Jacquelyn W. Chou, MPP, MPL

 To provide recommendations that will improve approaches to measuring the value of new medical technologies to patients.

 Informed discussion by experts after literature review.

 A working group was formed, and participants discussed how value frameworks should incorporate key features important to patients in evaluating new medical technologies, particularly for chronic diseases.

 The working group suggests that new value frameworks should integrate real-world evidence to complement randomized controlled trials, incorporate the ways in which real-world behavior mediates outcomes, and explicitly discuss how therapies affect real-world equity and disparities in care.

 Collective stakeholders that include key decision makers within our healthcare system need to recognize the importance of implementing real-world evidence and devote resources to further research into the chronic disease areas in which the impact of human behavior is amplified by the duration of disease and treatment.

Steps have been taken to develop critical evaluations of drugs with the creation of value frameworks from organizations such as the Institute for Clinical and Economic Review, American Society of Clinical Oncology, and Memorial Sloan Kettering, but more work can and should be done to further refine these approaches. The Value FORWARD (Frameworks, Outcomes, and Real-World Adherence in Chronic Disease) Committee puts forth the following recommendations:

Value frameworks should incorporate real-world effectiveness to complement randomized controlled trial efficacy.

Value assessments must explicitly incorporate the ways in which real-world behavior mediates outcomes.

Value assessments should explicitly discuss how therapies affect real-world equity and disparities in care.

Policy makers, healthcare payers, patients, employers, and other stakeholders continue to fret about the rising cost of new medical technologies. Many scientific organizations have responded by developing new tools to assess the value of these technologies, commonly called “value frameworks.” For example, the American Society of Clinical Oncology (ASCO),

 and the Institute for Clinical and Economic Review (ICER) have offered alternative approaches to assessing the value of technologies. In principle, better information about value can help moderate growth in the cost of technologies that do not provide sufficient benefit to patients.

Yet there remains a gap between the goal of measuring value conferred to patients and the available evidence for new medical technologies. Randomized controlled trial (RCT) evidence generated for regulatory approval often incorrectly measures or fails to measure aspects of value that are key to patients. Some of these gaps and limitations are widely understood,

 but others have received too little attention, such as the role of patient behavior in mediating clinical outcomes.

 For example, evidence generated by RCTs often reflects outcomes achieved with motivated patients treated in environments in which individual patient behaviors that are critical to driving real-world outcomes, including adherence to medications, are controlled. As a result, interventions that improve adherence may not demonstrate large efficacy benefits in RCTs but may demonstrate larger benefits in real-world settings in which adherence is typically lower.

A working group was formed in partnership with Precision Health Economics and Intarcia Therapeutics in 2017 to make recommendations on how value frameworks should close the gap between evidence and patient behavior when evaluating new medical technologies, particularly for chronic diseases. Our working group recommended that these value frameworks enhance attention to (1) real-world evidence (RWE), (2) the role of adherence, and (3) nonclinical components of the patient experience.

Unlike healthcare systems in countries such as England, Germany, and Australia, where health technology assessment processes are well established,

 the US healthcare system does not have a formalized approach for defining or measuring value. Private organizations have stepped in to fill this gap but offer varying perspectives and approaches. For example, ASCO has released a value framework meant to aid physician communication of cancer treatment options with patients.

 ICER evaluates the cost-effectiveness of drug therapies from a payer and health system perspective.

 Memorial Sloan Kettering’s drug evaluation framework, the Drug Abacus, which evaluates cancer drugs, enables users to input their own preferences on different dimensions of value.

 These value frameworks differ in the perspectives that they use and in the attributes of value that they include in their evaluations. As a result, different value frameworks evaluating the same drug may have different conclusions about what may be considered reasonable value.

Recommendation 1: Value Frameworks Should Incorporate Real-World Effectiveness to Complement RCT Efficacy

Value frameworks have tended to emphasize evidence generated in RCTs, excluding or downplaying the use of RWE. Clinical trial evidence is emphasized as the gold standard for health benefit, although recently, there has been a growing awareness and movement to improve databases and infrastructure for RWE.

Clinical trial populations often fail to mirror real-world populations. This external validity problem is already well documented.

 Clinical trials are conducted in controlled environments where the structure of the environment lends itself to optimal rates of treatment adherence.

 More recently, some prominent researchers have argued that RCTs with smaller samples, often seen in breakthrough treatments with accelerated market approval, suffer from internal validity problems such as misalignment between the characteristics of subjects in the treatment and comparator groups.

