April 2015, Vol 8, No 2 - Clinical
Stephanie Chen, PhD
Associate Director,
Health Economics and Outcomes Research,
Forest Research Institute, Inc,
Jersey City, NJ
An-Chen Fu, MS, BSPharm
Senior Research Analyst,
HealthCore, Inc
Rahul Jain, PhD
Research Manager,
HealthCore, Inc
Hiangkiat Tan, MS, BSPharm
Director, HealthCore, Inc,
Wilmington, DE
Download PDF
Abstract

BACKGROUND: The prevalence of hypertension is increasing in the United States and the associated costs are soaring. Despite the many treatment options, only approximately 50% of Americans with hypertension achieve optimal control. Patients receiving nebivolol, a third-generation beta-blocker, have fewer adverse events and better treatment persistence compared with patients receiving other antihypertensive agents. Little is known about the impact of switching from a second-generation beta-blocker, such as metoprolol, to nebivolol on healthcare resource utilization and costs.

OBJECTIVE: To assess the impact of switching patients with hypertension from metoprolol to nebivolol on the associated healthcare resource utilization and cost.

METHOD: This retrospective claims-based analysis included 765 adults aged ≥18 years who were diagnosed with hypertension between January 1, 2008, and December 31, 2012. Data were extracted from the HealthCore Integrated Research Database; the study was conducted between July 1, 2007, and June 30, 2013. To be included in the study, patients had to receive metoprolol for ≥6 months before switching from metoprolol to nebivolol (the preperiod), and continue to use nebivolol for an additional 6 months after switching (the postperiod). Patients with compelling indications for metoprolol but not for nebivolol were excluded from the study. The primary outcome measures were healthcare resource utilization and costs for cardiovascular (CV)-related events. The CV-related resource utilization was calculated based on 100 patients per month; the CV-related costs were calculated per patient per month (PPPM) in 2013 US dollars.

RESULTS: A total of 765 patients were included in the analysis. Compared with the preperiod, patients switching to nebivolol had significantly fewer CV-related emergency department visits (0.2 [standard deviation (SD), 1.9] vs 0.04 [SD, 0.8], respectively; P = .012) and fewer CV-related outpatient visits (9.2 [SD, 19.9] vs 6.7 [SD, 17.5], respectively; P <.001). The numbers of inpatient visits in the preperiod and postperiod were similar (0.3 [SD, 2.4] vs 0.1 [SD, 1.5], respectively; P = .164). Patients switching to nebivolol also had significantly lower CV-related emergency department costs ($6 [SD, $78] vs $1 [SD, $27] PPPM, respectively; P = .028) and lower CV-related total medical costs ($94 [SD, $526] vs $54 [SD, $266] PPPM, respectively; P = .020).

CONCLUSION: This analysis of real-world data suggests that patients with hypertension who switch from the second-generation antihypertensive metoprolol to the third-generation hypertensive nebivolol have significantly lower CV-related healthcare resource utilization (eg, emergency department and outpatient visits) and lower CV-related medical costs

KEY WORDS: nebivolol, metoprolol, hypertension, healthcare resource utilization, cardiovascular events

Am Health Drug Benefits. 2015;8(2):71-80 www.AHDBonline.com

Received December 11, 2014 Accepted in final form February 17, 2015

Disclosures are at end of text

According to the Eighth Joint National Committee, hypertension is a known risk factor for cardiovascular (CV) events, such as stroke, myocardial infarction, and heart failure.1 Hypertension is defined as persistent systolic/diastolic blood pressure of at least 140/90 mm Hg among patients aged <60 years or at least 150/90 mm Hg among patients aged ≥60 years for 6 months.1 The prevalence of hypertension is steadily increasing in the United States and is projected to rise from 29% of the US adult population in 2006 to approximately 38% by 2030, and the associated costs soaring from $70 billion in 2010 to an estimated $200 billion in 2030.2,3 The goal of therapy in patients with hypertension is to decrease the risk for CV events (such as myocardial infarction or stroke) by reducing and controlling blood pressure.1 A recent study showed that within 5 years, patients with hypertension with an average blood pressure reduction of 3.6/2.4 mm Hg can potentially have a 14% lower odds for overall CV events, 28% lower odds for stroke events, 19% lower odds for coronary events, and 20% lower odds for heart failure.4 Despite the numerous treatment options available, the management of patients with hypertension remains inadequate: only approximately 50% of US adults with hypertension achieve optimal control.5 Inadequately managed hypertension may contribute to several adverse health outcomes, including stroke, myocardial infarction, and heart failure.6-8

