Cost-effectiveness of the sequential application of tyrosine kinase inhibitors for the treatment of chronic myeloid leukemia.
Several tyrosine kinase inhibitors (TKIs) are approved for chronic myeloid leukemia (CML) therapy. We evaluated the long-term cost-effectiveness of seven sequential therapy regimens for CML in Austria. A cost-effectiveness analysis was performed using a state-transition Markov model. As model parameters, we used published trial data, clinical, epidemiological and economic data from the Austrian CML registry and national databases. We performed a cohort simulation over a life-long time-horizon from a societal perspective. Nilotinib without second-line TKI yielded an incremental cost-utility ratio of 121,400 €/quality-adjusted life year (QALY) compared to imatinib without second-line TKI after imatinib failure. Imatinib followed by nilotinib after failure resulted in 131,100 €/QALY compared to nilotinib without second-line TKI. Nilotinib followed by dasatinib yielded 152,400 €/QALY compared to imatinib followed by nilotinib after failure. Remaining strategies were dominated. The sequential application of TKIs is standard-of-care, and thus, our analysis points toward imatinib followed by nilotinib as the most cost-effective strategy.
a Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment , UMIT - University for Health Sciences, Medical Informatics and Technology , Hall in Tirol , Austria.|b Area 4: Health Technology Assessment and Bioinformatics, ONCOTYROL - Center for Personalized Cancer Medicine , Innsbruck , Austria.
Ursula
U
Rochau
a Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment , UMIT - University for Health Sciences, Medical Informatics and Technology , Hall in Tirol , Austria.
Gaby
G
Sroczynski
c Hematology and Oncology, Internal Medicine V, Medical University Innsbruck , Austria.|d Oncology, Hematology and Rheumatology, Medical Clinic III, University Clinic Bonn (UKB) , Germany.
Dominik
D
Wolf
c Hematology and Oncology, Internal Medicine V, Medical University Innsbruck , Austria.
Stefan
S
Schmidt
a Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment , UMIT - University for Health Sciences, Medical Informatics and Technology , Hall in Tirol , Austria.
Beate
B
Jahn
a Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment , UMIT - University for Health Sciences, Medical Informatics and Technology , Hall in Tirol , Austria.
Martina
M
Kluibenschaedl
a Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment , UMIT - University for Health Sciences, Medical Informatics and Technology , Hall in Tirol , Austria.
Annette
A
Conrads-Frank
e Department of Pharmacotherapy and Program in Personalized Health Care , University of Utah , Salt Lake City , UT , USA.|f Huntsman Cancer Institute, University of Utah Hospitals and Clinics , Salt Lake City , UT , USA.
David
D
Stenehjem
a Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment , UMIT - University for Health Sciences, Medical Informatics and Technology , Hall in Tirol , Austria.|b Area 4: Health Technology Assessment and Bioinformatics, ONCOTYROL - Center for Personalized Cancer Medicine , Innsbruck , Austria.|e Department of Pharmacotherapy and Program in Personalized Health Care , University of Utah , Salt Lake City , UT , USA.
Diana
D
Brixner
g Clinical Research Division, Fred Hutchinson Cancer Research Center , Seattle , WA , USA.
Jerald
J
Radich
c Hematology and Oncology, Internal Medicine V, Medical University Innsbruck , Austria.
Günther
G
Gastl
a Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment , UMIT - University for Health Sciences, Medical Informatics and Technology , Hall in Tirol , Austria.|b Area 4: Health Technology Assessment and Bioinformatics, ONCOTYROL - Center for Personalized Cancer Medicine , Innsbruck , Austria.|h Center for Health Decision Science, Department of Health Policy and Management , Harvard School of Public Health , Boston , MA , USA.|i Institute for Technology Assessment and Department of Radiology , Massachusetts General Hospital, Harvard Medical School , Boston , MA , USA.
Uwe
U
Siebert
D000970:Antineoplastic Agents / Q000009:adverse effects / Q000191:economics / Q000627:therapeutic use; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000009:adverse effects / Q000191:economics / Q000627:therapeutic use; D001317:Austria / Q000453:epidemiology; D003362:Cost-Benefit Analysis; D003661:Decision Support Techniques; D005260:Female; D017048:Health Care Costs; D018380:Hematopoietic Stem Cell Transplantation / Q000191:economics; D006801:Humans; D015464:Leukemia, Myelogenous, Chronic, BCR-ABL Positive / Q000175:diagnosis / Q000188:drug therapy / Q000453:epidemiology* / Q000628:therapy; D008297:Male; D008390:Markov Chains; D017063:Outcome Assessment, Health Care; D047428:Protein Kinase Inhibitors / Q000009:adverse effects / Q000191:economics / Q000627:therapeutic use; D019057:Quality-Adjusted Life Years; D012042:Registries
D000970:Antineoplastic Agents; D047428:Protein Kinase Inhibitors
Chronic myeloid leukemia; cost-effectiveness analysis; decision analysis; decision-analytic model; health economic modeling; tyrosine kinase inhibitors