Risk Assessment: Taking the Long View
ACCEL | Few topics have received as much attention in cardiovascular literature in the last few years as risk prediction. Broad risk scores go back to the Framingham Risk Score (FRS, 1991 and 1998), Adult Treatment Panel III (ATP III), PROCAM (Prospective Cardiovascular Munster), SCORE (Yes, the Systematic Coronary Risk Evaluation or SCORE score), QRISK (QRESEARCH Cardiovascular Risk Algorithm), the Reynolds score (one for men and another for women), and the Framingham Global CVD risk score (2008). Then there are highly specific scores, such as the “family” of CHADS scores to assess AF stroke risk. Named for various risk factors and their points, there are CHADS2, CHA2DS2-VASc, and, as discussed in the January 2015 issue of ACCEL, perhaps R2CHADS2 to account for renal function as a strong risk factor. And don’t forget the counterbalancing bleeding risk assessment tools: HAS-BLED, HEMORR2HAGES and ATRIA.
Five- and 10-year risk estimates were widely adopted by ATP III and other guidelines, usually based on multivariable regression equations—such as those derived from the Framingham cohorts—in which the levels of traditional risk factors (age, total cholesterol, high-density-lipoprotein cholesterol, systolic blood pressure, smoking status) are assigned weights (points) to predict CHD events. The calculated risk score is then converted into an absolute probability of developing CHD within that time frame.
In brief, the ATP IIII paradigm was that intensity of prevention efforts should match the absolute risk of the patient. Thus, if the estimated 10-year risk (based on FRS) was <10%, lifestyle modification was recommended; if the 10-year risk was between 10% and 20%, then further testing might be appropriate to determine whether a better approach would be lifestyle modification with or without drug therapy. If the 10-year risk was >20%, or the patient had diabetes mellitus, then a combination of lifestyle changes with pharmacotherapy was recommended.
Ten years is commonly used as the interval for risk estimation and was chosen as the focus for a variety of reasons. According to Donald M. Lloyd-Jones, MD, consideration of the 10-year risk identifies those patients most likely to benefit from drug therapy in the near term, thus improving cost effectiveness and safety of therapy.1 In addition, robust data for estimation of current CVD risks associated with risk factors in a contemporary environment require a focus on shorter-term follow-up.
The risk for CHD associated with traditional risk factors is continuous across the population, and there are no obvious natural thresholds. Nonetheless, the thresholds used by ATP III for clinical decision-making were determined from population data and cost-effectiveness estimates in an era when statin medications cost substantially more than they do currently. Thus, the 2001 ATP III document was a dated—almost historical—document by the time a new approach was developed and published in 2013.2
The new risk assessment tool has been the subject of several recent ACCEL interviews (Blumenthal, August 2014; Forrester, September 2014; and Stone, November 2014). The controversy that emerged from the new tool and cholesterol guidelines played out across medical journals (including worldwide criticism), the popular press, and hallways and sessions at local, national, and international medical meetings.
The condensed version of the history of the documents: in 2008, the National Heart, Lung and Blood Institute commissioned three expert panels (on cholesterol treatment, blood pressure treatment, and obesity and overweight management) and cross-cutting and supporting work groups (focused on lifestyle and risk assessment) to create updated clinical practice guidelines for cardiovascular disease prevention. (These were discussed in the February 2011 and November 2012 issues of ACCEL, by Sidney C. Smith, Jr., MD.)
With the federal government’s decision to get out of the guidelines business, the American Heart Association and American College of Cardiology completed and published the documents on November 12, 2013. For the first time, the guideline panels and work groups took an approach that was based almost solely on systematic reviews of the medical literature and synthesis of high-quality evidence. There was much less of the “expert consensus” of previous guidelines and the early consensus was that this was highly unusual and highly controversial. Certainly, the cholesterol guidelines and risk assessment tool redirected the focus from reducing LDL cholesterol levels to reducing CV risk by promoting personalized decisions about statin use.
Pitfalls of Short-Term Risk Estimates
Dr. Lloyd-Jones admits there are pitfalls associated with short-term risk estimates:
- The vast majority of younger adults (men <50 years and women <70 years) are considered to be at “low risk” regardless of risk-factor burden (based on the weight given to age, the 10-year risk window, and the clinical treatment thresholds imposed).
- There is a difference between low risk and no risk, and the former should not be considered the latter.
- Addressing multiple moderate or single elevated risk factors for truly long-term CHD prevention is important.
- Reliance solely on estimates of short-term absolute risk is problematic when they are used to communicate risk and make treatment decisions.