Metoprolol was the most often prescribed beta-blocker in the United States in 2011, with 72.3 million prescriptions.9 However, metoprolol and other second-generation beta-blockers have lower efficacy than other classes of antihypertensives, which led to the development of third-­generation beta-blockers.10 One of these third-generation beta-blockers, nebivolol, is a cardioselective agent with high selectivity for beta1-adrenergic receptors. Nebivolol also causes vasodilation, by interacting with the endothelial L-arginine/nitric oxide pathway.11-13 Cardioselective beta-blockers not only lower the heart rate by blocking the effect of adrenaline in the heart but also relax and widen blood vessels, improving blood flow.13 Having both properties, nebivolol reduces the peripheral vascular resistance and significantly increases stroke volume while preserving cardiac output.13

Clinical trials have shown that nebivolol is efficacious compared with other classes of antihypertensive medications and is well-tolerated among a wide range of patients.13-16 Moreover, in one study, patients receiving nebivolol reported fewer adverse events (eg, sexual dysfunction, fatigue, depression, and metabolic abnormalities) than patients receiving other beta-blockers.17 The presence of fewer adverse events generally is associated with a lower likelihood of treatment discontinuation,18,19 and a recent study by Signorovitch and colleagues demonstrated that patients with hypertension who received nebivolol had better medication persistence compared with patients receiving other beta-blockers (eg, metoprolol).20 The reduction in adverse events among patients with hypertension who receive nebivolol and their subsequent improved medication persistence may also result in better disease management compared with patients receiving other beta-blockers.

Although nebivolol may be a viable treatment alternative for patients with hypertension who do not respond to or cannot tolerate other beta-blockers, little is known about the impact of switching patients from metoprolol to nebivolol on the associated CV-related healthcare resource utilization and costs. This information is especially important to payers, because nebivolol is a branded drug with a significantly higher average wholesale price (listed in the Medi-Span Master Drug Database) than for generic metoprolol.21 Therefore, the aim of this study is to analyze and document the impact on CV-related economic outcomes for patients with hypertension who switch their treatment from metoprolol to nebivolol.

Methods


Data Source

For this retrospective observational study, medical, pharmacy, and eligibility claims data were extracted from the HealthCore Integrated Research Database. This database contains claims from 14 geographically dispersed US commercial health plans representing more than 45 million lives, making it one of the largest data sets of a commercially insured population. Overall, this database is comparable with the US Census data (the American Community Survey) in terms of age and sex, although the population in the database is slightly younger, because all members are commercially insured.

All personally identifiable data used in this study were deidentified and were accessed with protocols that are compliant with the Health Insurance Portability ­and Accountability Act of 1996. Patient confidentiality was preserved, and the anonymity of all patient data ­was safeguarded throughout the study. No waiver of informed consent was required from an Institutional Review Board.

Study Design

Claims were obtained from the HealthCore Integrated Research Database during the study period (July 1, 2007-June 30, 2013). Patients included in the analysis were aged ≥18 years with a diagnosis of hypertension (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] 401.xx-404.xx) in an inpatient or outpatient setting during the patient identification period (January 1, 2008-December 31, 2012). To be included in the analysis, patients had to receive metoprolol for at least 6 months before switching to nebivolol, and then receive nebivolol for at least 6 months after switching from metoprolol. A treatment gap of less than 30 days of prescription supply was considered a continuous or stable drug regimen.

