Barriers to receipt of novel oral oncolytics: A single-institution quality improvement investigation.

INTRODUCTION: Novel oral oncolytic agents have become the standard of care and first-line therapies for many malignancies. However, issues impacting access to these drugs are not well explored. As part of a quality improvement project in a large tertiary academic institution, we aim to identify potential barriers that delay treatment for patients who are prescribed novel oral oncolytics. METHODS: This was a retrospective review of adults who were newly prescribed a novel oral oncolytic for Food and Drug Administration-approved indications at a single tertiary care center. Patients were identified via electronic prescription data (e-Scribe). Demographics, insurance information, and prescription dates were extracted from the electronic medical record and pharmacy claims data. Statistical analyses were performed to determine whether time-to-receipt was associated with insurance category, pharmacy transfers, cost assistance, and drug prescribed. RESULTS: Of the 270 successfully filled prescriptions, the mean time-to-receipt was 7.3 ± 10.3 days (range: 0-109 days). Patients with Medicare experienced longer time-to-receipt (9.1 ± 13.1 days) compared to patients with commercial insurance (4.4 ± 3.3). Uninsured patients experienced the longest time-to-receipt (15.7 ± 7.8 days) overall. Pharmacy transfers and cost assistance programs were also significantly associated with longer time-to-receipt. Ten prescriptions remained unfilled 90 days after the study period and were considered abandoned. CONCLUSION: Insurance has a significant effect on the time-to-receipt of newly prescribed novel oral oncolytics. Pharmacy transfers and applying for cost assistance are also associated with longer wait times for patients. Our retrospective analysis identifies areas of improvement for future interventions to reduce wait times for patients receiving novel oral oncolytics.

Anticancer Drug Prescription Patterns in Japan: Future Directions in Cancer Therapy.

BACKGROUND: Despite their benefits, the rapid development of new cancer treatments has been a significant driver of increasing health care expenditures in the face of limited health care budgets. In this study, we analyzed the prescribing trends for anticancer drugs from 2010 through 2016 in Japan and sought to identify unique trends that could provide a basis for future medical economic research aiming to develop more efficacious and cost-effective cancer therapies. METHODS: We used publicly available marketing data for anticancer drugs in Japan for 2010-2016. The drugs selected for this research were categorized according to the Anatomical Therapeutic Chemical Classification System. We investigated the overall anticancer drug market size, the number of anticancer drugs, the top 30 selling anticancer categories, sales and prescription volumes, and changes in sales and prescription volumes between 2010 and 2016 in the country. RESULTS: The anticancer agent market expanded each year from 2010 to 2016, with sales exceeding 1 trillion yen in 2015. The proportion of molecular targeted drugs (antineoplastic mAbs and protein kinase inhibitors) among the top 30 selling anticancer categories has continued to increase, and both the sales and prescription volumes of these drugs exceeded those of drugs in other categories, suggesting that these treatments play a dominant role in cancer pharmacotherapy. CONCLUSION: The availability and increasing use of innovative but more expensive targeted therapies were major drivers of increases in pharmaceutical expenditures for cancer treatment in Japan. Therefore, the effective use of genetic testing can mitigate these rising costs.

Rising Prices of Targeted Oral Anticancer Medications and Associated Financial Burden on Medicare Beneficiaries.

Purpose The high cost of oncology drugs threatens the affordability of cancer care. Previous research identified drivers of price growth of targeted oral anticancer medications (TOAMs) in private insurance plans and projected the impact of closing the coverage gap in Medicare Part D in 2020. This study examined trends in TOAM prices and patient out-of-pocket (OOP) payments in Medicare Part D and estimated the actual effects on patient OOP payments of partial filling of the coverage gap by 2012. Methods Using SEER linked to Medicare Part D, 2007 to 2012, we identified patients who take TOAMs via National Drug Codes in Part D claims. We calculated total drug costs (prices) and OOP payments per patient per month and compared their rates of inflation with general health care prices. Results The study cohort included 42,111 patients who received TOAMs between 2007 and 2012. Although the general prescription drug consumer price index grew at 3% per year over 2007 to 2012, mean TOAM prices increased by nearly 12% per year, reaching $7,719 per patient per month in 2012. Prices increased over time for newly and previously launched TOAMs. Mean patient OOP payments dropped by 4% per year over the study period, with a 40% drop among patients with a high financial burden in 2011, when the coverage gap began to close. Conclusion Rising TOAM prices threaten the financial relief patients have begun to experience under closure of the coverage gap in Medicare Part D. Policymakers should explore methods of harnessing the surge of novel TOAMs to increase price competition for Medicare beneficiaries.

