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Cost-effectiveness of statin treatment for primary prevention in conditions of real-world adherence – Estimates from the Finnish prescription register
Atherosclerosis 239 (2015) 240e247
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Atherosclerosis journal homepage: www.elsevier.com/locate/atherosclerosis
Cost-effectiveness of statin treatment for primary prevention in conditions of real-world adherence e Estimates from the Finnish prescription register Emma Aarnio a, b, *, Maarit J. Korhonen c, Risto Huupponen a, c, Janne Martikainen b a b c
Department of Clinical Pharmacology, Tykslab, Turku University Hospital, Turku, Finland Pharmacoeconomics and Outcomes Research Unit (PHORU), School of Pharmacy, University of Eastern Finland, Kuopio, Finland Department of Pharmacology, Drug Development and Therapeutics, University of Turku, Turku, Finland
a r t i c l e i n f o
a b s t r a c t
Article history: Received 14 October 2014 Received in revised form 18 December 2014 Accepted 24 December 2014 Available online 14 January 2015
Objective: To estimate the cost-effectiveness of statin therapy for primary prevention of coronary heart disease (CHD) events under real-world adherence. Methods: A cost-effectiveness model was applied to estimate the expected 10-year costs and health outcomes (in terms of quality-adjusted life-years, QALYs) associated with and without statin treatment (at defined adherence levels) among hypothetical cohorts of Finnish men and women who were initially without established CHD. Treatment efficacy, cost, and quality of life estimates were obtained from published sources. Long-term treatment adherence was measured based on data from the national prescription register. Results: At an assumed willingness-to-pay threshold of V20,000 per QALY gained, statin treatment with real-world adherence was cost-effective among the older patient groups when the patients’ 10-year CHD risk was as high as 20% and did not seem cost-effective in the youngest age groups. Conversely, statin treatment with full adherence was cost-effective for almost all patient groups with a 10-year CHD risk of at least 15%. Conclusions: Even though generic statins are now low-cost drugs, treatment adherence seems to have a major impact on the cost-effectiveness of statin treatment in primary prevention. This finding stresses the importance of making a concerted effort for improving adherence among patients on statin therapy to obtain full benefit of the investment in statins. Therefore, novel cost-effective approaches to improve treatment adherence are warranted. © 2015 Elsevier Ireland Ltd. All rights reserved.
Keywords: Statins Adherence Cost-effectiveness analysis Primary prevention
1. Introduction Statins are effective in the primary prevention of cardiovascular disease (CVD) [1]. According to a recent Cochrane review, statins reduce all-cause mortality by 14%, the risk of fatal and non-fatal CVD events by 25%, and the risk of coronary heart disease (CHD) by 27% in individuals without evidence of CVD. However, the costeffectiveness of statin therapy in primary prevention is still a matter of debate [2e5] because this depends not only on the cost of
* Corresponding author. School of Pharmacy, University of Eastern Finland, P.O. Box 1627, FI-70211 Kuopio, Finland. E-mail addresses: emma.aarnio@uef.fi (E. Aarnio), maakor@utu.fi (M.J. Korhonen), rihuuppo@utu.fi (R. Huupponen), janne.martikainen@uef.fi (J. Martikainen). http://dx.doi.org/10.1016/j.atherosclerosis.2014.12.059 0021-9150/© 2015 Elsevier Ireland Ltd. All rights reserved.
the drugs themselves but also on patients’ CVD risk level. The relative risk reduction achieved with statins seems to be constant across patients at different risk levels, but the absolute benefit is greater when the subject has a higher risk for CVD [3,5]. Initiation of statin therapies has been shifting towards lower risk populations [6]. The 2013 ACC/AHA cholesterol treatment guideline recommends that statin therapy should be provided to an even broader range of people than in previous guidelines [7]. If one follows the new guideline then one can estimate that ~33 million Americans at 7.5% 10-year CVD risk and over 12 million at >5.0e7.4% 10-year risk could be recommended to receive statin therapy [8]. Also in England NICE has updated its guidance and recommends offering statin therapy for primary prevention to patients with a 10-year CVD risk of at least 10% [9]. However, even in the era of low-cost generic statins, statin therapy may not be cost-effective in low-
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risk populations in all situations [3e5,10]. In addition to encouraging the use of risk estimation as a part of patient management, current treatment guidelines highlight the importance of adherence to medication [11]. A substantial proportion of patients who are prescribed statins do not adhere to treatment [12]. Patients with poor adherence may experience worse outcomes and higher health care costs than patients with good adherence [13]. In previous studies where patient adherence has been taken into account, the results of the impact of patient adherence on the cost-effectiveness of statins in primary prevention have been conflicting [3,4,10]. Therefore, the aim of our present study was to explore the simultaneous effects of patients’ CHD risk level in combination with observed register-based real-world adherence (as well as ideal full adherence) on the cost-effectiveness of statin treatment in primary prevention of CHD events in the Finnish setting. This was done in an attempt to identify those patient groups for whom statin treatment is cost-effective under ideal and observed real-world adherence scenarios, and for whom the treatment from this perspective should be targeted or to whom adherence-supporting measures should be directed. 2. Methods 2.1. Cost-effectiveness model A previously constructed cost-effectiveness model [14e16] was modified to estimate the expected 10-year costs and health outcomes (in terms of quality-adjusted life-years, QALYs) associated either with statin treatment (with defined adherence levels) or without treatment with statins among hypothetical cohorts of Finnish men and women who were initially without signs or symptoms of CHD. Estimations were carried out for men and women separately at five different initial ages (i.e., 45, 50, 55, 60 and 65 years) with various levels of 10-year risk of CHD. The CHD risks were based on the FINRISK risk function for major coronary events (men ¼ (1/(1 þ exp(11.213e0.0802*age 0.6260*smoking 0.3293*cholesterol 0.0166*systolic blood pressure þ 0.5893*HDLcholesterol 0.7417*diabetes 0.3138*parents' infarction)))*100; women ¼ (1/(1 þ exp(11.839e0.0962*age 0.8776*smoking 0.2119*cholesterol 0.0175*systolic blood pressure þ 1.1009*HDLcholesterol 1.0303*diabetes 0.4090*parents’ infarction)))*100) [17]. The schematic presentation of the cost-effectiveness model is illustrated in Fig. 1. The model applied a Markov structure with a cycle length of one year. Each year, the hypothetical cohort of men or women without established CHD were at risk of having a fatal non-CHD event, a fatal CHD event, an acute non-fatal CHD event, or they might survive to the next year without suffering any kind of CHD event.
Fig. 1. Simplified schematic structure of the Markov model. CHD, coronary heart disease; MI, myocardial infarction.