The index date was defined as the date the patient switched from metoprolol to nebivolol; the preperiod (baseline) was defined as the 6 months of treatment with metoprolol before the index date, and the postperiod was the 6 months of continuous treatment with nebivolol after the index date. All patients were continuously enrolled in a health plan during the preperiod and post­period (Figure 1).

Figure 1
Figure 1

Patients were excluded from the analysis if they had any compelling indications identified by ICD-9-CM diagnosis codes, for which metoprolol but not nebivolol is an approved treatment (eg, angina [ICD-9-CM codes 411.1x and 413.xx], myocardial infarction [410.xx and 412.xx], or congestive heart failure [428.xx, 402.01, 402.11, 402.91, 404.x1, and 404.x3]). Patients were also excluded if they did not maintain a stable background treatment of other classes of antihypertensive medications (eg, angiotensin-II receptor blockers) during the preperiod and postperiod (Figure 2).

Figure 2
Figure 2

Outcome Measures

The primary outcome measures were healthcare resource utilization and costs associated with specific CV events, including cerebrovascular disease (including stroke), chronic ischemic heart disease, acute coronary syndrome, peripheral vascular disease, valvular disease, arrhythmia, and aortic aneurysm.

CV-related resource utilization was calculated as the number of times a healthcare resource was utilized divided by the number of months of follow-up during the preperiod or postperiod, multiplied by 100 patients, to reach the healthcare resource utilization per 100 patients per month. The CV-related healthcare costs were presented in 2013 US dollars per patient per month (PPPM); that is, the costs were calculated by dividing the CV-related cost (the total, inpatient, and outpatient costs) by the number of months during the preperiod or postperiod (6 months each).

Healthcare resource utilization and costs were then categorized by the setting of service (ie, inpatient, emergency department visit, and outpatient office visit). CV-related events in the inpatient or emergency department settings were identified from the primary diagnosis; because the primary diagnosis was unavailable in outpatient claims, patients receiving care in outpatient settings were identified using all diagnosis positions.

Sensitivity Analysis

In the main analysis, the change in the healthcare resource utilization and costs of patients with hypertension who switched from metoprolol to nebivolol were analyzed. The results of the main analysis may overstate the impact of switching to nebivolol, because only the patients who are likely to benefit the most from switching are included. To evaluate this possibility, a sensitivity analysis was conducted, in which the same outcomes were evaluated and compared between matched cohorts of patients who switched from metoprolol to nebivolol and those who did not switch but continued to receive metoprolol. The patients who switched from metoprolol to nebivolol were matched to those who did not switch and continued treatment with metoprolol, using propensity score matching on baseline demographic and clinical characteristics.

Statistical Analysis

Unadjusted differences between the preperiod and postperiod were assessed using McNemar’s test for nominal variables and a bootstrap paired t-test for continuous variables. All data analyses were conducted using SAS version 9.2 (SAS Institute; Cary, NC) or Stata version 12.0 (Stata Corporation; College Station, TX). All statistical tests were 2-sided hypothesis tests performed at a 5% level of significance.

Results


Patient Characteristics

A total of 765 patients were included in the analysis; the patients’ mean age was 55 years, and 59% were men (Table 1). At baseline, the majority (70%) of patients had a Charlson Deyo Comorbidity Index score of 022; only 12% had a score of 2 or higher (Table 2). The most common comorbidities of interest at baseline were chronic ischemic heart disease and fatigue (17% each), followed by arrhythmia and diabetes (14% each).

Table 1
Table 1

Table 2
Table 2

Medication Use and Resource Utilization

The mean (standard deviation [SD]) number of all prescription medications increased from 21 (14%) in the preperiod to 23 (14%; P <.001) in the postperiod (Table 3). Fewer treatment gaps were observed in the postperiod during treatment with nebivolol than in the preperiod while patients were receiving metoprolol (mean, 12.8 days vs 15.9 days, respectively).