RWE can help address these limitations. To be sure, it also suffers from limitations related to internal validity (eg, persons using novel therapies in the real world are often systematically different from their peers using older drugs at the same time). Methodological solutions exist to control for some of these confounders, and more generally, care must be taken to ensure the highest degree of internal validity in RWE. However, RWE is more than just a second-best alternative to RCT evidence; it provides inferences that are necessarily applicable to real-world populations. One major area of behavior around treatment that can be captured more realistically with RWE is adherence to treatment regimens.

 Our committee recommends explicit evaluation of RWE as a potential input into value assessments.

Recommendation 2: Value Assessments Must Explicitly Incorporate the Way Real-World Behavior Mediates Outcomes

As noted earlier, a critical moderator of health outcomes outside of clinical trials is adherence. At present, adherence is not explicitly included in any value framework or in the wider body of literature of cost-effectiveness models and budget impact models. Full adherence is typically “included” as an underlying assumption in these models and frameworks, as it is implicitly a part of clinical efficacy.

The need to do this is intuitive, particularly when comparing treatments in the same therapeutic area that possess different delivery mechanisms (eg, daily oral tablets vs weekly injections) or different adverse event profiles. An evaluation of a treatment that has a positive effect on behavior and encourages a higher rate of adherence than its comparator ought to consider the clinical consequences of better adherence (eg, an improvement in patient outcomes or achievement of treatment goals).

Adherence can also be considered an element for differentiating high-value and low-value care. Treatments that encourage improved adherence will result in less waste, because prescribed and dispensed treatments will actually be used. The importance of reducing this waste through improved adherence cannot be underestimated. Past estimates have found that more than $100 billion annually of avoidable costs are a result of medication nonadherence.

 Explicitly incorporating adherence would enable value frameworks to better identify high-value compared with low-value care.

The magnitude of this underuse has not been well understood, in part because our current adherence measures are not sufficiently nuanced to capture the full spectrum of behavior. Current measures of adherence do not infer medication consumption and are typically used as a binary measure of “good adherence” at or above 80% or “bad adherence” below 80%.

 This threshold implies that 80% is sufficient to achieve optimal outcomes, which has not been demonstrated across all diseases. Additionally, these measures primarily capture prescription behavior (ie, whether the prescription has been submitted/picked up), not whether the person has taken the treatment.

 Further, these measures do not capture primary nonadherence for persons who do not fill their initial prescription.

Starting with chronic diseases, we should seek to map adherence patterns and link those adherence patterns to outcomes. Work that has already started in this area—for example, in individuals with schizophrenia

—has demonstrated that adherence is not binary, with nuanced adherence patterns having real impacts on patient outcomes. We should seek to build on this work and develop studies that capture the value of adherence for health and quality-of-life outcomes so that adherence can be explicitly included as a separate value component in economic valuations of treatment.

Recommendation 3: Value Assessments Should Explicitly Discuss How Therapies Affect Real-World Equity and Disparities in Care

A critical aspect of treatment in the real world largely neglected by existing value frameworks is the impact on disparities in care. Previous research has demonstrated that nonclinical characteristics, such as education level, can affect adherence behaviors, which ultimately affect outcomes.

 Socially disadvantaged individuals are more likely to experience disease, at greater severity and with a higher likelihood of adverse effects.

 Combined with poorer adherence behaviors, disparities in healthcare can be compounded in chronic disease, where long-term consistent adherence to treatment is necessary for achieving positive outcomes. Explicitly evaluating how a new treatment can affect adherence and otherwise improve existing disparities in care would be an important element in determining the social impacts of therapeutic use.

A relatively strong body of literature already exists that articulates inequity in healthcare and some of the causes of those disparities. However, more research is required to develop methodologies to quantify and incorporate equity impacts into value assessments. It will be necessary to extend these equity concerns to additional nonclinical aspects of care, such as productivity and caregiver burden. The increased burden on productivity and caregivers also disproportionately affects disadvantaged individuals. Patients and providers have emphasized the importance of these aspects of care in making treatment decisions, but insufficient research exists to enable these aspects to play a large decision-making role. Further research and studies that take innovative approaches to, first, identifying the relevant nonclinical aspects of the patient experience and, second, measuring and quantifying these aspects are highly important to furthering our evidence base for treatment innovations and overall improving healthcare decision making.