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2.2. Event probabilities The annual total risk of initial non-fatal CHD event (International Classification of Diseases, ICD-10: I20.0, I21, and I22) or CHD death (ICD-10: I20eI25, I46, R96, and R98) was estimated using the FINRISK risk functions [17]. For simplicity, the estimated risks of CHD events at baseline were updated only on changes in patient's age keeping the other risk factors constant over the established 10year time horizon. Since the FINRISK risk functions were originally developed to predict total CHD risk, information from the National Cardiovascular Disease Register [18] was used to determine the age- and sex-specific case fatality. Annual age- and sex-specific risks of non-CHD death were estimated from the causes of death register by subtracting the fraction of deaths due to CHD (ICD-10: I20eI25, I46, R96, and R98) from the total mortality. After a nonfatal CHD event, the age- and sex-specific risks of death (CHD or non-CHD) were derived from published life tables. 2.3. Health care resource use and costs Costs, estimated from a societal perspective, included direct costs of statins and other medications, morbidity, rehabilitation, and production losses due to non-fatal CHD events. Annual ageand sex-specific costs (including costs of hospitalization, outpatient care and prescribed outpatient medications) resulting from acute CHD events were obtained from reports based on the national discharge and prescription registries [16,19]. The annual statin and other medication costs were obtained from the national registries. The average annual medication cost of treating dyslipidemia was estimated to be around V52 in men and women. This estimate was based on the distribution of different statins and strengths among new Finnish statin users starting treatment in 9/2007e12/2007 [20]. Reference prices in April 2013 were weighted by these proportions to estimate average annual statin costs. In addition, monitoring costs were estimated for patients using statins. These costs were based on the assumption of one additional doctor, nurse and laboratory visit annually and priced using Finnish standard health care costs [21]. The average annual costs for patients in secondary prevention were V363. This cost was based on the same monitoring costs as with statin treatment and the yearly costs of medications used in the secondary prevention of coronary heart disease according to Finnish Current Care Guidelines [22]. The costs of these medications were based on the yearly cost of low-dose aspirin (lowest price in May 2013) and yearly costs of adrenergic b-blocker agents, statins and angiotensin-converting-enzyme inhibitors derived from the Social Insurance Institution of Finland (SII). The costs from the SII were based on purchases in 2012 made by people entitled to a special reimbursement when buying these medications because they had been diagnosed with a severe, chronic disease like CHD. Adherence was not taken into account in secondary prevention. Costs of CHD rehabilitation were estimated by weighting the average rehabilitation costs obtained from the national rehabilitation registry at the SII by the proportion (3%) of CHD patients receiving rehabilitation. Productivity losses due to non-fatal CHD events were estimated by multiplying the average length of sickness leave due to myocardial infarction (i.e., 4.78 months) [23] by the average monthly income (including payroll tax) of Finnish employees in the year 2011. Productivity losses were applied to CHD patients below the average age of retirement, assumed to be 65 years, and taken into account in the sensitivity analyses. All costs (except medication costs) were adjusted to the 2011 price level using the official health care price index determined by the Association of Finnish Local and Regional Authorities. In
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addition, value-added tax of 10% was subtracted from the prices of medications. In the base-case, the costs were discounted at 3% per annum (as recommended by the Finnish health economic guidelines). All applied cost estimates are summarized in Table 1. 2.4. Quality-adjusted life-years Age- and sex-specific quality of life estimates measured by the generic EQ-5D instrument were used to represent the average quality of life in the Finnish population aged 45e74 years [24]. The disutility weights due to initial acute CHD event and post-acute CHD health state were obtained from previously published studies [24,25]. In the base-case, QALYs were also discounted at 3% per annum. The applied quality of life estimates are summarized in Table 1. 2.5. Medication adherence At the beginning of the simulation, the patient cohorts were assumed to start daily statin medication. The cost-effectiveness of statin treatment was assessed under observed real-world and ideal full adherence scenarios compared to no statin treatment. In realworld adherence scenario, adherence was determined from the Prescription Register managed by the SII. The cohort consisted of 45e75-year-old patients initiating statin treatment in primary prevention of CVD between Jan 1, 2000 and Dec 31, 2004 [26]. Primary prevention was determined as no sign of coronary heart disease, stroke, atherosclerosis or peripheral arterial disease in the Prescription Register, the Special Reimbursement Register or hospital discharge register maintained by the National Institute for Health and Welfare. Adherence was measured as the proportion of days covered (PDC) assuming that the patient took one tablet per day [27,28]. Yearly PDC-values for defined age groups for men and women were
estimated for the first 4 years of treatment because of the follow-up time in the data. Adherence was assumed to remain stable after year 4. Patients were classified to have either good (PDC 80%), moderate (40% PDC < 80%) or poor (PDC <40%) adherence [29e31]. In the full adherence scenario, all patients were assumed to have a PDC of 100%. The patients’ CHD event risk was modified by the risk reduction attributable to statins estimated in a published metaanalysis [1]. The risk ratio (RR) for combined fatal and non-fatal CHD events was 0.73 (95% confidence interval (CI) 0.67e0.80) (Table 1). The protective effect of statin treatment against CHD events was assumed to be conferred one year after treatment initiation (i.e., RR ¼ 1 in the first year) [32]. Patients classified as having good adherence had the same risk reduction as patients in the full adherence scenario. Patients with moderate adherence were assumed to have half of the risk reduction [33]. Patients classified as having poor adherence to statin treatment were estimated to have the same event risks as patients without statin treatment. From the second year onwards, the proportions of patients in each of the adherence classes in the previous year were determined and a weighted average of the risk reduction associated with statin treatment was estimated. The estimated annual average statin costs were used for patients in the full adherence scenario. In the real-world adherence scenario, the annual cost of statin treatment was weighted by the average PDC each year in the whole registry data. Monitoring costs were assumed to be the same for all statin patients regardless of different PDC-values and were the same in both adherence scenarios. 2.6. Sensitivity analysis Uncertainty associated with the model parameters (i.e., parameter uncertainty) was handled by determining probability
Table 1 Parameters applied in the Markov model. Parameter Costs AMI, mean (SE) 45e54 55e64 65e74 Fatal AMI Rehabilitation after MI (first year) Proportion of patients receiving rehabilitation after MI Statins Full adherence Real-world adherence
Monitoring a patient receiving statins in primary preventiona Secondary prevention Productivity costs due to non-fatal AMI Utilities, mean (SE) 45e54 55e64 65e74 Disutilities, mean (SE) AMI Post-AMI Treatment effectiveness of statins Fatal and non-fatal CHD event, RR (95% CI)
Men
V 15,873 (810) V 15,333 (782) V 13,793 (704)
Women
V 18,578 (948) V 17,329 (884) V 15,877 (810) V 1943 V 2305 3%
Distribution
Source
Normal Normal Normal Fixed Fixed Fixed
Martikainen et al., 2011 [16]
Hujanen et al., 2008 [21] SII SII, National Cardiovascular Disease Register
V 52.2 V 36.1 (1st year, average PDC 69.2%) V 31.5 (2nd year, average PDC 60.4%) V 31.2 (3rd year, average PDC 59.8%) V 31.5 (4th and subsequent years, average PDC 60.4%) V 147.9
Fixed Multinomial beta
Kiviniemi et al., 2011 [20], SII
Fixed
Hujanen et al., 2008 [21]
V 362.9 V 14,861
Fixed Fixed
Hujanen et al., 2008 [21], SII €inen et al., 2004 [23], Vehvila Statistics Finland
Beta Beta Beta
Estimated based on Saarni et al. (2006) and Soini et al. (2010) [24,25]
Beta Beta
Soini et al., 2010 [25] Saarni et al., 2006 [24]
Lognormal
Taylor et al., 2013 [1]
0.876 (0.005) 0.821 (0.006) 0.781 (0.008)
0.865 (0.005) 0.810 (0.006) 0.770 (0.008) 0.092 (0.029) 0.011 (0.009) 0.73 (0.67e0.80)
AMI, acute myocardial infarction; SE, standard error; MI, myocardial infarction; PDC, proportion of days covered; CHD, coronary heart disease; RR, risk ratio; CI, confidence interval; SII, Social Insurance Institution. a One additional doctor, nurse and laboratory visit.
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distributions for all relevant parameters and then conducting probabilistic sensitivity analysis (PSA) with 5000 iteration rounds [34]. The selection of proper probability distributions for the model parameters has been described previously in detail [15,16]. The proportion of patients in different adherence classes was assumed to follow a multinomial beta distribution. The results of the PSA were used to determine 95% CIs for the cost and health outcomes and to construct cost-effectiveness acceptability curves (CEACs). The CEACs were used to depict the probability of cost-effectiveness as a function of willingness-to-pay (WTP) per QALY gained. In addition, one-way and scenario sensitivity analyses were applied to test the robustness of model assumptions. The tested parameters included statin costs, monitoring costs, time horizon of the model, statin benefit in patients with moderate adherence, secondary prevention costs and discount rates. In real-world adherence scenarios, statin costs were weighted by the average PDC in the registry data in the same way as in the base case analyses. 3. Results The cost-effectiveness estimates of statin treatment in primary prevention of CHD in both real-world and full adherence scenarios in different patient populations are shown in Fig. 2 (more detailed results are presented in Appendices 1 and 2). At an assumed WTP threshold of V20,000 per QALY gained, statin treatment in the realworld adherence scenario seemed to be cost-effective among the older patient groups when the patients’ 10-year CHD risk was as high as 20% and did not seem cost-effective in the youngest age groups even at this highest tested risk level. However, in the full adherence scenario, statin treatment seemed to be cost-effective for almost all patient groups with a 10-year CHD risk of at least 15%. Also the incremental costs with statin treatment were smaller under full adherence than real-world adherence scenario in more than half of the tested patient groups (Appendices 1 and 2). In general, within age groups statin treatment was more cost-effective for patients with higher 10-year CHD risks due to higher incremental QALYs and lower incremental costs.
