Effect of Prior Intensive Therapy in Type 1 Diabetes on 10-Year Progression of Retinopathy in the DCCT/EDIC: Comparison of Adults and Adolescents

The design and methods of the DCCT have been reported previously (1). In brief, the DCCT was a multicenter, randomized controlled trial comparing the occurrence and progression of diabetes complications in subjects with type 1 diabetes randomized to INT or CON therapy. Eligible subjects between 13 and 39 years of age were randomized to INT or CON in either the primary prevention arm (diabetes duration 1–5 years, no retinopathy, urine albumin <40 mg/day) or the secondary intervention arm (duration 1–15 years, at least early background retinopathy but no severe retinopathy, urine albumin ≤200 mg/day). When the DCCT ended in 1993, all subjects were instructed on INT methods. In 1994, 1,375 of the DCCT participants enrolled in the EDIC study, an observational follow-up study of the DCCT. A1C was determined by high-performance liquid chromatography (8), in the same central laboratory during DCCT and EDIC. Nephropathy evaluation, including serum creatinine and a 4-h timed urine collection (to determine albumin excretion rate and creatinine clearance) and fasting lipoprotein profiles were performed every other year. Other annual evaluations included a standardized medical history and physical examination, electrocardiogram, and a lower extremity neuropathy examination.

Ophthalmologic examination, visual acuity, and seven-field fundus photography were scheduled for each subject every four years and for the entire cohort at EDIC years 4 and 10. Seven-field stereoscopic fundus photography was performed by trained and certified photographers and the photographs were graded at a central reading center using the Early Treatment of Diabetic Retinopathy Study (ETDRS) scale by graders masked to previous DCCT treatment group assignment and A1C levels (9,10). Further 3-step progression during EDIC, defined as a ≥3-step progression from the ETDRS level at DCCT closeout, is the primary outcome reported in this article.

To test for differences between groups, Wilcoxon rank-sum tests were used for quantitative or ordinal data (11), and χ² tests/Fisher exact tests were used for categoric data (12). The Mantel-Haenszel method was used to calculate unadjusted odds ratios (ORs), as well as stratified, adjusted ORs, with test-based confidence limits (13). The percentage reduction in the odds with INT versus CON therapy was computed as (1 − OR) × 100. Generalized estimating equations (GEEs) with unstructured working correlation matrix (14) were used to test for differences in odds reduction in further ≥3-step progression between EDIC years 4 and 10. All the analyses were performed in the adult and adolescent cohorts (as enrolled at DCCT baseline).

Interval censoring was observed because of the large intervals between visits at which photographs were collected. Weibull proportional hazard regression model was used because of its robustness in the presence of heavily interval censored data (15,16). This model evaluated the effects of prior treatment and other risk factors on the cumulative incidence of further retinopathy progression from DCCT closeout through EDIC years 4 and 10. It also evaluated the difference in treatment effect (metabolic memory) between adults and adolescents by including the interaction term of treatment and adult/adolescent in the model after adjustment for the other risk factors. The Weibull model used all fundus photographs over all EDIC years in all patients. Hazard ratios and P values were obtained from the Wald test. The overall treatment effect and adult/adolescent effect were calculated using a 2 degrees of freedom (df) likelihood ratio test. The proportion reduction in the magnitude of Madalla R² based on the value of the χ² from the likelihood ratio test was used to describe the proportion of variation in risk (difference in metabolic memory between adults and adolescents) explained by the A1C levels (13,17,18). All analyses were performed using SAS Version 9.1.

Of the 1,441 subjects (195 adolescents) originally enrolled in the DCCT, 1,375 (175 adolescents) were available at the conclusion of DCCT and enrolled in the EDIC study; 1,208 subjects (170 adolescents) were evaluated for retinopathy at EDIC year 4; and 1,211 subjects (156 adolescents) were evaluated at EDIC year 10. The prevalence analyses reported here are limited to the 1,211 subjects (156 adolescents) with a year-10 retinopathy evaluation.

