Heart Failure Risk Prediction in Childhood Cancer Survivors: Where Is Our Crystal Ball?

A key goal of preventive medicine is to anticipate and, when possible, prevent premature sickness and death. Cardiovascular risk profiles have allowed physicians to identify patients who are at increased risk of cardiac disease and to stratify, follow, treat, and counsel patients on the basis of the likelihood of disease. The Framingham Heart Study, the longest-running epidemiologic investigation in history, exemplifies the power of longitudinal cohort studies to identify risk factors for cardiovascular disease. Framingham data have been used to create disease-specific risk prediction tools for cardiovascular disease outcomes, including a points-based risk score for congestive heart failure (CHF) that includes hypertension, left ventricular hypertrophy, and a history of diabetes mellitus. Cardiac risk prediction models are currently a topic of great interest in preventive cardiology. For example, in November 2013, the American College of Cardiology and American Heart Association (ACC/AHA) released highly publicized recommendations for cholesterol-lowering therapy in adults with normal or mildly elevated low-density lipoprotein cholesterol and a 10-year anticipated risk of atherosclerotic cardiovascular disease of 7.5% or higher. Such risk-based recommendations require accuracy and precision when treatment decisions hinge on identifying patients at high risk. In the article that accompanies this editorial, Chow at al report on their study that derived and tested a new prediction model for the risk of heart failure among survivors of childhood cancer. The investigators used the Childhood Cancer Survivor Study (CCSS), a multiinstitutional research initiative funded by the National Cancer Institute, to systematically report long-term health outcomes after cancer therapy. This large, retrospective cohort included more than 14,000 survivors who were diagnosed with cancer before age 21 years, were treated between 1970 and 1986, and were alive at 5 years after cancer diagnosis with ongoing longitudinal follow-up. Medical records were abstracted to obtain detailed treatment data, including doses of chemotherapy and radiation. Cardiovascular outcomes were determined on the basis of participant responses to mailed questionnaires asking about CHF, coronary artery disease, valvular heart disease, and arrhythmia. Outcomes were included if they were severe, life threatening, or fatal on the basis of the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) grading system. The CTCAE categorized cardiomyopathy or congestive heart failure requiring medication as grade 3 (severe), cardiac transplantation as grade 4 (life threatening), and death as grade 5. Cardiac deaths were also ascertained by linking the cohort to the National DeathIndex.Inall, therewere285CHFeventsyieldingacumulative2.8% incidenceofCHFincancersurvivorsand0.3%inacomparisoncohortof CCSS siblings before age 40 years. Chow et al use logistic regression to identify the strongest predictors of CHF in young cancer survivors: female sex, younger age at cancer diagnosis, increasing doses of anthracycline chemotherapy (doxorubicin-equivalent doses), and direct radiation to the chest or heart. Three prediction models simulate real clinical scenarios in which a detailed off-treatment summary of all cancer modalities may or may not be known. The so-called standard model assigns points on the basis of cumulative doses of both anthracyclines and radiation to the chest. The simple model can be used when specific doses are unknown. A third model incorporates cardiac-specific dosimetry, which seems unlikely to be available outside of a research setting. All three models incorporate sex and age at cancer diagnosis. On the basis of a sum of points, risk is categorized as low, medium, or high, with 0.5%, 2.4%, or 11.7% risk of CHF by age 40 years (standard model). A consistent definition of outcomes is necessary in the derivation of an accurate prediction model. Application of CTCAE grading has been used in oncology clinical trials to standardize harms data. However, the accepted adjudication process in large cardiovascular cohorts relies on clear, established Framingham criteria for heart failure. The CCSS-CHFpredictionmodelincorporatesonlyself-reporteddiagnosisof CHF at CTCAE grades 3 to 5 without standard Framingham criteria or clinical adjudication. Chow et al also accepted self-reported treatment with heart failure medications as a proxy for CHF. However, many heart failure medications are used to treat other cardiac conditions such as hypertension, arrhythmia, or valvular heart disease. In addition, some patients diagnosed with CHF may not be receiving heart failure medications because of adverse effects and/or contraindications. Two additional aspects of the proposed prediction model should be critically appraised: the focus on heart failure symptoms without objective measurement (eg, imaging) of cardiac function, and the lack of data on the role of traditional cardiovascular risk factors. The 2009 American College of Cardiology/American Heart Association heart failure guidelines call for identification of stages in the development of CHF from A (asymptomatic but with risk factors present) through B (characterized by cardiac remodeling), C (symptomatic heart failure), and D (marked symptoms with refractory heart failure). The goal of this staging system is to identify early steps in disease progression for JOURNAL OF CLINICAL ONCOLOGY E D I T O R I A L VOLUME 33 NUMBER 5 FEBRUARY 1