Harms and benefits of the haemoglobin glycation index (HGI)

In 2002, Hempe et al.1 introduced the concept of the haemoglobin glycation index (HGI) in response to the fact that HbA1c is not necessarily correlated with mean blood glucose (MBG), especially in patients with type 1 diabetes. Even if there is a significant linear correlation between MBG and HbA1c, there is also a large variability of HbA1c. To overcome this problem, Hempe et al. proposed the calculation of the haemoglobin glycation index (HGI = observed HbA1c – predicted HbA1c), which quantifies the magnitude and direction of the difference between each patient’s set of observed and predicted HbA1c results. In the 1441 Diabetes Control and Complications Trial (DCCT) participants, HGI was calculated for each visit to assess biological variation based on the directional deviation of observed HbA1c from that predicted by MBG in the model.2 The population was subdivided by tertiles (high, moderate and low HGI groups) based on participants’ mean HGI during the study. At seven years of follow-up, patients in the high HGI group (‘higher-than-predicted HbA1c’) had three times greater risk of retinopathy (30% vs. 9%, p < 0.001) and six times greater risk of nephropathy (6% vs. 1%, p < 0.001) compared with the low HGI group. The authors suggested that HbA1c levels could reflect both differences in blood glucose levels over time and the individual effects of additional biological factors that influence non-enzymatic protein glycation; if so, they hypothesized that HGI identifies a phenotype of glucose metabolism characterized by individual differences in susceptibility to haemoglobin glycation. Thus the existence of high and low haemoglobin glycation phenotypes could help explain why some individuals with apparently poor control escape complications while others with apparently good control develop severe complications.3 Finally they proposed that HGI should be considered as a marker of inherent risk for developing diabetes complications and advocated for using it as a clinical tool to identify high-risk diabetic patients. More recently, since the results of the ACCORD trial4 have been published and further reanalysed,5,6 Hempe et al. have shown that HGI was able to identify subpopulations of type 2 diabetic patients who benefited or not from intensive treatment.7 For the record, ACCORD was a randomized trial of more than 10,000 patients with type 2 diabetes assigned to standard or intensive treatment with HbA1c goals of 7% to 7.9% or less than 6%, respectively. ACCORD participants were middle-aged and older people with type 2 diabetes and established cardiovascular disease or known cardiovascular risk factors. Intensive treatment failed to improve primary cardiovascular outcomes and was associated with 22% greater total mortality compared with standard treatment. Severe hypoglycaemia was associated with an increased risk of death in both groups but differences in HbA1c or rates of hypoglycaemia between groups failed to explain the greater mortality in the intensive group.5 In order to compute HGI, a linear regression equation was derived from 1000 patients randomly extracted from ACCORD at inclusion.7 Baseline fasting plasma glucose (FPG) values were used to calculate predicted HbA1c and HGI for the whole study population. The results showed that subjects with high HGIs at baseline had more retinopathy and nephropathy as previously reported in the DCCT trial.2 Further analyses demonstrated that intensive treatment was associated with improved cardiovascular outcomes in the low (hazard ratio = 0.75; 95% confidence interval: 0.59–0.95) and moderate (hazard ratio = 0.77; 0.61–0.97) HGI subgroups but not in the high HGI subgroup (hazard ratio = 1.14; 0.93–1.40). Higher total mortality was confined to the high HGI subgroup in the intensively treated patients although a high HGI was confirmed to be associated with a greater risk for hypoglycaemia in both standard and intensive treatment groups. These results call for taking into account HGI besides HbA1c, which is not a ‘one-size-fits-all indicator’ of diabetes complications risk. Van Steen et al.8 have investigated the relevance of HGI as an independent predictor of complications in another trial including type 2 diabetic patients. The AleCardio trial9 randomized 7226 type 2 diabetic patients with an acute coronary syndrome to aleglitazar, a dual agonist of peroxisome proliferator-activated receptors, or placebo. Here, the linear regression equation was derived from 6458 patients with baseline HbA1c and FPG values for estimation of predicted HbA1c and derived HGI. They found that patients with high HGIs were younger, more often non-Caucasian, had a longer duration of diabetes and showed more insulin use and more retinopathy. Hypoglycaemia occurred less often in the low HGI subgroup but this statistical difference disappeared after adjustment for duration of diabetes, insulin and sulphonylurea use. Low HGI patients were at lower risk for cardiovascular (hazard ratio 0.64; 0.44–0.93) and total mortality (hazard ratio = 0.69; 0.50–0.95) as compared with high HGI patients. When HGI was used as continuous variable, they showed that every percentage increase in HGI was associated with a 16% increase in the risk for both cardiovascular (hazard ratio = 1.16; 1.06–1.27) and total mortality (hazard ratio = 1.16; 1.04–1.28). But this association between HGI and mortality disappeared with further adjustment for HbA1c (hazard ratio = 0.93, 0.60–1.45 for total mortality, hazard ratio = 0.92; 0.55–1.54 for cardiovascular mortality), leading the authors to the conclusion that HGI is not better than HbA1c to predict mortality in diabetes patients with acute coronary syndrome. Finally, the evidence so far is that there is a substantial interindividual variation in the association between HbA1c and plasma glucose concentrations and that HGI permits to identify patients with higher risk of microangiopathic complications. Hence, subjects with high HGIs had more retinopathy whether in the context of type 1 diabetes in the DCCT study or in the context of type 2 diabetes in both the ACCORD and AleCardio trials. High HGI subjects were also more often treated by insulin and presented other severity characteristics, had longer duration of diabetes or were non-Caucasian phenotype. HGI seems to reflect the interindividual glycaemic variability that could lead to more complications such as microangiopathy and hypoglycaemia but its impact on cardiovascular disease and/or mortality is still debated. Interestingly, a recent study reinforces the relevance of HGI for identifying patients with higher risk of cardiovascular disease (CVD).10 This study focused on a population study of 1248 treatment-naïve subjects with pre-diabetes or diabetes. The highest HGI tertile was independently associated with a composite CVD criterion (odds ratio (OR) = 2.81; 95% confidence interval 1.59–4.98), coronary artery disease (OR = 2.30; 1.12–4.73), stroke (OR = 3.40; 1.50–7.73) and peripheral artery disease (OR = 6.37; 1.18–34.33) after adjustment for other CVD risk factors including HbA1c levels. Evidence of clinically significant interindividual variation in the quantitative relationship between blood glucose concentration and HbA1c pleads for not using solely HbA1c in the management of diabetes. HGI is a relevant, and maybe independent, marker of higher risk of diabetes complications. The development of continuous and connected glucose measurement devices should bring new opportunities to better identify subjects with high risk of complications and, at the end of the day, make personalized medicine a reality. CC wrote the editorial and SC reviewed the final version. The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The author(s) received no financial support for this research, authorship, and/or publication of this article.