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Switch to anti-programmed cell death protein 1 (anti-PD-1) fixed-dose regimen: What is the economic impact?
Arnaud Bayle1, Benjamin Besse2, Maxime Annereau3
1Department of Medical Oncology, Gustave Roussy, Université Paris-Saclay, Villejuif, France; Université Paris Sud, Université Paris Saclay, Faculté de Médecine Du Kremlin-Bicetre, Le Kremlin-Bicetre, France; Gustave Roussy, Service de Biostatistique et d'Epidémiologie, Villejuif, F-94805, France.
Background:
Nivolumab and pembrolizumab were initially developed using weight-based regimen doses. Recently, fixed-dose regimens were commercialised with reference weights higher than the accurate weight of patients with cancer in routine practice. This may have important economic consequences for healthcare systems.
Material And Methods:
Budget impact analysis was performed using real-world data both from Gustave Roussy database and the French National Hospital Discharge database and including patients treated with either nivolumab or pembrolizumab at Gustave Roussy and in France before the approval of fixed-dosing regimens in Europe. Main outcome is the expected annual budget impact of fixed-dosing regimens in France.
Results:
From January to April 2018, 978 perfusions of anti-programmed cell death protein 1 were administered at our institution including 560 perfusions of nivolumab in 103 patients and 418 perfusions of pembrolizumab in 125 patients mainly treated for lung cancer and melanoma. The mean extra cost attributable to flat doses would have amounted to €284 (95% confidence interval [CI]: 241-327) per infusion of nivolumab and to €1287 (95% CI: 1200-1373) per infusion of pembrolizumab. Annually, at Gustave Roussy, it would represent an extra cost of € 477 120 (95% CI: 404 880-549 360) and €1 613 898 (95% CI: 1 504 800-1 721 742), respectively, for the year 2018. At the French national level, the expected annual budget impact is estimated at €55 162 211 for the year 2017.
Conclusions:
Weight references for fixed-dose regimens do not reflect the accurate mean weight of patients under cancer treatment and are likely to have substantial economic impact for healthcare systems.
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