Real-World Treatment Patterns and Costs for Patients with Renal Cell Carcinoma Initiating Treatment with Sunitinib and Pazopanib.

BACKGROUND: Sunitinib and pazopanib are among the most prescribed targeted therapies for the systemic management of advanced renal cell carcinoma (RCC), but published cost comparisons between the 2 agents are few and limited by methodological and population differences. Also, sunitinib is administered on a 4-week on/2-week off cycle, and pazopanib is taken continuously. Thus, appropriate use and cost comparisons between the 2 drugs require methodological approaches to account for these differences. One way to accomplish this is to substitute expected for observed days supply. Recognizing the effects of nonrepresentative days supply values is important for assessing real-world treatment patterns and costs. OBJECTIVES: To (a) characterize demographic and clinical characteristics among patients with RCC newly initiating sunitinib or pazopanib, using a large administrative claims dataset; (b) characterize treatment patterns, persistence, and costs for each treatment group; and (c) assess the effect on treatment patterns and costs for sunitinib by substituting 42 days for prescriptions with 28- or 30-day supplies to account for sunitinib's 4-week on/2-week off dosing schedule. METHODS: This was a retrospective cohort study using health care claims data from the Truven MarketScan Research Databases, which include enrollment information and medical and pharmacy claims. Baseline patient demographic and clinical characteristics and treatment patterns (continuation, discontinuation, switching, or interruption; days supply; and persistence) were compared. Health care costs were calculated as mean daily index medication costs and as total, medical, and medication (all-cause and RCC-related) costs over the 12 months post-index period. Inclusion criteria were continuous health plan enrollment between 6 months pre-index and 12 months post-index; no RCC medications 6 months pre-index; ≥ 2 RCC diagnoses within ±180 days of index; and age ≥ 20 years. For demographic and clinical characteristics, treatment patterns, and costs, means (± standard deviations) for continuous data and relative frequencies for categorical data were reported. Chi-square tests or Student t-tests were used to evaluate differences other than costs. A generalized linear model with gamma distribution and log link was used for evaluating costs, controlling for patient demographic and pre-index clinical characteristics, persistence days, and index medication. All statistical tests were 2-tailed with significance set at P < 0.05 for all comparisons except for interactions with significance set at P < 0.10. The effects of substituting 42 days supply for sunitinib prescription records with 28 or 30 days supply were determined. RESULTS: In total, 609 (15.1% of the sunitinib overall sample) sunitinib patients and 183 (8.3% of the pazopanib overall sample) pazopanib patients were included. Demographic and clinical characteristics were similar for each treatment cohort. The persistence periods and number of prescriptions filled were also similar. Without substitution, significant differences were observed between treatment groups in patterns of index medication use (overall P = 0.0409), with fewer patients taking sunitinib continuing treatment than patients taking pazopanib. However, with substitution, treatment patterns differed significantly (overall P = 0.0026), but with more sunitinib patients than pazopanib patients continuing treatment. Without substitution, unadjusted daily mean index medication costs were significantly different for sunitinib ($216) versus pazopanib ($177, P < 0.0001). Substitution of sunitinib days supply eliminated the significant differences in daily index medication costs between treatment groups. The 1-year RCC-related and all-cause medication, medical, and total unadjusted costs were not significantly different between treatment groups, and substitution had no effect on these costs. After adjustment for possible confounding factors, these cost results were similar to those found with unadjusted analyses. CONCLUSIONS: In this study, patients with RCC who were initiating sunitinib and pazopanib had similar demographic and clinical characteristics and drug persistence patterns. The effect of substituting days supply values was demonstrated as an approach to considering differences in dosing cycles. Substitution significantly reduced sunitinib mean daily index medication costs and eliminated or reversed the direction of significant differences in costs between drugs during the persistence period. No significant differences were observed in unadjusted or adjusted 1-year costs. DISCLOSURES: This study was funded and conducted fully by Pfizer. All authors are employees of Pfizer. This work was presented in part as posters at the 2015 Genitourinary Cancers Symposium, of the American Society of Clinical Oncology; Rosen Shingle Creek, Orlando, FL; February 26-28, 2015, and the 20th Annual International Meeting of the International Society for Pharmacoeconomics and Outcomes Research; Philadelphia, PA; May 16-20, 2015. All authors contributed to study concept and design and to data interpretation. Mardekian was primarily responsible for data collection, along with Harnett. MacLean and Harnett worked on the manuscript, which was revised by MacLean and Mardekian.

