Prognostic value of haemoglobin A1c and fasting plasma glucose for incident diabetes and implications for screening

Adult Body Height Is Associated with the Risk of Type 2 but Not Type 1 Diabetes Mellitus: A Retrospective Cohort Study of 783,029 Individuals in Germany

Background: Diabetes mellitus is a major global health burden associated with high morbidity and mortality. Although a short adult body height has been associated with increased risk of type 2 diabetes (T2D), there are large inconsistencies between the studies. Therefore, we aimed to investigate the association between body height and T2D in a large cohort of adult outpatients in Germany. Methods: A total of 783,029 adult outpatients with available body height data from the Disease Analyzer (IQVIA) database were included in Germany between 2010 and 2020. The incidence of diabetes mellitus (type 1 and type 2) was evaluated as a function of the patients’ body height stratified by age, sex, and body-mass-index (BMI). Results: In both women and men in all age groups, incidence of T2D decreased with the increasing body height (<50, 51–60, 61–70, and >70 years). There was no association between the body height and the individual HbA1c value. In multivariable Cox regression analyses adjusted for patient age and BMI, hazard ratios for the development of T2D were 1.15 (95% CI: 1.13–1.17) for each 10 cm decrease in body height in women and 1.10 (95% CI: 1.09–1.12) in men. No significant association was found between body height and the development of T1D. Conclusions: We present the first data from a large cohort of outpatients in Germany, providing strong evidence for an association between adult body height and T2D. These data add to the current literature and might help in implementing body height into existing diabetes risk stratification tools to further reduce morbidity and mortality worldwide.

Diabetes in ageing: pathways for developing the evidence base for clinical guidance

Older adults with diabetes are heterogeneous in their medical, functional, and cognitive status, and require careful individualisation of their treatment regimens. However, in the absence of detailed information from clinical trials involving older people with varying characteristics, there is little evidence-based guidance, which is a notable limitation of current approaches to care. It is important to recognise that older people with diabetes might vary in their profiles according to age category, functional health, presence of frailty, and comorbidity profiles. In addition, all older adults with diabetes require an individualised approach to care, ranging from robust individuals to those residing in care homes with a short life expectancy, those requiring palliative care, or those requiring end-of-life management. In this Review, our multidisciplinary team of experts describes the current evidence in several important areas in geriatric diabetes, and outlines key research gaps and research questions in each of these areas with the aim to develop evidence-based recommendations to improve the outcomes of interest in older adults.

Development of type 2 diabetes mellitus in people with intermediate hyperglycaemia

BACKGROUND

Intermediate hyperglycaemia (IH) is characterised by one or more measurements of elevated blood glucose concentrations, such as impaired fasting glucose (IFG), impaired glucose tolerance (IGT) and elevated glycosylated haemoglobin A1c (HbA1c). These levels are higher than normal but below the diagnostic threshold for type 2 diabetes mellitus (T2DM). The reduced threshold of 5.6 mmol/L (100 mg/dL) fasting plasma glucose (FPG) for defining IFG, introduced by the American Diabetes Association (ADA) in 2003, substantially increased the prevalence of IFG. Likewise, the lowering of the HbA1c threshold from 6.0% to 5.7% by the ADA in 2010 could potentially have significant medical, public health and socioeconomic impacts.

OBJECTIVES

To assess the overall prognosis of people with IH for developing T2DM, regression from IH to normoglycaemia and the difference in T2DM incidence in people with IH versus people with normoglycaemia.

SEARCH METHODS

We searched MEDLINE, Embase, ClincialTrials.gov and the International Clinical Trials Registry Platform (ICTRP) Search Portal up to December 2016 and updated the MEDLINE search in February 2018. We used several complementary search methods in addition to a Boolean search based on analytical text mining.

SELECTION CRITERIA

We included prospective cohort studies investigating the development of T2DM in people with IH. We used standard definitions of IH as described by the ADA or World Health Organization (WHO). We excluded intervention trials and studies on cohorts with additional comorbidities at baseline, studies with missing data on the transition from IH to T2DM, and studies where T2DM incidence was evaluated by documents or self-report only.

DATA COLLECTION AND ANALYSIS

One review author extracted study characteristics, and a second author checked the extracted data. We used a tailored version of the Quality In Prognosis Studies (QUIPS) tool for assessing risk of bias. We pooled incidence and incidence rate ratios (IRR) using a random-effects model to account for between-study heterogeneity. To meta-analyse incidence data, we used a method for pooling proportions. For hazard ratios (HR) and odds ratios (OR) of IH versus normoglycaemia, reported with 95% confidence intervals (CI), we obtained standard errors from these CIs and performed random-effects meta-analyses using the generic inverse-variance method. We used multivariable HRs and the model with the greatest number of covariates. We evaluated the certainty of the evidence with an adapted version of the GRADE framework.

