INTRODUCTION

Coronary heart disease (CHD) remains one of the leading causes of morbidity and mortality today. Investigations into the causes of CHD include a recent high quality study which investigated over 50 clinical risk factors for their relationship with incident CHD among 28 024 healthy women [1▪▪]. During a median follow-up of 21.4 years, the leading risk factors for incident (first) CHD event (composite of first MI, percutaneous coronary intervention, coronary artery bypass grafting, or CHD death) were type 2 diabetes mellitus, insulin resistance, hypertension, tobacco smoking, elevated body mass index, and hyperlipidemia. Surprisingly, the associations of total cholesterol and low-density lipoprotein (LDL)-cholesterol with CHD were small (hazard ratios (HRs) = 1.39 and 1.38, respectively) compared to the association of type 2 diabetes (HR = 10.7), metabolic syndrome (HR = 6.0), and hypertension (HR = 4.6). This was a particularly important study because the methodology included a study population who had not yet developed clinical signs of CHD, which reduces confounding from other interventions if someone had already been diagnosed with CHD [2]. This study also confirms the comparatively low importance of hypercholesterolemia as a target for treatment in the case of primary prevention.

Many clinical practice guidelines focus on the use of 3-hydroxyl-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitor medications to reduce cardiovascular risk [3]. However, a recent study has provided greater refinement as to the effect of treating hypercholesterolemia with HMG-CoA inhibitors. In this meta-analysis of 21 clinical trials involving the use of statins to treat hyperlipidemia, the overall reduction in absolute risk for those randomized to statins in all-cause mortality was 0.8% (95% confidence interval (CI) 0.4–1.2%), for myocardial infarction was 1.3% (95% CI 0.9–1.7%), and for stroke was 0.4% (95% CI 0.2–0.6%) [4▪▪]. The benefits were greater when statin medication was used for secondary prevention of CHD rather than when used for primary prevention.

But, how does a clinician tailor this information for a given patient? Should a clinician merely follow the guidelines and prescribe medications at an arbitrary risk level? Under the principle of shared decision making, some clinicians attempt to individualize and communicate the risks and benefits of using these medications, and then let the patient make their own decision about treatment [5]. This review will discuss recent research about the effectiveness of HMG-CoA reductase inhibitors, and the use of decision-making tools in advising patients about the use of these medications. 

Box 1:

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PRESENTING THE BENEFITS OF HMG-COA REDUCTASE INHIBITORS

When patients are given medications for chronic medical problems like anti-hypertensives and HMG-CoA reductase inhibitors, health practitioners typically say the medication will “reduce your chance of cardiovascular disease, a heart attack or a stroke.” This statement gives the impression that the medication will work 100% of the time to reduce the risk in every patient, in a similar way as prescribing an antibiotic for an infection. However, that is not the case with partially effective medications that reduce – but do not eliminate – the risk of a problem. So the first principle in communication of a partially effective medication like an HMG-CoA reductase inhibitor should be to say something to the effect that “if you take this medication, it is possible that the medicine might help you, and it is possible that the medicine might not help you.” (This language is similar to what is used for informed consent in a research study.) In summary, the first thing to know about using HMG-CoA reductase inhibitors is that not everyone treated with the medication will benefit from the treatment. The next question is, how likely is it that the medication going to help the patient?

PRESENTATION OF MAGNITUDE OF BENEFITS OF HMG-COA REDUCTASE INHIBITORS

When a treatment is not 100% effective, there are several ways to communicate the magnitude of the benefits of the treatment. The most commonly used estimations are called absolute risk reduction and relative risk reduction. For example, if the percentage of people who have an event over a certain period of time is 10% without a treatment, and improves to 6% with a treatment, the absolute risk reduction (ARR) is 4% (ARR = 10% – 6% = 4%). Using the same numbers, another commonly used estimation called the relative risk reduction (RRR), is in this instance: 40% (RRR = (10% − 6%)/10%)). In this example, there is a large difference between a 6% ARR and a 40% RRR. If the RRR of 40% was mistaken for a 40% ARR, it would give you the impression that the absolute risk is going to be reduced by 40%, for example from 50% to 10% in terms of absolute risk of an event. But the ARR and RRR are not the same risk reduction at all. So, one major limitation to presenting information using ARR and RRR is the misinterpretation of the meaning.

