy and increasing severity of retinopathy were significantly lower than among those who had their diabetes diagnosed through conventional care, even when other risk factors for retinopathy such as duration, hyperglycaemia and blood pressure were considered. Early detection of diabetes reduces prediagnostic time spent with hyperglycaemia. In combination with early and regular screening for retinopathy, more effective prevention against retinopathy can be provided.

The Affordable Care Act and Diabetes Diagnosis and Care: Exploring the Potential Impacts

This article reviews available data on the implications of the Affordable Care Act (ACA) for the diagnosis and care of type 2 diabetes. We provide a general overview of the major issues for diabetes diagnosis and care, and describe the policies in the ACA that affect diabetes diagnosis and care. We also estimate that approximately 2.3 million of the 4.6 million people in the USA with undiagnosed diabetes aged 18-64 in 2009-2010 may have gained access to free preventive care under the ACA, which could increase diabetes detection. In addition, we note two factors that may limit the success of the ACA for improving access to diabetes care. First, many states with the highest diabetes prevalence have not expanded Medicaid eligibility, and second, primary care providers may not adequately meet the increase in Medicaid patients because federal funding to increase provider reimbursement for Medicaid visits recently expired. We close by discussing current gaps in the literature and future directions for research on the ACA's impact on diabetes diagnosis, care, and health outcomes.

Mortality and cardiovascular disease outcomes among 740 patients with new-onset Type 2 diabetes detected by screening or clinically diagnosed in general practice

AIM

Screening for Type 2 diabetes among people at high risk is recommended by many organizations. The aim of this study was to analyse all-cause mortality and cardiovascular disease (CVD) outcomes in patients with Type 2 diabetes detected by screening or diagnosed clinically.

METHODS

A diabetes register was established at the primary healthcare centre in Laxå, Sweden beginning in 1972. The register was based on data from clinical records with information on medical treatment and laboratory data, as well as all-cause mortality, CVD, myocardial infarction and stroke events from national registers until 31 December 2013. A total of 740 patients with new-onset Type 2 diabetes were registered between 1972 and 2001. In addition, an opportunistic diabetes-screening programme involving people aged 35-79 years started in 1983 and was repeated onwards in 5-year cycles.

RESULTS

Baseline characteristics showed a significantly higher CVD risk, mainly depending on more prevalent CVD events in the screened compared with the clinically detected group (propensity score 0.59 vs. 0.46, P < 0.0001). After mean follow-up periods of 12.9 and 13.6 years for screening detected vs. clinically detected patients, respectively, hazard ratios were as follows: all-cause mortality, 0.99 (P = 0.89); CVD, 1.17 (P = 0.10); myocardial infarction, 1.08 (P = 0.49); and stroke, 1.03 (P = 0.83).

CONCLUSIONS

No reduction in total mortality or CVD outcomes was found in patients with Type 2 diabetes that was detected by screening compared with those diagnosed clinically.

Determination of Prevalence of Type 2 Diabetes Mellitus by Screening Tests using a Mathematical Formula in Place of Invasive Blood Tests

INTRODUCTION

True prevalence rate of diabetes mellitus in a population can be obtained by using invasive tests but it is practically difficult on large scale.

AIM

To find out the feasibility of mass non-invasive screening test to detect the prevalence of diabetes mellitus in rural population of India with the help of a mathematical formula.

MATERIALS AND METHODS

From population of 18800 residing in two adjacent rural areas of Delhi, a systematic random sample of 1005 adult subjects was screened for diabetes by using urine benedicts test, Canrisk questionnaire, Madras Diabetes Research Foundation-Indian Diabetic Risk Score (MDRF-IDRS) and determined prevalence of diabetes (pA) gauzed by each of these screening tests. Simultaneously, each subject's glycaemic status was confirmed by standard fasting Plasma glucose (FPG) and postprandial plasma glucose (PPPG) levels. The blood test was also used to determine true prevalence which was cross-checked with the prevalence estimated (Pe) by the above stated screening tests using a mathematical formula.

RESULTS

The true prevalence of T2DM in more than 18 years of population by Fasting Plasma Sugar (FPS) was 4.5% while that by using mathematical formulae that estimated by urine test, Canrisk test and MDRF-IDRS was 4.4%, 4.4 and 4.3% respectively. When more than 35 years age-group was selected, true prevalence was 7.4% and estimated prevalence by Canrisk test was 7.1% (as against gold standard of Fasting) and 6.9% (as against PP). By fasting urine test it came out to be 7.2% and by PP urine test it was 7.4%. In population l8-35 years, the prevalence of diabetes was 1.1% by plasma glucose test. By using Canrisk, it came out to be 1.04%.

