The study sample’s baseline characteristics are listed in . The 25th and 75th percentile C-IMT of the 5,682 men and 7,463 women (13,145 total individuals) were 0.65 mm and 0.84 mm for men and 0.58 mm and 0.74 mm for women, respectively. Atherosclerotic plaque presence increased from 13.6% in the overall population with a C-IMT<25th percentile (17.4% in men, 10.7% in women), to 26.2% in those with a C-IMT between 25–75th percentile (33.5% for men and 20.7% for women), and to 65.3% in those with a C-IMT > 75th percentile (73.1% in men and 59.5% in women) respectively. When evaluated by risk groups, plaque prevalence increased from 24% in the 0–5% risk group to 34.3% in the 5–10%, 46.5% in the 10–20% and 54.6% in the >20%, 10-year CHD (high) risk groups, respectively.
Baseline characteristics [means (SD) or prevalence %] after exclusions: ARIC study, 1987–89
Over a mean follow-up period of 15.1 years (men=14.4 years, women=15.7 years), there were 1,812 incident CHD events (867 definite or probable MI’s, 159 CHD deaths, 688 coronary revascularizations, and 98 silent [ECG-confirmed] MI’s).
When examining the AUC, adding C-IMT and/or plaque information (individually and together) to TRF improved the AUC significantly (even after adjustment for optimism) in both men and women, except that adding C-IMT alone in women was not significant (). Adding plaque to TRF had a more pronounced effect than adding C-IMT to TRF on the AUC in women. In women, the AUC increased from 0.759 (TRF alone) to 0.762 (95% confidence interval [CI] for the difference in adjusted AUC, −0.002, 0.006) when C-IMT was added to TRF while the AUC increased to 0.770 (95% CI for the difference in adjusted AUC, 0.005, 0.016) for plaque alone + TRF. The TRF + C-IMT + plaque model was associated with a similar AUC of 0.770 (0.005, 0.017). On the other hand, adding C-IMT had a more pronounced effect than adding plaque to TRF on the AUC in men. In men, the AUC increased from 0.674 (TRF alone) to 0.690 (95% CI for the difference in adjusted AUC 0.009, 0.022) when C-IMT was added to TRF while the AUC increased to 0.686 (95% CI 0.005, 0.017) for plaque alone+TRF. The TRF+C-IMT+plaque model was associated with the most increase in AUC which increased to 0.694 (95% C.I. 0.011, 0.027). When we considered the addition of plaque to a model that included TRF+C-IMT, it significantly improved the AUC in women by 0.009 (95% CI 0.003, 0.012), while in men, the increase in AUC by 0.004 (95% CI −0.001, 0.006) was non-significant. On the other hand, when we considered the addition of C-IMT to a model that included TRF+plaque, it improved the AUC in men by 0.008 (95% CI 0.002, 0.011), while in women, the increase in AUC by 0.000 (95% CI −0.002, 0.002) was non-significant.
Adjusted area under the curve (AUC) for different models with confidence intervals for the difference in adjusted AUC
The CHD incidence rate per 1,000 person years in the various C-IMT categories taking into account the presence or absence of plaque is described in . In all C-IMT categories, the presence of plaque was associated with a higher incidence of CHD events.
Adjusted coronary heart disease incidence rate per 1,000 person year adjusted by C-IMT categories (<25th percentile, 25–75th percentile and >75th percentile) with and without plaque
Adding plaque information along with C-IMT to TRF resulted in the reclassification of 8.6%, 37.5%, 38.3% and 21.5% of the overall sample in the <5%, 5–10%, 10–20% and >20% 10-year estimated risk groups, respectively (), while adding plaque and C-IMT reclassified 17.4%, 32.8%, 36.6% and 25.2% of the men () and 5.1%, 40.2%, 38.4% and 24.9% of the women () in the same risk groups. Overall, more individuals were reclassified to a lower risk group (~12.4%) than to a higher risk group (~10.8%), and nobody was reclassified from the low risk group (<5% estimated 10-year CHD risk) to the high risk (>20%, 10-year estimated CHD risk) or vice versa.
We then examined the goodness-of-fit of the various models using the Grønnesby-Borgan statistic. When the overall population was considered, although model fit improved with the addition of C-IMT and/or plaque, none of the models had a good fit with the Chi-square statistic (p-value) being 30.0 (p=0.0004), 23.7 (p=0.005) and 24.3 (p=0.004) for the TRF only model, TRF + C-IMT model and TRF + C-IMT + plaque model, respectively. When men and women were considered separately, the model fit improved. In men, the C-IMT + TRF model was the best fit (Chi-square statistic=14.12, p=0.11), while the C-IMT+TRF+plaque model and TRF-only model were not as good fits (Chi-square statistic [p-values] = 17.9 [p=0.04] and 18.7 [p=0.028], respectively). On the other hand, in women, the Chi-square test statistic (p values) were 15.0 (p=0.09), 9.1 (p=0.43) and 8.7 (p=0.47) for the TRF only, TRF + C-IMT and TRF + C-IMT + plaque models, respectively, which suggested that the TRF+C-IMT+plaque model had the best model fit.
Finally, we examined the NRI and the clinical NRI (NRI in the intermediate groups). We compared several models () and found that the TRF+C-IMT+plaque model was better than the TRF-only model in the overall sample, in men, and in women. However, adding plaque data minimally affected the TRF+C-IMT model in men, while adding C-IMT information minimally affected the TRF+plaque model in women. Overall, the TRF+C-IMT+plaque model when compared to the TRF-only model was associated with significant NRI’s of 9.9% (clinical NRI 21.7%) in the overall sample, 8.9% (clinical NRI 16.4%) in men and 9.8% (clinical NRI 25.4%) in women. In the overall sample, adding C-IMT or plaque individually to TRF was associated with a significant NRI of ~7.1–7.7% while adding the second variable (i.e. plaque to a TRF+C-IMT model or C-IMT to a TRF+plaque model) non-significantly increased the NRI by about 2–3%. The IDI showed that the model predictivity was significantly improved by adding C-IMT and plaque to TRF: in the overall population the IDI was 0.011, while in women, it was 0.009; and, in men, 0.013 (Supplemental Table
Net reclassification index using various comparison models in the overall sample, men and women
When we added C-IMT and plaque information to a Framingham risk score (FRS)-based TRF model, the results were similar. The adjusted AUC in men and women using the FRS model alone were 0.661 and 0.741, respectively, and improved to 0.685 (95% confidence interval [CI] for the difference in adjusted AUC, 0.014, 0.032) and 0.751 (95% confidence interval [CI] for the difference in adjusted AUC, 0.003, 0.016) respectively by adding C-IMT and plaque. In men, 11.5%, 34%, 37.9% and 32% of those in the <5%, 5–10%, 10–20% and >20% FRS categories respectively were reclassified by adding C-IMT and plaque, resulting in a NRI of 12.7% and a clinical NRI of 18.9%. However, in women, 6.6%, 41%, 39.8% and 36.3% of those in the <5%, 5–10%, 10–20% and >20% FRS categories respectively were reclassified, resulting in a NRI of 7.7% and a clinical NRI of 21.2%. Finally, when the goodness-of-fit was tested using the Grønnesby-Borgan test statistic, the model with FRS+C-IMT+plaque was better than the FRS-only model in both men (Chi-square statistic for FRS only = 15.05, p=0.09, Chi-square statistic for FRS+C-IMT+plaque =10.18, p=0.34) and women (Chi-square statistic for FRS only = 8.63, p=0.47, Chi-square statistic for FRS+C-IMT+plaque =4.97, p=0.84).