Another complicating aspect of using these medications is that benefit of an HMG-CoA reductase inhibitor depends upon whether someone already has heart disease or not. There is greater clinical effect if the individual already has cardiovascular disease. “Primary prevention” means the individual has no history of heart disease. Primary prevention means preventing a first heart attack or the initial development of cardiovascular disease. “Secondary prevention” means the individual already has cardiovascular disease (stroke, heart attack). The benefit is greater in secondary prevention.

PRESENTATION OF MAGNITUDE OF BENEFITS USING THE NUMBER NEEDED TO TREAT

Another popular way to communicate the partial effectiveness of a treatment is to use a concept called the “number needed to treat,” or NNT [6,7]. The number needed to treat is the reciprocal of the absolute risk reduction or absolute risk increase (NNT = 1/ARR or 1/ARI). The NNT quantifies the number of individuals that are needed to be treated with a medication or other intervention in order to prevent an outcome in one person. The NNT is helpful when addressing treatments that are not 100% effective. If you prescribed an antibiotic that cures a bacterial infection in every case, this antibiotic would have an NNT of 1: treat one person and that person has a positive result. That is to say, everyone gets benefit.

As shown in Table 1, if a medication reduces the risk from 100% to 50%, the absolute risk reduction is 50%, the NNT is 2 (1/0.5), which means that two people need to be treated to help one person. If a medication reduces the risk from 100% to 95%, the absolute risk reduction is 5%, the NNT is 20 (1/0.05), which means 20 people need to be treated to help one person. Note in this table that the NNT does not give you information about the absolute risk of the event. An NNT of 2 could represent an ARR of 100% to 50% or an ARR of 20% to 10%. So, the NNT should always be interpreted in the context of the absolute risk.

Table 1 - Examples of absolute risks, relative risks and number needed to treat Absolute risk of outcome Before After Absolute risk reduction Number needed to treat (1/absolute risk reduction) 100% 0% 100% 1/1 = 1 100% 50% 50% 1/0.5 = 2 100% 75% 25% 1/0.25 = 4 100% 95% 5.0% 1/0.05 = 20 100% 98% 2.0% 1/0.02 = 50 50% 0% 50% 1/0.5 = 2 50% 25% 25% 1/0.25 = 4 50% 45% 5.0% 1/0.05 = 20 50% 48% 2.0% 1/0.02 = 50 10% 0% 10% 1/.10 = 10 10% 5% 5.0% 1/0.05 = 20 10% 8% 2.0% 1/0.02 = 50 10% 9% 1.0% 1/0.01 = 100

The NNT may have a different relevance depending upon the absolute risk. If the problem always occurs, and the 2% risk reduction is from 100% to 98% − meaning that there is a chance that you survive, then of course you would take the treatment, even though a 2% absolute risk reduction means it only works for every 1 in 50 individuals.The NNT may have a different relevance depending upon outcome is at risk. If the risk is death, heart attack or stroke, then these are given more weight than elevated liver function blood tests and myopathy, but would carry the same weight as death from rhabdomyolysis.NNT, number needed to treat.

Considering the specific case of an HMG-CoA reductase inhibitor, one representative study showed a 91.3% survival for those taking the medication over 5 years, compared to an 87.7% survival for those taking placebo: this represents an absolute risk reduction of 3.6%, the NNT is 27.8 (NNT = 1/0.036), which means about 28 people need to be treated to reduce one death over 5 years.

So, the first principle in communication of an incompletely effective medication like an HMG-CoA reductase inhibitor should be to say something to the effect of “if you take this medication, it is possible that the medicine might help you.” Then, how likely the medication going to help you can be communicated by the NNT: you will have a 1 in 28 chance of being helped by this medication. Because the clinical benefit varies based on underlying risk, an individual who takes a HMG-CoA reductase inhibitor may have a range of benefit from 1 in 10 to 1 in 40 for secondary prevention, and from 1 in 50 to 1 in 120 for primary prevention. (Table 2, Table 3) One benefit to using the NNT is that there is no confusion as to whether the risk you are communicating is the ARR or the RRR. A major problem with using the NNT is that most people are not accustomed to thinking in this way. In other words, most people expect that the medication will give them benefit, when most will not benefit.