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cost of monitoring, statin costs and to the time horizon of the model. If no monitoring costs were included in primary prevention, statin treatment seemed very cost-effective in both patient groups regardless of the adherence scenario employed and became cost-saving among 60-year-old women under full adherence scenario. The importance of monitoring costs in primary prevention was tested also with 45-year-old women with a 10-year CHD risk of 5%. The base case cost-effectiveness estimate for statin treatment was the highest in this patient group (V197,645 per QALY gained in the real-world adherence scenario). When no monitoring costs were assumed in primary prevention, the cost-effectiveness estimate improved substantially to V19,712 per QALY gained (data not shown). Results were quite sensitive to the costs of statins (Table 2). In the full adherence scenario, increasing annual statin costs to V220 raised the cost-effectiveness estimates in both patient groups to around V54,000e65,000 per QALY gained. However, in the realworld adherence scenario, even when no statin costs were taken into account, statin treatment did not seem to be cost-effective in either patient group. When a longer 15-year time horizon was used instead of the 10year time horizon, the cost-effectiveness estimates of statin treatment improved in all of the conducted sensitivity analyses in comparison to base case results (Table 2). Furthermore, the assumed benefit from statins in patients with moderate adherence also asserted an impact on the results. When no benefit from statins was assumed for patients with PDC under 80%, the cost-effectiveness estimates increased about V12,000eV15,000 per QALY gained in 55-year-old men and in 60-year-old women with a 10-year CHD risk of 10%. The estimated CEACs for 55-year-old men and 60-year-old women showed that the probability of statin treatment being costeffective increases as the patients’ risk levels rise (Fig. 3A and B). The CEACs also revealed how cost-effectiveness is improved under full adherence compared to real-world adherence. In both figures it can be seen that the probability of statin treatment being costeffective at a threshold of V15,000 per QALY gained is higher in patients with a 10-year CHD risk of 15% in the full adherence scenario than in patients with a 10-year CHD risk of 20% in the realworld adherence scenario.
3.1. Sensitivity analyses 4. Discussion Sensitivity analyses were conducted for 55-year-old men and 60year-old women with a 10-year CHD risk of 10% (Table 2). According to the sensitivity analyses, the study results were most sensitive to the
According to the results of this study, treatment adherence seems to have a major impact on the cost-effectiveness of statin
Fig. 2. Incremental cost-effectiveness ratio estimates (ICERs) for different age and risk groups by sex and adherence. Risk is the 10-year risk for suffering a fatal or non-fatal CHD event. QALY, quality-adjusted life-year; CHD, coronary heart disease.
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Table 2 One-way and scenario sensitivity analyses for 55-year-old men and 60-year-old women with a 10-year CHD risk of 10%. Real-world adherence
55-year-old men
DCosts (V)
60-year-old women
DQALY
Base case 1066 0.025 Productivity costs included 917 0.025 15-year time horizon 1429 0.054 Benefit from statins for patients with moderate adherence (base case: 50%) 0% 1098 0.020 30% 1079 0.023 80% 1047 0.028 Annual monitoring costs in primary prevention (base case: V 147.9) V0 64 0.025 V 300 2097 0.025 Annual statin costs with full adherence (base case: V 52.2 with full adherence)a V0 822 0.025 V 90 1244 0.025 V 220 1853 0.025 Annual secondary prevention costs (base case: V 362.9) V0 1079 0.025 V 1000 1046 0.025 Discount rates (base case: 3% for both costs and QALYs) 0%/0% 1262 0.031 5%/5% 959 0.021 Full adherence
ICER (V/QALY)
DCosts (V)
DQALY
ICER (V/QALY)
42,998 37,174 26,352
1018 936 1336
0.020 0.020 0.047
50,518 46,357 28,682
55,202 47,181 37,869
1062 1035 992
0.016 0.019 0.022
65,853 55,565 44,081
2596 84,713
9 2055
0.020 0.020
461 101,930
33,294 50,345 74,984
771 1197 1810
0.020 0.020 0.020
38,175 59,555 89,937
43,779 42,354
1032 991
0.020 0.020
51,144 49,233
41,282 44,639
1202 915
0.025 0.018
47,671 52,205
55-year-old men
DCosts (V)
60-year-old women
DQALY
Base case 1068 0.041 Productivity costs included 822 0.041 15-year time horizon 1420 0.089 Annual monitoring costs in primary prevention (base case: V 147.9) V0 58 0.041 V 300 2106 0.041 a Annual statin costs (base case V 52.2 with full adherence) V0 711 0.041 V 90 1326 0.041 V 220 2213 0.041 Annual secondary prevention costs (base case: V 362.9) V0 1088 0.041 V 1000 1032 0.041 Discount rates (base case: 3% for both costs and QALYs) 0%/0% 1261 0.051 5%/5% 961 0.036
ICER (V/QALY)
DCosts (V)
DQALY
ICER (V/QALY)
26,192 20,187 15,883
986 853 1267
0.033 0.033 0.076
29,960 25,974 16,730
1430 51,668
29 2031
0.033 0.033
Cost-saving 61,917
17,386 32,567 54,204
627 1247 2139
0.033 0.033 0.033
19,029 38,086 65,096
26,629 25,238
1011 944
0.033 0.033
30,775 28,766
24,847 27,023
1164 889
0.041 0.029
28,421 31,100
CHD, coronary heart disease; QALY, quality-adjusted life-year; ICER, incremental cost-effectiveness ratio. a V 90 reflects the annual cost of generic atorvastatin 10 mg and V 220 the annual cost of branded atorvastatin 10 mg.
treatment in primary prevention of CHD events. However, at an assumed WTP threshold of V20,000 per QALY gained, statin treatment did not seem to be cost-effective for patients with a 10year CHD risk of 10% even with the full adherence scenario. Apart from treatment adherence, the results of the cost-effectiveness assessments in the different patient groups were sensitive to monitoring costs in primary prevention, selected time horizon, and the cost of statins. Three recent studies have come to different conclusions about the cost-effectiveness of statin therapy and the sensitivity of costeffectiveness estimates with respect to statin adherence in primary prevention [3,4,10]. In the study of Greving et al., the base case result of the ICER of statin treatment was around V35,000 per QALY gained in the real-world adherence scenario [3]. With full adherence, the ICER estimate was around V26,000 per QALY gained. Lazar et al. reported that for most persons with even modestly elevated cholesterol levels or any CHD risk factors primary prevention with statins could be cost-effective [4]. Their cost-effectiveness estimates were insensitive to changes in statin adherence and an adherence level as low as 25% had only a minimal impact on statin cost-effectiveness. de Vries et al. estimated that starting statin treatment at the time of diagnosis of type 2 diabetes is costeffective, but that there are large differences in cost-effectiveness according to patients’ risk and age groups [10]. They reported adherence rates having a large effect on their results but chancing
adherence rates did not change the conclusion of statin costeffectiveness. Our study and the three recent studies [3,4,10] differ in many aspects. The time horizon in our study was 10 years as in the studies of Greving et al. [3] and de Vries et al. [10], whereas in the study by Lazar et al. [4] the time horizon was 30 years. The latter study [4] differed from the others also in that it modeled the statin effect by lowering the patient's LDL-levels which then affected the event risk. In contrast, our study and the two Dutch studies modeled the statin effect by lowering directly the patients' event risk. The choice of the modeling approach has been shown to affect costeffectiveness estimates [35]. Unlike our study, the three other studies [3,4,10] considered adverse events caused by statins in their cost-effectiveness models. They also took into account disutility from taking statins daily in their base case or sensitivity analyses. In contrast to our study and the study by Lazar et al. [4], the studies by Greving et al. [3] and de Vries et al. [4] considered the potential benefits of statins regarding stroke events in addition to CHD events. All the four studies differ in how nonadherence was modeled. There are also differences regarding patients in the models, cost and quality of life estimates used, modeling of secondary prevention, and assumptions used in the models. In the present study, statin treatment had lower incremental costs in many patient groups in the full adherence scenario as compared to real-world adherence scenario. This result is in
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Fig. 3. Cost-effectiveness acceptability curves for patients with different 10-year CHD risks in different adherence scenarios for 55-year-old men (A) and for 60-year-old women (B). WTP, willingness-to-pay; QALY, quality-adjusted life-year; CHD, coronary heart disease.
