Skin autofluorescence provides additional information to the UK Prospective Diabetes Study (UKPDS) risk score for the estimation of cardiovascular prognosis in type 2 diabetes mellitus

This study shows that skin autofluorescence is of additional clinical value in the evaluation of risk of fatal and non-fatal CV events and total mortality in type 2 diabetes mellitus. It is concluded that skin autofluorescence identifies a patient subgroup with an increased event rate within the group of patients at high risk for a fatal CV event (> 10% within the next 10 years) calculated with the UKPDS risk engine. The patient group with a UKPDS risk score >10% and a skin AF value above the median had a 10 year event rate (55.8%) significantly higher than that of the group with UKPDS risk score >10% and skin AF below the median (38.9%). As the majority (79%) of this cohort, who were well controlled in primary care with relatively recent onset of type 2 diabetes, has a UKPDS risk score >10%, it is clinically helpful to have an extra clinical tool to further differentiate risk.

By adding skin AF categories (below and above the median) and re-classifying patients with UKPDS risk scores <10%, a substantial proportion of patients (27%) would be re-classified to a higher-risk group. The incidence of CV events in patients with a low risk calculated with the UKPDS risk score was 59% higher if they had an AF above the median than if the AF was below the median. Re-classification of patients from low to high risk by AF seems, therefore, justified and should result in re-consideration of treatment strategies by extending or intensifying treatment in such individuals. Skin autofluorescence should not result in re-classification of patients from high risk (UKPDS risk score >10%) to low risk when skin AF is below the median, because the incidence rate of CV events is high in this group and ‘undertreatment’ is undesirable.

A history of macrovascular disease and a UKPDS risk score above 10% were significant predictors in the multivariate Cox regression analysis for all endpoints, and had the highest hazard ratios. Adding skin autofluorescence to UKPDS risk score in model 1 increased the AUC by an increment considered clinically relevant (>0.025); it was not statistically significant for the primary endpoint because of the sample size. For the endpoint ‘all-cause mortality’, the increase in AUC of the model with AF was higher and significant. In model 2, where a history of macrovascular disease was also included, the addition of AF was not relevant for the primary endpoint and was just relevant for the secondary endpoint. The small contribution of AF in this model might be due to the relation of AF to macrovascular disease. In our previous study with cross-sectional data we showed that AF was related to clinically apparent vascular damage, such as macrovascular disease [7]. The present follow-up study confirms skin AF to be a marker of vascular damage before it becomes clinically apparent because the incidence of CV events has increased in the patient group with a baseline skin AF value above the median.

The contributions of skin AF to all models were higher for the secondary endpoints, where ‘all-cause mortality’ was included. This suggests that skin AF or AGEs might also be involved in non-CV causes of death such as cancer.

A long-term follow-up study in a Finnish type 2 diabetes mellitus population showed that serum levels of AGEs were predictive for all-cause and CV mortality [16]. Other original papers on the predictive value of AGEs for CV morbidity or mortality are scarce. However, the mechanisms through which AGEs can result in vascular injury have been described by extension [1, 17, 18]. A recent study showed a pathophysiological example of the role of AGEs in CV disease by finding increased myocardial AGE deposition in patients with diabetes and heart failure with reduced left ventricular ejection fraction [19].

Despite our inclusion of patients with a history of CHD (which is different from the UKPDS), the expected UKPDS score event rates at 3.2 years in our group were in line with the observed rates, confirming that the UKPDS scores were applicable and calibrated for our group. The incidence of new CV events in our group was twice as high in the 20% of patients with a history of CHD as in patients without a history of CHD. Including patients with a history of CHD seems to be justified by daily practice where a history of CHD is common even in those newly diagnosed with type 2 diabetes. The UKPDS risk engine was developed in a young group (25–65 years, mean age at diagnosis 52 years) newly diagnosed with type 2 diabetes, without previous CV disease, identified between 1977 and 1991, selected for participation in a clinical trial, and using the mean of HbA_1c, BP and lipid levels in the first 2 years after diagnosis [9]. Despite the increased incidence at younger ages, type 2 diabetes presents mainly in individuals over 60 years of age in the Netherlands; these patients often have CHD and are already using statins or antihypertensive agents. When blood pressure or cholesterol values from such individuals are entered in the UKPDS risk engine, the calculated risk score might be an underestimated risk. The clinician is expected to identify those at the highest CV risk in order to adapt treatment targets. Our older patient group with HbA_1c levels comparable with those of the UKPDS cohort but with prevalent (39%) macrovascular disease reflects the differences between our ‘daily practice’ type 2 diabetes cohort and the UKPDS cohort.

