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November 15, 2016

Cholesterol, Cardiovascular Risk, Statins, PCSK9 Inhibitors, and the Future of LDL-C Lowering

Author Affiliations
  • 1Division of Cardiovascular Medicine, Stanford University, Stanford, California
  • 2Department of Medicine, Stanford University, Stanford, California
JAMA. 2016;316(19):1967-1968. doi:10.1001/jama.2016.16575

The primary and especially secondary prevention of coronary heart disease (CHD) through aggressive reduction of low-density lipoprotein cholesterol (LDL-C) has been one of the major public health accomplishments of the last 3 decades. Natural experiments have consistently shown that populations with low LDL-C levels experience a lower risk of CHD, whereas those with genetic mutations that confer higher LDL-C levels have a substantially higher risk of CHD events. Results from clinical trials have convincingly demonstrated that LDL-C is dose-dependently linked to CHD risk,1,2 suggesting a causal role in the atherogenesis pathway.

There is reliable, high-quality evidence that LDL-C is an intermediate marker that fulfills the criteria of surrogacy in the relationship between statins and CHD risk.3 However, whether this holds true with other drug classes remains to be determined. Recent negative trials with nonstatin lipid-lowering therapies of niacin and torcetrapib have shown that not all LDL-C–lowering strategies are equal in their ability to reduce both LDL-C levels and risk of CHD.4 Results from the Improved Reduction of Outcomes: Vytorin Efficacy International Trial (IMPROVE-IT) suggest that, in high-risk (post–myocardial infarction) patients, lowering LDL-C with the combination of moderate-intensity statin therapy and ezetimibe provides a modest and predictable clinical benefit.5

Similarly, clinical trial data from the proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors show promise of further reducing cardiovascular risk by lowering LDL-C beyond maximally tolerated statin therapy.6 In a recent systematic review and meta-analysis, Silverman and colleagues2 reported that statin and nonstatin therapies that act by upregulating the LDL receptor have similar effects on LDL-C lowering and thus on the subsequent risk of CHD events. However, these findings require long-term confirmatory clinical trials to ensure new drug safety and efficacy, particularly as they relate to PCSK9 inhibitors. To date, the PCSK9 inhibitors appear to be well tolerated, but the duration of clinical follow-up and data on CHD outcomes have been limited; in particular, there is interest in understanding the risk of neurocognitive adverse effects and diabetes associated with these agents. A series of large, long-term randomized clinical trials testing different PCSK9 inhibitors in patients with cardiovascular disease are under way and will be reported in the next few years.

Against this background, the 2013 American College of Cardiology/American Heart Association (ACC/AHA) cholesterol guidelines were a stark departure from prior iterations by shifting away from target LDL-C categories and instead describing 4 “statin benefit groups.”7 Because statins predictably lower LDL-C, this guideline recommended high-intensity statin treatment for the highest-risk groups of individuals who stand to benefit most from treatment. The subsequent 2016 ACC consensus statement provides further guidance on selective nonstatin therapies to treat those with residual risk.8 The statement specifically recommends ways to ensure adequacy of statin therapies and fills gaps from the 2013 guidelines. For example, for patients with atherosclerotic cardiovascular disease receiving statin therapy for secondary prevention and who have less than a 50% LDL-C reduction, have not reached expected LDL-C targets, or both, clinicians should consider intensifying lifestyle interventions and adding ezetimibe (first-line treatment) or PCSK9 inhibitors.

Of course, clinicians do not treat populations, but rather, treat individual patients. Some patients may not achieve the desired LDL-C lowering with statins alone, and others may be unable to tolerate high-intensity statin therapy owing to adverse effects such as muscle pain. Some patients with high LDL-C levels will never experience a cardiovascular event, whereas some with low LDL-C levels may experience an unexpected myocardial infarction. Moreover, statins are not free of adverse effects, including myopathy, new-onset diabetes, and possibly hemorrhagic stroke.1 The role of precision medicine is therefore of paramount importance in helping clinicians select which patients will tolerate and benefit the most from a given therapy, such as high-intensity statins, and when to add nonstatin therapies (ie, ezetimibe and PCSK9 inhibitors) to lower residual cardiovascular risk. Clinical risk scores and calculators, while useful in facilitating patient conversations and decision making, have limitations because they are population-based, may not have adequate predictive information on diverse patient populations, and also fail to consider lifetime risk. Ultimately, results from randomized trials and observational outcomes studies need to be generalizable to the diverse patient populations seen in clinical practice.

Where do clinicians go from here? The challenge and the opportunity are to reconcile population- and individual-based treatment approaches through the tools of modern investigation, including implementation science. For example, even though there is substantial evidence that statins effectively lower LDL-C and predictably reduce cardiovascular events, fewer than half of patients with clinical CHD are being treated with high-intensity statins9; thus, many patients with clinical CHD remain at high risk of future events. Addressing this residual risk necessitates a multilevel approach involving creative system-based solutions (ie, pragmatic clinical trials embedded in the electronic health record) as well as patient-level interventions (ie, point-of-care drug efficacy and safety testing).

To improve adherence to the therapies that work for secondary prevention (ie, statins), one approach is to leverage social media and digital health. Text messaging reminders and virtual health coaching are just a few ways in which patients can be engaged in shared decision making. In a digital platform, patients can query their physicians about symptoms such as myalgias before stopping their statins, giving physicians an opportunity to suggest a different statin or an alternative dosing strategy that is better tolerated. The concepts of social networking with peers may also be valuable in understanding and promoting drug and lifestyle adherence.

Finally, the role of discovery science in developing more precise risk-prediction models cannot be overstated. By studying large, diverse populations, it should be possible to identify patients at greatest risk by incorporating information from their genes, proteins, metabolites, environment, and behaviors. In essence, these insights gained from population-based data will serve as the foundation for personalized medicine and decision making for reducing cardiovascular disease risk.

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Article Information

Corresponding Author: Robert A. Harrington, MD, Department of Medicine, Stanford University, 300 Pasteur Dr, S-102, MC 5110, Stanford, CA 94305 (robert.harrington@stanford.edu).

Conflict of Interest Disclosures: Both authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Harrington reported receiving grants from CSL as steering committee co-chair and from sanofi-aventis as an executive committee member; receiving grants and personal fees from Merck as steering committee chair and for regulatory consulting and from The Medicine Company as steering committee co-chair and for regulatory consulting; receiving personal fees from Amgen for clinical development consulting; receiving research grants to his institution from AstraZeneca, GlaxoSmithKline, Janssen, Novartis, and Portola; serving as an advisor or consultant to Adverse Events, Element Science, Gilead, MyoKardia, Vida Health, and WebMD; and serving on the board of directors for the American Heart Association, Stanford Healthcare, Scanadu, and SignalPath. No other disclosures were reported.

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