accordance with previous studies where better adherence has been reported to be associated with lower overall health care costs [13]. It seems that full adherence to statin treatment could be costsaving compared to treatment with only real-world adherence. Therefore concerted effort is needed to motivate the patients who have been prescribed statins to actually take their medication in order to achieve the full benefit from investment in statins. However, improving patients’ adherence is not easy because of the complexity of medication-taking behavior [36]. Different risk functions and guidelines can lead to very different treatment decisions [37]. Using characteristics of a 50-year-old woman whose 10-year CHD risk according to the FINRISK risk function is 10% and CVD risk is around 17% [17], the ASCVD risk estimator from the ACC/AHA guideline calculates a 10-year CVD risk of around 19% (assuming no treatment for hypertension) [38]. The QRISK2-tool recommended by NICE estimates the 10-year CVD
risk to be almost 21% (assuming moderate smoking, type 2 diabetes, no other chronic diseases and a BMI of 29.8 kg/m2) [39]. According to the guidelines by the Japan Atherosclerosis Society, a patient with similar characteristics would be regarded as belonging to the high-risk group (a 10-year risk of death from coronary artery disease at least 2% or with high-risk conditions such as diabetes) [40]. Because we used the FINRISK risk function and concentrated in CHD events in our study, our cost-effectiveness estimates are not directly applicable to patient populations whose risks are estimated using other risk functions (especially with those which estimate risk for CVD events). There is uncertainty about the benefit of statins in patients with less than good adherence. We used an estimate of 50% benefit for patients with moderate adherence which was used also in a previous study [33]. The cost-effectiveness results were quite sensitive to this assumption especially when assuming no benefit from
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statins to patients with less than good adherence. However, changing the assumption from 50% to 30% did not have any major impact on the results. The lower PDC-limit for moderate adherence (i.e., 40%) used in our study was quite high as compared to that applied in the previous study by Cherry et al. [33]. However, in Finland it is possible to purchase up to 3 months’ medication at one transaction. This one purchase alone would mean a PDC-value of around 27% for one year. For this reason, a PDC-value of 40% was thought to be high enough to represent those patients with moderate adherence. Our research has limitations. First, we used a time horizon of 10 years. Statins are often meant to be used as a life-long treatment and it is possible that the time horizon used was too short to capture all the possible costs and benefits related to statin treatment. However, the use of a longer time horizon would have introduced more uncertainty into the final results. Second, adherence rates in the present study were based on patients starting statin treatment in the early 2000s. It is possible that adherence rates among new statin users have changed in the last 10 years. It is also possible that adherence rates differ between patients in different risk groups [41]. In our study, we used the same adherence figures regardless of the patients' 10-year risks. Third, the yearly cost of statin treatment was based on the distribution of different statins and strengths among new statin users in the fall of 2007. This meant that we could not take into account the possible changes made to patients’ treatment after treatment initiation. This probably underestimates the statin costs if treatment adjustments are made towards higher strengths and higher-potency statins. The statin costs employed do not reflect the costs of statins and strengths used in clinical trials on whose outcomes the clinical benefit of statin was based in the analyses. Fourth, neither adverse effects of statin treatment nor thrombotic stroke events were included in the cost-effectiveness model. Statins are generally well tolerated and serious adverse effects are rare [42]. The inclusion of the adverse effects would probably have raised the ICER estimates of statin treatment because there would have been fewer patients gaining benefit from statin treatment and greater costs due to the need to treat adverse effects. It has been estimated that about 10e15% of patients using statin suffer from muscle side effects [43]. Since all patients do not tolerate statins, full adherence cannot be achieved in real-world conditions. In addition, a diabetogenic action has been ascribed to statin use [44], and although it is clearly inferior to the beneficial effects of statins, it might have potential negative impact on the cost-effectiveness of statin treatment especially in the primary prevention setting. However, the inclusion of thrombotic stroke events in the cost-effectiveness model would have probably lead to lower ICER estimates, since statin treatment has been reported to reduce the risk of combined fatal and non-fatal stroke in primary prevention [1]. One strength of our study was that we used different sex, age and risk groups instead of an average patient group. We also used register-based estimates of real-world adherence instead of assumptions. Finally, effective prevention of CHD requires a multifaceted approach. In addition to dyslipidemia, other cardiovascular risk factors such as obesity, diabetes, smoking and elevated blood pressure should be addressed with changes in lifestyle and when required, with pharmacotherapy [11]. The therapeutic effectiveness and cost-effectiveness of statin treatment is significantly modulated by success or failure in adopting this holistic approach. 5. Conclusions The results of this study indicate that, even in the era of low-cost generic statins, treatment adherence potentially plays a major impact on the cost-effectiveness of statin treatment in primary
prevention of CHD events. This finding stresses the importance of making a concerted effort for improving adherence among patients on statin therapy to obtain full benefit of the investment in statins. Accordingly, novel cost-effective approaches for screening and improving treatment adherence are warranted. Conflict of interest statement The authors have the following conflicts: EA is funded by state funding for university-level health research (Grant L 3820). She has received consultancy fees from ESiOR Ltd. JM is the senior partner of ESiOR Ltd, which provides health economic and outcomes research (HEOR) services for pharmaceutical companies and hospitals. MJK and RH have been funded by the grants from the Social Insurance Institution (SII) (10/26/2007) and the Academy of Finland (number 138255). RH is a member of the Advisory Board for Social and Medical Affairs of the SII. He has conducted consultancy for Orion Corporation as an Independent External Member of a Data Monitoring and Safety Committee in a clinical trial, and assisted Santen Pharmaceutical Co in pharmacokinetic calculations. The authors declare no other financial or non-financial (professional or personal) conflict of interests. Acknowledgments Our study was funded by state funding for University-level Health Research (Grant L 3820), the Social Insurance Institution of Finland (www.kela.fi) (grant 10/26/2007) and the Academy of Finland (www.aka.fi, decision number 138255). The funders had no role in the design, analyses, interpretation of data, writing the report, or in the decision to submit the manuscript. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.atherosclerosis.2014.12.059. References [1] F. Taylor, M.D. Huffman, A.F. Macedo, et al., Statins for the primary prevention of cardiovascular disease, Cochrane Database Syst. Rev. 1 (2013) CD004816, http://dx.doi.org/10.1002/14651858.CD004816.pub5. [2] M. Neyt, C. De Laet, H. Van Brabandt, et al., Cost-effectiveness of statins in the primary prevention of cardiovascular disease: a systematic review and economic analysis for Belgium, Acta Cardiol. 64 (2009) 1e10. [3] J.P. Greving, F.L. Visseren, G.A. de Wit, A. Algra, Statin treatment for primary prevention of vascular disease: whom to treat? Cost-effectiveness analysis, BMJ 342 (2011) d1672, http://dx.doi.org/10.1136/bmj.d1672. [4] L.D. Lazar, M.J. Pletcher, P.G. Coxson, et al., Cost-effectiveness of statin therapy for primary prevention in a low-cost statin era, Circulation 124 (2011) 146e153, http://dx.doi.org/10.1161/CIRCULATIONAHA.110.986349. [5] A.P. Mitchell, R.J. Simpson, Statin cost effectiveness in primary prevention: a systematic review of the recent cost-effectiveness literature in the United States, BMC Res. Notes 5 (2012) 373, http://dx.doi.org/10.1186/1756-0500-5373. [6] M. Rikala, R. Huupponen, A. Helin-Salmivaara, M.J. Korhonen, Channelling of statin use towards low-risk population and patients with diabetes, Basic Clin. Pharmacol. Toxicol. 113 (2013) 173e178, http://dx.doi.org/10.1111/ bcpt.12075. [7] N.J. Stone, J.G. Robinson, A.H. Lichtenstein, et al., ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines, Circulation 129 (2014) S1eS45, http://dx.doi.org/10.1161/01.cir.0000437738.63853.7a. [8] P.M. Ridker, N.R. Cook, Statins: new American guidelines for prevention of cardiovascular disease, Lancet 382 (2013) 1762e1765, http://dx.doi.org/ 10.1016/S0140-6736(13)62388-0. [9] S. Rabar, M. Harker, N. O'Flynn, et al., Lipid modification and cardiovascular risk assessment for the primary and secondary prevention of cardiovascular disease: summary of updated NICE guidance, BMJ 349 (2014) g4356, http:// dx.doi.org/10.1136/bmj.g4356. [10] F.M. de Vries, P. Denig, S.T. Visser, et al., Cost-effectiveness of statins for primary prevention in patients newly diagnosed with type 2 diabetes in the
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Atherosclerosis journal homepage: www.elsevier.com/locate/atherosclerosis
Cost-effectiveness of statin treatment for primary prevention in conditions of real-world adherence e Estimates from the Finnish prescription register Emma Aarnio a, b, *, Maarit J. Korhonen c, Risto Huupponen a, c, Janne Martikainen b a b c
Department of Clinical Pharmacology, Tykslab, Turku University Hospital, Turku, Finland Pharmacoeconomics and Outcomes Research Unit (PHORU), School of Pharmacy, University of Eastern Finland, Kuopio, Finland Department of Pharmacology, Drug Development and Therapeutics, University of Turku, Turku, Finland
a r t i c l e i n f o
a b s t r a c t
Article history: Received 14 October 2014 Received in revised form 18 December 2014 Accepted 24 December 2014 Available online 14 January 2015
Objective: To estimate the cost-effectiveness of statin therapy for primary prevention of coronary heart disease (CHD) events under real-world adherence. Methods: A cost-effectiveness model was applied to estimate the expected 10-year costs and health outcomes (in terms of quality-adjusted life-years, QALYs) associated with and without statin treatment (at defined adherence levels) among hypothetical cohorts of Finnish men and women who were initially without established CHD. Treatment efficacy, cost, and quality of life estimates were obtained from published sources. Long-term treatment adherence was measured based on data from the national prescription register. Results: At an assumed willingness-to-pay threshold of V20,000 per QALY gained, statin treatment with real-world adherence was cost-effective among the older patient groups when the patients’ 10-year CHD risk was as high as 20% and did not seem cost-effective in the youngest age groups. Conversely, statin treatment with full adherence was cost-effective for almost all patient groups with a 10-year CHD risk of at least 15%. Conclusions: Even though generic statins are now low-cost drugs, treatment adherence seems to have a major impact on the cost-effectiveness of statin treatment in primary prevention. This finding stresses the importance of making a concerted effort for improving adherence among patients on statin therapy to obtain full benefit of the investment in statins. Therefore, novel cost-effective approaches to improve treatment adherence are warranted. © 2015 Elsevier Ireland Ltd. All rights reserved.