The characteristics of these 1,211 subjects are summarized in Table 1. Compared with adults, at DCCT baseline adolescents were more likely to be from the primary prevention cohort, have higher A1C, and have milder retinopathy. They also had longer DCCT follow-up, higher DCCT mean A1C, more severe retinopathy, and higher albumin excretion rate (AER) levels at DCCT closeout. At DCCT entry, there were no significant differences between INT and CON groups in any of the risk factors reported in Table 1 in either the adult or adolescent cohort. At DCCT closeout (equivalent to EDIC entry), treatment group differences were seen in adults for the distribution of retinopathy severity, the need for photocoagulation, and microalbuminuria (AER >40 mg/24 h). In adolescents, there was a similar (but nonsignificant) shift toward milder levels in overall distribution of retinopathy severity in the INT group (the risk of sustained 3-step progression was significantly reduced in the INT group in adolescents during DCCT as reported earlier [2]), but there was no difference in rates of photocoagulation, or AER levels. Mean A1C levels during DCCT and across DCCT and EDIC combined were significantly lower in the INT group in both adults and adolescents.

During the 10 years of EDIC follow-up, diabetes management was similar between former DCCT CON and INT groups. At EDIC year 10, the majority of patients were using intensive therapy, either continuous subcutaneous insulin infusion or multiple daily insulin injections (Table 1). In addition, more than half of the patients were self-monitoring blood glucose more than three times a day except in the CON adolescents (39%).

As shown in Table 1, there was no difference in A1C at DCCT baseline between INT and CON groups in either adolescents or adults, but the DCCT baseline A1C was higher in the adolescents (9.6 vs. 9.0% in adults, P < 0.0001). As previously reported, the A1C was reduced in the INT compared with the CON group during DCCT in both age groups. However, adolescents had higher DCCT mean A1C levels than the adult cohort in both the INT and the CON group (Table 1, P < 0.0001). During the EDIC follow-up, mean A1C was similar between adults and adolescents and between former INT and CON subjects (INT adult: 8.0 ± 1.1%; CON adult: 8.1 ± 1.1%; INT adolescent: 8.2 ± 1.3%; CON adolescent: 8.2 ± 2.1%, each P > 0.05).

As previously reported for both the entire DCCT/EDIC cohort (4) and for the adolescent cohort (5), the prevalence of further 3-step progression of retinopathy from end of DCCT at EDIC year 4 was significantly lower in the former INT group than in the former CON group despite similar A1C during this period; this was referred to as metabolic memory. Figure 1 compares the metabolic memory effect on further 3-step progression at 4 and 10 years of EDIC follow-up between adolescents and adults who were free of scatter photocoagulation during DCCT and had retinopathy evaluations at EDIC years 4 and 10. At EDIC year 10, prolonged beneficial treatment effect continued to be observed in the adult cohort. The prevalence of further 3-step progression was 22% in the INT adults and 41% in the CON adults, with odds reduction of 57% (CI: 43–67%) in INT versus CON (P < 0.0001); this is attenuated compared with that at EDIC year 4 (odds reduction: 72%; 95% CI: 57–82%; P < 0.0001). In the adolescent cohort, however, there was no longer evidence of metabolic memory. After 10 years of EDIC follow-up, 40% of both the INT and CON adolescents had further retinopathy progression (odds reduction: 0%; 95% CI: −88 to 49%; P = 0.9500) compared with 23% in CON and 8% in INT 4 years after DCCT closeout (odds reduction: 72%; 95% CI: 17–90%, P = 0.0165). GEE analysis verified that the odds reduction was significantly different between EDIC years 4 and 10 in both the adults (P = 0.0329) and adolescents (P = 0.0071).

Similar analyses were performed for the other retinopathy outcomes in the adolescents (Table 2) and adults (Table 3). In the adult cohort, the odds for each of these outcomes were significantly lower in the INT group compared with the CON group at DCCT closeout, at EDIC year 4, and at EDIC year 10 (odds reduction: 59–79%, 64–94%, and 48–74%, respectively; all P < 0.002), reflecting a strong persistence of metabolic memory all the way through EDIC year 10. In the adolescent cohort, however, metabolic memory did not appear to be present for any of these outcomes at EDIC year 10 and was present only for ≥3-step progression and severe nonproliferative diabetic retinopathy at year 4.

