Summary
We described the use of Bayesian decision theory in the design of a dose-individualization study. The particular application was treatment of leukemia with high-dose chemotherapy and stem-qell transplantation. Data were assumed already available from earlier phase II studies in which patients received a fixed high dose of chemotherapy. In one of the earlier studies, patients received a low, test dose of the drug, in addition to the same high-dose chemotherapy as in the other phase II study. We wanted to combine the historical information with inference about a patient’s own pharmacokinetics to help make more precise predictions of the patient’s AUC at various high doses, compared with using only the patient’s low-dose PK information. With the use of a simple, asymmetric loss function, we computed the expected loss for each possible dose and determined the dose that minimized the loss.
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Rosner, G.L., Müller, P., Tang, F., Madden, T., Andersson, B.S. (2004). Dose Individualization for High-dose anti-cancer Chemotherapy. In: D’Argenio, D.Z. (eds) Advanced Methods of Pharmacokinetic and Pharmacodynamic Systems Analysis Volume 3. The International Series in Engineering and Computer Science, vol 765. Springer, Boston, MA. https://doi.org/10.1007/0-306-48523-0_13
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DOI: https://doi.org/10.1007/0-306-48523-0_13
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