CLINICAL. The Effect of Switching on Compliance and Persistence: The Case of Statin Treatment

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1 The Effect of Switching on Compliance and Persistence: The Case of Statin Treatment Patrick Thiebaud, PhD; Bimal V. Patel, PharmD; Michael B. Nichol, PhD; and David M. Berenbeim, MD Objective: To determine the effect of switching drugs on the compliance and persistence of new statin users. Study Design: Retrospective database analysis of pharmacy claims provided by a large pharmacy benefit manager. The study sample consisted of new statin users 18 to 65 years old beginning treatment with atorvastatin calcium, fluvastatin sodium, lovastatin, pravastatin sodium, or simvastatin. Methods: Compliance was measured by the medication possession ratio, and persistence was measured by the time to discontinuation. Switching rates were derived from the proportions of patients filling a prescription other than the initial statin. Results: Patients who switched statins were less compliant by 18.9% (odds ratio, 0.81; P <.001), as defined by the probability of having a medication possession ratio of 0.8 or higher, and were less persistent by 20.9% to 48.3% (P <.001) depending on the gap length used to define discontinuation. Conclusions: Switching statins substantially reduces the likelihood that patients will be compliant and remain on treatment long enough to obtain the full benefit of statin treatment. To ensure better compliance, special care should be given to patients who change drugs. (Am J Manag Care. 2005;11: ) Coronary heart disease and stroke impose a large burden on individual patients and society. In 2001, coronary heart disease and stroke had prevalences of 6.4% and 2.0%, respectively, 1 and their combined projected cost in 2005 is $142.1 billion. 2 Since the National Cholesterol Education Program (NCEP) issued in 2001 its third report of the Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III), 3 other investigations have suggested that a more aggressive approach should be taken in cholesterol management, targeting lower levels of low-density lipoprotein (LDL) cholesterol. 4 These 2004 guidelines recommend a low-density lipoprotein cholesterol level of less than 100 mg/dl (<2.59 mmol/l). Regardless of their initial LDL cholesterol levels, patients should initiate therapeutic lifestyle changes first, followed by drug therapy if additional reduction is needed. Statins are recommended as the first-line drug therapy because of their effectiveness and good tolerability, 3 but nonstatin options such as bile acid sequestrant or nicotinic acid are also available. Statins have been shown to reduce the number of vascular events when used in primary and secondary prevention of coronary heart disase. 5-8 They also contribute to a lower incidence of stroke. 1,2 Despite the weight of evidence supporting sustained treatment, nonadherence and suboptimal adherence remain common problems among patients treated with statins Poor compliance not only deprives patients of the benefit of treatment but also can lead to serious adverse events Compliance and persistence depend partially on how successful the treatment is at lowering cholesterol to a target concentration and on what the patient perceives to be the health benefit. 18,19 Treatment adverse effects are also a major source of low compliance, as 41% of patients discontinue therapy because of poor efficacy or adverse events. 20 Prescribing suboptimal initial drugs and maintaining patients on low dosages for too long, among other inappropriate therapies, reduce the chance that treatment will succeed in reaching cholesterol targets. 21 Once drug treatment has started, LDL cholesterol control may require higher dosages of the initial drug, additional lipid-lowering agents, or a switch to another statin, a therapeutic step justified by variation in the tolerability and efficacy of statins In this context, it is critical to determine what effect switching statins has on compliance and whether a drug change compromises treatment goals. A better knowledge of statin utilization patterns in clinical practice would clarify the options available to physicians for Ascend Media From the Department of Pharmaceutical Economics and Policy, School of Pharmacy, University of Southern California, Los Angeles (PT, MBN); and MedImpact Healthcare Systems, Inc, San Diego, Calif (BVP, DMB). This research was conducted as part of postdoctoral work at the University of Southern California (PT) and was made possible by a grant from Pfizer Inc, New York, NY. Pfizer Inc had no control over the collection, analysis, or interpretation of data or the article resulting from this research. The authors have unrestricted publication rights. Address correspondence to: Patrick Thiebaud, PhD, Department of Pharmaceutical Economics and Policy, School of Pharmacy, University of Southern California, 1540 East Alcazar Street, CHP 140, Los Angeles, CA thiebaud@usc.edu. 670 THE AMERICAN JOURNAL OF MANAGED CARE NOVEMBER 2005