Keywords: Statins Adherence Cost-effectiveness analysis Primary prevention
1. Introduction Statins are effective in the primary prevention of cardiovascular disease (CVD) [1]. According to a recent Cochrane review, statins reduce all-cause mortality by 14%, the risk of fatal and non-fatal CVD events by 25%, and the risk of coronary heart disease (CHD) by 27% in individuals without evidence of CVD. However, the costeffectiveness of statin therapy in primary prevention is still a matter of debate [2e5] because this depends not only on the cost of
* Corresponding author. School of Pharmacy, University of Eastern Finland, P.O. Box 1627, FI-70211 Kuopio, Finland. E-mail addresses: emma.aarnio@uef.fi (E. Aarnio), maakor@utu.fi (M.J. Korhonen), rihuuppo@utu.fi (R. Huupponen), janne.martikainen@uef.fi (J. Martikainen). http://dx.doi.org/10.1016/j.atherosclerosis.2014.12.059 0021-9150/© 2015 Elsevier Ireland Ltd. All rights reserved.
the drugs themselves but also on patients’ CVD risk level. The relative risk reduction achieved with statins seems to be constant across patients at different risk levels, but the absolute benefit is greater when the subject has a higher risk for CVD [3,5]. Initiation of statin therapies has been shifting towards lower risk populations [6]. The 2013 ACC/AHA cholesterol treatment guideline recommends that statin therapy should be provided to an even broader range of people than in previous guidelines [7]. If one follows the new guideline then one can estimate that ~33 million Americans at 7.5% 10-year CVD risk and over 12 million at >5.0e7.4% 10-year risk could be recommended to receive statin therapy [8]. Also in England NICE has updated its guidance and recommends offering statin therapy for primary prevention to patients with a 10-year CVD risk of at least 10% [9]. However, even in the era of low-cost generic statins, statin therapy may not be cost-effective in low-
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risk populations in all situations [3e5,10]. In addition to encouraging the use of risk estimation as a part of patient management, current treatment guidelines highlight the importance of adherence to medication [11]. A substantial proportion of patients who are prescribed statins do not adhere to treatment [12]. Patients with poor adherence may experience worse outcomes and higher health care costs than patients with good adherence [13]. In previous studies where patient adherence has been taken into account, the results of the impact of patient adherence on the cost-effectiveness of statins in primary prevention have been conflicting [3,4,10]. Therefore, the aim of our present study was to explore the simultaneous effects of patients’ CHD risk level in combination with observed register-based real-world adherence (as well as ideal full adherence) on the cost-effectiveness of statin treatment in primary prevention of CHD events in the Finnish setting. This was done in an attempt to identify those patient groups for whom statin treatment is cost-effective under ideal and observed real-world adherence scenarios, and for whom the treatment from this perspective should be targeted or to whom adherence-supporting measures should be directed. 2. Methods 2.1. Cost-effectiveness model A previously constructed cost-effectiveness model [14e16] was modified to estimate the expected 10-year costs and health outcomes (in terms of quality-adjusted life-years, QALYs) associated either with statin treatment (with defined adherence levels) or without treatment with statins among hypothetical cohorts of Finnish men and women who were initially without signs or symptoms of CHD. Estimations were carried out for men and women separately at five different initial ages (i.e., 45, 50, 55, 60 and 65 years) with various levels of 10-year risk of CHD. The CHD risks were based on the FINRISK risk function for major coronary events (men ¼ (1/(1 þ exp(11.213e0.0802*age 0.6260*smoking 0.3293*cholesterol 0.0166*systolic blood pressure þ 0.5893*HDLcholesterol 0.7417*diabetes 0.3138*parents' infarction)))*100; women ¼ (1/(1 þ exp(11.839e0.0962*age 0.8776*smoking 0.2119*cholesterol 0.0175*systolic blood pressure þ 1.1009*HDLcholesterol 1.0303*diabetes 0.4090*parents’ infarction)))*100) [17]. The schematic presentation of the cost-effectiveness model is illustrated in Fig. 1. The model applied a Markov structure with a cycle length of one year. Each year, the hypothetical cohort of men or women without established CHD were at risk of having a fatal non-CHD event, a fatal CHD event, an acute non-fatal CHD event, or they might survive to the next year without suffering any kind of CHD event.
Fig. 1. Simplified schematic structure of the Markov model. CHD, coronary heart disease; MI, myocardial infarction.