In the present study, HbA_1c was not found to add predictive value for any of the endpoints. The contribution of HbA_1c in the prediction of increased CV risk in type 2 diabetes was illustrated in the UKPDS by an almost twofold increase in 10 year CHD risk, and by a higher odds ratio for fatal to non-fatal events for both myocardial infarction and stroke [9, 20]. This seeming discrepancy with our models that include skin AF may reflect the relatively low mean HbA_1c in our population. Another potential explanation lies in the following concept. First, skin AF and skin biopsy AGEs may reflect the impact of the history of hyperglycaemic episodes in diabetes and preceding impaired glucose tolerance better than the short-term measure of hyperglycaemia indicated by HbA_1c (weeks). Second, AGEs are also formed during oxidative stress via the pathway of reactive carbonyl compound formation [18]. An earlier study found skin AF to be related to C-reactive protein and inversely related to antioxidant levels, suggesting that skin AF represents inflammatory as well as hyperglycaemic episodes [21]. The DCCT-EDIC group reported that skin collagen AGE and collagen-linked fluorescence from skin biopsies were better predictors than HbA_1c of diabetic complications in type 1 diabetes mellitus [2, 3]. They introduced the idea of ‘metabolic memory’—that stable AGEs bound to long-lived proteins such as skin collagen provide long-term (years) memory of episodes of hyperglycaemia and oxidative stress—as an explanation for the superiority of skin AGE as a risk predictor. The recent long-term follow-up of glucose control in the UKPDS cohort showed in the intensive therapy group a continued reduction in risk for microvascular complications, myocardial infarction and all-cause mortality during 10 years of post-trial follow-up. This occurred despite the early loss of glycaemic and HbA_1c differences, and adds further support to the above concept [22].

Some limitations of our study should be kept in mind: the follow-up period is relatively short. Our calculations were all based on single measurements. The effects of regression dilution bias cannot be excluded. As for the comparison with the UKPDS risk score, in the design of the UKPDS the years 0–4 were excluded from the analysis, as the mortality rates were lower in the first years of the clinical trial. We used a cohort which had been recruited and followed for at least 3 years before the baseline AF measurements. Furthermore, our population size was small compared with larger studies specifically designed to develop risk-prediction models. This study was not powered to reach significance with the clinically relevant increase in AUC of 0.025 by skin AF. However, relevant increase in AUC became visible in this small cohort at this stage of the follow-up. Finally, our results were obtained in a predominantly white group. AF measurements in dark-skinned persons were not considered reliable using the prototype device in our study. Thus, the predictive results of skin AF may not directly be extrapolated to groups with darker skin, but probably need additional validation with newer versions of the AGE Reader.

In conclusion, non-invasive skin AF is a clinical tool which could be used in addition to the UKPDS risk score to identify diabetic individuals with preclinical vascular damage who have a particularly high risk of developing CV events. A high skin AF value can also result in re-classification to a high-risk group patients who are classified as ‘low risk’ according to the UKPDS risk engine. Although many type 2 diabetes patients are nowadays controlled tightly according to guidelines for their classic risk factors, they still develop micro- and macrovascular complications. Therefore, there is a need for additional markers to identify patients at high risk for complications. Furthermore, risk calculators may underestimate CV risk in patients already treated with antihypertensive or lipid-lowering drugs. Improvement of risk-prediction strategies is important to further reduce the incidence or progression of complications in patients with diabetes.