Table 3
Table 3

Compared with the preperiod, patients switching to nebivolol in the postperiod had significantly fewer CV-related emergency department visits (0.2 [SD, 1.9] vs 0.04 [SD, 0.8], respectively; P = .012) and CV-related outpatient visits (9.2 [SD, 19.9] vs 6.7 [SD, 17.5], respectively; P <.001). These results are shown in Figure 3.

Figure 3
Figure 3

The number of inpatient visits in the preperiod and postperiod were similar (0.3 [SD, 2.4] vs 0.1 [SD, 1.5], respectively; P = .164). The proportion of patients with at least 1 CV-related outpatient visit was significantly lower in the postperiod than in the preperiod (21% vs 27%, respectively; P <.001), as shown in Figure 4.

Figure 4
Figure 4

CV-related healthcare costs followed a pattern similar to healthcare utilization (Table 4). Compared with the preperiod, patients switching to nebivolol had significantly lower CV-related emergency department mean costs ($6 [SD, $78] vs $1 [SD, $27] PPPM, respectively; P = .028) and lower CV-related total medical costs ($94 [SD, $526] vs $54 [SD, $266] PPPM, respectively; P = .020), as shown in Figure 5.

Figure 5
Figure 5

The CV-related inpatient costs were similar between the preperiod and postperiod ($29 [SD, $324] vs $13 [SD, $161] PPPM, respectively; P =.173), as were the CV-related outpatient costs ($59 [SD, $400] vs $40 [SD, $206] PPPM, respectively; P = .130).

The sensitivity analysis produced results similar to the primary analysis, although the differences between the patients who switched to nebivolol and those who did not switch were not statistically significant (Table 5).

Table 5
Table 5

Discussion


The results of this analysis of real-world data demonstrates that patients with hypertension who switched from metoprolol to nebivolol and who continued the drug regimen for at least 6 months had significantly fewer CV-related emergency department and outpatient visits, as well as lower CV-related emergency department and total medical costs in the 6 months after switching. Our results add to clinical studies,16 and suggest that the use of nebivolol has a role in improving hypertension disease management by reducing the likelihood of CV-related utilization and costs when patients switched from metoprolol for any reasons.

The reduction in CV-related emergency department and outpatient visits after the treatment regimen switch could be in part a result of the pharmacologic features of nebivolol. This third-generation medication has been shown to activate endothelial nitric oxide production, which helps to reduce the peripheral resistance of the blood vessels, leading to improved stroke volume with a neutral impact on cardiac output.16,23,24 This effect is useful in the treatment of hypertension, heart failure, ischemia reperfusion injury, and stroke.

It is possible that the observed reduction in the CV-related emergency department and outpatient visits for patients who switched to nebivolol may be related to better management of hypertension and CV disease, which is consistent with previously published clinical trials.25

In addition, the higher treatment persistence observed among patients receiving nebivolol, as measured by fewer days of treatment gaps compared with patients receiving metoprolol, may also contribute to better disease management and potentially lower CV-related emergency department and outpatient visits after switching drugs. Consistent with the results of this present study, in a previously published study, patients receiving nebivolol were found to have better persistence relative to metoprolol.20 Yang and colleagues recently showed that patients with hypertension who were nonpersistent with therapy had significantly more CV-related hospitalizations and emergency department visits than patients who were persistent with therapy.26

Together, the lower CV-related healthcare resource utilization and lower CV-related emergency department costs observed with nebivolol may translate into the significantly lower CV-related medical costs seen after switching from metoprolol. Hypertension is a known risk factor for severe CV diseases such as stroke, myocardial infarction, and heart failure, which result in substantial medical expenditures and account for a large proportion of the total healthcare costs. For example, the estimated direct costs of CV disease-related complications that were attributable to hypertension were predicted to increase from $130.7 billion in 2010 to $389 billion in 2030.3 Added to that were indirect costs (eg, lost productivity) that were estimated to be $25.4 billion in 2010 and were expected to rise to $42.8 billion by 2030.3 The more effectively a treatment can manage hypertension, the lower the risk for severe CV diseases in the near future,26 which can possibly lead to better health and can minimize CV-related resource utilization as well as overall healthcare resource utilization and costs.