A wide range of stakeholders are demanding better evidence of value. Value assessments and frameworks must adapt by making better use of real-world data and considering how individual behavior causes real-world outcomes to diverge from those seen in clinical trials. Our recommendations can help align value frameworks with value to individuals in the real world. Although we have already taken good steps forward to develop critical evaluations of drugs, more work can and should be done to further refine these approaches. Minimally, further efforts should be made to incorporate RWE to more accurately reflect the performance of new innovations by including adherence and measuring patient outcomes in the usual settings of patient care. To do so, the collective stakeholders that comprise key decision makers of our healthcare system need to devote resources to further research in chronic diseases where the impact of human behavior is amplified by the duration of disease and treatment.

The authors would like to thank Tiffany Shih for administrative and editorial support.

 Harvard Medical School (ABJ), Boston, MA; Precision Health Economics (JWC, LY), Los Angeles, CA; University of California, San Francisco (WMA), San Francisco, CA; Health Intelligence Partners (JB), Chicago, IL; University of Illinois, Chicago (WB), Chicago, IL; University of Michigan (AMF), Ann Arbor, MI; Pennsylvania State University (DMF), University Park, PA; Intarcia Therapeutics (DF, JY, BS, KY-I), Boston, MA; Dentons US LLP (RK), Washington, DC; University of Southern California (DNL), Los Angeles, CA; Tufts Medical Center (PJN), Boston, MA; The Brookings Institution (KP), Washington, DC.

 Funding for the Value FORWARD Committee was provided by Intarcia Therapeutics. Support was provided by the Office of the Director, National Institutes of Health (1DP5OD017897-01, Dr Jena). The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript.

 Dr Jena reports receiving consulting fees unrelated to this work from Amgen, Analysis Group, AstraZeneca, Biogen, Bristol Myers Squibb, Celgene, Eli Lilly, Hill Rom Services, Novartis, Pfizer, Precision Health Economics, Sanofi Aventis, Tesaro, and Vertex Pharmaceuticals. Ms Chou is an employee of Precision Health Economics, a healthcare consultancy with clients in the life sciences industry, and holds equity in Precision Medicine Group, parent company of Precision Health Economics. Ms Yoon is a previous employee of Precision Health Economics. Dr Aubry attended paid advisory boards and meetings for Intarcia on April 8, 2017, and May 16, 2017, and serves as a consultant to Precision Health Economics. Dr Burton has consulted for and received lecture fees from Amgen. Dr Fendrick has consulted for AbbVie, Amgen, Bayer, Centivo, Community Oncology Association, EmblemHealth, Exact Sciences, Freedman Health, Health at Scale Technologies, Lilly, Mallinckrodt, MedZed, Merck, Risalto, Sempre Health, State of Minnesota, Takeda, Wellth, and Zansors; has performed research for the Agency for Healthcare Research and Quality, Boehringer-Ingelheim, Gary and Mary West Health Policy Center, Laura & John Arnold Foundation, National Pharmaceutical Council, Patient-Centered Outcomes Research Institute, PhRMA, Robert Wood Johnson Foundation, and State of Michigan/CMS; and holds outside positions as co-editor-in-chief of 

, member of the Medicare Evidence Development & Coverage Advisory Committee, and partner in V-BID Health, LLC. Mr Franklin is employed by Intarcia Therapeutics, Inc. Dr Lakdawalla is a consultant to Precision Health Economics and holds equity in its parent company, Precision Medicine Group. Dr Neumann reports participating on advisory boards or consulting for AbbVie, Avexis, Bayer, Bluebird, Celgene, DePuy Synthes, GSK, Merck, Novartis, Novo Nordisk, Pacira, Paratek, Precision Health Economics, Vertex, Boston Health Economics, and Congressional Budget Office. Drs Yee, Sakurada, and Yu-Isenberg are former employees of Intarcia Therapeutics. Drs Sakurada and Yu-Isenberg have attended Academy of Managed Care Pharmacy, American Diabetes Association, Asembia, International Society for Pharmacoeconomics and Outcomes Research, and National Association of Managed Care Physicians conferences when under employment of Intarcia Therapeutics. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

 Concept and design (ABJ, JWC, WMA, JB, WB, DMF, RK, DNL, KP, JY, BS, KY-I); acquisition of data (LY, DF, KY-I); analysis and interpretation of data (ABJ, WMA, JB, AMF, DMF, RK, DNL, PJN, KP, BS, KY-I); drafting of the manuscript (ABJ, JWC, LY, WB, AMF, PJN, KP, KY-I); critical revision of the manuscript for important intellectual content (JWC, WMA, JB, WB, AMF, DMF, DF, RK, DNL, PJN, KP, JY, BS, KY-I); provision of patients or study materials (KY-I); obtaining funding (DF, KY-I); administrative, technical, or logistic support (JWC, LY); and supervision (DNL, KY-I).