2 The Effects of Switching Statins improving lipid management and would allow them to better understand the consequences of altering drug treatment. To our knowledge, no published research has focused on this issue. This research seeks to fill this void by estimating how switching statins affects compliance and persistence among new statin users in a managed care environment. METHODS Study Sample and Selection Criteria We conducted a retrospective cohort study based on data provided by a West Coast pharmacy benefit manager. Patients were between the ages of 18 and 65 years. All patients were new statin users as defined by a 1-year wash-out period before filling the first prescription for a statin. Each patient had been continuously eligible for benefits for 2 years between April 2001 and June 2004, specifically for 1 year before and 1 year after filling the first statin prescription. The beginning date for continuous eligibility varied among patients. The date of first prescription fill defined the index date for the analysis. Outcome Measures Compliance and persistence were measured for the following 5 statins: atorvastatin calcium, fluvastatin sodium, lovastatin, pravastatin sodium, and simvastatin. (Rosuvastatin calcium was introduced too recently to allow for evaluation of compliance within the time frame of the analysis.) Compliance was measured by the number of days the medication was available to the patient, called the medication possession ratio (MPR). The MPR is the sum of the days of supply for 1 year after the first prescription was filled, divided by 360. Any prescriptions filled later than 360 days after the index date were excluded, as were any days of supply that occurred after the end of follow-up. The MPR calculation included all statins after the index date, even if different from the initial drug. Persistence represents the length of time patients remained supplied with statins. It was measured by the time to discontinuation, defined as the number of days before the first gap in medication possession. A gap is the number of days between the time patients ran out of their current prescription and the time they filled a new prescription. Before reaching this threshold, patients were assumed to be fully compliant. The supply of overlapping statin prescriptions was added to the total days of continuous supply. Results are provided herein for gap lengths of 15, 30, and 60 days. Finally, we defined indicators of switching statins and of increasing the dosage. We used binary indicators for switching to another statin during the 1-year followup and for increasing the dosage from the strength of the initial statin. Predictors All predictors were used as covariates in the multivariate analyses. They were divided into 4 categories. First, we defined predictors related to patients, including age, sex, geographic region, and health status as determined by RxRisk, a risk assessment system that classifies patients by their medication use during the year before their statin index date. 25 Second, we defined predictors related to health insurance, including formulary types, health plan sizes, and mean copayments. There are 3 formulary types, ranked from the most to the least restrictive, namely, closed, incentive, and open types. A closed formulary does not cover nonformulary drugs, an incentive formulary covers nonformulary drugs but at a higher copayment, and an open formulary covers nonformulary drugs at the same copayment. The health plan size variables were divided into the following categories based on the total number of enrollees: fewer than , to , and more than The mean copayments were calculated by averaging out-of-pocket costs across all prescriptions filled before switching statins if there was a switch and across all prescriptions otherwise. Third, to control for the effect of complex drug treatment and possible drug interactions on adherence, we defined variables related to drugs used after the initial statin. These variables included the utilization of nonstatin antilipidemic agents, the use of antihypertensive drugs for cardiovascular disease (antiarrythmics, vasodilators, and cardiac stimulants), and the number of prescriptions per month before the switch for switchers and during the whole year for nonswitchers. We also accounted for the use of nonstatin antilipidemic agents before treatment initiation. Fourth, the year of treatment initiation was included in our estimates to remove the effect of treatment trends and stricter treatment guidelines. Statistical Analysis One of the challenges of observational studies is to distinguish the effect of treatment from the effect of factors that influence treatment selection. Without random assignment, treatment groups may differ in ways that influence treatment choice and treatment outcomes, thereby introducing bias in the estimation of treatment effect. In this study, it was important to account for the differences that may affect outcomes VOL. 11, NO. 11 THE AMERICAN JOURNAL OF MANAGED CARE 671