In this study, we evaluated the CV-related healthcare resource utilization and the costs of patients with hypertension who switched from metoprolol to nebivolol; therefore, the preperiod and postperiod approach was the appropriate study design for the main analysis. Although the reasons for switching from metoprolol to nebivolol were not evaluated, it was recognized that only patients who were likely to benefit the most from switching were likely to switch.

To test the importance of this assumption, we performed a sensitivity analysis to evaluate the outcomes that were the same between matched patients receiving metoprolol and those receiving nebivolol. The results of the sensitivity analysis were similar to those of the primary analysis, although the differences were not statistically significant. In other words, the point estimate of reduction in the healthcare resource utilization and costs were consistent with that of the main analysis, but with larger variation, and were therefore statistically insignificant.

Taken together, these results demonstrate that switching from the second-generation beta-blocker metoprolol to the third-generation beta-blocker nebivolol is likely to reduce CV-related resource utilization and costs.

To quantify the impact of switching to nebivolol, this study was limited to patients who consistently took metoprolol and nebivolol for 6 months or more.

Limitations


The findings of this study may also not be generalizable to patients who are not taking metoprolol and nebivolol consistently.

It is possible that the observed effect of cost-saving in this study is more applicable to patients who respond and adhere to their antihypertension medications.
This study is subject to limitations similar to other retrospective database studies, including coding errors or omissions, incomplete claims, unreliable clinical coding, and unobservable factors that may have influenced the outcomes.

However, there is no evidence that this potential measurement error would be nonrandom between the periods that patients were receiving metoprolol and nebivolol. The impact of the measurement error is likely to increase the confidence interval of the estimate (results toward nonsignificant), but the point estimate is likely to be robust.

Because this study was based on a commercially insured population in the United States, the results may not be generalizable to patients with other types of health insurance or those living outside of the United States.

Conclusion


In this analysis, which was based on real-world data, patients with hypertension who switched from metoprolol to nebivolol had significantly lower CV-related healthcare resource utilization (eg, emergency department and outpatient visits) and lower CV-related healthcare costs. The lower CV-related resource utilization and costs may indicate improved disease management of hypertension. Additional studies are needed to identify these key drivers and to quantify the long-term economic impact of switching from other antihypertensive agents to nebivolol.

Funding Source
Funding for this study was provided by Forest Research Institute, Inc.

Author Disclosure Statement
Dr Chen was an employee of Forest Research Institute at the time of this study; Ms Fu, Dr Jain, and Mr Tan are employees of HealthCore, Inc, a consultancy whose activities on the project were funded by Forest Research Institute.