MAIN RESULTS

We included 103 prospective cohort studies. The studies mainly defined IH by IFG5.6 (FPG mmol/L 5.6 to 6.9 mmol/L or 100 mg/dL to 125 mg/dL), IFG6.1 (FPG 6.1 mmol/L to 6.9 mmol/L or 110 mg/dL to 125 mg/dL), IGT (plasma glucose 7.8 mmol/L to 11.1 mmol/L or 140 mg/dL to 199 mg/dL two hours after a 75 g glucose load on the oral glucose tolerance test, combined IFG and IGT (IFG/IGT), and elevated HbA1c (HbA1c5.7: HbA1c 5.7% to 6.4% or 39 mmol/mol to 46 mmol/mol; HbA1c6.0: HbA1c 6.0% to 6.4% or 42 mmol/mol to 46 mmol/mol). The follow-up period ranged from 1 to 24 years. Ninety-three studies evaluated the overall prognosis of people with IH measured by cumulative T2DM incidence, and 52 studies evaluated glycaemic status as a prognostic factor for T2DM by comparing a cohort with IH to a cohort with normoglycaemia. Participants were of Australian, European or North American origin in 41 studies; Latin American in 7; Asian or Middle Eastern in 50; and Islanders or American Indians in 5. Six studies included children and/or adolescents.Cumulative incidence of T2DM associated with IFG5.6, IFG6.1, IGT and the combination of IFG/IGT increased with length of follow-up. Cumulative incidence was highest with IFG/IGT, followed by IGT, IFG6.1 and IFG5.6. Limited data showed a higher T2DM incidence associated with HbA1c6.0 compared to HbA1c5.7. We rated the evidence for overall prognosis as of moderate certainty because of imprecision (wide CIs in most studies). In the 47 studies reporting restitution of normoglycaemia, regression ranged from 33% to 59% within one to five years follow-up, and from 17% to 42% for 6 to 11 years of follow-up (moderate-certainty evidence).Studies evaluating the prognostic effect of IH versus normoglycaemia reported different effect measures (HRs, IRRs and ORs). Overall, the effect measures all indicated an elevated risk of T2DM at 1 to 24 years of follow-up. Taking into account the long-term follow-up of cohort studies, estimation of HRs for time-dependent events like T2DM incidence appeared most reliable. The pooled HR and the number of studies and participants for different IH definitions as compared to normoglycaemia were: IFG5.6: HR 4.32 (95% CI 2.61 to 7.12), 8 studies, 9017 participants; IFG6.1: HR 5.47 (95% CI 3.50 to 8.54), 9 studies, 2818 participants; IGT: HR 3.61 (95% CI 2.31 to 5.64), 5 studies, 4010 participants; IFG and IGT: HR 6.90 (95% CI 4.15 to 11.45), 5 studies, 1038 participants; HbA1c5.7: HR 5.55 (95% CI 2.77 to 11.12), 4 studies, 5223 participants; HbA1c6.0: HR 10.10 (95% CI 3.59 to 28.43), 6 studies, 4532 participants. In subgroup analyses, there was no clear pattern of differences between geographic regions. We downgraded the evidence for the prognostic effect of IH versus normoglycaemia to low-certainty evidence due to study limitations because many studies did not adequately adjust for confounders. Imprecision and inconsistency required further downgrading due to wide 95% CIs and wide 95% prediction intervals (sometimes ranging from negative to positive prognostic factor to outcome associations), respectively.This evidence is up to date as of 26 February 2018.

AUTHORS' CONCLUSIONS

Overall prognosis of people with IH worsened over time. T2DM cumulative incidence generally increased over the course of follow-up but varied with IH definition. Regression from IH to normoglycaemia decreased over time but was observed even after 11 years of follow-up. The risk of developing T2DM when comparing IH with normoglycaemia at baseline varied by IH definition. Taking into consideration the uncertainty of the available evidence, as well as the fluctuating stages of normoglycaemia, IH and T2DM, which may transition from one stage to another in both directions even after years of follow-up, practitioners should be careful about the potential implications of any active intervention for people 'diagnosed' with IH.

Discordance in glycemic categories and regression to normality at baseline in 10,000 people in a Type 2 diabetes prevention trial

The world diabetes population quadrupled between 1980 and 2014 to 422 million and the enormous impact of Type 2 diabetes is recognised by the recent creation of national Type 2 diabetes prevention programmes. There is uncertainty about how to correctly risk stratify people for entry into prevention programmes, how combinations of multiple 'at high risk' glycemic categories predict outcome, and how the large recently defined 'at risk' population based on an elevated glycosylated haemoglobin (HbA1c) should be managed. We identified all 141,973 people at highest risk of diabetes in our population, and screened 10,000 of these with paired fasting plasma glucose and HbA1c for randomisation into a very large Type 2 diabetes prevention trial. Baseline discordance rate between highest risk categories was 45.6%, and 21.3-37.0% of highest risk glycaemic categories regressed to normality between paired baseline measurements (median 40 days apart). Accurate risk stratification using both fasting plasma glucose and HbA1c data, the use of paired baseline data, and awareness of diagnostic imprecision at diagnostic thresholds would avoid substantial overestimation of the true risk of Type 2 diabetes and the potential benefits (or otherwise) of intervention, in high risk subjects entering prevention trials and programmes.

Prediction of Type 2 Diabetes by Hemoglobin A1c in Two Community-Based Cohorts

OBJECTIVE

Hemoglobin A_1c (HbA_1c) can be used to assess type 2 diabetes (T2D) risk. We asked whether HbA_1c was associated with T2D risk in four scenarios of clinical information availability: 1) HbA_1c alone, 2) fasting laboratory tests, 3) clinic data, and 4) fasting laboratory tests and clinic data.

RESEARCH DESIGN AND METHODS

We studied a prospective cohort of white (N = 11,244) and black (N = 2,294) middle-aged participants without diabetes in the Framingham Heart Study and Atherosclerosis Risk in Communities study. Association of HbA_1c with incident T2D (defined by medication use or fasting glucose [FG] ≥126 mg/dL) was evaluated in regression models adjusted for 1) age and sex (demographics); 2) demographics, FG, HDL, and triglycerides; 3) demographics, BMI, blood pressure, and T2D family history; or 4) all preceding covariates. We combined results from cohort and race analyses by random-effects meta-analyses. Subsidiary analyses tested the association of HbA_1c with developing T2D within 8 years or only after 8 years.

RESULTS

Over 20 years, 3,315 individuals developed T2D. With adjustment for demographics, the odds of T2D increased fourfold for each percentage-unit increase in HbA_1c. The odds ratio (OR) was 4.00 (95% CI 3.14, 5.10) for blacks and 4.73 (3.10, 7.21) for whites, resulting in a combined OR of 4.50 (3.35, 6.03). After adjustment for fasting laboratory tests and clinic data, the combined OR was 2.68 (2.15, 3.34) over 20 years, 5.79 (2.51, 13.36) within 8 years, and 2.23 (1.94, 2.57) after 8 years.

CONCLUSIONS

HbA_1c predicts T2D in different common scenarios and is useful for identifying individuals with elevated T2D risk in both the short- and long-term.

Use of HbA1c to diagnose type 2 diabetes mellitus among high risk Sri Lankan adults

AIM

Even though, glycosylated hemoglobin (HbA1c) was found to be effective in predicting diabetes especially in Caucasians there is limited evidence of its diagnostic utility in high risk Sri Lankan adults. This study aimed to determine the optimal HbA1c cut-off points for detecting diabetes in a high risk population in Sri Lanka.

