In >66 000 individuals with >1 million person-years of follow-up, a single measurement of fitness as measured by exercise treadmill time significantly improved measures of discrimination and reclassification of CVD mortality risk when added to traditional risk factors. Even after 25 years of follow-up, baseline fitness provided modest improvement in discrimination and reclassification, particularly in women. These data extend prior observations on the association of fitness with CVD mortality, suggesting the potential clinical utility of incorporating fitness estimates in CVD risk prediction algorithms.
Several prior studies have observed a consistent, inverse association between levels of fitness and the risk for CVD mortality, including the CCLS,8,9,15
the Veterans Affairs study,14
and the Lipid Research Clinics Study.10
In addition, a few recent studies have demonstrated that low fitness is associated with increased CVD and all-cause mortality, even after adjustment for global risk scores.5–7,12,16
In the present study, we assessed the performance of fitness in improving clinically relevant metrics of discrimination, calibration, and reclassification beyond traditional risk factors.
Although traditional risk factors alone provided excellent discrimination of CVD mortality in the CCLS cohort, the addition of fitness improved all measures of discrimination. Given the limitation of using discrimination as the sole risk-prediction performance criterion,17
the ability of a novel marker to reclassify subjects across clinically relevant thresholds of risk represents a new benchmark.21
The NRI represents clinically meaningful improvement in risk classification achieved with a new marker and is calculated by measuring the net change in risk categories among cases and controls after the addition of a new marker to the baseline model.18,26
Unlike the NRI, the IDI is a measure of improvement in discrimination that is independent of risk categories and represents the improvements in true-positive rates minus the worsening in false-positive rates with the new marker.18,26
The relative IDI represents proportional improvement in discrimination by the new model versus the traditional model.18,26
Of note, the addition of fitness to traditional risk factors correctly reclassified 18.5% of cases into a higher-risk category but incorrectly reclassified 7.2% of cases into a lower-risk category, for a net correct classification of 11.3% among men with CVD death. In contrast, the addition of fitness had a negligible effect on the reclassification of noncases, resulting in an overall significant NRI10
of 0.121 (). These findings suggest that an assessment of fitness may have significant impact on risk prediction algorithms by providing a meaningful improvement in the identification of those individuals at risk for future CVD mortality. In addition, these data might also be useful to practicing clinicians, facilitating more effective risk communication regarding the health benefits of fitness. Not only is fitness a marker for CVD that improves multiple clinically relevant risk-prediction performance metrics, but fitness itself represents an established treatment target with few associated risks.1
Risk prediction in the general population remains a challenge because the majority of the general population is low risk.21,30 –32
Prior efforts have emphasized the potential role of blood-based markers (eg, C-reactive protein and cystatin C) and imaging modalities (eg, brachial flow-mediated dilation and carotid intima-media thickness) in risk prediction algorithms.33–36
With the exception of coronary artery calcium, most of these novel risk markers have limited discrimination and reclassification ability.33–37
Although significant improvements in the NRI are achieved with coronary artery calcium,37
there are particular concerns about radiation exposure and cost with the widespread use of coronary artery calcium scanning.38
In contrast, significant NRI is achieved with the addition of fitness without any associated radiation exposure. At a minimum, the findings from the present study suggest that in the short term, a single measurement of fitness is at least as useful as most biomarkers and imaging modalities in stratifying CVD risk.
Current CVD risk prediction algorithms (Framingham Risk Score, European Systematic Coronary Risk Evaluation [SCORE]) assess only short-term CVD risk and classify >98% of women aged <60 years and 80% of men aged <50 years as low short-term risk for CVD39
despite the fact that >1 in 3 adults will develop CVD in their lifetime.38,40,41
In response, recent guidelines on primary prevention of CVD have emphasized long-term risk assessment in individuals at low short-term risk.32,40
By extending the follow-up time in this study, we were able to accrue enough events to assess the reclassification ability of fitness for long-term risk separately in men and women. We observed that the improvement in risk classification persisted even after 25 years of follow-up, particularly in women (). The NRI25
in the overall cohort was lower than the NRI10
, which may be due to changes in fitness level over time, thus weakening the association of fitness with long-term CVD mortality. Nevertheless, these data suggest the potential role for fitness as a novel approach for long-term risk prediction, particularly in women.
Several limitations should be noted. First, the CCLS represents a unique cohort of predominantly white participants with high socioeconomic status and lower risk factor burden compared with the general population.39
Despite these unique characteristics, levels of fitness and the effect of traditional risk factors in the CCLS are overall quite similar to those observed in the general population.41,42
Importantly, we believe that the healthy nature of the CCLS participants actually represents an important strength, providing an estimate of the contribution of fitness to reclassification of risk for CVD mortality among low-risk individuals not referred for exercise testing. Although further analyses regarding cost-effectiveness of exercise testing are needed, simpler methods of fitness assessment, such as the Rockport Walking Test, may make assessing fitness an efficient and effective CVD risk stratification tool.43
Second, the MET levels used in this study are estimated from treadmill testing and not measured by metabolic testing. Although participants were encouraged not to hold onto the railing and were given encouragement to exert maximal effort, the fitness level could be overestimated if subjects used the handrails on the treadmill for support.
Third, we did not have high-density lipoprotein cholesterol in our baseline model, and additional adjustment for high-density lipoprotein cholesterol may have attenuated the effect of fitness on the NRI. However, prior literature suggests a more limited contribution of high-density lipoprotein cholesterol to risk prediction for CVD mortality.44
Similarly, data on other laboratory measurements, such as hemoglobin A1C
and high-sensitivity C-reactive protein, were also not available.
Fourth, using CVD death as the outcome variable based on the National Death Index has well-recognized limitations, with potential misclassification of the cause of death at older ages.45
In addition, competing risks increase with advancing age because of the higher levels of non-CVD death at older ages. Nevertheless, in the present study, we also performed sensitivity analyses using all-cause death as the outcome variable and observed a similar pattern of results. Furthermore, we have shown recently that the effect of fitness on long-term risk for CVD mortality remains even after adjustment for competing risks.41
Finally, we acknowledge that fitness levels and risk factor burden may have changed during the follow-up period. We believe that this observation actually represents an important strength of our findings, suggesting that a single, baseline measure of fitness retains its effect on the reclassification of risk for CVD mortality at 25 years of follow-up.
In a predominantly low-risk, asymptomatic cohort of individuals without known CVD, the addition of fitness to traditional risk factors significantly improves reclassification of the risk of CVD mortality across short-term and long-term follow-up.