 Anupam B. Jena, MD, PhD, 180 Longwood Ave, Boston, MA 20115. Email: jena@hcp.med.harvard.edu.

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Articles

New value frameworks should incorporate real-world evidence that reflects patient treatment behavior, adherence to medication, and equity concerns arising from disparities in care.

Understanding and Improving Value Frameworks With Real-World Patient Outcomes

Lipid-lowering therapy (LLT) is suboptimally used in patients with hyperlipidemia in the 2 highest statin benefit groups (SBGs), as categorized by the American College of Cardiology and the American Heart Association. This study estimated the social value of reducing low-density lipoprotein cholesterol (LDL-C) levels by 50% for patients in SBGs 1 and 2 who have been treated with standard LLT but have not reached LDL-C goal, as well as the potential value of PCSK9 inhibitors for patients in these groups.

We used National Health and Nutrition Examination Surveys (NHANES) and US Census data to project the population of SBGs 1 and 2 in the time period 2015 to 2035. We used insurance claims data to estimate incidence rates of major adverse cardiac events (MACEs), and NHANES with National Vital Statistics data to estimate cardiovascular disease mortality rates. Using established associations between LDL-C and MACE risk, we estimated the value of reducing LDL-C levels by 50%. We incorporated results from a meta-analysis to estimate the value of PSCK9 inhibitors.

Among those treated with LLT with LDL-C  >70 mg/dL in SBGs 1 and 2, the cumulative value of reducing LDL-C levels by 50% would be $2.9 trillion from 2015 to 2035, resulting primarily from 1.6 million deaths averted. The cumulative value of PCSK9 inhibitors would range from $3.4 trillion to $5.1 trillion (1.9-2.8 million deaths averted), or $12,000 to $17,000 per patient-year of treatment. 

 Lowering LDL-C in high-risk patients with hyperlipidemia has enormous potential social value. For patients in these high-risk groups, PCSK9 inhibitors may have considerable net value depending on the final prices payers ultimately select.

	Before PCSK9 inhibitors even reached market, their costs to the healthcare system were the subject of much scrutiny. We estimated the social value of PCSK9 inhibitors to place their costs in context with the value they generate for patients and society.

		Our study confirmed what we already knew: reducing lipid levels significantly in high-risk patients can have a considerable health impact. 

		Our study suggests that depending on the resulting confirmation of current estimates of effectiveness, PCSK9 inhibitors can provide considerable value when appropriately targeted, even at currently negotiated prices. 

		We also show that estimates of the likely budget impact are considerably off the mark when realistic uptake patterns are applied.

Cardiovascular disease (CVD) remains the leading cause of death, disability, and medical costs in the United States. Nearly 1 in 3 Americans dies of heart disease or stroke, and the annual cost of CVD in the United States exceeds $600 billion.

 Elevated low-density lipoprotein cholesterol (LDL-C) has been associated with increased risk for CVD events and death.

 Historically, statins have served as first-line lipid-lowering therapy (LLT) for LDL-C reduction, although recent guidelines have questioned the role of specific LDL-C goals in the primary and secondary prevention of CVD events.

Despite estimates of the costs of CVD in the United States, little is known about the economic value of reducing the hyperlipidemia burden among those at high risk for CVD who, despite use of standard LLT, do not achieve conventional LDL-C goals (eg, ≤70 mg/dL). The American College of Cardiology (ACC) and American Heart Association (AHA) classify patients as being in the highest-risk statin benefit groups (SBGs) with established atherosclerotic CVD (ASCVD) (SBG 1), LDL-C levels >190 mg/dL (SBG 2), and diabetes (SBG 3).

 Previous research estimated that up to 75% of high-risk patients treated with statins fail to achieve LDL-C of ≤70 mg/dL.

 High CVD event rates in this population, coupled with a substantial proportion of patients not at conventional LDL-C goals, suggest potentially large economic value from reducing the burden of hyperlipidemia. Previously, eliminating deaths resulting from CVD has been estimated to be worth nearly $50 trillion in economic value.