3 between patients who do and do not switch drugs. To control for this problem, the propensity score (PS) method was used to adjust for pretreatment differences between treatment groups. 26 Controlling for potential bias and adjusting for pretreatment differences require that variables determining selection, such as alternative treatments, be included in the estimation of the PS as controls. The PS is a patient s estimated probability of switching drugs as calculated by logistic regression of all pretreatment variables (age, sex, health status, mean copayment, use of nonstatin antilipidemic agents, etc) on a binary variable equal to 1 if the patient switched drugs. The inverse of the PS is then used to weigh each observation in other logistic regressions. Propensity score weighted logistic regressions were used to evaluate the effect of treatment on the probability of compliance (ie, having an MPR of 0.8) and different degrees of low compliance Table 1. Characteristics of the Study Sample* Did Not Switch Drugs Switched Drugs Variable (n = ) (n = 3248) Age, mean, y Female sex Geographic region Pacific Central Mountain East Southeast Comorbidities Anxiety Asthma Depression Diabetes mellitus Gastric acid disorder Heart disease Thyroid disorder Formulary type Closed Incentive Open Copayment, mean, $ Before switch After switch # *Data are given as percentages of patients unless otherwise indicated. With more than 5% of patients affected. Other than hypercholesterolemia. Percentages do not sum to 100 because of missing data. P <.05, χ 2 test, for switchers vs nonswitchers. P <.001, t test, for switchers vs nonswitchers. # Not significant for switchers vs nonswitchers. (ie, having MPRs of and < 0.4). Other PSweighted logistic regressions were used to estimate the probability of the time to discontinuation (ie, having first gaps in treatment of 180 and 360 days). Analyses were performed with SAS 9.1 (SAS Institute Inc, Cary, NC). RESULTS There were patients included in the study sample. Among these, 8.4% switched drugs during their first year of treatment, and the others continued taking their initial drug throughout follow-up or stopped statin treatment completely (Table 1). Patients who switched statins were slightly older than nonswitchers (P <.001, t test) and were more likely to be female (P <.05, χ 2 test). They were also more likely to receive drug treatments for comorbidities, but the differences in their health status were generally small (P <.05, χ 2 test). Their geographic distribution was also similar (P <.05, χ 2 test), with the largest numbers of patients living in the eastern United States. Statin switchers, 56.5% of whom switched within 6 months of the initial prescription, were less likely to be compliant than nonswitchers (Table 2). They were more likely to experience a gap in therapy of at least 30 days within the first year or first 6 months of initial therapy. Switchers were less likely to increase the dosage of their initial prescription. Finally, by switching, patients reduced their out-of-pocket cost per prescription by $1.33 on average. Multivariate analysis confirmed that switching statins can hurt compliance. Switching reduced the odds of high compliance by 18.9% (odds ratio [OR], 0.81; P <.001). Relative to nonswitchers, the probabilities of an effect on compliance (adjusted with PS weights) were as follows for the 3 MPR levels ( 0.8, , and <0.4): OR, 0.81 (95% confidence interval [CI], ); OR, 1.82 (95% CI, ); and OR, 0.66 (95% CI, ); respectively. Persistence was similarly affected by switching, as demonstrated by the probabilities that patients will discontinue treatment or experience a gap in treatment before 360 or 180 days. Depending on the gap length used to define discontinuation, the probability of interrupting treatment before the end of the first year was 20.9% (for a 60-day gap) to 48.3% (for a 15-day gap) greater for switchers than nonswitchers. Relative to nonswitchers, the probabilities of an effect on persistence (adjusted with PS weights) were as follows for the 3 gap lengths (15 day, 30 day, and 60 day): for discontinuation before 360 days, OR, 1.48 (95% CI, THE AMERICAN JOURNAL OF MANAGED CARE NOVEMBER 2005

4 The Effects of Switching Statins 1.54); OR, 1.44 (95% CI, ); and OR, 1.21 (95% CI, ); respectively; and for discontinuation before 180 days, OR, 1.36 (95% CI, ); OR, 1.35 (95% CI, ); and OR, 1.16 (95% CI, ); respectively. Evidence showed that switching was the cause of the low compliance and persistence observed among switchers. First, the observed difference in persistence between switchers and nonswitchers increased substantially over time, from 34.6% at 6 months to 44.2% at 1 year for a 30- day gap in treatment. This difference resulted in part because the proportion of switchers increased with the length of time from the initial prescription (at 6 months, only 56.5% of the switchers had changed their statin treatment) (Table 2). Second, most switchers filled 4 or more prescriptions (based on an MPR level of 0.4). This level of compliance is to be expected because switchers need to be sufficiently motivated to stay on treatment long enough to undergo a change in therapy. Those who lack this minimum level of motivation and consider stopping treatment after 1 or 2 prescriptions are unlikely to try a different statin. Despite this, the mean MPR and the likelihood of compliance