Budget impact of adding lesinurad for second-line treatment of gout: a US health plan perspective.

Aim: To estimate budget impact of adopting lesinurad as add-on to allopurinol for urate-lowering therapy in gout. Methods: A budget impact model was developed for a US payer perspective, using a Markov model to estimate costs, survival and discontinuation in a one-million-member health plan. The population included patients failing first-line gout therapy, followed for 5 years. Results: Incremental costs of adding lesinurad versus no lesinurad were US$241,907 and US$1,098,220 in first and fifth years, respectively. Cumulative 5-year incremental cost was US$3,633,440. Estimated incremental mean cost per treated patient with gout per year was US$112. The mean per-member per-month cost increased by US$0.06. Conclusion: Initiating lesinurad would result in an incremental per-member per-month cost of US$0.06 over 5 years.

The Budget Impact of Including Necitumumab on the Formulary for First-Line Treatment of Metastatic Squamous Non-Small Cell Lung Cancer: U.S. Commercial Payer and Medicare Perspectives.

BACKGROUND: Necitumumab (Neci) was the first biologic approved by the FDA for use in combination with gemcitabine and cisplatin (Neci + GCis) in first-line treatment of metastatic squamous non-small cell lung cancer (msqNSCLC). The potential financial impact on a health plan of adding Neci + GCis to drug formularies may be important to value-based decision makers in the United States, given ever-tightening budget constraints. OBJECTIVE: To estimate the budget impact of introducing Neci + GCis for first-line treatment of msqNSCLC from U.S. commercial and Medicare payer perspectives. METHODS: The budget impact model estimates the costs of msqNSCLC before and after adoption of Neci + GCis in hypothetical U.S. commercial and Medicare health plans over a 3-year time horizon. The eligible patient population was estimated from U.S. epidemiology statistics. Clinical data were obtained from randomized clinical trials, U.S. prescribing information, and clinical guidelines. Market share projections were based on market research data. Cost data were obtained from online sources and published literature. The incremental aggregate annual health plan, per-patient-per-year (PPPY), and per-member-per-month (PMPM) costs were estimated in 2015 U.S. dollars. One-way sensitivity analyses were conducted to assess the effect of model parameters on results. RESULTS: In a hypothetical 1,000,000-member commercial health plan with an estimated population of 30 msqNSCLC patients receiving first-line chemotherapy, the introduction of Neci + GCis at an initial market share of approximately 5% had an overall year 1 incremental budget impact of $88,394 ($3,177 PPPY, $0.007 PMPM), representing a 2.9% cost increase and reaching $304,079 ($10,397 PPPY, $0.025 PMPM) or a 7.4% cost increase at a market share of 14.7% in year 3. This increase in total costs was largely attributable to Neci drug costs and, in part, due to longer survival and treatment duration for patients treated with Neci+GCis. Overall, treatment costs increased by $81,812 (13.5%), and disease costs increased by $7,951 (0.4%), whereas adverse event costs decreased by $1,368 (0.5%) in year 1. From the Medicare perspective, the overall year 1 incremental budget impact was $438,056 ($0.037 PMPM, $3,112 PPPY), representing a 3.0% cost increase. The higher incremental budget in Medicare, compared with commercial plans, was due to higher msqNSCLC incidence in the older Medicare patients (154 vs. 30 patients, respectively). Results were most sensitive to Neci drug costs. CONCLUSIONS: Based on projected market shares, coverage for first-line therapy with Neci + GCis appeared to modestly affect overall U.S. health care budgets for msqNSCLC-related care. Given the small eligible patient population, the PMPM budgetary impact on a commercial health plan of reimbursing Neci + GCis in the first year was less than $0.01, rising with increased use of Neci + GCis to $0.025 in the third year. The real-world effect of Neci + GCis needs to be evaluated to validate this analysis; however, these findings may help policymakers in making coverage decisions for Neci + GCis. DISCLOSURES: This study was funded by Eli Lilly and Company. Molife, Brown, Tawney, and Cuyun Carter are equity holders and employees of Eli Lilly and Company. Bly, Cinfio, and Klein are employees of Medical Decision Modeling, which received funding from Eli Lilly and Company to conduct this research and prepare this manuscript.

Enhancing the Budget Impact Model for Institutional Use: A Tool with Practical Applications for the Hospital Oncology Pharmacy.

BACKGROUND: The cost of cancer care is increasing, and tools are needed to understand the economic impact of new drugs on the hospital pharmacy budget. OBJECTIVE: To develop an interactive budget impact model (BIM) through a collaborative effort of industry, academia, and modeling experts to evaluate the use of a new agent in non-small cell lung cancer (NSCLC); this BIM included an institutional module specific to the needs of practices that purchase medications for use in institutional settings. METHODS: Treatment regimens, doses, duration of therapy, toxicity, and cost data are from published sources. All input data may be modified to match the local population. Outputs include cost of care, reimbursement, and margin overall and by treatment regimen. RESULTS: The base case assumes 20 NSCLC patients progressing after initial therapy (3 receiving ramucirumab+docetaxel, 2 bevacizumab+erlotinib, 3 docetaxel, 6 erlotinib, and 6 pemetrexed), wholesale acquisition cost (WAC) purchase price, and reimbursement at WAC+4.3%. The model estimated the total cost and reimbursement for the institutional oncology pharmacy to be $699,413 and $729,487, respectively, resulting in a margin of $30,075 (difference due to rounding) for the year for regimens utilized in the treatment of NSCLC in the post-progression setting. Results will vary depending on the input data. CONCLUSIONS: There is an increasing need for institutional pharmacies to plan ahead and anticipate the impact of new drugs on their oncology budgets. This interactive Excel-based institutional BIM may provide evidence-based support for pharmacy decision making.