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2.2. Event probabilities The annual total risk of initial non-fatal CHD event (International Classification of Diseases, ICD-10: I20.0, I21, and I22) or CHD death (ICD-10: I20eI25, I46, R96, and R98) was estimated using the FINRISK risk functions [17]. For simplicity, the estimated risks of CHD events at baseline were updated only on changes in patient's age keeping the other risk factors constant over the established 10year time horizon. Since the FINRISK risk functions were originally developed to predict total CHD risk, information from the National Cardiovascular Disease Register [18] was used to determine the age- and sex-specific case fatality. Annual age- and sex-specific risks of non-CHD death were estimated from the causes of death register by subtracting the fraction of deaths due to CHD (ICD-10: I20eI25, I46, R96, and R98) from the total mortality. After a nonfatal CHD event, the age- and sex-specific risks of death (CHD or non-CHD) were derived from published life tables. 2.3. Health care resource use and costs Costs, estimated from a societal perspective, included direct costs of statins and other medications, morbidity, rehabilitation, and production losses due to non-fatal CHD events. Annual ageand sex-specific costs (including costs of hospitalization, outpatient care and prescribed outpatient medications) resulting from acute CHD events were obtained from reports based on the national discharge and prescription registries [16,19]. The annual statin and other medication costs were obtained from the national registries. The average annual medication cost of treating dyslipidemia was estimated to be around V52 in men and women. This estimate was based on the distribution of different statins and strengths among new Finnish statin users starting treatment in 9/2007e12/2007 [20]. Reference prices in April 2013 were weighted by these proportions to estimate average annual statin costs. In addition, monitoring costs were estimated for patients using statins. These costs were based on the assumption of one additional doctor, nurse and laboratory visit annually and priced using Finnish standard health care costs [21]. The average annual costs for patients in secondary prevention were V363. This cost was based on the same monitoring costs as with statin treatment and the yearly costs of medications used in the secondary prevention of coronary heart disease according to Finnish Current Care Guidelines [22]. The costs of these medications were based on the yearly cost of low-dose aspirin (lowest price in May 2013) and yearly costs of adrenergic b-blocker agents, statins and angiotensin-converting-enzyme inhibitors derived from the Social Insurance Institution of Finland (SII). The costs from the SII were based on purchases in 2012 made by people entitled to a special reimbursement when buying these medications because they had been diagnosed with a severe, chronic disease like CHD. Adherence was not taken into account in secondary prevention. Costs of CHD rehabilitation were estimated by weighting the average rehabilitation costs obtained from the national rehabilitation registry at the SII by the proportion (3%) of CHD patients receiving rehabilitation. Productivity losses due to non-fatal CHD events were estimated by multiplying the average length of sickness leave due to myocardial infarction (i.e., 4.78 months) [23] by the average monthly income (including payroll tax) of Finnish employees in the year 2011. Productivity losses were applied to CHD patients below the average age of retirement, assumed to be 65 years, and taken into account in the sensitivity analyses. All costs (except medication costs) were adjusted to the 2011 price level using the official health care price index determined by the Association of Finnish Local and Regional Authorities. In
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addition, value-added tax of 10% was subtracted from the prices of medications. In the base-case, the costs were discounted at 3% per annum (as recommended by the Finnish health economic guidelines). All applied cost estimates are summarized in Table 1. 2.4. Quality-adjusted life-years Age- and sex-specific quality of life estimates measured by the generic EQ-5D instrument were used to represent the average quality of life in the Finnish population aged 45e74 years [24]. The disutility weights due to initial acute CHD event and post-acute CHD health state were obtained from previously published studies [24,25]. In the base-case, QALYs were also discounted at 3% per annum. The applied quality of life estimates are summarized in Table 1. 2.5. Medication adherence At the beginning of the simulation, the patient cohorts were assumed to start daily statin medication. The cost-effectiveness of statin treatment was assessed under observed real-world and ideal full adherence scenarios compared to no statin treatment. In realworld adherence scenario, adherence was determined from the Prescription Register managed by the SII. The cohort consisted of 45e75-year-old patients initiating statin treatment in primary prevention of CVD between Jan 1, 2000 and Dec 31, 2004 [26]. Primary prevention was determined as no sign of coronary heart disease, stroke, atherosclerosis or peripheral arterial disease in the Prescription Register, the Special Reimbursement Register or hospital discharge register maintained by the National Institute for Health and Welfare. Adherence was measured as the proportion of days covered (PDC) assuming that the patient took one tablet per day [27,28]. Yearly PDC-values for defined age groups for men and women were
estimated for the first 4 years of treatment because of the follow-up time in the data. Adherence was assumed to remain stable after year 4. Patients were classified to have either good (PDC 80%), moderate (40% PDC < 80%) or poor (PDC <40%) adherence [29e31]. In the full adherence scenario, all patients were assumed to have a PDC of 100%. The patients’ CHD event risk was modified by the risk reduction attributable to statins estimated in a published metaanalysis [1]. The risk ratio (RR) for combined fatal and non-fatal CHD events was 0.73 (95% confidence interval (CI) 0.67e0.80) (Table 1). The protective effect of statin treatment against CHD events was assumed to be conferred one year after treatment initiation (i.e., RR ¼ 1 in the first year) [32]. Patients classified as having good adherence had the same risk reduction as patients in the full adherence scenario. Patients with moderate adherence were assumed to have half of the risk reduction [33]. Patients classified as having poor adherence to statin treatment were estimated to have the same event risks as patients without statin treatment. From the second year onwards, the proportions of patients in each of the adherence classes in the previous year were determined and a weighted average of the risk reduction associated with statin treatment was estimated. The estimated annual average statin costs were used for patients in the full adherence scenario. In the real-world adherence scenario, the annual cost of statin treatment was weighted by the average PDC each year in the whole registry data. Monitoring costs were assumed to be the same for all statin patients regardless of different PDC-values and were the same in both adherence scenarios. 2.6. Sensitivity analysis Uncertainty associated with the model parameters (i.e., parameter uncertainty) was handled by determining probability
Table 1 Parameters applied in the Markov model. Parameter Costs AMI, mean (SE) 45e54 55e64 65e74 Fatal AMI Rehabilitation after MI (first year) Proportion of patients receiving rehabilitation after MI Statins Full adherence Real-world adherence
Monitoring a patient receiving statins in primary preventiona Secondary prevention Productivity costs due to non-fatal AMI Utilities, mean (SE) 45e54 55e64 65e74 Disutilities, mean (SE) AMI Post-AMI Treatment effectiveness of statins Fatal and non-fatal CHD event, RR (95% CI)
Men
V 15,873 (810) V 15,333 (782) V 13,793 (704)
Women
V 18,578 (948) V 17,329 (884) V 15,877 (810) V 1943 V 2305 3%
Distribution
Source
Normal Normal Normal Fixed Fixed Fixed
Martikainen et al., 2011 [16]
Hujanen et al., 2008 [21] SII SII, National Cardiovascular Disease Register
V 52.2 V 36.1 (1st year, average PDC 69.2%) V 31.5 (2nd year, average PDC 60.4%) V 31.2 (3rd year, average PDC 59.8%) V 31.5 (4th and subsequent years, average PDC 60.4%) V 147.9
Fixed Multinomial beta
Kiviniemi et al., 2011 [20], SII
Fixed
Hujanen et al., 2008 [21]
V 362.9 V 14,861
Fixed Fixed
Hujanen et al., 2008 [21], SII €inen et al., 2004 [23], Vehvila Statistics Finland
Beta Beta Beta
Estimated based on Saarni et al. (2006) and Soini et al. (2010) [24,25]
Beta Beta
Soini et al., 2010 [25] Saarni et al., 2006 [24]
Lognormal
Taylor et al., 2013 [1]
0.876 (0.005) 0.821 (0.006) 0.781 (0.008)
0.865 (0.005) 0.810 (0.006) 0.770 (0.008) 0.092 (0.029) 0.011 (0.009) 0.73 (0.67e0.80)
AMI, acute myocardial infarction; SE, standard error; MI, myocardial infarction; PDC, proportion of days covered; CHD, coronary heart disease; RR, risk ratio; CI, confidence interval; SII, Social Insurance Institution. a One additional doctor, nurse and laboratory visit.
E. Aarnio et al. / Atherosclerosis 239 (2015) 240e247
distributions for all relevant parameters and then conducting probabilistic sensitivity analysis (PSA) with 5000 iteration rounds [34]. The selection of proper probability distributions for the model parameters has been described previously in detail [15,16]. The proportion of patients in different adherence classes was assumed to follow a multinomial beta distribution. The results of the PSA were used to determine 95% CIs for the cost and health outcomes and to construct cost-effectiveness acceptability curves (CEACs). The CEACs were used to depict the probability of cost-effectiveness as a function of willingness-to-pay (WTP) per QALY gained. In addition, one-way and scenario sensitivity analyses were applied to test the robustness of model assumptions. The tested parameters included statin costs, monitoring costs, time horizon of the model, statin benefit in patients with moderate adherence, secondary prevention costs and discount rates. In real-world adherence scenarios, statin costs were weighted by the average PDC in the registry data in the same way as in the base case analyses. 3. Results The cost-effectiveness estimates of statin treatment in primary prevention of CHD in both real-world and full adherence scenarios in different patient populations are shown in Fig. 2 (more detailed results are presented in Appendices 1 and 2). At an assumed WTP threshold of V20,000 per QALY gained, statin treatment in the realworld adherence scenario seemed to be cost-effective among the older patient groups when the patients’ 10-year CHD risk was as high as 20% and did not seem cost-effective in the youngest age groups even at this highest tested risk level. However, in the full adherence scenario, statin treatment seemed to be cost-effective for almost all patient groups with a 10-year CHD risk of at least 15%. Also the incremental costs with statin treatment were smaller under full adherence than real-world adherence scenario in more than half of the tested patient groups (Appendices 1 and 2). In general, within age groups statin treatment was more cost-effective for patients with higher 10-year CHD risks due to higher incremental QALYs and lower incremental costs.
