Rochelle Henderson, PhD, MPA

Chronic myeloid leukemia, also called chronic myelogenous leukemia (CML), is a slow-growing cancer of the white blood (myeloid) cells in bone marrow and blood. It is estimated that there will be 5920 new cases of CML and 610 deaths due to CML in the United States in 2013. The incidence of CML increases with age, with half of all new cases of CML diagnosed in individuals 65 years or older.

 As record numbers of American baby boomers (born between 1946 and 1964) reach their mid-60s, the number of new patients diagnosed with CML is expected to increase.

Untreated, CML takes an average of 4 years to become more aggressive and reach the blastic stage, when it is usually fatal. However, the prognosis and survival of CML patients have improved dramatically since imatinib, an orally administered chemotherapeutic agent, was approved by the US Food and Drug Administration in 2001. Five-year survival rates for newly diagnosed patients with CML increased from 40% between 1996 and 2000 to more than 55% between 2001 and 2007.

Long-term studies have shown dramatically decreased mortality and improved survival among CML patients taking imatinib.

 Consequently, CML has effectively been transformed into a chronic disease with patients using imatinib and other CML medications over extended periods of time.

 Despite imatinib’s life-extending benefits, many patients struggle to remain adherent to it. A large body of scientific evidence has demonstrated that optimum outcomes from drug therapy are reliant on adherence.

Although previously published studies have defi ned optimum adherence to imatinib as 90% or above, actual average adherence among US commercially insured CML patients is reported at about 80%,

 with only 54% of patients taking imatinib achieving adherence of 90% or higher.

CML patients face many challenges influencing their medication adherence, including coordination with physicians and other healthcare providers, managing complex treatment regimens, medication side effects, and healthcare costs. Common side effects of imatinib include diarrhea, muscle cramps, nausea, skin reactions, swelling, and vomiting. More serious adverse effects such as myelosuppression (decreased ability of bone marrow to produce blood cells) and elevated liver transaminase levels (indicative of liver damage) may require treatment interruptions.

 Additionally, with the annual cost of therapy reported to be $92,000 in 2012, the economic burden of imatinib is substantial.

 Couple the clinical challenges with the out-of-pocket drug cost facing cancer patients, and it is not surprising that medication adherence is lower than desired, posing a serious concern to patients, clinicians, and payers.

The need to improve medication adherence among patients using oral oncology medications such as imatinib is widely recognized.

 According to a National Comprehensive Cancer Center Task Force, oncology-specific support from specialty pharmacies improves adherence, encourages communication between patients and pharmacists, identifies potential safety concerns, helps prevent unwarranted drug expenditures, and ensures appropriate use of medications.

 Given the suboptimal adherence rates to imatinib therapy, patients given this medication, especially those who are new to imatinib therapy,

 are ideal candidates for therapy-related services commonly provided by specialty pharmacies such as refill reminder programs and oncology care management.

Our hypothesis was that adherence to imatinib would be higher among patients starting a new course of therapy with a specialty pharmacy instead of other dispensing channels. Our study objective was to compare imatinib adherence between patients using specialty pharmacy and those using other dispensing channels.

A claims-based, retrospective study was conducted using de-identified prescription data collected by a large national pharmacy benefi ts manager (PBM) with an in-house specialty pharmacy. Patients receiving imatinib through the specialty pharmacy had access to supportive services designed to enhance clinical outcomes, increase drug safety, manage side effects, and help patients stay on therapy. Nurses and pharmacists specifically trained in oncology provided education and care management through proactive patient outreach throughout the course of therapy at clinically meaningful intervals. Telephonic prescription refill reminders were timed to be made when the patient’s quantity of imatinib reached a specifi ed level prior to depletion, to ensure an uninterrupted supply of medication.

Pharmacy claims data for the period July 1, 2010, to August 31, 2012, were analyzed. Irrespective of the type of pharmacy or dispensing channel used, the claims data set included all patients for whom the PBM processed claims for oncology drugs. Thus, patients in the study could obtain imatinib from any combination of the inhouse specialty pharmacy, other specialty pharmacies, retail pharmacies, or home delivery pharmacies. Patients who obtained a simple majority of their 30-day adjusted imatinib prescriptions from the PBM’s in-house specialty pharmacy were assigned to the specialty pharmacy group. Patients receiving a majority of their imatinib supply from other channels were assigned to the other pharmacy group. The design of this study was not submitted to an institutional review board, as only de-identified administrative data were used. All regulations related to the Health Insurance Portability and Accountability Act were followed.