MATERIALS AND METHODS

This community based study consisted of 254 previously healthy adults with history of diabetes in one or more first-degree relatives. Fasting plasma glucose (FPG) , glucose tolerance test (GTT) and HbA1c were measured in all and GTT was used as a reference to diagnose diabetes. Receiver operating characteristic curve was created to find the optimum HbA1c cut-off value to predict diabetes.

RESULTS

Prevalence of diabetes was 12.2% (n=31) with FPG and 16.1% (n=41) with GTT. Prevalence rose to 27.6% (P<0.01) when HbA1c with cut-off of ≥6.5% was used as the diagnostic test. The ROC curves showed the HbA1c threshold of 6.3% provided the optimum balance between sensitivity (80.5%) and specificity (79%). In compared to GTT, FPG had only a modest sensitivity (65%) in diagnosing diabetes in this high risk population.

CONCLUSION

Our study showed that optimum HbA1C cut-off for detecting diabetes was 6.3% and it had better sensitivity, but lower specificity than FPG. This study further showed that the prevalence of diabetes would become double if HbA1c is used over FPG to screen this high risk population.

Education achievement and type 2 diabetes-what mediates the relationship in older adults? Data from the ESTHER study: a population-based cohort study

OBJECTIVE

The study aims to identify the mediating factors of the relationship between education achievement and incident type 2 diabetes mellitus (T2DM) in older adults.

DESIGN

Population-based cohort study.

SETTING

Participants were recruited from the German federal state of Saarland.

PARTICIPANTS

Participants were excluded if they had prevalent T2DM or missing data on prevalent T2DM, missing or zero follow-up time for incident T2DM or were under 50 years of age. The total sample consisted of 7462 individuals aged 50-75 years (42.8% men, mean age 61.7 years) at baseline (2000-02). The median follow-up time was 8.0 years.

METHODS

Cox proportional hazards regression was initially used to determine the direct association between education achievement and incident T2DM. Using the Baron and Kenny approach, we then investigated the associations between education achievement and incident T2DM with the potential mediators. The contribution of each of the putative mediating variables was then calculated.

RESULTS

A clear socioeconomic gradient was observed with regard to T2DM incidence with the lowest educated individuals at a greater risk of developing the disease during the follow-up period: HR (95% CI) high education: 0.52 (0.34 to 0.80); medium education: 0.80 (0.66 to 0.96). Seven of the variables considered explained a proportion of the education-T2DM relationship (body mass index, alcohol consumption, hypertension, fasting triglycerides, high-density lipoprotein (HDL) cholesterol, physical activity and smoking status), where the contribution of the variables ranged from 1.0% to 17.7%. Overall, the mediators explained 31.7% of the relationship.

CONCLUSION

By identifying the possible mediating factors of the relationship between education achievement and incident T2DM in older adults, the results of this study can be used to assist with the development of public health strategies that aim to reduce socioeconomic inequalities in T2DM.

Diagnostic performance of HbA1c for diabetes in Arab vs. European populations: a systematic review and meta-analysis

AIM

To examine differences in the performance of HbA_1c for diagnosing diabetes in Arabs compared with Europeans.

METHODS

The PubMed, Embase and Cochrane library databases were searched for records published between 1998 and 2015. Estimates of sensitivity, specificity and log diagnostic odds ratios for an HbA_1c cut-point of 48 mmol/mol (6.5%) were compared between Arabs and Europeans, using a bivariate linear mixed-model approach. For studies reporting multiple cut-points, population-specific summary receiver operating characteristic (SROC) curves were constructed. In addition, sensitivity, specificity and Youden Index were estimated for strata defined by HbA_1c cut-point and population type. Database searches yielded 1912 unique records; 618 full-text articles were reviewed. Fourteen studies met the inclusion criteria; hand-searching yielded three additional eligible studies. Three Arab (N = 2880) and 16 European populations (N = 49 127) were included in the analysis.

RESULTS

Summary sensitivity and specificity for a HbA_1c cut-point of 48 mmol/mol (6.5%) in both populations were 42% (33-51%), and 97% (95-98%). There was no difference in area under SROC curves between Arab and European populations (0.844 vs. 0.847; P = 0.867), suggesting no difference in HbA_1c diagnostic accuracy between populations. Multiple cut-point summary estimates stratified by population suggest that Arabs have lower sensitivity and higher specificity at a HbA_1c cut-point of 44 mmol/mol (6.2%) compared with European populations. Estimates also suggest similar test performance at cut-points of 44 mmol/mol (6.2%) and 48 mmol/mol (6.5%) for Arabs.

CONCLUSIONS

Given the low sensitivity of HbA_1c in the high-risk Arab American population, we recommend a combination of glucose-based and HbA_1c testing to ensure an accurate and timely diagnosis of diabetes.

α-Hydroxybutyric Acid Is a Selective Metabolite Biomarker of Impaired Glucose Tolerance

OBJECTIVE

Plasma metabolites that distinguish isolated impaired glucose tolerance (iIGT) from isolated impaired fasting glucose (iIFG) may be useful biomarkers to predict IGT, a high-risk state for the development of type 2 diabetes.

RESEARCH DESIGN AND METHODS

Targeted metabolomics with 23 metabolites previously associated with dysglycemia was performed with fasting plasma samples from subjects without diabetes at time 0 of an oral glucose tolerance test (OGTT) in two observational cohorts: RISC (Relationship Between Insulin Sensitivity and Cardiovascular Disease) and DMVhi (Diabetes Mellitus and Vascular Health Initiative). Odds ratios (ORs) for a one-SD change in the metabolite level were calculated using multiple logistic regression models controlling for age, sex, and BMI to test for associations with iIGT or iIFG versus normal. Selective biomarkers of iIGT were further validated in the Botnia study.