References


1. James PA, Oparil S, Carter BL, et al. 2014 evidence-based guideline for the management of high blood pressure in adults: report from the panel members appointed to the Eighth Joint National Committee (JNC 8). JAMA. 2014;­311:507-520. Erratum in: JAMA. 2014;311:1809.
2. Go AS, Mozaffarian D, Roger VL, et al; for the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics—2013 update: a report from the American Heart Association. Circulation. 2013;127:e6-e245. Erratum in: Circulation. 2013;127:e841.
3. Heidenreich PA, Trogdon JG, Khavjou OA, et al; for the American Heart Association Advocacy Coordinating Committee; Stroke Council; Council on Cardiovascular Radiology and Intervention; Council on Clinical Cardiology; Council on Epidemiology and Prevention; Council on Arteriosclerosis, Thrombosis and Vascular Biology; Council on Cardiopulmonary, Critical Care, Perioperative and Resuscitation; Council on Cardiovascular Nursing; Council on the Kidney in Cardiovascular Disease; Council on Cardiovascular Surgery and Anesthesia; Interdisciplinary Council on Quality of Care and Outcomes Research. Forecasting the future of cardiovascular disease in the United States: a policy statement from the American Heart Association. Circulation. 2011;123:933-944.
4. Sundström J, Arima H, Jackson R, et al; for the Blood Pressure Lowering Treatment Trialists’ Collaboration. Effects of blood pressure reduction in mild hypertension: a systematic review and meta-analysis. Ann Intern Med. 2015;162:184-191.
5. National Center for Health Statistics. Health, United States, 2013: With Special Feature on Prescription Drugs. Hyattsville, MD: US Department of Health & Human Services; 2014. www.cdc.gov/nchs/data/hus/hus13.pdf. Accessed October 14, 2014.
6. Aiyagari V, Gorelick PB. Management of blood pressure for acute and recurrent stroke. Stroke. 2009;40:2251-2256.
7. Kaplan RC, Psaty BM, Heckbert SR, et al. Blood pressure level and incidence of myocardial infarction among patients treated for hypertension. Am J Public Health. 1999;89:1414-1417.
8. Manickavasagam S, Merla R, Koerner MM, et al. Management of hypertension in chronic heart failure. Expert Rev Cardiovasc Ther. 2009;7:423-433.
9. Clinton P, Cacciotti J. Pharm Exec 50: growth from the bottom up. Pharm Exec. May 1, 2012. www.pharmexec.com/pharmexec/Top+Feature/Pharm-Exec-­50-Growth-from-the-Bottom-Up/ArticleStandard/Article/detail/773562. Accessed October 14, 2014.
10. Toblli JE, DiGennaro F, Giani JF, Dominici FP. Nebivolol: impact on cardiac and endothelial function and clinical utility. Vasc Health Risk Manag. 2012;8:151-160.
11. Bystolic (nebivolol) tablets [prescribing information]. St Louis, MO: Forest Laboratories, Inc; January 2014.
12. Grassi G, Trevano FQ, Facchini A, et al. Efficacy and tolerability profile of nebivolol vs atenolol in mild-to-moderate essential hypertension: results of a double-blind randomized multicentre trial. Blood Press Suppl. 2003;2:35-40.
13. Cheng JW. Nebivolol: a third-generation β-blocker for hypertension. Clin Ther. 2009;31:447-462.
14. Van Nueten L, Taylor FR, Robertson JIS. Nebivolol vs atenolol and placebo in essential hypertension: a double-blind randomised trial. J Hum Hypertens. 1998;12:135-140.
15. Weiss RJ, Saunders E, Greathouse M. Efficacy and tolerability of nebivolol in stage I-II hypertension: a pooled analysis of data from three randomized, placebo-controlled monotherapy trials. Clin Ther. 2011;33:1150-1161.
16. Weiss R. Nebivolol: a novel beta-blocker with nitric oxide-induced vasodilatation. Vasc Health Risk Manag. 2006;2:303-308.
17. Wojciechowski D, Papademetriou V. Beta-blockers in the management of hypertension: focus on nebivolol. Expert Rev Cardiovasc Ther. 2008;6:471-479.
18. Veronesi M, Cicero AF, Prandin MG, et al. A prospective evaluation of persistence on antihypertensive treatment with different antihypertensive drugs in clinical practice. Vasc Health Risk Manag. 2007;3:999-1005.
19. Grégoire JP, Moisan J, Guibert R, et al. Determinants of discontinuation of new courses of antihypertensive medications. J Clin Epidemiol. 2002;55:728-735.
20. Signorovitch JE, Samuelson TM, Ramakrishnan K, et al. Persistence with nebivolol in the treatment of hypertension: a retrospective claims analysis. Curr Med Res Opin. 2012;28:591-599.
21. Wolters Kluwer Health. Medi-Span Master Drug Database. www.medispan.com/drug-information-products/. Accessed October 14, 2014.
22. D’Hoore W, Bouckaert A, Tilquin C. Practical considerations on the use of the Charlson Comorbidity Index with administrative data bases. J Clin Epidemiol.­ 1996;49:1429-1433.
23. Weber MA. The role of the new β-blockers in treating cardiovascular disease. Am J Hypertens. 2005;18(12 pt 2):169S-176S.
24. Kamp O, Sieswerda GT, Visser CA. Comparison of effects on systolic and diastolic left ventricular function of nebivolol versus atenolol in patients with uncomplicated essential hypertension. Am J Cardiol. 2003;92:344-348.
25. Celik T, Iyisoy A, Kursaklioglu H, et al. Comparative effects of nebivolol and metoprolol on oxidative stress, insulin resistance, plasma adiponectin and soluble P-selectin levels in hypertensive patients. J Hypertens. 2006;24:­­591-596.
26. Yang W, Kahler KH, Fellers T, et al. Copayment level, treatment persistence, and healthcare utilization in hypertension patients treated with single-­pill combination therapy. J Med Econ. 2011;14:267-278.