 For those initiating statin therapy between 1997 and 2008 alone, the value of averted deaths and CVD events may exceed $1 trillion.

Members of a novel class of therapies called PCSK9 inhibitors have recently been approved for treatment of hyperlipidemia in patients in SBGs 1 and 2 who do not achieve LDL-C of ≤70 mg/dL despite receiving maximally tolerated LLT. In phase 2 and 3 trials, PCSK9 inhibitors have been shown to reduce LDL-C by between 50% and 77%, on average.

 Preliminary clinical outcomes from these studies suggest that PCSK9 inhibitors may reduce rates of major adverse cardiac events (MACEs) by up to 50%.

 Based on these findings, the FDA approved alirocumab and evolocumab for use in adults with heterozygous familial hypercholesterolemia or ASCVD, who require additional LDL-C reduction.

 Amidst these developments, payers and policy makers have expressed concern that PCSK9 inhibitors’ costs—announced at $14,100 and $14,600 annually for evolocumab and alirocumab, respectively&mdash;will dramatically increase healthcare spending.

In this study, we estimated the economic value to the United States over the next 20 years (2015-2035) of reducing hyperlipidemia burden among those at high risk for MACEs (SBGs 1 and 2) who have not achieved conventional LDL-C goals despite use of standard LLT therapy. As a case study, we estimated the value to the United States of using PCSK9 inhibitors in these patients who are currently on LLT but have not achieved an LDL-C of ≤70 mg/dL.

Our study had 2 objectives: first, we sought to quantify the clinical and economic values of reducing the burden of hyperlipidemia among patients in the United States at high risk for MACEs or CVD mortality who have been treated with standard LLT but have not achieved conventional LDL-C goals. Second, we sought to project the clinical and economic value of PCSK9 inhibitors in patients at particularly high risk of MACEs or CVD mortality who may be eligible for treatment with these agents—those in SBGs 1 and 2&mdash;who have been treated with standard LLT but have not achieved conventional LDL-C goals. We defined conventional LDL-C goals to be ≤70 mg/dL and analyzed the sensitivity to a higher threshold of 

We used the 2011 to 2012 National Health and Nutrition Examination Study (NHANES)

 to first estimate the proportion of the US adult population (nonpregnant adults 18 years or older) in SBGs 1 and 2, as outlined by ACC and AHA guidelines

 We then divided each of these groups into 3 risk subgroups based on their use of, and LDL-C response to, LLT: subgroup A—patients on LLT who have not successfully reduced LDL-C to ≤70 mg/dL (or ≤100 mg/dL, in sensitivity analyses); subgroup B&mdash;patients at goal LDL-C on LLT; and subgroup C&mdash;patients not on LLT.

 We used US Census projections to estimate the size of each these populations from 2015 to 2035.

 We used the Truven Marketscan insurance claims database to estimate the rates of nonfatal CVD events (ie, unstable angina, myocardial infarction, coronary arterial revascularization, and ischemic stroke) and a combination of the NHANES mortality files and National Vital Statistics Mortality Report (2012) to estimate mortality rates for each of these groups (see eAppendix Tables 3-5).

With projected prevalence of patients not at goal LDL-C despite being on LLT (or who are intolerant to statins), we estimated the number of CVD-related deaths and MACEs averted for subgroup A in the time period 2015 to 2035 if LDL-C levels were hypothetically reduced by 50%, as suggested by the ACC and AHA.

 To estimate the effects of LDL-C reductions, we used the quantitative relationship between LDL-C and relative risk of CVD events and mortality from the Cholesterol Treatment Trialists’ (CTT) Collaboration meta-analysis.

 We then quantified the economic value to the United States of averted CVD-related deaths and MACEs using standard health economic valuation approaches.

We simulated the effects of PCSK9 inhibitor use for SBGs 1 and 2 in subgroup A patients. We projected the number of CVD-related deaths and MACEs averted in the time period 2015 to 2035, and the associated economic value if these patients were to receive PCSK9 inhibitors for further LDL-C reduction. We estimated the effects of PCSK9 inhibitors in 2 ways. First, we combined the LDL-C—lowering effects from PCSK9 inhibitor trials with the LDL-C relationship from the CTT Collaboration meta-analysis.

 Second, we used data on the effects of PCSK9 inhibitors on CVD-related death and MACEs from a meta-analysis of recent randomized controlled trials of these drugs.