RESULTS

α-Hydroxybutyric acid (α-HB) was most strongly associated with iIGT in RISC (OR 2.54 [95% CI 1.86-3.48], P value 5E-9) and DMVhi (2.75 [1.81-4.19], 4E-5) while having no significant association with iIFG. In Botnia, α-HB was selectively associated with iIGT (2.03 [1.65-2.49], 3E-11) and had no significant association with iIFG. Linoleoyl-glycerophosphocholine (L-GPC) and oleic acid were also found to be selective biomarkers of iIGT. In multivariate IGT prediction models, addition of α-HB, L-GPC, and oleic acid to age, sex, BMI, and fasting glucose significantly improved area under the curve in all three cohorts.

CONCLUSIONS

α-HB, L-GPC, and oleic acid were shown to be selective biomarkers of iIGT, independent of age, sex, BMI, and fasting glucose, in 4,053 subjects without diabetes from three European cohorts. These biomarkers can be used in predictive models to identify subjects with IGT without performing an OGTT.

Examining the relationship between HbA1c and diabetes risk models in a European population indicates a lower threshold to identify 'high risk' is required

This study examined whether changes in HbA1c values are reflected in the risk scores and categories of four validated risk-assessment tools (QDiabetes, Leicester Risk Assessment, Finnish Diabetes Risk Score and Cambridge Risk Score). Retrospective analysis was performed on 651 individuals with no prior diagnosis of cardiovascular disease or diabetes who participated in a UK workplace-based risk-assessment initiative. There were significant positive correlations (p < 0.01) revealed between HbA1c values and predicted risk scores: QDiabetes (r = 0.362), Leicester Risk Assessment (r = 0.315), Finnish Diabetes Risk Score (r = 0.202) and Cambridge Risk Score (r = 0.335). HbA1c values increased within risk prediction categories, and at 'high-risk' categories, median HbA1c values were at least 39 mmol mol(-1) (5.7%) irrespective of gender or risk-assessment model. Overall, an association is present between increases in HbA1c scores and predicted risk of type 2 diabetes. Furthermore, the 'high-risk' median HbA1c values in each of the risk assessments are more akin to the lower American recommendations rather than those suggested by the UK expert group.

Type 2 Diabetes Prevention: Implications of Hemoglobin A1c Genetics

Hemoglobin A1c (HbA1c) is a biomarker used for population-level screening of type 2 diabetes (T2D) and risk stratification. Large-scale, genome-wide association studies have identified multiple genomic loci influencing HbA1c. We discuss the challenges of classifying these genomic loci as influencing HbA1c through glycemic or nonglycemic pathways, based on their probable biology and pleiotropic associations with erythrocyte traits. We show that putative nonglycemic genetic variants have a measurable, albeit small, impact on the classification of T2D status by HbA1c in white and Asian populations. Accounting for their effect on HbA1c may be relevant when screening populations with higher frequencies of nonglycemic HbA1c-altering alleles. As carriers of such HbA1c-altering alleles have HbA1c levels that may not accurately reflect overall glycemia, we describe how accounting for genotype may improve the performance of HbA1c in T2D prediction models and risk stratification, allowing for lifestyle intervention strategies to be directed towards those who are truly at elevated risk for developing T2D. In a Mendelian randomization framework, genetic variants can be used as instrumental variables to estimate causal relationships between HbA1c and T2D-related complications. This approach may help to support or refute HbA1c as an appropriate biomarker for long-term health outcomes in the general population.

Incidence of type 2 diabetes and associated factors in the adult population of the Community of Madrid. PREDIMERC cohort

OBJECTIVES

Determine the incidence and risk factors of type2 diabetes in the adult population of Madrid (Spain) and compare the predictive models of type2 diabetes based on the prediabetes criteria of the American Diabetes Association (ADA) and the World Health Organisation (WHO).

MATERIAL AND METHODS

A prospective study was conducted on a population cohort composed of 2048 individuals between 30 and 74years of age with no diabetes. At the start of the study, an epidemiological survey was performed, and baseline glycaemia, HbA1c, body mass index and waist circumference were measured. A follow-up of 6.4years was conducted. New cases of type2 diabetes were identified using the electronic primary care medical history.

RESULTS

The incidence of type2 diabetes was 3.5 cases/1000 person-years. In the multivariate analysis, the variables that were associated with the onset of type2 diabetes were age, family history of diabetes, baseline glycaemia (100-125mg/dL), HbA1c (5.7-6.4%) and waist circumference (≥94cm for men and ≥80cm for women). Of these, the most significantly associated variables were baseline glycaemia and HbA1c. The ADA and WHO criteria for defining prediabetes had the same predictive capacity.

CONCLUSION

The incidence of type2 diabetes measured in Madrid was lower than that found in other population studies, with the glucometabolic state the main factor associated with progression to type2 diabetes. There were no differences between the prediabetes defined by the ADA and the WHO for predicting the onset of the disease.

Primary care screening for individuals with impaired glucose metabolism with focus on impaired glucose tolerance

AIM

To evaluate the utility of three short questions (the Skövde Form) combined with a random plasma glucose, and HbA1c as alternative tools for detection of individuals with impaired glucose metabolism (IGM), and particularly impaired glucose tolerance (IGT).

METHODS

Three questions concerning BMI ≥ 25 kg/m(2), heredity for type 2 diabetes, and known hypertension were asked in a random population of 573 individuals. All with two positive answers or one positive answer and a random plasma glucose > 7.2 mmol/l were invited for an oral glucose tolerance test and an HbA1c examination. FINDRISC was completed for comparison.

RESULTS

The positive predictive value (PPV) for IGM, using the Skövde Form, was 31% while sensitivity and specificity were 59% and 73%, respectively. Corresponding values for IGT were 11%, 50% and 69%. Using HbA1c ≥ 42 mmol/mol, the PPV for IGM was 64% while sensitivity and specificity were 28% and 97%, respectively. The corresponding values for IGT were 15%, 16% and 94%.

CONCLUSION

The Skövde Form combined with a random plasma glucose may be used as an alternative tool for detection of individuals with IGM and IGT in particular. HbA1c may be used to identify individuals with type 2 diabetes but fails to detect most individuals with prediabetes.