Stakeholder Perspective
Moving Beyond Measures into Outcomes in Hypertension Research
Michael F. Murphy, MD, PhD
Chief Medical and Scientific Officer
Worldwide Clinical Trials
King of Prussia, PA

Novel chemical and biological entities herald significant advances in disease management across a variety of therapeutic areas. Too frequently, however, therapeutic novelty becomes an impetus for expanded clinical use without an attendant demonstration of benefits in health-related outcomes across representative patients in diverse environments. When “novelty is not enough,” this becomes a clarion call for outcome studies initiated in tandem, or subsequent to prototypical registration programs.1

In their article in this issue of the journal, Chen and colleagues provide a methodologically rigorous example of a retrospective/prospective claims-based analysis for a cardioselective beta-blocker indicated for the treatment of hypertension that complements and validates results from controlled clinical studies. Data suggest that a newer class of agent, in contrast to a widely utilized second-generation beta-blocker, may improve disease management and reduce overall cardiovascular utilization and cost.

RESEARCHERS: Properly designed observational studies yield estimates of treatment effect comparable to randomized controlled trials.2 They also generate ecologically relevant data to support marketing authorization with costs/resource utilization estimates to inform formulary placement and extent of coverage. Differentiation of therapy in a more heterogeneous population of patients and physicians is more feasible in observational research3 compared with designs necessitated by a preregistration program in which patient and research center characteristics are optimized under the constraints of a protocol design for the purposes of demonstrating evidence of efficacy and safety.

Observational research permits sampling of a larger spectrum of clinical end points to measure effectiveness and efficiency in typical practice settings compared with current standards of care. Conclusions are framed with limitations common to observational studies using a claims database. However, sensitivity analyses in this report used propensity score matching oåf prognostically important variables can mute criticisms associated with nonrandomized trials that provide insights not available in traditional randomized prospective clinical trials.4

PAYERS: Policy mandates, accelerating costs, and changes in demographics require that new therapeutic entities submitted for marketing to prevalent, chronic conditions demonstrate effects on outcomes, as well as measures as part of their development program. Moving beyond measures into outcomes is a prerequisite for informing decisions in benefit design. Studies that provide insights on healthcare resource utilization and cost as part of a switching strategy in hypertension move the discussion from being focused on compound attributes to one that is focused on clinical attributes, within a time frame of patient exposure that is sufficient for inferring clinically relevant outcomes.
With adherence dictating reduction in longer-term outcomes, a cardioselective agent with fewer reported adverse events bodes well for reduction in significant drivers of cost. Copayment can be a strong predictor of adherence to antihypertensive therapy, indicating that price sensitivity of patients dictates medication adherence.5 Observational studies suggesting that a pharmacologically sophisticated agent may displace second-generation medications inform this consideration.