243
cost of monitoring, statin costs and to the time horizon of the model. If no monitoring costs were included in primary prevention, statin treatment seemed very cost-effective in both patient groups regardless of the adherence scenario employed and became cost-saving among 60-year-old women under full adherence scenario. The importance of monitoring costs in primary prevention was tested also with 45-year-old women with a 10-year CHD risk of 5%. The base case cost-effectiveness estimate for statin treatment was the highest in this patient group (V197,645 per QALY gained in the real-world adherence scenario). When no monitoring costs were assumed in primary prevention, the cost-effectiveness estimate improved substantially to V19,712 per QALY gained (data not shown). Results were quite sensitive to the costs of statins (Table 2). In the full adherence scenario, increasing annual statin costs to V220 raised the cost-effectiveness estimates in both patient groups to around V54,000e65,000 per QALY gained. However, in the realworld adherence scenario, even when no statin costs were taken into account, statin treatment did not seem to be cost-effective in either patient group. When a longer 15-year time horizon was used instead of the 10year time horizon, the cost-effectiveness estimates of statin treatment improved in all of the conducted sensitivity analyses in comparison to base case results (Table 2). Furthermore, the assumed benefit from statins in patients with moderate adherence also asserted an impact on the results. When no benefit from statins was assumed for patients with PDC under 80%, the cost-effectiveness estimates increased about V12,000eV15,000 per QALY gained in 55-year-old men and in 60-year-old women with a 10-year CHD risk of 10%. The estimated CEACs for 55-year-old men and 60-year-old women showed that the probability of statin treatment being costeffective increases as the patients’ risk levels rise (Fig. 3A and B). The CEACs also revealed how cost-effectiveness is improved under full adherence compared to real-world adherence. In both figures it can be seen that the probability of statin treatment being costeffective at a threshold of V15,000 per QALY gained is higher in patients with a 10-year CHD risk of 15% in the full adherence scenario than in patients with a 10-year CHD risk of 20% in the realworld adherence scenario.
3.1. Sensitivity analyses 4. Discussion Sensitivity analyses were conducted for 55-year-old men and 60year-old women with a 10-year CHD risk of 10% (Table 2). According to the sensitivity analyses, the study results were most sensitive to the
According to the results of this study, treatment adherence seems to have a major impact on the cost-effectiveness of statin
Fig. 2. Incremental cost-effectiveness ratio estimates (ICERs) for different age and risk groups by sex and adherence. Risk is the 10-year risk for suffering a fatal or non-fatal CHD event. QALY, quality-adjusted life-year; CHD, coronary heart disease.
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Table 2 One-way and scenario sensitivity analyses for 55-year-old men and 60-year-old women with a 10-year CHD risk of 10%. Real-world adherence
55-year-old men
DCosts (V)
60-year-old women
DQALY
Base case 1066 0.025 Productivity costs included 917 0.025 15-year time horizon 1429 0.054 Benefit from statins for patients with moderate adherence (base case: 50%) 0% 1098 0.020 30% 1079 0.023 80% 1047 0.028 Annual monitoring costs in primary prevention (base case: V 147.9) V0 64 0.025 V 300 2097 0.025 Annual statin costs with full adherence (base case: V 52.2 with full adherence)a V0 822 0.025 V 90 1244 0.025 V 220 1853 0.025 Annual secondary prevention costs (base case: V 362.9) V0 1079 0.025 V 1000 1046 0.025 Discount rates (base case: 3% for both costs and QALYs) 0%/0% 1262 0.031 5%/5% 959 0.021 Full adherence
ICER (V/QALY)
DCosts (V)
DQALY
ICER (V/QALY)
42,998 37,174 26,352
1018 936 1336
0.020 0.020 0.047
50,518 46,357 28,682
55,202 47,181 37,869
1062 1035 992
0.016 0.019 0.022
65,853 55,565 44,081
2596 84,713
9 2055
0.020 0.020
461 101,930
33,294 50,345 74,984
771 1197 1810
0.020 0.020 0.020
38,175 59,555 89,937
43,779 42,354
1032 991
0.020 0.020
51,144 49,233
41,282 44,639
1202 915
0.025 0.018
47,671 52,205
55-year-old men
DCosts (V)
60-year-old women
DQALY
Base case 1068 0.041 Productivity costs included 822 0.041 15-year time horizon 1420 0.089 Annual monitoring costs in primary prevention (base case: V 147.9) V0 58 0.041 V 300 2106 0.041 a Annual statin costs (base case V 52.2 with full adherence) V0 711 0.041 V 90 1326 0.041 V 220 2213 0.041 Annual secondary prevention costs (base case: V 362.9) V0 1088 0.041 V 1000 1032 0.041 Discount rates (base case: 3% for both costs and QALYs) 0%/0% 1261 0.051 5%/5% 961 0.036
ICER (V/QALY)
DCosts (V)
DQALY
ICER (V/QALY)
26,192 20,187 15,883
986 853 1267
0.033 0.033 0.076
29,960 25,974 16,730
1430 51,668
29 2031
0.033 0.033
Cost-saving 61,917
17,386 32,567 54,204
627 1247 2139
0.033 0.033 0.033
19,029 38,086 65,096
26,629 25,238
1011 944
0.033 0.033
30,775 28,766
24,847 27,023
1164 889
0.041 0.029
28,421 31,100
CHD, coronary heart disease; QALY, quality-adjusted life-year; ICER, incremental cost-effectiveness ratio. a V 90 reflects the annual cost of generic atorvastatin 10 mg and V 220 the annual cost of branded atorvastatin 10 mg.
treatment in primary prevention of CHD events. However, at an assumed WTP threshold of V20,000 per QALY gained, statin treatment did not seem to be cost-effective for patients with a 10year CHD risk of 10% even with the full adherence scenario. Apart from treatment adherence, the results of the cost-effectiveness assessments in the different patient groups were sensitive to monitoring costs in primary prevention, selected time horizon, and the cost of statins. Three recent studies have come to different conclusions about the cost-effectiveness of statin therapy and the sensitivity of costeffectiveness estimates with respect to statin adherence in primary prevention [3,4,10]. In the study of Greving et al., the base case result of the ICER of statin treatment was around V35,000 per QALY gained in the real-world adherence scenario [3]. With full adherence, the ICER estimate was around V26,000 per QALY gained. Lazar et al. reported that for most persons with even modestly elevated cholesterol levels or any CHD risk factors primary prevention with statins could be cost-effective [4]. Their cost-effectiveness estimates were insensitive to changes in statin adherence and an adherence level as low as 25% had only a minimal impact on statin cost-effectiveness. de Vries et al. estimated that starting statin treatment at the time of diagnosis of type 2 diabetes is costeffective, but that there are large differences in cost-effectiveness according to patients’ risk and age groups [10]. They reported adherence rates having a large effect on their results but chancing
adherence rates did not change the conclusion of statin costeffectiveness. Our study and the three recent studies [3,4,10] differ in many aspects. The time horizon in our study was 10 years as in the studies of Greving et al. [3] and de Vries et al. [10], whereas in the study by Lazar et al. [4] the time horizon was 30 years. The latter study [4] differed from the others also in that it modeled the statin effect by lowering the patient's LDL-levels which then affected the event risk. In contrast, our study and the two Dutch studies modeled the statin effect by lowering directly the patients' event risk. The choice of the modeling approach has been shown to affect costeffectiveness estimates [35]. Unlike our study, the three other studies [3,4,10] considered adverse events caused by statins in their cost-effectiveness models. They also took into account disutility from taking statins daily in their base case or sensitivity analyses. In contrast to our study and the study by Lazar et al. [4], the studies by Greving et al. [3] and de Vries et al. [4] considered the potential benefits of statins regarding stroke events in addition to CHD events. All the four studies differ in how nonadherence was modeled. There are also differences regarding patients in the models, cost and quality of life estimates used, modeling of secondary prevention, and assumptions used in the models. In the present study, statin treatment had lower incremental costs in many patient groups in the full adherence scenario as compared to real-world adherence scenario. This result is in
E. Aarnio et al. / Atherosclerosis 239 (2015) 240e247
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Fig. 3. Cost-effectiveness acceptability curves for patients with different 10-year CHD risks in different adherence scenarios for 55-year-old men (A) and for 60-year-old women (B). WTP, willingness-to-pay; QALY, quality-adjusted life-year; CHD, coronary heart disease.