CONCLUSION

Individual screening tests such as urine, Canrisk and MDRF-IDRS can be used to estimate prevalence rates of diabetes in rural areas by means of mathematical formula which would be close to true estimates.

Screening for Colorectal Cancer Using a Multitarget Stool DNA Test: Modeling the Effect of the Intertest Interval on Clinical Effectiveness

BACKGROUND

A multitarget stool DNA (mt-sDNA) test was recently approved for colorectal cancer (CRC) screening for men and women, aged ≥ 50 years, at average risk of CRC. The guidelines currently recommend a 3-year interval for mt-sDNA testing in the absence of empirical data. We used clinical effectiveness modeling to project decreases in CRC incidence and related mortality associated with mt-sDNA screening to help inform interval setting.

MATERIALS AND METHODS

The Archimedes model (Archimedes Inc., San Francisco, CA) was used to conduct a 5-arm, virtual, clinical screening study of a population of 200,000 virtual individuals to compare the clinical effectiveness of mt-sDNA screening at 1-, 3-, and 5-year intervals compared with colonoscopy at 10-year intervals and no screening for a 30-year period. The study endpoints were the decrease in CRC incidence and related mortality of each strategy versus no screening. Cost-effectiveness ratios (US dollars per quality-adjusted life year [QALY]) of mt-sDNA intervals were calculated versus no screening.

RESULTS

Compared with 10-year colonoscopy, annual mt-sDNA testing produced similar reductions in CRC incidence (65% vs. 63%) and related mortality (73% vs. 72%). mt-sDNA testing at 3-year intervals reduced the CRC incidence by 57% and CRC mortality by 67%, and mt-sDNA testing at 5-year intervals reduced the CRC incidence by 52% and CRC mortality by 62%. At an average price of $600 per test, the annual, 3-year, and 5-year mt-sDNA screening costs would be $20,178, $11,313, and $7388 per QALY, respectively, compared with no screening.

CONCLUSION

These data suggest that screening every 3 years using a multitarget mt-sDNA test provides reasonable performance at acceptable cost.

Electronic health record phenotyping improves detection and screening of type 2 diabetes in the general United States population: A cross-sectional, unselected, retrospective study

OBJECTIVES

An estimated 25% of type two diabetes mellitus (DM2) patients in the United States are undiagnosed due to inadequate screening, because it is prohibitive to administer laboratory tests to everyone. We assess whether electronic health record (EHR) phenotyping could improve DM2 screening compared to conventional models, even when records are incomplete and not recorded systematically across patients and practice locations, as is typically seen in practice.

METHODS

In this cross-sectional, retrospective study, EHR data from 9948 US patients were used to develop a pre-screening tool to predict current DM2, using multivariate logistic regression and a random-forests probabilistic model for out-of-sample validation. We compared (1) a full EHR model containing commonly prescribed medications, diagnoses (as ICD9 categories), and conventional predictors, (2) a restricted EHR DX model which excluded medications, and (3) a conventional model containing basic predictors and their interactions (BMI, age, sex, smoking status, hypertension).

RESULTS

Using a patient's full EHR or restricted EHR was superior to using basic covariates alone for detecting individuals with diabetes (hierarchical X(2) test, p<0.001). Migraines, depot medroxyprogesterone acetate, and cardiac dysrhythmias were associated negatively with DM2, while sexual and gender identity disorder diagnosis, viral and chlamydial infections, and herpes zoster were associated positively. Adding EHR phenotypes improved classification; the AUC for the full EHR Model, EHR DX model, and conventional model using logistic regression, were 84.9%, 83.2%, and 75.0% respectively. For random forest machine learning out-of-sample prediction, accuracy also was improved when using EHR phenotypes; the AUC values were 81.3%, 79.6%, and 74.8%, respectively. Improved AUCs reflect better performance for most thresholds that balance sensitivity and specificity.

CONCLUSIONS

EHR phenotyping resulted in markedly superior detection of DM2, even in the face of missing and unsystematically recorded data, based on the ROC curves. EHR phenotypes could more efficiently identify which patients do require, and don't require, further laboratory screening. When applied to the current number of undiagnosed individuals in the United States, we predict that incorporating EHR phenotype screening would identify an additional 400,000 patients with active, untreated diabetes compared to the conventional pre-screening models.