PATIENTS: Medication-related issues represent one of many dimensions modifying overall antihypertensive medication adherence.6 Across cultures, an appreciation of the rationale for chronic therapy in the absence of symptoms is also an important modifying variable, which is entwined with the quality of the physician–patient relationships.7 The significance of medication attributes as represented by a novel cardioselective antihypertensive agent lies in its being a modifiable risk factor in contrast to social, economic, and other condition-related dimensions that may prove to be too distant or too intractable for effective intervention.

1. Shah NR. Evidence standards in the era of comparative effectiveness. Am Health Drug Benefits. 2009;2(1 suppl):S41-S48.
2. Concato J, Shah N, Horwitz RI. Randomized, controlled trials, observational studies, and the hierarchy of research designs. N Engl J Med. 2000;342:­1887-1892.
3. Marko NF, Weil RJ. The role of observational investigations in comparative effectiveness research. Value Health. 2010;13:989-997.
4. Newgard CD, Hedges JR, Arthur M, Mullins RJ. Advanced statistics: the propensity score—a method for estimating treatment effect in observational research. Acad Emerg Med. 2004;11:953-961.
5. Taira DA, Wong KS, Frech-Tamas F, Chung RS. Copayment level and compliance with antihypertensive medication: analysis and policy implications for managed care. Am J Manag Care. 2006;12:678-683.
6. Krousel-Wood M, Joyce C, Holt E, et al. Predictors of decline in medication adherence: results from the cohort study of medication adherence among older adults. Hypertension. 2011;58:804-810.
7. Gascón J, Sánchez-Ortuño M, Llor B, et al. Why hypertensive patients do not comply with the treatment: results from a qualitative study. Fam Pract. 2004;21:125-130.

Related Items
Major Cardiovascular Events in Patients with Gout and Associated Cardiovascular Disease or Heart Failure and Chronic Kidney Disease Initiating a Xanthine Oxidase Inhibitor
JoAnne Foody, MD;, Robin S. Turpin, PhD, Beni A. Tidwell, BS, Debra Lawrence, PhD, Kathy L. Schulman, MS
November 2017 Vol 10, No 8 published on November 21, 2017 in Clinical, Original Research
Medication Adherence, Treatment Patterns, and Dose Reduction in Patients with Metastatic Castration-Resistant Prostate Cancer Receiving Abiraterone Acetate or Enzalutamide
Ajay S. Behl, PhD, Lorie A. Ellis, PhD, Dominic Pilon, MA, Yongling Xiao, PhD
September 2017 Vol 10, No 6 published on September 20, 2017 in Clinical, Original Research
The Relative Burden of Menopausal and Postmenopausal Symptoms versus Other Major Conditions: A Retrospective Analysis of the Medical Expenditure Panel Survey Data
Annlouise R. Assaf, PhD, Andrew G. Bushmakin, MS, Nina Joyce, PhD, Michael J. Louie, MD, MPH, MSc, Michael Flores, MPH, Margaret Moffatt, MPH
September 2017 Vol 10, No 6 published on September 20, 2017 in Clinical, Original Research
The Medical and Economic Burden of Narcolepsy: Implications for Managed Care
Michael J. Thorpy, MB, ChB, George Hiller, RPh, James T. Kenney, RPh, MBA
July 2017 Vol 10, No 5 published on July 24, 2017 in Clinical
Comparing Medication Adherence and Persistence Among Patients with Type 2 Diabetes Using Sodium-Glucose Cotransporter 2 Inhibitors or Sulfonylureas
Kelly F. Bell, PharmD, MSPhr, MS, Katherine Cappell, PhD, Michael Liang, MS, Amanda M. Kong, MPH
June 2017 Vol 10, No 4 published on June 22, 2017 in Clinical, Original Research
Last modified: May 12, 2015
  •  Association for Value-Based Cancer Care
  • Value-Based Cancer Care
  • Value-Based Care in Rheumatology
  • Oncology Practice Management
  • Rheumatology Practice Management
  • Urology Practice Management
  • Inside Patient Care: Pharmacy & Clinic
  • Lynx CME