Fasting Glucose Variation Predicts Microvascular Risk in ACCORD and VADT

Jin J. Zhou; Juraj Koska; Gideon Bahn; Peter Reaven

Disclosures

J Clin Endocrinol Metab. 2021;106(4):1150-1162. 

In This Article

Results

There were 10 026 participants in ACCORD who had at least 2 measurements of fasting glucose after baseline and before a microvascular event occurred. Of these, 1106 developed a primary composite microvascular event. In the VADT, 1658 individuals had at least 2 measurements of fasting glucose after the first 6 months and before a microvascular event occurred, and 186 developed a primary composite event. The mean and median follow-up times were 59.5 and 59.8 months for the ACCORD, and 67.1 and 68.8 months for the VADT cohort. This provided on average 9 (median 6) and 18 (median 20) measures of fasting glucose in ACCORD and VADT, respectively. In ACCORD, the number of missing glucose measures ranged from 2.3% at the second visit (month 4) to 12.5% at the last time point (month 84). In the VADT, missing glucose measures at each visit were 4% or less. As noted in the ACCORD and VADT trial original publications for microvascular complications,[2,3] the proportion of participants lost to follow-up was very low (0.5%).[12] There were 3% of eye outcomes missing for the ACCORD cohort, while the rates of missing data for other outcomes were negligible for both studies. Baseline characteristics for both cohorts are shown by incident event status during the studies for both primary and secondary outcomes (Supplementary Tables 2 and 3[13]).

The Pearson correlation coefficient between CV-glucose and ARV-glucose in ACCORD was 0.86, while correlation coefficients between glucose variability measures and the cumulative mean of HbA1c were relatively low, at 0.25 and 0.26 for CV and ARV, respectively. In the VADT, a similar degree of correlation was observed between CV and ARV and the cumulative mean of HbA1c. Plots of cumulative CV and ARV in ACCORD and VADT across all visits separated by treatment arms show that variability in intensive groups was slightly higher than in standard treatment group throughout the study (Supplementary Figure 2 and Supplementary Figure 3, upper panel[13]). Similar plots show that glucose variability was higher among insulin users than in nonusers (Supplementary Figure 2 and Supplementary Figure 3, lower panel[13] ).

Glucose Variability and Risk of Microvascular Outcome in ACCORD and VADT

In an age-adjusted model (Model 1), the risk for microvascular outcomes with increasing quintiles of glucose variability demonstrated a striking linear trend (illustrated in Figure 1, panel A). Table 1 (top panel) shows estimated hazard ratios (HR) for glucose variability measures in 3 models for the primary and 2 secondary outcomes in ACCORD. Both CV and ARV were significant risk factors (P < 0.05) for the primary composite and secondary microvascular outcomes in Model 1 (age-adjusted only) and remained significant predictors for both primary and secondary microvascular outcomes after the adjustment for differences in risk factors for microvascular outcomes (Model 2). All these associations, except for the risk of ARV with retinopathy, remained significant after adjustment for the cumulative mean of HbA1c (Model 3). The estimated risks (ie, HRs) associated with glucose variability was in general higher for nephropathy than retinopathy.

Figure 1.

Hazard ratio (HR) estimates for quintiles of Log(CV)-glucose and ARV-glucose for the primary composite outcome in ACCORD and VADT in age-adjusted models. Vertical bars shown are the 95% CI associated with HR estimates. **indicates estimated HR in the indicated variability quintile is significantly higher than the HR of lowest variability quintile (quintile 1). Trend test results are presented as the text annotation in the figures.

As ACCORD also defined a broad range of other renal and eye outcomes, we also examined risk of glucose variability measures for these secondary outcomes, using the fully adjusted Model 3 (Supplementary Figure 4[13]). Thus, there were a total of 5 nephropathy-related microvascular outcomes with event numbers ranging from 486 (Neph-2) to 2751 (Neph-4). The strongest association of glycemic variability with nephropathy was with the primary renal outcome Neph-3 (HR 1.27; 95% CI, 1.11–1.46). However, glycemic variability appeared to be a significant risk factor for all nephropathy outcomes except Neph-5 (development of microalbuminuria). While Eye-3 (3-line change in visual acuity) had more than 3000 events, the number of events for the secondary eye disease outcomes were generally smaller (ranging from 490 to 551). Although glycemic variability increased the risk for all eye outcomes, only the Eye-1 risk (photocoagulation or vitrectomy) was significant. As with the primary outcomes, the associations of glycemic variability with the development of other eye outcomes appeared weaker compared with the risk for development of secondary nephropathy outcomes. In the VADT, risk for microvascular outcomes with increasing glucose variability also demonstrated a generally linear trend (illustrated in Figure 1, panel B). Table 1 (bottom panel) shows HRs of glucose measures for the primary and secondary outcomes. CV and ARV of fasting glucose were significant risk factors for the primary composite outcome in Model 1 (age-adjusted only) and remained significant risk factors of the primary microvascular outcome after all adjustments, including the cumulative mean of HbA1c (Model 3).