Screening for Abnormal Blood Glucose and Type 2 Diabetes Mellitus: U.S. Preventive Services Task Force Recommendation Statement

DESCRIPTION

Update of the 2008 U.S. Preventive Services Task Force (USPSTF) recommendation on screening for diabetes in asymptomatic adults.

METHODS

The USPSTF reviewed the evidence on screening for impaired fasting glucose, impaired glucose tolerance, and type 2 diabetes in asymptomatic, nonpregnant adults who are at average or high risk for diabetes and its complications.

POPULATION

This recommendation applies to adults aged 40 to 70 years seen in primary care settings who do not have symptoms of diabetes and are overweight or obese.

RECOMMENDATION

The USPSTF recommends screening for abnormal blood glucose as part of cardiovascular risk assessment in adults aged 40 to 70 years who are overweight or obese. Clinicians should offer or refer patients with abnormal blood glucose to intensive behavioral counseling interventions to promote a healthful diet and physical activity. (B recommendation).

Development and demonstration of a state model for the estimation of incidence of partly undetected chronic diseases

Background

Estimation of incidence of the state of undiagnosed chronic disease provides a crucial missing link for the monitoring of chronic disease epidemics and determining the degree to which changes in prevalence are affected or biased by detection.

Methods

We developed a four-part compartment model for undiagnosed cases of irreversible chronic diseases with a preclinical state that precedes the diagnosis. Applicability of the model is tested in a simulation study of a hypothetical chronic disease and using diabetes data from the Health and Retirement Study (HRS).

Results

A two dimensional system of partial differential equations forms the basis for estimating incidence of the undiagnosed and diagnosed disease states from the prevalence of the associated states. In the simulation study we reach very good agreement between the estimates and the true values. Application to the HRS data demonstrates practical relevance of the methods.

Discussion

We have demonstrated the applicability of the modeling framework in a simulation study and in the analysis of the Health and Retirement Study. The model provides insight into the epidemiology of undiagnosed chronic diseases.

Electronic supplementary material

The online version of this article (doi:10.1186/s12874-015-0094-y) contains supplementary material, which is available to authorized users.

Methods for Building and Validating Equations for Physiology-Based Mathematical Models: Glucose Metabolism and Type 2 Diabetes in the Archimedes Model

OBJECTIVES

Describe steps for deriving and validating equations for physiology processes for use in mathematical models. Illustrate the steps using glucose metabolism and Type 2 diabetes in the Archimedes model.

METHODS AND RESULTS

The steps are as follows: identify relevant variables, describe their relationships, identify data sources that relate the variables, correct for biases in data sources, use curve fitting algorithms to estimate equations, validate the accuracy of curve fitting against empirical data, perform partially and fully independent external validations, examine any discrepancies to determine causes and make corrections, and periodically update and revalidate equations as necessary. Specific methods depend on the available data. Specific data sources and methods are illustrated for equations that represent the cause of Type 2 diabetes and its effect on fasting plasma glucose in the Archimedes model. Methods for validating the equations are illustrated. Applications enabled by including physiological equations in healthcare models are discussed.

CONCLUSIONS

The methods can be used to derive equations that represent the relationships between physiological variables and the causes of diseases and that validate well against empirical data.

Treatment of prediabetes

Progression of normal glucose tolerance (NGT) to overt diabetes is mediated by a transition state called impaired glucose tolerance (IGT). Beta cell dysfunction and insulin resistance are the main defects in type 2 diabetes mellitus (type 2 DM) and even normoglycemic IGT patients manifest these defects. Beta cell dysfunction and insulin resistance also contribute to the progression of IGT to type 2 DM. Improving insulin sensitivity and/or preserving functions of beta-cells can be a rational way to normalize the GT and to control transition of IGT to type 2 DM. Loosing weight, for example, improves whole body insulin sensitivity and preserves beta-cell function and its inhibitory effect on progression of IGT to type 2 DM had been proven. But interventions aiming weight loss usually not applicable in real life. Pharmacotherapy is another option to gain better insulin sensitivity and to maintain beta-cell function. In this review, two potential treatment options (lifestyle modification and pharmacologic agents) that limits the IGT-type 2 DM conversion in prediabetic subjects are discussed.