OBJECTIVES: Decision analysis is commonly used to perform economic evaluations of new pharmaceuticals. The outcomes of such studies are often reported as an incremental cost per quality-adjusted life year (QALY) gained with the new agent. Decision analysis can also be used in the context of estimating drug cost before market entry. The current study used neurokinin-1 (NK-1) receptor antagonists, a new class of antiemetics for cancer patients, as an example to illustrate the process using an incremental cost of dollars Can20,000 per QALY gained as the target threshold. METHODS: A decision model was developed to simulate the control of acute and delayed emesis after cisplatin-based chemotherapy. The model compared standard therapy with granisetron and dexamethasone to the same protocol with the addition of an NK-1 before chemotherapy and continued twice daily for five days. The rates of complete emesis control were abstracted from a double-blind randomized trial. Costs of standard antiemetics and therapy for breakthrough vomiting were obtained from hospital sources. Utility estimates characterized as quality-adjusted emesis-free days were determined by interviewing twenty-five oncology nurses and pharmacists by using the Time Trade-Off technique. These data were then used to estimate the unit cost of the new antiemetic using a target threshold of dollars Can20,000 per QALY gained. RESULTS: A cost of dollars Can6.60 per NK-1 dose would generate an incremental cost of dollars Can20,000 per QALY. The sensitivity analysis on the unit cost identified a range from dollars Can4.80 to dollars Can10.00 per dose. For the recommended five days of therapy, the total cost should be dollars Can66.00 (dollars Can48.00-dollars Can100.00) for optimal economic efficiency relative to Canada's publicly funded health-care system. CONCLUSIONS: The use of decision modeling for estimating drug cost before product launch is a powerful technique to ensure value for money. Such information can be of value to both drug manufacturers and formulary committees, because it would facilitate negotiations for optimal pricing in a given jurisdiction.
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OBJECTIVES: Decision analysis is commonly used to perform economic evaluations of new pharmaceuticals. The outcomes of such studies are often reported as an incremental cost per quality-adjusted life year (QALY) gained with the new agent. Decision analysis can also be used in the context of estimating drug cost before market entry. The current study used neurokinin-1 (NK-1) receptor antagonists, a new class of antiemetics for cancerpatients, as an example to illustrate the process using an incremental cost of dollars Can20,000 per QALY gained as the target threshold. METHODS: A decision model was developed to simulate the control of acute and delayed emesis after cisplatin-based chemotherapy. The model compared standard therapy with granisetron and dexamethasone to the same protocol with the addition of an NK-1 before chemotherapy and continued twice daily for five days. The rates of complete emesis control were abstracted from a double-blind randomized trial. Costs of standard antiemetics and therapy for breakthrough vomiting were obtained from hospital sources. Utility estimates characterized as quality-adjusted emesis-free days were determined by interviewing twenty-five oncology nurses and pharmacists by using the Time Trade-Off technique. These data were then used to estimate the unit cost of the new antiemetic using a target threshold of dollars Can20,000 per QALY gained. RESULTS: A cost of dollars Can6.60 per NK-1 dose would generate an incremental cost of dollars Can20,000 per QALY. The sensitivity analysis on the unit cost identified a range from dollars Can4.80 to dollars Can10.00 per dose. For the recommended five days of therapy, the total cost should be dollars Can66.00 (dollars Can48.00-dollars Can100.00) for optimal economic efficiency relative to Canada's publicly funded health-care system. CONCLUSIONS: The use of decision modeling for estimating drug cost before product launch is a powerful technique to ensure value for money. Such information can be of value to both drug manufacturers and formulary committees, because it would facilitate negotiations for optimal pricing in a given jurisdiction.
Authors: Kednapa Thavorn; Doug Coyle; Jeffrey S Hoch; Lisa Vandermeer; Sasha Mazzarello; Zhou Wang; George Dranitsaris; Dean Fergusson; Mark Clemons Journal: Support Care Cancer Date: 2017-03-09 Impact factor: 3.603