To further assess metabolic memory, we compared the cumulative incidence of further ≥3-step progression during EDIC from the level at DCCT closeout between former INT and CON treatment groups in adolescents and adults. Separate Weibull proportional hazards regression models were constructed in adolescent and adult groups after adjustment for DCCT primary prevention and secondary intervention cohort, diabetes duration, A1C at DCCT entry, and retinopathy severity at DCCT closeout. The models used evaluations from all years in all eligible subjects, excluding 29 adults and 7 adolescents who underwent scatter photocoagulation in either eye during DCCT. Figure 2 shows the estimated cumulative incidence for each treatment group in adults and adolescents during the first 4 years of EDIC (A and B) and for the first 10 years of EDIC follow up (C and D). The Weibull model (Fig. 2) revealed a highly significant beneficial effect of former INT in both adults and adolescents 4 years after the end of DCCT (adjusted hazard reduction 72%, P < 0.0001 and 67%, P = 0.01, respectively). At EDIC year 10, this highly significant beneficial effect of the former INT therapy was still apparent (adjusted hazard reduction 56%, P < 0.0001), although attenuated compared with EDIC year 4, in the adult cohort. In the adolescent cohort, the difference in 10-year cumulative incidence between INT and CON groups was still in favor of the former INT group, but the adjusted hazard reduction was less pronounced and no longer significant (32%, P = 0.1399).

Table 4 examines the risk factors for further retinopathy progression from DCCT closeout in a multivariate Weibull regression model after combining the adult and adolescent cohorts, and including the interaction of treatment (INT/CON) and age (adult/adolescent). The model demonstrates that the risk of further progression of retinopathy increased significantly with higher A1C level at DCCT baseline (P < 0.0001) and with higher mean blood pressure and blood lipids at DCCT closeout (P < 0.0001). Risk was also associated with retinopathy severity at DCCT closeout; patients with no retinopathy were at greater risk of progression than those with microaneurysms only or mild nonproliferative retinopathy but at lesser risk than those with moderate or severe retinopathy.

As expected from previous results, after controlling for other risk factors, the interaction between DCCT treatment group (INT vs. CON) and age cohort (adolescent vs. adult) remained significant (P = 0.0381), indicating that the prolonged treatment effect on metabolic memory differed by age. Likewise, this also indicates that the age effect differed by treatment group. In the former INT group, the hazard ratio (HR) of adolescent versus adult was 1.7 (P = 0.0078), indicating that INT adolescents had 70% higher risk of developing further 3-step progression in retinopathy than the INT adults after adjustment for the other risk factors. In the former CON group, however, the HR was 1.0, indicating that CON adolescents had the same risk of further retinopathy progression as CON adults. The overall age (adolescent vs. adult) effect (P < 0.0001; df = 2) and the overall treatment (INT vs. CON) effect (P = 0.0290; df = 2) on retinopathy progression are both significant.

To determine how much of the metabolic memory difference between adolescents and adults could be attributed to the mean A1C levels achieved during DCCT and during EDIC, separate Weibull models (as in Table 4) were constructed with and without further adjustment for mean A1C during DCCT or across DCCT and EDIC combined (Table 5). These models show that 79% of the metabolic memory difference between adults and adolescents (P = 0.0385) is attributed to the difference in mean A1C level during DCCT (8.1 vs. 8.9 for the combined INT and CON adults vs. adolescents, respectively), and 86% is attributed to mean A1C difference across DCCT and EDIC combined (8.0 vs. 8.4 for the combined INT and CON adults vs. adolescents, respectively). Furthermore, given the difference in effect of age in the two treatment groups, as shown in Table 4, similar Weibull models were constructed in the INT and CON groups separately. In the INT group, 93% of the observed difference in further retinopathy progression between INT adults and adolescents (P = 0.0155) was explained by their mean A1C difference in DCCT (7.2 vs. 8.1%). However, in the CON group, the age effect was not significant (P = 0.8848), indicating that CON adults and CON adolescents had similar risk of further retinopathy progression despite a significant difference in the DCCT mean A1C (9.7 vs. 8.9%).

To further examine the relationship of DCCT mean A1C and retinopathy progression between the treatment groups and adult/adolescent cohorts, separate Weibull models were constructed in the INT and CON groups, after further adjusting for A1C and the interaction of age (adult vs. adolescent) and A1C. In each treatment group of each age cohort, the risk of further retinopathy progression increases with the DCCT mean A1C (adjusted HR per 10% increase in A1C, e.g., 8–8.8, 1.5 or greater in each of the four categories, P < 0.003 in each).

