Population Pharmacodynamic Model for Bayesian Prediction of Myelosuppression Profiles Based on Routine Clinical Data after Gemcitabine and Carboplatin Treatment

摘要: Background: Hematological toxicity is a serious adverse event and often dose-limiting factor in anticancer drugs. The objective of the present study was to develop modeling simulation (M&S) procedure for predictions time course profiles blood cell counts that reflect myelosuppression profiles. Methods: A method Bayesian prediction during chemotherapy using population pharmacodynamic model proposed, predictabilities nadir values times (Tnadir) after gemcitabine carboplatin treatment were evaluated. based on an equation Erlang distribution, which we previously it explains platelet (PLT), red (RBC) white (WBC). Results Conclusion: PLT, RBC WBC retrospectively collected from 61 courses (a total 472 points) 27 cancer patients. Predictive performance by one-point evaluated data day 8 consideration applicability outpatients. Some good predictability obtained with some exceptions PLT RBC, whereas Tnadir insufficient. Although not acceptable enough, this M&S approach could be used supportive care chemotherapy.