Association Between Glycosylated Hemoglobin and Cardiovascular Events and Mortality in Older Adults without Diabetes Mellitus in the General Population: The Leiden 85-Plus Study

OBJECTIVES

To examine the association between glycosylated hemoglobin (HbA1c) and incident cardiovascular disease and mortality in 85-year-old individuals without diabetes mellitus from the general population.

DESIGN

Population-based prospective follow-up study.

SETTING

General population.

PARTICIPANTS

Individuals without known diabetes mellitus (N = 445, n = 291 female).

MEASUREMENTS

HbA1c levels were categorized into three groups (<5.0% (31 mmol/mol), 5.0-5.7% (31-39 mmol/mol; reference), 5.7-6.5% (39-48 mmol/mol)).

RESULTS

At baseline, a history of myocardial infarction (MI) was more prevalent in subjects in the highest HbA1c group (18%) than in the reference group (7%) (P = .001). Prospectively, those with the highest level of HbA1c at baseline had a risk of incident MI during the 5-year follow-up that was 3.6 (95% confidence interval = 1.5-8.3) times as great as that of the reference group. No association was found between HbA1c level and incident stroke, cardiovascular mortality, or all-cause mortality.

CONCLUSION

In individuals aged 85 and older without diabetes mellitus, higher HbA1c is associated with greater risk of MI but not with stroke and mortality.

A novel test for IGT utilizing metabolite markers of glucose tolerance

The oral glucose tolerance test (OGTT) is the only method to diagnose patients having impaired glucose tolerance (IGT), but its use has diminished considerably in recent years. Metabolomic profiling studies have identified a number of metabolites whose fasting levels are associated with dysglycemia and type 2 diabetes. These metabolites may serve as the basis of an alternative test for IGT. Using the stable isotope dilution technique, quantitative assays were developed for 23 candidate biomarker metabolites. These metabolites were measured in fasting plasma samples taken just prior to an OGTT from 1623 nondiabetic subjects: 955 from the Relationship between Insulin Sensitivity and Cardiovascular Disease Study (RISC Study; 11.7% IGT) and 668 subjects from the Diabetes Mellitus and Vascular Health Initiative (DMVhi) cohort from the DEXLIFE project (11.8% IGT). The associations between metabolites, anthropometric, and metabolic parameters and 2hPG values were assessed by Pearson correlation coefficients and Random Forest classification analysis to rank variables for their ability to distinguish IGT from normal glucose tolerance (NGT). Multivariate logistic regression models for estimating risk of IGT were developed and evaluated using AUCs calculated from the corresponding ROC curves. A model based on the fasting plasma levels of glucose, α-hydroxybutyric acid, β-hydroxybutyric acid, 4-methyl-2-oxopentanoic acid, linoleoylglycerophosphocholine, oleic acid, serine and vitamin B5 was optimized in the RISC cohort (AUC = 0.82) and validated in the DMVhi cohort (AUC = 0.83). A novel, all-metabolite-based test is shown to be a discriminate marker of IGT. It requires only a single fasted blood draw and may serve as a more convenient surrogate for the OGTT or as a means of identifying subjects likely to be IGT.

Definition of intervention points in prediabetes

With respect to clinical phenotype and pathophysiology, prediabetes is akin to diabetes. Prediabetes is prevalent in the global population, and those affected are at high risk of progression to overt diabetes, and also at risk of cardiovascular disease (CVD). Progression to diabetes can occur because of worsening insulin resistance, β-cell dysfunction, or both, but the timecourse can be non-linear and, therefore, unpredictable. Intervention-by lifestyle modification, glucose-lowering drugs, or a combination-can postpone deterioration of glucose control, but effects of intervention are variable and can be transient. Furthermore, to what extent interventions can reduce cardiovascular risk is uncertain. Lifestyle intervention mainly hinges on weight loss; as such, risk of failure in the long-term is high, and implementation at the community level is difficult. The ideal candidate for intervention is an individual with prediabetes-identified by targeted screening-with many well documented cardiovascular risk factors, and who is highly motivated to initiate and maintain multifactorial risk-control using a personalised mix of lifestyle-adaptation and pharmacological treatment.

Comparison of fasting plasma glucose and haemoglobin A1c point-of-care tests in screening for diabetes and abnormal glucose regulation in a rural low income setting

AIMS

Glycated haemoglobin (HbA1C) has been suggested to replace glucose tests in identifying diabetes and pre-diabetes. We assessed agreement between fasting plasma glucose (FPG) and HbA1C rapid tests in classifying abnormal glucose regulation (AGR), and their utility for preventive screening in rural Africa.

METHODS

A population-based survey of 795 people aged 35-60 years was conducted in a mainly rural district in Uganda. FPG was measured using On-Call® Plus glucometers, and classified using World Health Organization (WHO) and American Diabetes Association (ADA) criteria. HbA1C was measured using A1cNow® kits and classified using ADA criteria. Body mass index and blood pressure were measured. Percentage agreement between the two tests was computed.

RESULTS

Using HbA1C, 11.3% of participants had diabetes compared with 4.8% for FPG. Prevalence of HbA1C-defined pre-diabetes (26.4%) was 1.2 times and 2.5 times higher than FPG-defined pre-diabetes using ADA (21.8%) and WHO (10.1%) criteria, respectively. With FPG as the reference, agreement between FPG and HbA1C in classifying diabetes status was moderate (Kappa=22.9; Area Under the Curve (AUC)=75%), while that for AGR was low (Kappa=11.0; AUC=59%). However, agreement was high (over 90%) among negative tests and among participants with risk factors for type 2 diabetes (obesity, overweight or hypertension). HbA1C had more procedural challenges than FPG.

CONCLUSIONS

Although low in the general sample, agreement between HbA1C and FPG is excellent among persons who test negative with either test. A single test can therefore identify the majority at lower risk for type 2 diabetes. Nurses if trained can conduct these tests.

