In this study, we examined the external validity of the Health ABC HF model in the CHS cohort. The model showed clinically adequate properties in this independent cohort and performed well in sex- and gender-based subgroups. These data support the potential use of this model to determine heart failure risk in the elderly and possibly identify individuals who would benefit the most from preventive interventions.
The Health ABC HF model was developed in a well-functioning, well-characterized, elderly population and showed good performance on internal validation. However, internal validation takes into account only sampling variability; thus, external validation is necessary in order to assess generalizability of a model.18, 19
Moreover, baseline echocardiographic assessment was not performed in the Health ABC Study, raising the possibility that individuals with asymptomatic systolic dysfunction (stage B heart failure) may have been inadvertently included in the analysis. The CHS was designed to assess the development and progression of cardiovascular disease in the elderly and was ideally suited for external validation of the Health ABC HF model. The enrollment criteria provided an opportunity for a broader group of elderly persons to be studied. In contrast to the Health ABC Study, all subjects in the original CHS cohort had a baseline echocardiogram performed. The performance of the model in this independent cohort supports heart failure risk prediction with this tool. Moreover, model performance remained stable when assessed in the subset of individuals with normal left ventricular systolic function, alleviating concerns about the validity of the original results due to potential influence of inclusion of participants with baseline asymptomatic ventricular dysfunction, i.e. in transition from stage B to stage C heart failure. It is important to note, however, that although assessment of ventricular function is not recommended for screening purposes, impaired left ventricular systolic function increases risk for heart failure and, when known, probably adds to risk stratification. Thus, although assessment of ventricular function is not a cost-effective screening procedure in the general population,20, 21
targeted assessment of ventricular function in individuals at intermediate or higher risk for heart failure might be worth investigating in prospective studies.
Literature continues to evolve elucidating the differences between men and women with respect to risk factors and outcomes related to cardiovascular diseases.22, 23
The majority of previous literature on heart failure risk factors was derived from white populations, including the Framingham Heart Failure Risk Score.24
We have previously demonstrated that blacks have a higher accumulation of heart failure risk factors, a higher prevalence of heart failure, and worse outcomes once heart failure develops.25
. Even for risk factors that are predictive of heart failure in both white and blacks, there are significant differences in the population attributable risk for these risk factors -- a prime example being electrocardiographic left ventricular hypertrophy --between the two races.25
These differences derive in turn from differences in the prevalence and relative contribution of the various risk factors and may directly affect the performance of a predictive model in different racial and sex groups. Based on these important differences in race- and gender-based subgroups, it is important for any risk prediction scheme to be tested in these specific populations. Without a wide applicability of screening tools in the general population, the practical applicability may be significantly limited. The Health ABC HF model was the first attempt to systematically stratify heart failure risk in these major demographic subgroups.5
In this external validation study, the model had adequate performance in white women; however, risk was underestimated among white men in the intermediate risk category. The cause of this deviation is not obvious and may represent a more prominent role of non-traditional risk factors, necessitating assessment of other risk markers for further risk classification in the intermediate risk male population. On the other hand, we did not observe systematic effects of race on model performance; however, the overall number of participants and events was low in black men and black women and therefore these results need to be cautiously interpreted.
Considering the increasing proportion of elderly individuals in the population, the already worsening heart failure epidemic is likely to accentuate.3, 26
This will have major clinical, quality of life, and economic consequences. For many other common, lethal, and costly diseases, like breast or colon cancer and coronary heart disease, there are specific tools to either risk stratify individuals or perform screening tests to detect high risk individuals.27–29
Heart failure is an exception where there are no targeted risk stratification tools.30
This is partly rooted in the belief that treating individual risk factors like hypertension or diabetes would reduce the risk for heart failure. Although largely true, such an approach misses many details and opportunities. For example, there is a growing literature that treating blood pressure with different agents leads to a differential reduction in cardiovascular risk,31
and that for other risk factors, like diabetes, intensive control may have no impact on certain clinical outcomes.32
Treatment of individual risk factors is a disease- and not a patient-based approach. Many subjects have multiple risk factors that act in concert to determine an individual’s risk. Therefore, patients may need differential control of risk factors if multiple risk factors coexist, e.g. hypertension control in individuals with both hypertension and diabetes is different than those with hypertension alone.33
Moreover, evidence suggests that among agents used to control a risk factor, e.g. hypertension, there may be differential preventive effects regarding development of heart failure. For example, in the ALLHAT trial,34
there was a significantly higher risk of new onset heart failure with doxazosin-based therapy. Similarly, there were quantitative differences in incident heart failure between chlorthalidone-based versus lisinopril- or amlodipine-based therapy.34
These data suggest that careful therapeutic consideration needs to be given when attempting to treat risk factors for heart failure in order to achieve maximum benefit. Also, the Health ABC model could serve as a tool to identify individuals who might require intensified control of individual risk factors based on the overall heart failure risk profile; however, this concept is speculative and needs further study. It is also likely, though not proven, that non-pharmacologic life style interventions might reduce heart failure risk in high-risk individuals. The Health ABC HF model therefore puts the risk for incident heart failure development in a comprehensive perspective and may potentially be used both for individual risk assessment and for intervention evaluation in research settings.
Both the Health ABC Study and CHS enrolled older adults. However, as the risk factor profile for cardiovascular diseases, including obesity and metabolic syndrome increases in the society,35
it is possible that a higher proportion of younger individuals may develop heart failure.36
How the Health ABC HF model will perform for risk assessment in younger individuals needs further study. Neither the Health ABC Study nor CHS had left ventricular function systematically assessed after heart failure development and thus the differential properties of the model for prediction of heart failure with reduced vs. preserved left ventricular systolic function need further investigation. Prevalence of risk factors and their impact on developing disease may vary by race; for example, risk for coronary heart disease in subjects of Asian descent tends to be lower at the same levels of risk factors like body mass index or cholesterol levels.37
The performance of the model in individuals not of white or black race needs further study. In addition, risk calculation is based on accurate identification of prevalent risk factors in a population; although variability in risk factor ascertainment is less of a concern for physical examination (e.g. blood pressure), laboratory (e.g. serum creatinine), and behavioral (e.g. smoking) parameters, ascertainment of coronary heart disease may be challenging. Despite the vigorous study design of CHS,8
documentation of coronary imaging or revascularization is not always present, and history of myocardial infarction, and even more so angina, can be subject to interpretation. This can adversely affect the model estimates as presence of coronary heart disease may be overdiagnosed (e.g. subjective chest pain and use of beta-blockers or calcium blocker for other indications like hypertension) or underdiagnosed (e.g. recall bias or suboptimal therapy). Also, it is important to note that the Health ABC HF model is based on inpatient incident heart failure and, therefore, provides only an estimate of the risk of hospitalization for incident heart failure among the elderly. Finally, in the development of the Health ABC HF prediction model, we specifically focused on commonly available clinical variables that may be suitable for screening purposes. Imaging modalities and biomarkers may also help classify risk further, especially in the intermediate risk group. However, the cost-effectiveness of these more expensive tests needs further study.
In conclusion, the Health ABC HF model demonstrated adequate performance for heart failure risk assessment in a large, prospective cohort. Whether determination of heart failure risk in the community using this tool and subsequent lifestyle or other intervention will help reduce heart failure incidence needs further study. Considering the epidemiologic trends in both, the societal demographics and the cardiovascular risk factor profile, such efforts are essential.