 For a more detailed description of our methods for population and prevalence projections and event and mortality rate estimates, please see the eAppendix.

Across all PCSK9 inhibitor trials, the mean difference in LDL-C between those receiving LLT plus PCKS9 inhibitors compared with LLT alone was 59% (95% CI, 57%-61%). We used data from the CTT Collaboration meta-analysis (described in the eAppendix) to estimate the effect on clinical outcomes.

 Using this method, PCSK9 inhibitor use in SBG 1 was associated with a reduction in MACE risk ranging from 43% to 50%, and a 32% reduction in CVD mortality risk, assuming the same baseline LDL-C level as indicated above. In SBG 2, the mortality reduction was 45%. The estimated impact of PCSK9 inhibitors on clinical outcomes in this scenario was termed the “conservative efficacy” treatment scenario. Next, we modeled the impact of PCSK9 inhibitors on MACEs and CVD deaths by using direct outcomes data from a meta-analysis of PCSK9 trials.

 In the meta-analysis, PCSK9 inhibitor use was associated with a 50% relative risk reduction in rates of MACEs and CVD mortality. We termed this scenario the “high-efficacy” treatment scenario.

It should be noted that the studies in this meta-analysis were not weighted to detect differences in MACE outcomes, but for changes in LDL-C levels. Therefore, these results should be interpreted with caution.

We then modeled 3 uptake scenarios for PCSK9 inhibitors. In each scenario, PCSK9 inhibitor uptake began at 3% of the eligible population in 2015 (the eligible population included patients in SBGs 1 and 2 treated with standard LLT, but with LDL-C >70 mg/dL). Starting in 2016, uptake was assumed to increase linearly by 1%, 2%, or 3% for scenarios 1, 2, and 3, respectively, until 2023, when treatment uptake reached the maximum of 10% (scenario 1), 20% (scenario 2), or 30% (scenario 3) of the eligible population, and then remained constant through 2035.

Translating Clinical Outcomes Into Estimates of Economic Value

We estimated the economic value associated with averted CVD-related deaths and MACEs as follows. First, we identified the number of life-years gained by averting a single CVD-related death to be 14.9 additional life-years.

 As this number was taken from follow-up data based on a clinical trial, and clinical trials tend to exclude older age groups, we were concerned that this number may overstate the additional life-years after a CVD event. Therefore, we also undertook the same analysis using the mean life-years lost from an ischemic heart disease death from the US Burden of Disease Study

 (these results are shown in eAppendix Table A6). To value the gain in life-years, we used a value of $150,000 per life-year.

 The World Health Organization’s report on macroeconomics and health outlined an alternative approach to estimating the social value of lives saved due to healthcare interventions and concluded that healthcare interventions that save 1 life-year at a cost of less than 3 times the gross domestic product per capita (for a given country) are cost-effective.

Second, we assessed the value of reducing CVD-related hospitalizations using a recent review of the incremental costs of these hospitalizations in the United States. We estimated total cost savings from averted CVD hospitalizations by multiplying these unit cost estimates by the number of events averted.

 The value of life-years gained and savings from reduced CVD hospitalizations were summed to estimate both the total value of reducing residual LDL-C by the ACC/AHA goal of 50%, and the value of PCSK9 inhibitors in SBGs 1 and 2 for each of the 3 uptake scenarios described above. Future costs and benefits were discounted at 3%, using 2015 as the base year.

We estimated that in 2015, 32 million individuals in the United States would fall into ACC/AHA SBGs 1 and 2. Of these, 17.1 million did not receive LLT, 11.8 million were treated with standard LLT but had LDL-C >70 mg/dL, and 6.1 million were treated with standard LLT but had LDL-C >100 mg/dL. We projected that these figures would increase to 21.4 million, 16 million, and 8.1 million individuals, respectively, by 2035, absent changes in LLT use (

). In 2015, the largest SBG—SBG 1&mdash;was estimated to have 10.1 million individuals with LDL-C >70 mg/dL and 4.4 million with LDL-C >100 mg/dL despite having been treated with LLT. By 2035, these figures were projected to increase to 14.0 million and 6.1 million, respectively.