Hemoglobin A1c as a marker for identifying diabetes and cardiovascular risk factors: the China Health and Nutrition Survey 2009

Hemoglobin A1c (HbA1c) has been recommended as an optional method for diagnosing diabetes. The impact of HbA1c on the diagnosis of diabetes has not been evaluated in China, a country with the greatest number of people with diabetes in the world. Hence, we aim to examine how well HbA1c performs as compared with fasting plasma glucose (FPG) for diagnosing diabetes in Chinese population. We conducted a cross-sectional analysis of 7,641 Chinese men and women aged ≥18 years using data from the China Health and Nutrition Survey 2009 in which FPG and standardized HbA1c were measured. HbA1c was measured with high-performance liquid chromatography system. Diabetes is defined as having FPG ≥7 mmol/l or HbA1c ≥6.5 %. Overall, 5.0 and 5.8 % had undiagnosed diabetes by FPG ≥7 mmol/l and HbA1c ≥6.5 %, respectively. Overlap between HbA1c- and FPG-based diagnosis of diabetes was limited (n = 214, 34.9 %). Similar trends were noted in both genders, all age groups, urban/rural settings, regions, body mass index (BMI) categories, waist circumference (WC) groups, and blood pressure status. Solely HbA1c-defined individuals exhibited higher levels of BMI, WC, total cholesterol, and hypersensitive C-reactive protein and lower levels of homeostasis model assessment of insulin resistance. We note limited overlap between FPG- and HbA1c-based diagnosis of diabetes. The limited overlap between FPG- and HbA1c-based diagnosis of diabetes persisted in each evaluated subgroup. HbA1c criterion for the diagnosis of diabetes identifies individuals with a worse cardiovascular risk profile compared with FPG.

The potential of novel biomarkers to improve risk prediction of type 2 diabetes

The incidence of type 2 diabetes can be reduced substantially by implementing preventive measures in high-risk individuals, but this requires prior knowledge of disease risk in the individual. Various diabetes risk models have been designed, and these have all included a similar combination of factors, such as age, sex, obesity, hypertension, lifestyle factors, family history of diabetes and metabolic traits. The accuracy of prediction models is often assessed by the area under the receiver operating characteristic curve (AROC) as a measure of discrimination, but AROCs should be complemented by measures of calibration and reclassification to estimate the incremental value of novel biomarkers. This review discusses the potential of novel biomarkers to improve model accuracy. The range of molecules that serve as potential predictors of type 2 diabetes includes genetic variants, RNA transcripts, peptides and proteins, lipids and small metabolites. Some of these biomarkers lead to a statistically significant increase of model accuracy, but their incremental value currently seems too small for routine clinical use. However, only a fraction of potentially relevant biomarkers have been assessed with regard to their predictive value. Moreover, serial measurements of biomarkers may help determine individual risk. In conclusion, current risk models provide valuable tools of risk estimation, but perform suboptimally in the prediction of individual diabetes risk. Novel biomarkers still fail to have a clinically applicable impact. However, more efficient use of biomarker data and technological advances in their measurement in clinical settings may allow the development of more accurate predictive models in the future.

The Rotterdam Study: 2014 objectives and design update

The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, oncological, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. The findings of the Rotterdam Study have been presented in over a 1,000 research articles and reports (see www.erasmus-epidemiology.nl/rotterdamstudy ). This article gives the rationale of the study and its design. It also presents a summary of the major findings and an update of the objectives and methods.

Use of high-normal levels of haemoglobin A(1C) and fasting plasma glucose for diabetes screening and for prediction: a meta-analysis

BACKGROUND

Using high-normal levels of haemoglobin A1C (Abnormal-A1C ) or fasting plasma glucose (FPG) (Abnormal-FPG) for diabetes screening are expected to improve the ability to detect persons with or at high risk of diabetes. We assessed the diagnostic and predictive capacity for diabetes of Abnormal-A1C and Abnormal-FPG. We compared these to the combined use of the two measures to the single use of either measurement.

METHODS

We analysed 31 eligible cross-sectional or cohort studies that assessed diagnostic or predictive ability, respectively, by using lower A1C and FPG cutoff values than recommended by current diabetes criteria. Positive and negative likelihood ratios (LR+ and LR-) were calculated to assess the ability to confirm or exclude diabetes, respectively, on the basis of a bivariate random-effects model.

RESULTS

With both Abnormal-A1C and Abnormal-FPG, the pooled LR+ was above 4 for diagnosing diabetes and above 3 for predicting diabetes. However, the pooled LR- for predicting diabetes was higher with Abnormal-A1C (0.48) and Abnormal-FPG (0.49) in comparison with that for diagnosing diabetes (0.27, Abnormal-A1C ; 0.28, Abnormal-FPG). In eight studies that assessed the predictive ability of the combination of A1C and FPG, using either Abnormal-A1C or Abnormal-FPG could lower LR- to 0.17 from 0.43 for only Abnormal-A1C and from 0.38 for only Abnormal-FPG. Accordingly, LR+ was also lowered to 2.37 from 3.36 for only Abnormal-A1C and from 3.84 for only-Abnormal-FPG.

CONCLUSION

The use of the two blood glucose tests had insufficient capacity to identify subjects at high risk for diabetes but had considerable capacity to identify undiagnosed diabetes.

Prognostic association of HbA1c and fasting plasma glucose with reduced kidney function in subjects with and without diabetes mellitus. Results from a population-based cohort study from Germany

OBJECTIVE

To determine the risk for incident reduced kidney function (RKF) of subjects with pre-diabetes (impaired fasting glucose (IFG, 5.6-6.9 mmol/L)) or HbA1c-defined pre-diabetes (5.7%-6.4%) and to determine dose-response relationships of fasting glucose and HbA1c with RKF in subjects with manifest diabetes mellitus.

METHOD

In a German population-based cohort, recruited 2000-2002 with ages 50-74 years, log-binomial regression was used to estimate relative risks (RR) with 95% confidence intervals (95%CI) and restricted cubic splines to plot dose-response relationships.

RESULTS

During 8 years of follow-up, 678 of 3538 study participants developed primary RKF. Although RKF risk factor prevalences and RKF incidences were higher in subjects with pre-diabetes than in subjects with normal FPG and/or HbA1c levels, an increased risk did not persist after adjusting for established cardiovascular risk factors (RR(IFG): 0.97 (95% CI: 0.75-1.25) and RR(HbA1c-defined pre-diabetes): 1.03 (95% CI: 0.86-1.23)). In subjects with manifest diabetes, RKF risk increased linearly to a more than three-fold risk with increasing fasting glucose and HbA1c levels (at HbA1c>6.4%).