Interestingly, in the INT group, but not in the CON group, the association between DCCT mean A1C and risk of retinopathy progression between DCCT closeout and EDIC year 10 was stronger in adults than in adolescents (Fig. 3). In the INT group, HRs per 10% increase in A1C were 2.2 in adults and 1.5 in adolescents (and per 10% decrease were 0.42 and 0.62, respectively) (P = 0.0140). In the CON group, corresponding HRs were 1.6 (increase) and 0.59 (decrease), respectively, for adults and adolescents.

The EDIC study demonstrated the surprising and unexpected phenomenon that the benefits of improving glycemic control on the development and progression of retinopathy (4,5) persisted for 4 years after completion of the DCCT, despite A1C levels that were similar in the two former treatment groups (metabolic memory). The benefits of INT therapy and improved glycemic control were substantial and similar in both adults and adolescents during and for up to 4 years after the end of DCCT, although adolescents had higher A1C as well as higher rates of hypoglycemia (4,5) during DCCT.

In contrast, after 10 years of EDIC follow-up, the different metabolic memory effect between adults and adolescents presented here indicates that lower A1C during INT intervention is an important determinant of the long-term durability of its benefits. Indeed, the difference in DCCT mean A1C between adults and adolescents (8.1 vs. 8.9%) explains 79% of the observed difference in the metabolic memory effect on further retinopathy progression between adults and adolescents after 10 years of EDIC follow-up. Examining the A1C information further (Table 1), adolescents started with a higher mean A1C level than adults at DCCT enrollment in both the INT (9.6 vs. 9.0%) and CON (9.5 vs. 8.9%) groups, and A1C remained higher in both groups during the entire DCCT period (8.1 vs. 7.2% in INT; 9.7 vs. 8.9% in CON). It was only during the EDIC follow-up that the mean A1C between adolescents and adults, as well as between former INT and CON groups, converged.

Interestingly, although the CON adolescents had higher A1C levels than the CON adults at DCCT enrollment (9.5 vs. 8.9%) and during the entire DCCT period (9.7 vs. 8.9%), the hazard of further retinopathy progression did not differ between CON adolescents and adults (adjusted hazard reduction 1.0) 10 years after the end of DCCT after adjustment for the other risk factors. However, with a similar trend of higher A1C in INT adolescents than in INT adults at DCCT enrollment (9.6 vs. 9.0%) and during DCCT (8.1 vs. 7.2%), INT adolescents had significantly higher risk of retinopathy progression at 10 years compared with the INT adults (adjusted hazard reduction 1.7, P = 0.0078), and 93% of the observed difference between the two age groups in the former INT therapy was explained by their difference in DCCT mean A1C. Further analysis reveals that INT adults are more sensitive to the A1C in DCCT than the INT adolescents. Because INT adults have lower A1C levels than the INT adolescents (7.2 vs. 8.1), a higher sensitivity means a greater hazard reduction (58 vs. 38% per 10% decrease in A1C) and a better treatment effect in the INT adults. Therefore, the lower A1C during DCCT and the higher sensitivity of retinopathy progression to the DCCT mean A1C in the INT adults than in the INT adolescents are likely the driving force of the long-term durability of the benefits of intensive therapy. That is, the reduced ability to maintain glycemic levels as close to normal as possible during DCCT in the INT adolescents compared with INT adults and the lower sensitivity of the INT adolescents to the A1C level during DCCT account for the differing duration of metabolic memory in retinopathy progression between adolescents and adults 10 years after the end of DCCT. These data provide further compelling evidence that the metabolic memory phenomenon is largely driven by the prior levels of glycemic control achieved. However, the mechanism for the metabolic memory phenomenon is not well understood.