Value of Averted MACEs and CVD Deaths Associated With a Hypothetical 50% LDL-C Reduction in SBGs 1 and 2

We estimated that by 2020, approximately 3.6 million MACEs would be averted if LDL-C levels were reduced by 50% among those treated with standard LLT but who still had LDL-C levels >70 mg/dL (

). Additionally, we estimated that approximately 1.9 million MACEs would be averted by then if LDL-C levels were reduced by 50% among those treated with standard LLT but who still had LDL-C >100mg/dL. By 2035, these figures were estimated to increase to 14.2 million and 7.5 million, respectively.

We also estimated that by 2020, approximately 400,000 CVD deaths would be averted if LDL-C levels were reduced by 50% among those treated with standard LLT but who still had LDL-C levels >70mg/dL (eAppendix Figure 1). Approximately 230,000 CVD-related deaths would be prevented by 2020 for those with LDL-C >100 mg/dL. These figures increased to 1.6 million and 900,000, respectively, by 2035.

We estimated that by 2035, the cumulative value of averted CVD deaths and MACEs associated with a hypothetical 50% LDL-C reduction would be $2.9 trillion among individuals treated with standard LLT but who still had LDL-C >70mg/dL and $1.6 trillion among individuals with LDL-C >100mg/dL.

Value of Averted MACEs and CVD Deaths Associated With PCSK9 Inhibitor Use in SBGs 1 and 2

We estimated that by 2035, approximately 17 million MACEs (eAppendix Figure 2) and 2 million CVD deaths (eAppendix Figure 3) would be averted under a conservative PCSK9 inhibitor efficacy scenario if all patients in SBGs 1 and 2 treated with standard LLT, but who still had LDL-C >70 mg/dL, used PCSK9 inhibitors. Under the high-efficacy scenario, which assumed a 50% reduction in CVD mortality with PCSK9 inhibitor use, PCSK9 inhibitor use would prevent approximately 19 million MACEs and 3 million CVD-related deaths. In patients treated with standard LLT, but who still had LDL-C >100 mg/dL, 100% uptake of PCSK9 inhibitors would prevent approximately 9 million MACEs and 1 million CVD-related deaths under the conservative-efficacy scenario, as well as 10 million MACEs and 1.5 million CVD-related deaths under the high-efficacy scenario.

For patients in SBGs 1 and 2 treated with standard LLT but who still had LDL-C >70 mg/dL, we estimated the cumulative value of averted deaths and MACEs by 2035 to be $3.4 trillion under the conservative scenario and $5.1 trillion under the high-efficacy scenario (assuming 100% PCSK9 inhibitor uptake) (

). For patients in SBGs 1 and 2 treated with standard LLT, but who still had LDL-C >100 mg/dL, we projected the cumulative value of averted deaths and MACEs by 2035 to be $1.9 trillion under the conservative-efficacy scenario and $2.7 trillion under the high-efficacy scenario (again assuming 100% PCSK9 inhibitor uptake).

We modeled how varying PCSK9 inhibitor uptake influenced our projections. In our low-uptake scenario (in which a maximum of 10% of eligible patients use PCSK9 inhibitors by 2035), we estimated the value of averted MACEs and CVD-related deaths by 2035 to be $300 billion in the conservative-efficacy PCSK9 inhibitor scenario and $430 billion in the high-efficacy scenario (

). In contrast, in a high-uptake scenario (in which a maximum of 30% of eligible patients by 2035 use PCSK9 inhibitors), we estimated the value of averted MACEs and CVD-related deaths by 2035 to be $830 billion in the conservative-efficacy PCSK9 scenario and $1.2 trillion in the high-efficacy scenario.

Per-Person Value of Averted MACE and CVD Deaths Associated With PCSK9 Inhibitor Treatment

In addition to estimating MACEs, CVD-related deaths, and the potential value of averted events associated with PCSK9 inhibitor use at the population level, we estimated the value per person-year of treatment with a PCSK9 inhibitor for patients in SBGs 1 and 2 (

). For patients treated with standard LLT but who still had LDL-C >70 mg/dL, we projected the value per person-year of treatment to be $11,600 in the conservative-efficacy scenario and $17,100 in the high-efficacy scenario. At a goal LDL-C of ≤100 mg/dL, the estimated value per person-year of treatment with PCSK9 inhibitors was $12,600 in the conservative-efficacy scenario and $18,000 in the high-efficacy scenario. These estimates illustrate the potential range of social value per eligible patient treated with PCSK9 inhibitors.

We estimated the economic value to the United States over the next 20 years of reducing the burden of hyperlipidemia among patients in the highest ACC and AHA SBGs.