CONCLUSION

This study provides further evidence that pre-diabetes may not directly contribute to the development of kidney disease. Subjects with pre-diabetes might nevertheless profit from preventive efforts reducing their cardiovascular risk profile because cardiovascular and kidney disease share common risk factors.

Prediabetic increase in hemoglobin A1c compared with impaired fasting glucose in patients receiving antipsychotic drugs

BACKGROUND

In 2010, the American Diabetes Association recommended that individuals with hemoglobin A1c 5.7-6.4% be classified as prediabetic even in the absence of impaired fasting glucose (IFG).

AIM OF STUDY

To compare the clinical and metabolic characteristics of patients receiving antipsychotic drugs who have normal glucose tolerance (NGT), hemoglobin A1c 5.7-6.4% or IFG (fasting glucose 100-125 mg/dL).

METHOD

Body mass index, waist circumference, fasting glucose, insulin, lipids, hemoglobin A1c, and insulin resistance assessed with the homeostatic model (HOMA-IR) were measured in a consecutive cohort of adult psychiatric inpatients with NGT (N = 423), hemoglobin A1c 5.7-6.4% (N = 130), IFG (N = 52) and IFG plus hemoglobin A1c 5.7-6.4% (n = 39).

RESULTS

The hemoglobin A1c 5.7-6.4% group had lower fasting insulin levels (9.8 ± 5.6 vs. 15.5 ± 11.4 μU/mL, p < 0.0001) and HOMA-IR (2.1 ± 1.2 vs. 4.1 ± 3.1, p < 0.0001) than the IFG group, but were metabolically similar to those with NGT. The hemoglobin A1c 5.7-6.4% was the predominant prediabetic pattern in patients treated with antipsychotics other than clozapine or olanzapine. Patients with hemoglobin A1c 5.7-6.4% and those with IFG were statistically similar in age (40.1 ± 13.6 vs. 39.7 ± 10.3 years), body mass index (26.0 ± 4.8 vs. 26.3 ± 4.9) and waist circumference 93.1 ± 13.9 vs. 98.1 ± 12.1 cm for males and 92.5 ± 13.5 vs. 90.7 ± 15.8 cm for females.

CONCLUSION

The hemoglobin A1c in the 5.7-6.4% range is common in euglycemic patients receiving antipsychotic drugs and this prediabetic pattern has metabolic and pharmacological features that differentiates it from IFG.

Fasting plasma glucose and HbA1c in cardiovascular risk prediction: a sex-specific comparison in individuals without diabetes mellitus

AIMS/HYPOTHESIS

This study aimed to assess the cardiovascular risk of individuals with fasting plasma glucose (FPG)- and/or HbA(1c)-defined prediabetes (5.6-6.9 mmol/l and 39-47 mmol/mol [5.7-6.4%], respectively) or manifest diabetes mellitus and to evaluate whether FPG or HbA(1c) can improve risk prediction beyond that estimated by the Systematic Coronary Risk Evaluation (SCORE) chart in individuals without diabetes mellitus.

METHODS

Cox regression was employed to estimate HRs for primary incident cardiovascular events (CVEs) in a cohort of 8,365 individuals aged 50-74 years. Furthermore, HbA(1c) and FPG were added individually to the variables of the SCORE and measures of model discrimination and reclassification were assessed.

RESULTS

During 8 years of follow-up, 702 individuals had a primary CVE. After adjusting for conventional cardiovascular risk factors, HRs were attenuated close to one for the prediabetes groups (especially for women), whereas a 1.7- and a 1.9-fold increased risk persisted for men and women with diabetes, respectively. Extension of the SCORE variables by either FPG or HbA(1c) did not improve its predictive abilities in individuals without diabetes. There was a non-significant net reclassification improvement for men when HbA(1c) was added (2.2%, p = 0.16).

CONCLUSIONS/INTERPRETATION

The increased cardiovascular risk of individuals with FPG- or HbA(1c)-defined prediabetes can mainly be explained by other cardiovascular risk factors. Adding FPG or HbA(1c) did not significantly improve CVE risk prediction by the SCORE variables in individuals without diabetes mellitus.

Development of a new scoring system for predicting the 5 year incidence of type 2 diabetes in Japan: the Toranomon Hospital Health Management Center Study 6 (TOPICS 6)

AIMS/HYPOTHESIS

The aims of this study were to assess the clinical significance of introducing HbA(1c) into a risk score for diabetes and to develop a scoring system to predict the 5 year incidence of diabetes in Japanese individuals.

METHODS

The study included 7,654 non-diabetic individuals aged 40-75 years. Incident diabetes was defined as fasting plasma glucose (FPG) ≥7.0 mmol/l, HbA(1c) ≥6.5% (48 mmol/mol) or self-reported clinician-diagnosed diabetes. We constructed a risk score using non-laboratory assessments (NLA) and evaluated improvements in risk prediction by adding elevated FPG, elevated HbA(1c) or both to NLA.

RESULTS

The discriminative ability of the NLA score (age, sex, family history of diabetes, current smoking and BMI) was 0.708. The difference in discrimination between the NLA + FPG and NLA + HbA(1c) scores was non-significant (0.836 vs 0.837; p = 0.898). A risk score including family history of diabetes, smoking, obesity and both FPG and HbA(1c) had the highest discrimination (0.887, 95% CI 0.871, 0.903). At an optimal cut-off point, sensitivity and specificity were high at 83.7% and 79.0%, respectively. After initial screening using NLA scores, subsequent information on either FPG or HbA(1c) resulted in a net reclassification improvement of 42.7% or 52.3%, respectively (p < 0.0001). When both were available, net reclassification improvement and integrated discrimination improvement were further improved at 56.7% (95% CI 47.3%, 66.1%) and 10.9% (9.7%, 12.1%), respectively.

CONCLUSIONS/INTERPRETATION

Information on HbA(1c) or FPG levels after initial screening by NLA can precisely refine diabetes risk reclassification.