It should be noted that the persistent adverse effects of hyperglycemia and the long-term beneficial effects of lowering glycemia on the development and progression of complications have also been shown in animal models of diabetes (19), in which it has also been termed metabolic memory. One possible explanation for the metabolic memory phenomenon is the slow accumulation, and subsequent slow degradation, of advanced glycation end products (AGEs) (20). Indeed, DCCT patients in the INT group had lower concentrations of these AGEs in skin collagen than did patients in the CON group (21). The levels of these skin collagen AGEs were also shown to be associated with the subsequent increase in progression of retinopathy (and nephropathy) over the first 10 years of EDIC (22). The finding that the metabolic memory effect appears to be waning between EDIC years 4 and 10 in the entire cohort (7) and in the adult cohort (data reported here) and is no longer present in the adolescent cohort may be the result of a combination of clearance of the long-lasting AGEs in the former CON group and the accumulation of AGEs in the former INT group. There are currently no direct data to prove this speculation, and comparison of AGEs between adult and adolescent cohorts of DCCT/EDIC is not currently available. However, in the near future, measurements of skin fluorescence may provide data related to this speculation.

Another possible, but equally speculative, mechanism by which prior glycemic control could have persistent effects on development and progression of diabetes complications is by epigenetic mechanisms. The phenomenon of epigenetics refers to the chemical modification of cellular DNA or nuclear histones by factors in the internal environmental milieu of the individual. Persistent changes in key chromatin histone methylation could be induced by hyperglycemia and result in sustained dysregulation (expression or repression) of gene expression for long periods of time. Epigenetic chromatin regulation of cellular transcription can operate at both the local (that is, single gene) level and at a global level over a period of time, affecting multiple chromosomal domains. With the initiation of the EDIC Epigenetics study, epigenetic modifications of chromatin and alterations of gene expression that could persist for a long period of time are being evaluated.

Despite the demonstrated differences in metabolic memory at 10 years between adult and adolescent cohorts, a few limitations must be acknowledged. First, the sample size of the adolescent cohort is small relative to the adult cohort, providing less power to demonstrate a significant effect should it exist in this age group. The small sample size of the adolescent cohort will not affect our conclusion related to the primary outcome of this study, further 3-step progression from DCCT closeout, because the odds reduction at EDIC year 10 for adolescents was 0% (Fig. 1). We cannot, however, rule out a type 2 error in other retinopathy outcomes, such as severe nonproliferative diabetic retinopathy or worse, proliferative diabetic retinopathy, or photocoagulation therapy (odds reduction: 46, 41, and 64%, respectively) (Table 2), due to the low power (20–40%) engendered by the small sample size of adolescents. Second, 18% of the adults and 25% of the adolescents who enrolled in the DCCT did not have a retinopathy assessment after 10 years of EDIC follow-up. Among these nonparticipants, 5 adolescents and 33 adults died prior to EDIC year 10. Further analyses (supplementary Table 1, available in an online appendix at http://diabetes.diabetesjournals.org/cgi/content/full/db09-1216/DC1) indicated that participants and nonparticipants are similar in treatment group, age, sex, diabetes duration, A1C, retinopathy levels, blood pressure, and lipids in the adult cohort, and similar in the majority of characteristics in the adolescent cohort except that the 10-year adolescent participants were slightly older at DCCT entry (14.9 vs. 14.2 years; P = 0.0034) and had worse retinopathy (P = 0.0301) at DCCT closeout. A possible reason may be that patients with milder retinopathy pay less attention to the monitoring of their retinopathy levels. However, because the treatment group is balanced between participants and nonparticipants, this observed slight imbalance should not bias the conclusion in this study.

The DCCT/EDIC studies have shown that intensive treatment directed at achieving blood glucose and A1C levels as close to normal as safely possible without severe hypoglycemia, and starting as early in the course of diabetes as safely possible, is vital for achieving sustained reductions of diabetic retinopathy. The results of the present analyses reinforce the need to maintain A1C at target values for as long as possible and demonstrate the waning benefits over time in the face of higher A1C levels.

The DCCT/EDIC project is supported by contracts with the Division of Diabetes, Endocrinology, and Metabolic Diseases of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) the National Eye Institute, the National Institute of Neurological Disorders and Stroke, the General Clinical Research Centers Program and Clinical and Translational Science Awards Program, National Center for Research Resources, and Genentech through a Cooperative Research and Development Agreement with the NIDDK.

Contributors of free or discounted supplies and/or equipment: Lifescan, Roche, Aventis, Eli Lilly, OmniPod, Can-Am, B-D, Animas, Medtronic, Medtronic Minimed, Bayer (one-time donation, 2008), Omron.

No potential conflicts of interest relevant to this article were reported.