accordance with previous studies where better adherence has been reported to be associated with lower overall health care costs [13]. It seems that full adherence to statin treatment could be costsaving compared to treatment with only real-world adherence. Therefore concerted effort is needed to motivate the patients who have been prescribed statins to actually take their medication in order to achieve the full benefit from investment in statins. However, improving patients’ adherence is not easy because of the complexity of medication-taking behavior [36]. Different risk functions and guidelines can lead to very different treatment decisions [37]. Using characteristics of a 50-year-old woman whose 10-year CHD risk according to the FINRISK risk function is 10% and CVD risk is around 17% [17], the ASCVD risk estimator from the ACC/AHA guideline calculates a 10-year CVD risk of around 19% (assuming no treatment for hypertension) [38]. The QRISK2-tool recommended by NICE estimates the 10-year CVD
risk to be almost 21% (assuming moderate smoking, type 2 diabetes, no other chronic diseases and a BMI of 29.8 kg/m2) [39]. According to the guidelines by the Japan Atherosclerosis Society, a patient with similar characteristics would be regarded as belonging to the high-risk group (a 10-year risk of death from coronary artery disease at least 2% or with high-risk conditions such as diabetes) [40]. Because we used the FINRISK risk function and concentrated in CHD events in our study, our cost-effectiveness estimates are not directly applicable to patient populations whose risks are estimated using other risk functions (especially with those which estimate risk for CVD events). There is uncertainty about the benefit of statins in patients with less than good adherence. We used an estimate of 50% benefit for patients with moderate adherence which was used also in a previous study [33]. The cost-effectiveness results were quite sensitive to this assumption especially when assuming no benefit from
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statins to patients with less than good adherence. However, changing the assumption from 50% to 30% did not have any major impact on the results. The lower PDC-limit for moderate adherence (i.e., 40%) used in our study was quite high as compared to that applied in the previous study by Cherry et al. [33]. However, in Finland it is possible to purchase up to 3 months’ medication at one transaction. This one purchase alone would mean a PDC-value of around 27% for one year. For this reason, a PDC-value of 40% was thought to be high enough to represent those patients with moderate adherence. Our research has limitations. First, we used a time horizon of 10 years. Statins are often meant to be used as a life-long treatment and it is possible that the time horizon used was too short to capture all the possible costs and benefits related to statin treatment. However, the use of a longer time horizon would have introduced more uncertainty into the final results. Second, adherence rates in the present study were based on patients starting statin treatment in the early 2000s. It is possible that adherence rates among new statin users have changed in the last 10 years. It is also possible that adherence rates differ between patients in different risk groups [41]. In our study, we used the same adherence figures regardless of the patients' 10-year risks. Third, the yearly cost of statin treatment was based on the distribution of different statins and strengths among new statin users in the fall of 2007. This meant that we could not take into account the possible changes made to patients’ treatment after treatment initiation. This probably underestimates the statin costs if treatment adjustments are made towards higher strengths and higher-potency statins. The statin costs employed do not reflect the costs of statins and strengths used in clinical trials on whose outcomes the clinical benefit of statin was based in the analyses. Fourth, neither adverse effects of statin treatment nor thrombotic stroke events were included in the cost-effectiveness model. Statins are generally well tolerated and serious adverse effects are rare [42]. The inclusion of the adverse effects would probably have raised the ICER estimates of statin treatment because there would have been fewer patients gaining benefit from statin treatment and greater costs due to the need to treat adverse effects. It has been estimated that about 10e15% of patients using statin suffer from muscle side effects [43]. Since all patients do not tolerate statins, full adherence cannot be achieved in real-world conditions. In addition, a diabetogenic action has been ascribed to statin use [44], and although it is clearly inferior to the beneficial effects of statins, it might have potential negative impact on the cost-effectiveness of statin treatment especially in the primary prevention setting. However, the inclusion of thrombotic stroke events in the cost-effectiveness model would have probably lead to lower ICER estimates, since statin treatment has been reported to reduce the risk of combined fatal and non-fatal stroke in primary prevention [1]. One strength of our study was that we used different sex, age and risk groups instead of an average patient group. We also used register-based estimates of real-world adherence instead of assumptions. Finally, effective prevention of CHD requires a multifaceted approach. In addition to dyslipidemia, other cardiovascular risk factors such as obesity, diabetes, smoking and elevated blood pressure should be addressed with changes in lifestyle and when required, with pharmacotherapy [11]. The therapeutic effectiveness and cost-effectiveness of statin treatment is significantly modulated by success or failure in adopting this holistic approach. 5. Conclusions The results of this study indicate that, even in the era of low-cost generic statins, treatment adherence potentially plays a major impact on the cost-effectiveness of statin treatment in primary
prevention of CHD events. This finding stresses the importance of making a concerted effort for improving adherence among patients on statin therapy to obtain full benefit of the investment in statins. Accordingly, novel cost-effective approaches for screening and improving treatment adherence are warranted. Conflict of interest statement The authors have the following conflicts: EA is funded by state funding for university-level health research (Grant L 3820). She has received consultancy fees from ESiOR Ltd. JM is the senior partner of ESiOR Ltd, which provides health economic and outcomes research (HEOR) services for pharmaceutical companies and hospitals. MJK and RH have been funded by the grants from the Social Insurance Institution (SII) (10/26/2007) and the Academy of Finland (number 138255). RH is a member of the Advisory Board for Social and Medical Affairs of the SII. He has conducted consultancy for Orion Corporation as an Independent External Member of a Data Monitoring and Safety Committee in a clinical trial, and assisted Santen Pharmaceutical Co in pharmacokinetic calculations. The authors declare no other financial or non-financial (professional or personal) conflict of interests. Acknowledgments Our study was funded by state funding for University-level Health Research (Grant L 3820), the Social Insurance Institution of Finland (www.kela.fi) (grant 10/26/2007) and the Academy of Finland (www.aka.fi, decision number 138255). The funders had no role in the design, analyses, interpretation of data, writing the report, or in the decision to submit the manuscript. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.atherosclerosis.2014.12.059. References [1] F. Taylor, M.D. Huffman, A.F. Macedo, et al., Statins for the primary prevention of cardiovascular disease, Cochrane Database Syst. Rev. 1 (2013) CD004816, http://dx.doi.org/10.1002/14651858.CD004816.pub5. [2] M. Neyt, C. De Laet, H. Van Brabandt, et al., Cost-effectiveness of statins in the primary prevention of cardiovascular disease: a systematic review and economic analysis for Belgium, Acta Cardiol. 64 (2009) 1e10. [3] J.P. Greving, F.L. Visseren, G.A. de Wit, A. Algra, Statin treatment for primary prevention of vascular disease: whom to treat? Cost-effectiveness analysis, BMJ 342 (2011) d1672, http://dx.doi.org/10.1136/bmj.d1672. [4] L.D. Lazar, M.J. Pletcher, P.G. Coxson, et al., Cost-effectiveness of statin therapy for primary prevention in a low-cost statin era, Circulation 124 (2011) 146e153, http://dx.doi.org/10.1161/CIRCULATIONAHA.110.986349. [5] A.P. Mitchell, R.J. Simpson, Statin cost effectiveness in primary prevention: a systematic review of the recent cost-effectiveness literature in the United States, BMC Res. Notes 5 (2012) 373, http://dx.doi.org/10.1186/1756-0500-5373. [6] M. Rikala, R. Huupponen, A. Helin-Salmivaara, M.J. Korhonen, Channelling of statin use towards low-risk population and patients with diabetes, Basic Clin. Pharmacol. Toxicol. 113 (2013) 173e178, http://dx.doi.org/10.1111/ bcpt.12075. [7] N.J. Stone, J.G. Robinson, A.H. Lichtenstein, et al., ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines, Circulation 129 (2014) S1eS45, http://dx.doi.org/10.1161/01.cir.0000437738.63853.7a. [8] P.M. Ridker, N.R. Cook, Statins: new American guidelines for prevention of cardiovascular disease, Lancet 382 (2013) 1762e1765, http://dx.doi.org/ 10.1016/S0140-6736(13)62388-0. [9] S. Rabar, M. Harker, N. O'Flynn, et al., Lipid modification and cardiovascular risk assessment for the primary and secondary prevention of cardiovascular disease: summary of updated NICE guidance, BMJ 349 (2014) g4356, http:// dx.doi.org/10.1136/bmj.g4356. [10] F.M. de Vries, P. Denig, S.T. Visser, et al., Cost-effectiveness of statins for primary prevention in patients newly diagnosed with type 2 diabetes in the
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