Patient records selected for the study showed at least 1 prescription claim for imatinib (Medi-Span Generic Product Identifier code 21-53-40-35-10) during the index period between January 1, 2011, and August 31, 2011. Analysis was limited to patients new to therapy, defined as patients with no imatinib claims in the 6 months prior to the index imatinib claim. To accurately assess newto-therapy status and postinitiation adherence, study patients were required to be continuously eligible for pharmacy benefits 6 months prior to and 12 months following the index imatinib claim. Medicare and Medicaid beneficiaries were excluded from the analysis since these patients’ pharmacy benefit design is different from that of commercial patients. Patients who paid 100% of the out-of-pocket cost for imatinib were also excluded from the analysis because it was likely that imatinib was not covered by the pharmacy benefi t for these patients. We may not have captured all transactions for patients who paid 100% of their medication cost. These patients may not have used the pharmacy benefit and hence generated no claims. Each study patient was followed for 365 days after the index imatinib claim.

The outcome of interest was optimum imatinib adherence, a dichotomous variable defi ned as a proportion of days covered (PDC) of 90% or higher during follow-up. The PDC was calculated as the number of days the patient had medication on hand during the 365-day followup period divided by 365.

When the days of supply from a new fill overlapped the last 7 days of supply of imatinib from a previous fill, the fill date for the new fill was adjusted forward to the depletion date of the earlier fill. The patients were thus credited for finishing the supply of imatinib from the previous fill before using the supply of imatinib from the subsequent fill. In situations where multiple claims for imatinib representing different drug strengths (100 mg and 400 mg) occurred concurrently on the same fill date, it was assumed that medication from both claims would be used concurrently and no adjustment was made. The PDC was also evaluated as a continuous variable.

A literature review identifi ed adherence channel confounders, which were included in multivariate analysis. Demographic confounders included patient sex and age at the time of the index imatinib claim.

 Because urbanicity may impact access to pharmacies and therefore  adherence,

 we created a dichotomous indicator for whether the 5-digit zip code of the patient’s residence was inside the urban center of a US Census—defined Core Based Statistical Area.

Patient out-of-pocket cost burden was determined by averaging the amounts paid by the patient (copayment, coinsurance, and deductible) per 30-day supply of imatinib during the follow-up period.

 was the number of therapy classes (as established by the number of unique 2-digit Medi-Span Generic Product Identifi er codes) used by the patient during the follow-up period.

 Because the use of more days of supply per prescription may also improve adherence,

 the average number of days of supply per unadjusted imatinib prescription was included as a covariate. Finally, an indicator was created to identify patients who had at least 1 imatinib claim paid by a plan sponsor whose pharmacy benefit design included a days-of-supply optimization program for specialty medications including imatinib.

As part of this program, patients starting a new course of imatinib therapy were provided medication in 30-day increments for the initial 90 days of therapy, after which patients transitioned from 30-day prescriptions to 90-day prescriptions of imatinib for the remainder of follow-up. Although the program was intended to maximize appropriate use, it may have affected the imatinib PDC in 2 ways. First, patients who completed the first 90 days of therapy would have a higher PDC based on having more days of supply per prescription. Second, those patients who discontinued therapy before completing the first 90 days of therapy would have a lower PDC based on having fewer days of supply per prescription.

Differences in age and imatinib PDC between the specialty pharmacy group and other pharmacy group were evaluated using 

 tests. Differences in out-of-pocket pharmacy spending per 30-day adjusted imatinib claim, medication burden, and days of supply per unadjusted imatinib prescription were evaluated using nonparametric Wilcoxon rank sum tests because the distributions of these variables were highly skewed. Differences in categorical variables were evaluated with χ

 tests. Logistic regression models were created with dichotomous imatinib adherence as the primary dependent variable, dispensing channel as the primary independent variable, and other covariates. Multivariate adjustment for continuous imatinib PDC was performed using ordinary least squares regression with PDC as the dependent variable, dispensing channel as the primary independent variable, and other known confounders as covariates.

The Figure outlines the patient selection procedure. A total 6121 patients had at least 1 prescription claim for imatinib between January 1, 2011, and August 31, 2011. Excluded were 1550 patients who were not continuously eligible for pharmacy benefi ts 6 months before and 12 months after the index imatinib claim, 3556 patients who had a claim for imatinib in the 6 months prior to the index claim, 2 patients with inconsistencies in their eligibility information, 292 whose pharmacy costs were paid by Medicare Part D, 3 who were Medicaid beneficiaries, and 14 who paid the entire cost of imatinib out of pocket. The fi nal study sample consisted of 704 patients, of which 433 were in the specialty pharmacy group and 271 in the other pharmacy group.

Selected characteristics of the study patients are presented in 

. Patients in the 2 study groups had similar distributions of age, sex, and urbanicity. Compared with the other pharmacy group patients, patients in the specialty pharmacy group had lower out-of-pocket imatinib costs and a lower medication burden. Patients in the specialty pharmacy group had on average about 15 additional days of imatinib per prescription. More patients in the specialty pharmacy group had at least 1 fill of imatinib through a benefit that encouraged 90-day fills only for patients stabilized on imatinib therapy.