Table 2 - AR, ARR and NNT for statin medication when used for primary prevention of cardiovascular disease Absolute 5-year risk all endpoints Placebo Statin Absolute risk reduction Number needed to treat 5.5% 3.5% 2% 1/.02 = 50

AR, absolute risk; ARR, absolute risk reduction; NNT, number needed to treat.

Table 3 - AR, ARR and NNT for statin medication when used for secondary prevention of cardiovascular disease Absolute 5-year risk of death Placebo Statin Absolute risk reduction Number needed to treat 12% 8% 4% 1/.04 = 25

AR, absolute risk; ARR, absolute risk reduction; NNT, number needed to treat.

At a population-level, if a large number of people take the medication, then many people will benefit, but for a given individual there may not be benefit. This is the typical tension between a public health or population perspective versus the individual patient perspective. “What is best for the individual” is not always “what is best for society in general.” From the perspective of the individual, it is not possible to predict which patients will experience the benefits, and which patients will experience the risks.

The NNT can be refined and extended in several ways. For example, a time dimension may be added so that the NNT may refer to the risk of an event over a 5- or 10-year period. Many risk calculations will include, “your risk of a cardiovascular event is 10% over the next 10 years,” for example.

PRESENTATION OF LIKELIHOOD OF HARM OR SIDE EFFECTS

The inverse of the absolute risk increase can be calculated and this is known as the “number needed to harm” (NNH) For HMG-CoA reductase inhibitors, there is a risk of muscle aches, diabetes, and rarely very severe side effects. The current estimate of the NNH for muscle pain is 1 in 10, and for diabetes in 1 in 50 [8]. Additionally, the NNT can be augmented by combining the benefit and the risk into one number called the “NNTnet.” In this case, the denominator subtracts the absolute increase from the absolute risk reduction[9].

ON-LINE TOOLS FOR DECISION-MAKING: CVRISKCALCULATOR

This is a tool to calculate an individual's risk of cardiovascular disease based on the a widely used clinical guideline and is for primary prevention only (no prior cardiovascular disease, stroke, or myocardial infarction) [10]. The input variables are age, gender, race, total cholesterol, high-density lipoprotein (HDL)-cholesterol, systolic blood pressure, diastolic blood pressure, treated for high blood pressure, presence of diabetes, smoker. The calculator then gives you an estimate of your 10-year risk of heart disease or stroke using the atherosclerotic cardiovascular disease (ASCVD) algorithm published in 2013 [11].

ON-LINE TOOLS FOR DECISION MAKING: MAYO CLINIC STATIN DECISION AID

(https://statindecisionaid.mayoclinic.org/).

This on-line resource gives the option of using three different prediction tools to estimate the individual's cardiovascular risk over the next 10 years and the predicted benefit from using either low-dose or high-dose statin treatment [12]. Options exist for using the American College of Cardiology/American Heart Association algorithm, Framingham and Reynolds (if high-sensitivity C-reactive protein if available) risk prediction models.

The output is displayed in a graph that the absolute risk, relative risk, as well as the predicted absolute risk reduction of low and high-dose statin treatment. The example shown in Fig. 1 shows an individual with a risk of 2% (2 in 100, graph on the left), and that the risk will go down to 1% (1 in 100, graph on the right) with statin treatment. As shown in the graph, over 10 years with statin treatment in this low risk situation, 1 person will have a heart attack, 98 will not have a heart attack, and one person will be “saved from” a heart attack. The ARR is 1%, the RRR is 50%, and the NNT is 1 in 100.

FIGURE 1:

Using the Mayo Statin Decision Aid Tool: Low Risk. Using this decision tool, for this individual the calculated risk of 2% (2 in 100) will be reduced to 1% (1 in 100) with statin treatment.

