Characteristics of the study sample are shown in . The mean age was 58 ± 6 years. Hypertension was common, with 3,204 (63%) participants on anti-hypertensive therapy or with a blood pressure of 140/90 mm Hg or higher. Diabetes mellitus was present in 391 (8%) participants. Median follow-up time was 12.8 years (interquartile range: 12.1, 13.5).
The highest age- and sex-adjusted correlations between biomarkers were observed between N-BNP and MR-proANP (r=0.47, 95% confidence interval [CI], 0.45–0.49), and between MR-proADM and cystatin C (r=0.47, 95% CI, 0.45–0.49).
Prediction of cardiovascular events using single biomarkers
The proportionality of hazards criterion was met in all analyses of biomarkers in relation to cardiovascular and coronary events. The 10-year incidence of cardiovascular events was 7.8%. After adjustment for conventional risk factors, 5 of 6 biomarkers examined individually showed a significant relationship with incident cardiovascular events (Supplementary Table 1A
). The comparative performance of the biomarkers was assessed in the 4,483 participants with data on all 5 biomarkers, in whom 364 experienced a first incident cardiovascular event during follow up. Multivariable-adjusted hazard ratios for each biomarker are shown in . The strongest associations were observed for N-BNP (adjusted hazard ratio per SD increment in N-BNP, 1.22, 95% CI, 1.10–1.36) and CRP (1.19, 95% CI, 1.07–1.32).
Individual biomarkers and incident cardiovascular events
Several metrics were used to summarize the prognostic utility of adding individual biomarkers to conventional risk factors (). A model based on conventional risk factors had a c-statistic of 0.758 (95% CI, 0.734–0.781), and the addition of individual biomarkers resulted in small increases in the c-statistic (all changes less than 0.005, ). Models with or without biomarkers were well-calibrated, with modified Hosmer-Lemeshow p-values >0.05. The NRI and IDI were non-significant for all biomarkers.
Prediction of coronary events using single biomarkers
The 10-year incidence of coronary events was 4.4%. Three biomarkers (N-BNP, MR-proADM, and cystatin C) were significant predictors of first incident coronary events after multivariable adjustment (Supplementary Table 1B
). The adjusted hazards ratio associated with CRP had borderline significance (p=0.05).
Results based on the 4,600 participants with data on the 3 significant biomarkers, in whom there were 216 first incident coronary events, are shown in . Elevations in N-BNP and MR-proADM were associated with the highest hazards for coronary events, with adjusted hazard ratios per SD increment of 1.28 (95% confidence interval, 1.12–1.47) and 1.21 (95% confidence interval, 1.07–1.37), respectively. The c-statistic associated with conventional risk factors for predicting coronary events was 0.760 (95% CI, 0.730–0.789). As with cardiovascular events, addition of individual biomarkers did not raise the c-statistic appreciably (). Model calibration was good (Hosmer-Lemeshow p>0.05) with or without biomarkers, and the NRI was non-significant. The IDI was significant for MR-proADM (p=0.02), and borderline significant for N-BNP (p=0.08).
Individual biomarkers and incident coronary events
Multiple biomarkers for cardiovascular and coronary events
In backward elimination models, 2 biomarkers were retained for prediction of cardiovascular events (N-BNP and CRP), and 2 biomarkers were retained for prediction of coronary events (N-BNP and MR-proADM). Results of multivariable Cox proportional hazards models are shown in , for both outcomes. Incorporation of the set of significant biomarkers into prediction models for cardiovascular and coronary events led to small increments (approximately 0.01) in the c-statistics. The NRI was non-significant for cardiovascular events (p=0.99) and coronary events (p=0.09). The IDI had p-values of 0.08 for cardiovascular events and 0.03 for coronary events. Results for c-statistics, NRI, and IDI were unchanged when models were modified to include all biomarkers retained at p<0.10, or all biomarkers regardless of p-value.
Multiple biomarkers and incident cardiovascular and coronary events
shows the number of participants reclassified using the panels of informative biomarkers for cardiovascular events (n=238) and coronary events (n=144), respectively, during the first 10 years of follow-up. For cardiovascular events, use of biomarkers moved 335 participants (7.5%) into a higher or lower risk category. Only 35 participants (0.8%) were moved into the high risk category (10-year predicted risk ≥20%). For coronary events, 231 (5.0%) participants were reclassified into a higher or lower risk category, with only 22 (0.5%) moved into the high risk category. When “high-risk” was redefined as a 10-year predicted risk ≥10%, rather than 20%, the proportion of individuals reclassified to high-risk using biomarkers remained small (2.3% for cardiovascular events and 1.2% for coronary events).