During the follow-up period, patients in the specialty pharmacy group had greater odds of being adherent (a PDC of at least 90%) (unadjusted odds ratio [OR] = 1.87, 95% confi dence interval [CI], 1.36-2.58) compared with patients in the other pharmacy group. After adjusting for confounders, patients in the specialty pharmacy group were signifi cantly more likely to achieve optimum imatinib adherence (adjusted OR = 1.46, 95% CI, 1.02-2.09; 

). When we examined the second outcome, continuous PDC, we found that the unadjusted average PDC for imatinib was greater for the specialty pharmacy group than for patients in the other pharmacy group (75.78% vs 60.37%; 

 <.0001). After multivariate adjustment using ordinary least squares, controlling for known confounders, and setting all model coeffi cients to their mean values, the adjusted PDC for specialty pharmacy patients was 74.14% versus 63.34% in the other pharmacy group (

Our study found that patients who used a specialty pharmacy that provided refill reminders and comprehensive clinical care management programs to fill a majority of their imatinib prescriptions had a significantly higher likelihood of attaining optimum imatinib adherence compared with those using other dispensing channels for a majority of their 30-day adjusted imatinib prescriptions.

Adherence to imatinib has been associated with lower healthcare costs. A study of US commercially insured CML patients starting imatinib therapy found that those with medication possession ratios (MPRs) of 85% and above incurred $17,727 less in total healthcare costs over a 12-month follow-up period than patients with lower MPRs.

Another study of CML patients found that a 10% using a retail pharmacy. In the same study, specialty pharmacy patients had 13% lower total healthcare costs (medical and pharmacy) compared with retail pharmacy patients over a 12-month follow-up period.

Goals proposed by the National Comprehensive Cancer Network Task Force on Specialty Pharmacy include maximizing adherence, optimizing clinical outcomes, and improving economic outcomes.

 The specialty pharmacy investigated in this study offered patients a  number of interventions and programs to attain these goals. From the initiation of imatinib therapy, patients using the specialty pharmacy had access to oncology-trained nurses and pharmacists for disease and drug education and support. Planned, proactive interactions also allowed for detection of potential side effects, medication errors, and premature discontinuation of therapy. In addition, adherence monitoring and refi ll reminders affected the imatinib adherence of specialty pharmacy patients.

There are several limitations to this study, a number of which result from the exclusive use of pharmacy claims data for this analysis. Because integrated medical claims and patient chart data were unavailable, patients could not be selected or stratifi ed based on medical diagnosis or cancer stage. Disease severity could not be controlled for in the multivariate adjustment. The PDC calculation did not adjust for time spent in the inpatient setting among those patients who were admitted. A proxy to control for the impact of medication burden on adherence was created, but this proxy did not completely capture comorbidity burden. A possession-based measure of adherence was used as the study outcome, assuming that any imatinib possessed by the patient was taken as prescribed. Similar measures have been used in earlier studies.

 A 6-month preindex period was used to select imatinib patients starting a new course of therapy. It is possible that all study patients may not have been imatinib naïve at the time of the index imatinib claim in this study, which may have had an infl uence on imatinib adherence.

The findings from this study are generalizable only to commercially insured patients with PBM-administered pharmacy benefits. Additionally, some patients in the other pharmacy group may have obtained the majority of their medications from another specialty pharmacy. However, it has been reported that specialty pharmacies have a wide range of pharmacy delivery models and offer a variety of oncology care management interventions.

 Because the specific care model of each external specialty pharmacy or retail pharmacy could not be determined, all patients using one of these channels for a majority of their imatinib prescriptions were combined into a single comparator group. Patients in the other pharmacy group may have been provided with intensive and comprehensive oncology care through their pharmacy; thus, this analysis represents a conservative estimate of the impact of specialty pharmacy on imatinib adherence. Finally, this study may be biased because of the “healthy adherer” effect. Patients who generally espouse healthy behaviors may select specialty pharmacy over other channels to take advantage of the more intensive and disease-focused approach of this channel and may also be more motivated to be adherent to medications. It is possible that part of the superior adherence observed in specialty pharmacy may be explained by a greater proportion of healthy adherers using specialty pharmacy, rather than channel characteristics.

This study found that commercially insured patients using specialty pharmacy integrated with refi ll reminders and a comprehensive oncology care management program were 46% more likely to achieve optimum adherence to imatinib compared with patients who did not use the specialty pharmacy. With an increasing number of oral medications for cancer entering the marketplace,

patient adherence is an increasingly important determinant of treatment success. Plan sponsors, payers, and patients may benefit from a pharmacy model used by the specialty pharmacy evaluated in this study for the dispensing and use of oral oncology medications.

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