In sensitivity analyses, glucose variability generally remained a significant predictor of incident microvascular disease events after removing participants with baseline eye disease and renal disease or adjusting for insulin use. Risk of glucose variability was even slightly higher after restricting analyses to those with ≥5 glucose measures, and the primary results in the ACCORD did not change after using glucose data collected only during the shorter active glucose-lowering treatment phase of the study (all shown in Supplementary Table 5[13]).

Meta-analysis of ACCORD and VADT

In order to perform a meta-analysis of the effect of measures of glucose variability, we modified the ACCORD definition of nephropathy to be consistent with that used in the VADT (as described above) so that all outcomes were similar between studies. This definition reduced event numbers within ACCORD to 950 composite events and 99 nephropathy events, while eye events remained unchanged (baseline covariates and event numbers shown in Supplementary Table 4).[13] We then reassessed the risk of glucose variability for composite and renal outcomes in ACCORD using the fully adjusted model (Figure 2). The HRs for all outcomes in ACCORD remained similar and significant, and as when using the original ACCORD definition, were slightly lower compared with HRs estimates based on the VADT. For example, the HR for CV for the composite outcome was estimated to be 1.16 (1.06–1.26) in ACCORD vs 1.39 (1.14–1.69) in the VADT.

Figure 2.

Meta-analysis of the risk of glucose variability for microvascular complications in ACCORD and VADT. Hazard ratios for each individual study were estimated using fully adjusted models (Model-3 in text). Fixed-effect meta-analysis and inverse variance weighted method was used. Composite outcome: Nephropathy or Retinopathy; Nephropathy: 2 consecutive values of serum creatinine ≥3.3 or eGFR < 30; Retinopathy: Photocoagulation or Vitrectomy.

The meta-analysis of the ACCORD and VADT demonstrated that glucose variability (measured by both CV and ARV) is a significant risk factor for the composite microvascular outcome as well as for both nephropathy and retinopathy individually, with estimated I 2 statistics of 63%, 55%, and 42%, respectively. The pooled risk estimate of glucose variability was greatest for nephropathy (HR of 1.29 for ARV and 1.38 for CV, Figure 2).

To explore a differential effect between the treatment arms, we added a glucose variability by treatment interaction and assessed the pooled interaction effect. For the composite outcome, the P value for the CV-glucose interaction was 0.07. In stratified-metanalysis, the HR for CV-glucose in the standard treatment group was significant for the composite outcome, as well as for nephropathy and retinopathy individually (Figure 3). In contrast, it was not a significant predictor for any outcome in the intensive treatment group. This difference between treatment groups was most apparent for development of renal outcomes, with a HR of 1.88 (1.37–2.58, P < 0.001) in the standard group vs 1.14 (0.87–1.48, P = 0.35) in the intensive group. This treatment related modification of the relationship of glucose variability with each outcome was also apparent in each study, with the HRs for CV-glucose achieving statistical significance only in the standard treatment group (Figure 3). This pattern of differential effects of glucose variability by treatment group was also present for ARV-glucose.

Figure 3.

Meta-analysis of the risk of glucose variability for microvascular complications stratified by treatment arms of ACCORD and VADT. Hazard ratios (95% CI) in each study were estimated based on fully adjusted Model-3. Fixed-effect meta-analysis and inverse variance weighted method was used. Differential risks of glucose variability were assessed by assessing an interaction between glucose variability and treatment groups. For composite outcome#, P value of interaction is 0.07 and 0.24 for CV and ARV respectively. For nephropathy*, P values for interactions were 0.06 and 0.08 for CV and ARV respectively. For retinopathy+, P values for interactions were 0.06 and 0.30 for CV and ARV, respectively.

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