In an era when age is given such weight, it’s important to note the abundance of data in recent years demonstrating that the roots of CVD are often demonstrated as early as adolescence. Partly due to the obesity epidemic, we also know that CVD in general and diabetes in particular are emerging earlier than in generations past.
How big of an issue are we talking about? According to National Health and Nutrition Examination Survey (NHANES) data from 2003 through 2006, 56% of American adults have low short-term but high lifetime predicted risk.3 In other words, the analysis by Dr. Lloyd-Jones and colleagues suggests that while 82% of US adults are at low short-term risk, about two-thirds of this group, or 87 million people, are at high lifetime predicted risk for cardiovascular disease.
Dr. Lloyd-Jones emphasizes that it’s not 10-year or lifetime risk assessment, but rather 10-year and lifetime risk assessment for CVD. As he noted, lifetime risk estimation:
- Is the absolute cumulative risk of an individual developing a given disease before death.
- Accounts for risk of disease of interest, remaining life expectancy, and competing causes of death.
- Reflects real-life risks and population burden of disease better than Kaplan-Meier cumulative incidence.
- Allows for comparison of disease burden now and in the future.
Is lifetime risk assessment viable? Dr. Lloyd-Jones and colleagues conducted a meta-analysis at the individual level using data from 18 cohort studies involving a total of 257,384 black and white men and women whose risk factors for CVD were measured at the ages of 45, 55, 65, and 75 years.4 Blood pressure, cholesterol level, smoking status, and diabetes status were used to stratify participants according to risk factors into five mutually exclusive categories. They observed marked differences in the lifetime risks of CVD across risk-factor strata.
Among participants who were 55 years of age, those with an optimal risk-factor profile had substantially lower risks of death from CVD through age 80 than participants with two or more major risk factors (4.7% vs. 29.6% among men, 6.4% vs. 20.5% among women). Those with an optimal risk-factor profile also had lower lifetime risks of fatal CHD or nonfatal MI (3.6% vs. 37.5% among men, <1% vs. 18.3% among women) and fatal or nonfatal stroke (2.3% vs. 8.3% among men, 5.3% vs. 10.7% among women). Similar trends within risk-factor strata were observed among blacks and whites and across diverse birth cohorts.
He argues that lifetime risk estimates can help develop a “high-risk strategy” that can identify younger individuals with low short-term but high lifetime risk. It also helps with a “population strategy” that can be used to better communicate risk, raise disease awareness, and motivate lifestyle change and adherence to preventive therapy.
Obviously, more data are necessary. Until then, current evidence supports the idea that lifetime risk estimates may be an important adjunct to 10-year risk estimates.
Novel Markers of Risk
Members of the guidelines Work Group considered a list of novel risk markers, prioritized based on factors that have engendered substantial discussion in the scientific community and that could be reasonably considered as feasible for widespread use in routine clinical settings in the US.
The final list of new risk markers evaluated included several blood and urine biomarkers: apoB, high-sensitivity C-reactive protein (hs-CRP), creatinine (or estimated glomerular filtration rate), and microalbuminuria. Several measures of subclinical cardiovascular disease were considered, too: coronary artery calcium, carotid intima-media thickness (CIMT), and ankle brachial index (ABI). Plus, the Work Group considered family history and cardiorespiratory fitness.
Of this list, four were deemed—based on current (limited) evidence—to show promise for clinical utility: assessments of family history of premature CVD and measurement of hs-CRP, CAC, and ABI (TABLE). The rest (with one exception) were thought to lack sufficient evidence, at the moment, meaning no recommendation was possible. The exception: the guidelines recommend against measuring CIMT in routine clinical practice for risk assessment of a first atherosclerotic CVD (ASCVD) event. The decision to give CIMT a Class III recommendation (no benefit) was based on not only a lack of evidence supporting its use but also concerns about measurement quality.
Thus, the guidelines state: “If, after quantitative risk assessment, a risk-based treatment decision is uncertain, assessment of one or more of the following—family history, hs-CRP, CAC score, or ABI—may be considered to inform treatment decision-making.”
Editor’s Note: A web-based application enabling estimation of 10-year and lifetime risk of ASCVD is available here.
- Lloyd-Jones DM. Circulation. 2010;121:1768-77.
- Goff DC, Lloyd-Jones DM, Bennett G, et al. J Am Coll Cardiol. 2014;63(25_PA):2935-59. Marma AK, Berry JD, Ning H, Persell SD, Lloyd-Jones DM. Circ Cardiovasc Qual Outcomes. 2010;3:8-14.
- Berry JD, Dyer A, Cai X, et al. N Engl J Med. 2012;366:321-9.
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