and persistence were lower for switchers than nonswitchers, lending support to the idea that compliance drops after switching drugs. DISCUSSION The decision to switch to a new drug for the treatment of hypercholesterolemia is motivated by several factors. A physician may observe that a course of statin treatment has failed to lower cholesterol sufficiently, or a patient may experience intolerable adverse effects and ask for another drug. Some patients may also try to lower their out-of-pocket cost by switching to a drug with a lower copayment. For these patients, switching translates into low compliance and persistence. Patients who switched were 18.9% less likely than nonswitchers to maintain sufficient compliance to obtain the full benefit of statin treatment, as measured by the MPR. Patients who switched were also 20.9% to 48.3% more likely to discontinue treatment (P <.001), depending on the gap length used to define discontinuation and the duration of follow-up. There is evidence that lower compliance and persistence among patients who switch statins can be mostly attributed to the effect of switching drugs. As time from the initial prescription passes, an increasing proportion of patients taking statins switch drugs. If the switch is detrimental to persistence, we should observe a widening gap between switchers and nonswitchers. This is precisely what happens, with the odds of discontinuation within a year being at least 25% greater than within the first 6 months. Moreover, patients need to maintain a level of compliance before switching to a new drug. Patients who seriously try to follow their treatment plan are far more likely to fill a prescription for another statin than patients who stop their treatment altogether. This pattern was clear in the analysis of compliance herein, with fewer switchers than nonswitchers filling less than 4 prescriptions during follow-up. The decision to switch drugs does not appear to be motivated by cost considerations. Patients who switched to a new drug saved $1.33 per prescription on average, which is too small an amount to act as a significant incentive for most patients. Our results suggest that switching statins, while an important tool of drug therapy for lipid management, should be done with caution. Physicians should be aware of the compliance risks that accompany switching and give special attention to patients undergoing a change in statin therapy. Regarding future research, more extensive data would provide additional insight into drug utilization behaviors. Limitations of our data did not allow us to evaluate the effect of nondrug treatments such as programs to encourage lifestyle changes. Interventions to promote lifestyle changes are important first steps in lipid therapy and may be partial substitutes for drug treatments. Accounting for treatment options would Table 2. Summary of Compliance, Persistence, and Initial Statin Dosage* Did Not Switch Drugs Switched Drugs Variable (n = ) (n = 3248) Medication possession ratio Time to discontinuation, d < < Switching before 180 d 56.5 Dosage Was increased from the initial strength Was prescribed the minimum strength for the initial statin *Data are given as percentages of patients. For all variables except switching before 180 days, comparisons are for a gap length of at least 30 days, with P <.001, χ 2 test, for switchers vs nonswitchers. VOL. 11, NO. 11 THE AMERICAN JOURNAL OF MANAGED CARE 673

5 allow us to better assess the effect of switching drugs on compliance. Comprehensive information about patients socioeconomic background, unavailable to us, would also improve our understanding of the effect of switching drugs on utilization and adherence patterns. For example, low-income patients may reduce their out-of-pocket costs by using free samples or by filling prescriptions for higher dosages and splitting these pills. Free samples may also be used to try out new medications, altering the observed drug switching rates and compliance levels. Further research is also needed to evaluate the longterm effect of drug switching on compliance. Our study included a short follow-up, restricting our analysis to the evaluation of patients who switched drugs within a few months of treatment initiation. Finally, the prescription utilization patterns of populations who are not reflected in our pharmacy claims database are also of interest. Because our study sample consisted of continuously eligible commercially insured patients, the results may not be generalizable to other populations such as retirees or patients transitioning between employer-sponsored insurance plans. Therefore, caution should be used when applying these results to other populations. REFERENCES 1. National Heart, Lung, and Blood Institute. Morbidity and Mortality: 2004 Chartbook on Cardiovascular, Lung, and Blood Diseases. Bethesda, Md: National Heart, Lung, and Blood Institute. May American Heart Association. Heart disease and stroke statistics: 2005 update. Available at: HDSStats2005Update.pdf. Accessed January 10, Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). 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