When to Start a Statin Is a Preference-Sensitive Decision
Article, see p 1087
In this issue of Circulation, Heller et al1 report results of a simulation model suggesting that the American Heart Association/American College of Cardiology (AHA/ACC) primary prevention lipid treatment guidelines treat many more people with a statin but also save many more lives compared with ATP III. These findings are consistent with previous reports,2,3 but their results further suggest that starting a statin at 40 years of age in everyone regardless of cardiovascular disease (CVD) risk would extend statin treatment to >28 million more Americans but would further and substantially improve the public’s health, but only if the disutility associated with pill burden is quite low.
Public Versus Individual Decisions
If starting a statin in all adults at 40 years of age would really save hundreds of thousands of quality-adjusted life years (QALYs), implementing such a policy would seem to be a public health priority. However, this perspective has several problems. Principally, taking a statin is an individual not a public health decision, such as interventions to improve air quality or a decision with externalities, such as treating contagious diseases. For an individual decision without externalities, an individual’s chance and magnitude of net benefit (absolute risk reduction minus absolute risk increase plus/minus uncertainties) is the only meaningful consideration.4 This may sound heretical, especially coming from a professor of public health, but the ethical and legal standards are clear. When counseling an individual patient about treatment, the most relevant question is almost always, “What is the magnitude of and uncertainty bounds for estimated net benefit for the considered treatment?” Heller et al1 present a relevant estimate in this regard. If their base-case estimates are correct, adoption of the treat at 40 years of age policy, compared with AHA/ACC guidelines, would average 1 additional QALY gained for every additional 1080 statin treatment years (ie, number needed to treat [NNT]=1 QALY gained per 108 patients treated for 10 years).
However, this average NNT hides dramatic variation in the expected benefits among individuals in the additional 28.8 million Americans who would start a statin under a treat at 40 years of age strategy beyond those treated by the AHA/ACC guidelines. For a 40-year-old woman with a baseline risk of <1%, starting a statin probably would result in net harm even under the optimistic assumptions, and a 55-year-old with a 7.4% 10-year CVD risk would have about the same estimated net benefit as a patient with a 7.6% 10-year risk. Personally, although an age criterion only is certainly quite simple, I think estimating an individual’s CVD risk, as proposed by the AH/ACA guideline, is sufficiently simple to move the most important question to, “At what CVD risk should a statin be started?”2
An appreciation of the individual perspective for individual decisions inevitably leads to acknowledging a continuum of benefit and the existence of grey zones—a range within which the right decision almost is determined completely by an individual patient’s personal preferences.4–6 In other words, as the chance of benefit declines (NNT=2 versus 25 versus 100 versus 1000), a point must inevitably come when the best decision is highly sensitive to how the patient feels about pursing a small chance of benefit against the treatment’s hassles and potential harms, known and unknown. This phenomenon has been demonstrated for a variety of conditions and decisions, from intensifying glycemic control to taking a daily aspirin.6,7 When the NNT per QALY is relatively low (NNT per QALY <50), competing risks, treatment hassle, and adverse effects tend to be relatively unimportant because the benefits are so substantial. In contrast, as NNT per QALY further increases, treatment decisions soon become highly preference-sensitive. How sensitive? Well, the 0.00384 treatment disutility that Heller et al1 found would neutralize the marginal benefits of the treat at 40 years of age strategy is equivalent to someone saying that, to take a daily statin for the next 10 years, I expect to gain, on average, ≥2 weeks of high-quality life. Personally, this is not the type of low therapeutic window for which I am willing to make strong recommendations to my patients, especially given a variety of unknowns that could dramatically lower the risk-benefit tradeoffs.8
Donald Rumsfeld famously referred to “known unknowns . . . things that we now know we don’t know.” Such unknowns are the raison d’être for researchers, but as Secretary Rumsfeld was implying, decision makers need to make decisions based on the information in hand (see Known Unknowns, below). What people appreciate less is the frequent unknowables in medicine. The null never can be proved, especially when it is something difficult to study, such as whether being on a statin for 20 to 25 years has no major long-term adverse effects. Could being on a statin for 25 years result in a 25% increase in decline in cognitive function or a 35% acceleration in the decline in muscle health associated with aging? Such effects are unknowable given any data source currently available.9 Because starting statins at 40 years of age would result in 10s of millions of people being put on a daily, highly biologically active medication 10 to 20 years earlier than under current guidelines, such questions are relevant. For example, if being on a daily statin for 25 years had even a modest negative impact on common aspects of aging, then it would not just reverse the marginal benefits of routinely starting a stain at 40 years of age, it also would be a public health disaster. How likely is it that such undetectable long-term harm exists? Who knows because how can you estimate the frequency of something that is currently undetectable? I would propose that the unknowability of long-term harms is yet one more reason that when the chance of an individual benefiting is small (such as potentially 1 QALY gained per 1000 treatment years), at most shared decision making without a strong recommendation, either for or against, is in order.