Figure 2 shows an individual with a risk of 48% (48 in 100, graph on the left), and that the risk will go down to 29% (29 in 100, graph on the right) with statin treatment. So, over 10 years with statin treatment in this high risk situation, 29 people will have a heart attack, 52 will not have a heart attack, and 19 people will be “saved from” a heart attack. The ARR is 19%, the RRR is 48%, and the NNT is 1 in 5.

FIGURE 2:

Using the Mayo Statin Decision Aid Tool: High Risk. Using this decision tool, for this individual with a calculated risk of 48% (48 in 100) will be reduced to 29% (29 in 100) with statin treatment.

REFINEMENT OF DETERMINATION OF RISK AND BENEFIT

These recommendations for use of HMG-CoA reductase inhibitors are largely based on older clinical trials, and there may be newer refinements of the risks and benefits based on research published since that time. For example, in primary prevention, there may be subgroups who have even less risk or less benefit from taking these medications. For example, if an anatomical test shows the absence of cardiovascular disease, or a blood test shows very low levels of inflammation, the benefit from a statin treatment may even be lower in these instances [13,14]. In one study, using a Coronary Artery Calcium (CAC) score to determine cardiac risk, the estimated number needed to treat (NNT) in 10 years to prevent 1 event varied greatly according to CAC score. For ASCVD events, the NNT was 87 for CAC = 0 and 19 for CAC >100. For CHD events, the NNT was 197 for CAC = 0 and 28 for CAC >100 [13]. In another study, the predicted 5-year NNT was 549 for CAC score 0, 94 for scores 1–100, and 24 for scores greater than 100. For cardiovascular disease, the NNT was 124, 54, and 19 [15]. Another study found that a CAC score of 0 was associated with a low risk of cardiovascular events, suggesting the utility of CAC score assessment for stratifying risk [16].

LIMITATIONS OF DECISION TOOLS

These tools are used only in the case of primary prevention. The general consensus is that everyone should be taking an HMG-CoA reductase inhibitor for secondary prevention. The data entry inputs have a limited range; for example, the upper limit for age is 70, and for HDL-cholesterol is 100. If an individual is over the age of 75 not all experts agree the benefits outweigh the risks for primary prevention [8].

Recommendations are then given based on the individual's situation, but these guideline recommendations are directed toward the medication management of these conditions (aspirin, cholesterol-lowering medications), and do not include non-medication options (i.e. lifestyle or surgery).

WHAT IS A DESIRABLE NUMBER NEEDED TO TREAT?

Although the optimal NNT is one, there is a wide range of NNT when experts create policy recommendations. These aids and recommendations cannot take into account the risk-taking or risk-aversive behavior of a given individual. Does the individual want to do everything that he/she can to prevent this problem, even if it is possible that there might be a side effect? In a study assessing ways to communicate stroke prevention with aspirin in the context of atrial fibrillation, there was a wide range of risk acceptance to get benefit [17]. Patients required at least a 0.8% (NNT = 125) annual absolute risk reduction and 15% relative risk reduction in the risk of stroke in order to agree to initiate antithrombotic therapy. Patients were willing to hypothetically endure 4.4 major bleeds in order to prevent hypothetical stroke. There was a substantial amount of inter-individual variability in opinion regarding tolerance of bleeding risk in the hypothetical clinical situation.

CONCLUSION

Decision aids are available to assist patients in deciding about whether to take partially effective medications like HMG-CoA reductase inhibitors. The beneficial effect of these medications for hyperlipidemia depends upon the prior risk of cardiovascular disease of the individual. If cardiovascular disease is already clinically apparent, most experts would agree the benefits outweigh the risks. However, if a serious adverse effect develops, then the decision making may change.

Acknowledgements

None.

Financial support and sponsorship

None.

Conflicts of interest

Dr Westman receives royalties from book sales and has founder shares in Adapt Your Life, a company based on low-carbohydrate diet principles.

REFERENCES AND RECOMMENDED READING

Papers of particular interest, published within the annual period of review, have been highlighted as:

▪ of special interest

▪▪ of outstanding interest

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