Annual costs of tumor necrosis factor inhibitors using real-world data in a commercially insured population in the United States.

OBJECTIVE: To calculate annual cost per treated patient of tumor necrosis factor (TNF) inhibitors etanercept, adalimumab, and infliximab for common approved indications, based on actual TNF-inhibitor use in clinical practice. METHODS: Adults with ≥1 claim for etanercept, adalimumab, or infliximab between January 2005 and March 2009 were identified from the IMS LifeLink™ Health Plan Claims Database. Patients new to therapy or continuing therapy (i.e., a prior claim for a TNF-inhibitor) were analyzed separately. Included patients had been enrolled from 180 days before the first TNF-inhibitor claim (index date) through 360 days after the index date and had a diagnosis during the pre-index period for rheumatoid arthritis, psoriasis, psoriatic arthritis, or ankylosing spondylitis. Patients with Crohn's disease, ulcerative colitis, or juvenile idiopathic arthritis were excluded. Annual costs were calculated using wholesale acquisition costs for the TNF-inhibitor and Medicare Physician Fee Schedule for drug administration. Costs from restarting or switching TNF-inhibitor therapy during the first year were included. RESULTS: A total of 27,704 patients (11,528 new, 16,176 continuing) had claims for etanercept, adalimumab, or infliximab, most commonly (65%) for treatment of rheumatoid arthritis. The most commonly used agent was etanercept (14,777 patients; 53%), followed by adalimumab (6862 patients; 25%) and infliximab (6065 patients; 22%). Annual cost per treated patient was etanercept $14,873, adalimumab $17,766, and infliximab $21,256 across all indications. Annual cost per treated patient by disease was (etanercept/adalimumab/infliximab): rheumatoid arthritis ($14,314/$17,700/$20,390), psoriasis ($17,182/$17,682/$23,935), psoriatic arthritis ($15,030/$18,483/$24,974), and ankylosing spondylitis ($14,254/$16,925/$23,056). New and continuing patients showed similar results, with etanercept having the lowest costs. LIMITATIONS: This analysis is limited to three TNF-inhibitors and a US managed-care population. CONCLUSIONS: Based on this analysis of real-world use of TNF-inhibitors among patients in nationwide clinical practice settings, the annual TNF-inhibitor cost per treated patient was lowest for etanercept across all indications.

Do drug prices reflect development time and government investment?

BACKGROUND: Lengthy development times are cited by the pharmaceutical industry as one reason for high drug prices. OBJECTIVE: We compared the prices of different groups of drugs after accounting for development time, government support, market size, and other drug characteristics. DESIGN: We conducted a retrospective study of 180 human therapeutic drugs categorized into 8 drug groups by assembling data on drug development times, government support, drug characteristics, and prices. MEASURES: First, we compared the development time and level of government support across the 8 drug groups. Second, we assessed the independent effect of drug group on median price per day in a multivariable analysis, controlling for development time and all other variables. RESULTS: Thirty percent of antiretroviral drugs had government patents compared with 16% of other infectious disease drugs, 6% of cancer drugs, and less than 6% of any other drug group (P < 0.002). Fifty percent of antiretrovirals had NIH trials listed in the new drug application for approval by the Food and Drug Administration compared with less than 6% of any other drug group (P < 0.001). More antiretroviral and cancer drugs received fast track status and accelerated review during regulatory review by the Food and Drug Administration (P < 0.001). The median price of antiretrovirals was 8 US dollars per day more, cancer drugs 11 US dollars per day more, than the reference group after adjustment for other variables (P < 0.001). Development time was not associated with drug price. CONCLUSIONS: Antiretroviral and cancer drugs, even after accounting for development time, are among the most highly priced medications. Notably, drugs with rapid development and more government support did not have lower drug prices.