 We estimated that reducing LDL-C by 50% in SBG 1 and 2 patients who have been treated with standard LLT but still have LDL-C levels >70 mg/dL could avert approximately 14.2 million MACEs, including 1.6 million CVD-related deaths, by 2035.

Our study complements previous estimates of the economic value of LLT, including statin therapy, in the United States.

 Our estimates of the value of PCSK9 inhibitors are lower than the previously estimated social value of statins of approximately $51,000 per patient (in 2015 dollars).

 One factor that may partly explain this difference is that the growing use of percutaneous coronary intervention, P2Y12 inhibitors, angiotensin-converting enzyme inhibitors, aldosterone antagonists, and implantable cardiac defibrillators has led to dramatic improvements in CVD outcomes since statins were introduced.

 It is also possible that new CVD treatments produce smaller absolute benefits compared with those projected for statins, simply because overall morbidity and mortality for CVD were higher 20 years ago than today.

Although PCSK9 inhibitors may lower LDL-C and improve health outcomes for high-risk populations, policy makers and clinicians have raised concerns about the cost of these drugs to the healthcare system.

 The prices per patient-year of treatment were set recently at $14,100 and $14,600 per year for evolocumab and alirocumab, respectively. Some have estimated that systemwide costs for these drugs could be $150 billion annually.

 A critical question for patients and payers will be whether the value of PCSK9 inhibitor benefits outweighs their expense. Our estimates suggest that whether PCSK9 inhibitors deliver net social value (ie, generate benefits in excess of costs) depends on the assumptions about drug efficacy, the economic value of mortality improvements, which patient populations receive PCSK9 inhibitors, and the ultimate prices paid for these drugs. PCSK9 inhibitors would generate net positive social value for the average patients in SBGs 1 and 2, as long as the annual net price falls below $18,000 in a high-efficiency scenario or $12,000 in a conservative-efficiency scenario. According to a recent report, the average reported rebates for branded pharmaceutical drugs are around 30%,

 which would mean an average cost per year for PCSK9 inhibitors of around $10,000. Because our estimates do not include any benefits from increases in health-related quality of life from treatments or events avoided, our estimates may be conservative.

Our findings also add to our understanding of the size of the populations likely to receive PCSK9 inhibitors initially. Several current estimates assume that a majority of the 70 million patients in the 4 ACC/AHA SBGs (only 3 of which were included in this study) will eventually receive PCSK9 inhibitors, which may overestimate the actual societal cost of PCSK9 inhibitors if they are instead primarily prescribed to high-risk patients with poorly controlled LDL-C despite LLT—a small subset of all patients in these 4 SBGs. Our models for patients in the 2 highest SBGs (patients with ASCVD or LDL-C >190 mg/dL) were designed to reflect the reality that clinicians and payers are likely to focus initially on the smaller subset of patients who have up-titrated to maximal statins, but have still failed to achieve LDL-C reduction. For this reason, our projections of the potential benefits and value of PCSK9 inhibitors over the next 3 to 5 years may be more accurate than previous estimates. Nonetheless, even if PCSK9 inhibitors are prescribed only to patients in SBGs 1 and 2 who have been treated with standard LLTs but have not reached the LDL-C goal, some estimates suggest that healthcare spending on LLTs may increase by $10 billion annually over the next 2 decades.

Our study has several limitations. First, our estimated clinical impacts rely on epidemiologic models and evidence from studies of statins of the association among LDL-C levels, MACEs, and CVD-related deaths, which may differ in patients receiving PCSK9 inhibitors. Our estimated impacts assume a linear relationship among the levels of LDL-C reduction and MACEs and CVD-related deaths, which may not be the case at the lower levels of resulting LDL-C simulated in our model. In addition, our analysis of PCSK9 inhibitors used early clinical outcomes data for these drugs; relative risk reductions estimated from larger patient populations may differ from current estimates. Although existing studies suggest that PCSK9 inhibitors are associated with reduced MACEs and deaths, definitive evidence will not be available for several years. Furthermore, even definitive trial evidence may differ from real-world outcomes. Real-world efficacy patterns will be affected by patient treatment heterogeneity and physician decision making.

Reducing lipid levels in high-risk patients can significantly reduce disease burden and, depending on final negotiated prices, PCSK9 inhibitors can make an economic contribution to this goal.

Jacquelyn W. Chou, MPP, MPL

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