Simulation models are powerful tools, but for informing policy, the known unknowns can have a large impact. Heller et al1 fully acknowledge that one highly influential assumption in their model is unknown. How much does a nonfatal CVD event causally increase a person’s future risk of CVD events and mortality? The answer to this question may seem easily determined but is epidemiologically complex. Heller et al1 assume that a nonfatal CVD event approximately doubles future risk, including mortality. This estimate has strong evidence when predicting a person’s future risk but could be a dramatic overestimation in terms of the benefit of preventing a nonfatal event. Having a heart attack increases a person’s predicted risk of future events for both causal and noncausal reasons. Substantial tissue damage almost certainly causally increases future mortality risk for an individual, but minor CVD events (which are a large proportion of all nonfatal events) increase future risk for the same reason that a high coronary artery calcium score increases predicted risk—because it is a marker for having greater underlying vascular disease than expected. Most of the estimated 1 QALY saved per 1080 statin years is because of extrapolations of future impacts of nonfatal CVD events. Therefore, the Heller et al1 estimated benefits for treating individuals with a lower CVD risk is perhaps a substantial overestimate.
Another uncertain assumption bears mentioning in passing. The Heller et al1 results are fairly favorable regarding the efficiency of the ATP treat to low-density lipoprotein (LDL) target approach. In part, this is related to the assumption that a nonfatal CVD event causally doubles future CVD risks as discussed earlier, but it probably also is influenced heavily by the model’s assumption that the relative effect of a statin is directly related to baseline LDL level. In the absence of direct evidence supporting this assumption and some evidence suggesting that this is not the case,10 the AHA/ACC guideline committee dropped LDL targets and adopted risk-based approaches. It would be quite simple for the Cholesterol Treatment Trialists group to test the relationship between baseline LDL and a statin’s relative effects using data in hand. Answering this important clinical question would let us determine whether an individual’s absolute risk reduction is best estimated by using their 10-year CVD risk alone or whether their baseline LDL level also is important.10 If I were forced to guess, my suspicion is that the impact of baseline LDL has a modest but clinically important impact on a statin’s relative effect on outcomes but not as strong as that assumed by Heller et al.1 There also is a chance that the answer differs for primary and secondary prevention.9
Heller et al1 rightly point out that if there are no unknown harms of long-term statin use, then starting a statin much earlier would have a small chance of helping an individual but a large public health benefit because it would extend statin treatment to >28 million more Americans. Because the chance of each individual benefiting is so small, even a small pill burden would eliminate this benefit and a modest long-term adverse effect of statins (such as an exponentially increasing risk of diabetes mellitus over 20 years) would result in this guideline causing substantial net harm. How one feels about pill burden and potential yet unknown or unknowable treatment harms is more an issue of personal viewpoints and preferences, which in my view puts them in the realm of shared decision making and not clinician recommendations.
The opinions expressed in this article are not necessarily those of the editors or of the American Heart Association.
Circulation is available at http://circ.ahajournals.org.
- © 2017 American Heart Association, Inc.
- Heller DJ,
- Coxson PG,
- Penko J,
- Pletcher MJ,
- Goldman L,
- Odden MC,
- Kazi DS,
- Bibbins-Domingo K
- Sussman JB,
- Vijan S,
- Choi H,
- Hayward RA
- Hayward RA
- Sauser K,
- Levine DA,
- Hayward RA
- Hofer TP,
- Hayward RA