The Generation R Study: design and cohort update 2012

The Generation R Study is a population-based prospective cohort study from fetal life until adulthood. The study is designed to identify early environmental and genetic causes and causal pathways leading to normal and abnormal growth, development and health during fetal life, childhood and adulthood. The study focuses on six areas of research: (1) maternal health; (2) growth and physical development; (3) behavioural and cognitive development; (4) respiratory health and allergies; (5) diseases in childhood; and (6) health and healthcare for children and their parents. Main exposures of interest include environmental, endocrine, genetic and epigenetic, lifestyle related, nutritional and socio-demographic determinants. In total, n = 9,778 mothers with a delivery date from April 2002 until January 2006 were enrolled in the study. Response at baseline was 61 %, and general follow-up rates until the age of 6 years exceed 80 %. Data collection in mothers, fathers and children include questionnaires, detailed physical and ultrasound examinations, behavioural observations, and biological samples. A genome and epigenome wide association screen is available in the participating children. From the age of 5 years, regular detailed hands-on assessments are performed in a dedicated research center including advanced imaging facilities such as Magnetic Resonance Imaging. Eventually, results forthcoming from the Generation R Study contribute to the development of strategies for optimizing health and healthcare for pregnant women and children.

Screening for pre-diabetes to predict future diabetes using various cut-off points for HbA(1c) and impaired fasting glucose: the Toranomon Hospital Health Management Center Study 4 (TOPICS 4)

AIM

To evaluate various screening criteria for pre-diabetes to identify which combination of impaired fasting glucose and elevated HbA(1c) values performs most effectively in predicting future diabetes in a large cohort of Japanese individuals.

METHODS

The study included 4670 men and 1571 women without diabetes (diabetes: fasting plasma glucose ≥ 7.0 mmol/l, HbA(1c) ≥ 48 mmol/mol (≥ 6.5%), or self-reported clinician-diagnosed diabetes). Pre-diabetes was diagnosed by a combination of impaired fasting glucose (fasting plasma glucose 5.6-6.9 mmol/l or 6.1-6.9 mmol/l) and elevated HbA(1c) [39-46 mmol/mol (5.7-6.4%) or 42-46 mmol/mol (6.0-6.4%)].

RESULTS

During a 5-year follow-up, 338 incident cases of diabetes occurred. The combination of HbA(1c) 39-46 mmol/mol (5.7-6.4%) and fasting plasma glucose 5.6-6.9 mmol/l yielded the highest sensitivity (86%) and generated a large population-attributable per cent risk (78%) for predicting development of diabetes. Among individuals classified as having pre-diabetes by any of the four combined criteria, 20.5-32.0% reverted to the normoglycaemic state as having neither elevated HbA(1c) nor impaired fasting glucose at the last follow-up examination. At 5.6 years after the baseline examination, however, pre-diabetic individuals who fulfilled both HbA(1c) 42-46 mmol/mol (6.0-6.4%) and fasting plasma glucose 6.1-6.9 mmol/l had a 100% cumulative risk of developing diabetes.

CONCLUSIONS

The combination of HbA(1c) 39-46 mmol/mol (5.7-6.4%) and fasting plasma glucose 5.6-6.9 mmol/l would have the best performance in reducing the likelihood of missing future cases of diabetes. Identifying pre-diabetic individuals who strictly fulfil HbA(1c) 42-46 mmol/mol (6.0-6.4%) and fasting plasma glucose 6.1-6.9 mmol/l would predict definite progression to diabetes.

Metformin use among individuals at risk for type 2 diabetes

Excess total and cardiovascular morbidity and mortality remain very high among those with type 2 diabetes versus those without diabetes. Clinical trials to lower blood glucose have been disappointing probably because the participants were too late in the natural history of diabetes and already had extensive vascular disease. Insulin resistance measured simply by elevated fasting blood insulin is an early marker of β-cell stress and peripheral insulin resistance. Metformin will prevent development of diabetes among patients with impaired fasting glucose but only for the short term. Metformin reduces risk of coronary heart disease. The drug is safe, low cost, and may also prevent cancer. The combination of diet and exercise followed by metformin in the early phase of "insulin resistance" may reduce or delay both atherosclerosis and arteriosclerosis complications associated with diabetes. Preventive therapy must begin much earlier than before clinical diagnosis of diabetes and aim to initially lower blood insulin levels or insulin resistance.

Clinical utility of creatinine- and cystatin C-based definition of renal function for risk prediction of primary cardiovascular events in patients with diabetes

OBJECTIVE

To assess the cardiovascular risk of diabetic subjects with chronic kidney disease (CKD) based on different estimated glomerular filtration rate (eGFR) equations and to evaluate which definition of CKD best improves cardiovascular risk prediction of the Framingham Cardiovascular Risk Score (Framingham-CV-RS).

RESEARCH DESIGN AND METHODS

CKD was defined as eGFR <60 mL/min/1.73 m(2), estimated by the creatinine-based Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations and a cystatin C-based equation (CKD-CysC). Cox regression was used to estimate hazard ratios (HRs) of subjects with CKD for incident cardiovascular events in a cohort of 1,153 individuals with diabetes (baseline age 50-74 years). Furthermore, the CKD definitions were added individually to a reference model comprising the Framingham-CV-RS variables and HbA(1c), and measures of model discrimination and reclassification were assessed.

RESULTS

During 5 years of follow-up, 95 individuals had a primary cardiovascular event. Crude HRs were increased for all CKD definitions. However, after adjusting for established cardiovascular risk factors, HRs for both creatinine-based CKD definitions were attenuated to point estimates of 1.03, whereas the HRs for the cystatin C-based CKD definition remained significantly increased (HR 1.75 [95% CI 1.07-2.87]). Extension of the reference model by the different CKD definitions resulted in an increase in the c statistic only when adding CKD-CysC (from 0.638 to 0.644) along with a net reclassification improvement of 8.9%.

CONCLUSIONS

Only the cystatin C-based CKD definition was an independent risk predictor for cardiovascular events in our diabetic study cohort and indicated a potentially better clinical utility for cardiovascular risk prediction than creatinine-based equations.