Reclassification of 10-year predicted risk
Calibration was essentially the same in models with and without biomarkers. For cardiovascular events, actual event rates in the low, intermediate, and high risk groups were 2%, 11%, and 24% with conventional risk factors, and 2%, 11%, and 25% with risk factors and biomarkers. Corresponding event rates for coronary disease were 2%, 9%, and 27% with conventional risk factors, and 2%, 10%, and 23% with risk factors and biomarkers.
We also assessed reclassification using the ATP3 algorithm as the base clinical model, rather than a model fitted using the Malmö data. With the addition of biomarkers to the ATP algorithm, the NRI was significant for cardiovascular events, although the net proportion correctly reclassified was still modest (6.2%, p=0.004). The NRI was non-significant for coronary events (p=0.89).
Analyses in “intermediate risk” participants
We performed additional analyses restricted to “intermediate risk” participants (10-year predicted risk 6% to <20%). Most intermediate risk participants (57% for cardiovascular events and 59% for coronary events) had 10-year predicted risks <10%. Women comprised 44% of the intermediate risk group for cardiovascular events, and 26% of the intermediate risk group for coronary events.
For cardiovascular disease, 13% of the overall number of intermediate-risk individuals were down-classified, and only 3% were up-classified. The NRI for this subgroup was significant, 7.4% (95% CI, 0.7%–14.1%; p=0.03), although this was driven solely by individuals without events who were correctly down-classified (133 out of 973, 14%). Among those with events, a greater number (n=10, or 8%) were inappropriately down-classified than appropriately up-classified (n=6, or 4%). Similarly, for coronary disease events, 19% were down-classified and only 4% were up-classified. The NRI was 14.6% (95% CI, 5.0%–24.2%; p=0.003), due to the high proportion of individuals without events who were down-classified (107 out of 525, 20%). Among intermediate-risk individuals with coronary events, 3 (6%) were inappropriately down-classified and 2 (4%) were appropriately up-classified.
Simple “multimarker” risk scores were constructed for each endpoint. For each participant, standardized values of each biomarker (expressed in SD units from the mean), were summed to produce a score. Score values were then divided into quartiles (with the lowest scores defining quartile 1). The median multimarker scores in each quartile for cardiovascular events were −1.66 (range −5.47, −1.01), −0.52 (−1.01, −0.04), 0.37 (−0.04, 0.90), and 1.65 (0.90, 5.62). The median multimarker scores in each quartile for coronary events were −1.62 (−5.14, −1.02), −0.50 (−1.02, −0.06), 0.38 (−0.06, 0.88), and 1.60 (0.88, 11.65).
depicts the cumulative incidence of cardiovascular (Panel A) or coronary (Panel B) events, according to quartiles of the biomarker risk scores. In multivariable-adjusted models, hazards ratios associated with the 2nd through 4th quartiles of the score for cardiovascular events were 1.07 (95% CI, 0.75–1.52), 1.36 (0.98–1.89), and 1.61 (1.17–2.23; p for trend=0.001). Adding this cardiovascular disease biomarker score to conventional risk factors resulted in small improvements in the c-statistic (0.007), the NRI (0.0%, p=0.88), and the IDI (P=0.09). Adjusted hazards ratios associated with the 2nd through 4th quartiles of the score for coronary events were 1.01 (95% CI, 0.64–1.59), 1.11 (0.71–1.73), and 1.86 (1.22–2.83; p for trend =0.001). Adding the score for coronary events to conventional risk factors increased the c-statistic by 0.009, with NRI 5.5% (p=0.055) and IDI (P=0.02).
Figure 1 Kaplan-Meier plot showing one minus cumulative cardiovascular event-free survival during follow up in quartiles (Q1 to Q4 with Q1 representing subjects with lowest values) of a multimarker score based on the summed standardized values (expressed as number (more ...)
There were 392 all-cause deaths in the follow-up period. In the stepwise prediction model for mortality, 3 biomarkers were retained: N-BNP (multivariable-adjusted hazard ratio 1.13 per SD increment in N-BNP, 95% CI, 1.02–1.26; p=0.02), CRP (1.16, 95% CI, 1.03–1.28; p=0.007), and MR-ADM (1.14, 95% CI, 1.03–1.26; p=0.01). The addition of biomarkers increased the c-statistic for predicting total mortality from 0.700 to 0.711. The IDI was significant (p<0.001). The NRI was not calculated due to the absence of clinical risk categories for mortality.
The addition of heart failure to the cardiovascular endpoint (481 events overall) did not change the biomarkers retained in the stepwise model: N-BNP (multivariable-adjusted hazard ratio, 1.29, 95% CI, 1.17–1.43; p<0.001) and CRP (1.22, 95% CI, 1.10–1.35; p<0.001). The c-statistic rose from 0.759 to 0.770 and the IDI was significant (p=0.003). The NRI remained non-significant (p=0.52).