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Integrated Simulation Framework for Toxicity, Dose Intensity, Disease Progression, and Cost Effectiveness for Castration-Resistant Prostate Cancer Treatment With Eribulin.

van Hasselt JG, Gupta A, Hussein Z, Beijnen JH, Schellens JH, Huitema AD - CPT Pharmacometrics Syst Pharmacol (2015)

Bottom Line: In addition, cost-effectiveness evaluations of investigational compounds are becoming increasingly important.Here, we developed an integrated model-based framework including relevant treatment effects for patients with castration-resistant prostate cancer treated with the anticancer agent eribulin.Subsequently, simulations evaluating alternative treatment protocols or patient characteristics were performed in order to derive inferences on expected efficacy and cost effectiveness.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical Pharmacology, Netherlands Cancer Institute Amsterdam, The Netherlands ; Department of Pharmacy & Pharmacology, Netherlands Cancer Institute Amsterdam, The Netherlands ; Division of Pharmacology, Cluster Systems Pharmacology, Leiden Academic Centre for Drug Research, Leiden University Leiden, The Netherlands.

ABSTRACT
Quantitative model-based analyses are helpful to support decision-making in drug development. In oncology, disease progression/clinical outcome (DPCO) models have been used for early predictions of clinical outcome, but most of such approaches did not include adverse events or dose intensity. In addition, cost-effectiveness evaluations of investigational compounds are becoming increasingly important. Here, we developed an integrated model-based framework including relevant treatment effects for patients with castration-resistant prostate cancer treated with the anticancer agent eribulin. The framework included (i) a DPCO model relating prostate-specific antigen (PSA) dynamics to survival; (ii) models for adverse events including dose-limiting neutropenia and other graded toxicities; (iii) a model for Eastern Cooperative Oncology Group (ECOG) performance score; (iv) a model for dropout; (v) the consideration of cost effectiveness. The model allowed simulation of realistic treatment courses. Subsequently, simulations evaluating alternative treatment protocols or patient characteristics were performed in order to derive inferences on expected efficacy and cost effectiveness.

No MeSH data available.


Related in: MedlinePlus

Schematic representation of the integrated simulation framework that was developed. PSA, prostate-specific antigen; LYG, life years gained; ICER, incremental cost-effectiveness ratio; QALY, quality-adjusted life years; PK, pharmacokinetics.
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fig01: Schematic representation of the integrated simulation framework that was developed. PSA, prostate-specific antigen; LYG, life years gained; ICER, incremental cost-effectiveness ratio; QALY, quality-adjusted life years; PK, pharmacokinetics.

Mentions: The schematic structure of this simulation framework is presented in Figure1. The figure accounts for the causal relationships between dose, exposure, toxicity, efficacy, and cost effectiveness. First, the interaction between dose, pharmacokinetics (PK), and toxicities results in a realized dose regimen for each patient that includes dose reductions. Then, the patient-specific PSA response is predicted, together with its relation with expected overall survival. Finally, the ECOG performance score was included as a surrogate metric for quality-of-life, and finally dropout was considered. Ultimately, this framework was developed to provide predicted efficacy and cost-effectiveness metrics including life-years gained (LYG), incremental cost-effectiveness ratios (ICERs), and quality-adjusted life years across a population of patients. Where possible, models included interindividual variability on parameters and associated predictors for this variability, to evaluate with flexibility different potential treatment scenarios.


Integrated Simulation Framework for Toxicity, Dose Intensity, Disease Progression, and Cost Effectiveness for Castration-Resistant Prostate Cancer Treatment With Eribulin.

van Hasselt JG, Gupta A, Hussein Z, Beijnen JH, Schellens JH, Huitema AD - CPT Pharmacometrics Syst Pharmacol (2015)

Schematic representation of the integrated simulation framework that was developed. PSA, prostate-specific antigen; LYG, life years gained; ICER, incremental cost-effectiveness ratio; QALY, quality-adjusted life years; PK, pharmacokinetics.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4544051&req=5

fig01: Schematic representation of the integrated simulation framework that was developed. PSA, prostate-specific antigen; LYG, life years gained; ICER, incremental cost-effectiveness ratio; QALY, quality-adjusted life years; PK, pharmacokinetics.
Mentions: The schematic structure of this simulation framework is presented in Figure1. The figure accounts for the causal relationships between dose, exposure, toxicity, efficacy, and cost effectiveness. First, the interaction between dose, pharmacokinetics (PK), and toxicities results in a realized dose regimen for each patient that includes dose reductions. Then, the patient-specific PSA response is predicted, together with its relation with expected overall survival. Finally, the ECOG performance score was included as a surrogate metric for quality-of-life, and finally dropout was considered. Ultimately, this framework was developed to provide predicted efficacy and cost-effectiveness metrics including life-years gained (LYG), incremental cost-effectiveness ratios (ICERs), and quality-adjusted life years across a population of patients. Where possible, models included interindividual variability on parameters and associated predictors for this variability, to evaluate with flexibility different potential treatment scenarios.

Bottom Line: In addition, cost-effectiveness evaluations of investigational compounds are becoming increasingly important.Here, we developed an integrated model-based framework including relevant treatment effects for patients with castration-resistant prostate cancer treated with the anticancer agent eribulin.Subsequently, simulations evaluating alternative treatment protocols or patient characteristics were performed in order to derive inferences on expected efficacy and cost effectiveness.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical Pharmacology, Netherlands Cancer Institute Amsterdam, The Netherlands ; Department of Pharmacy & Pharmacology, Netherlands Cancer Institute Amsterdam, The Netherlands ; Division of Pharmacology, Cluster Systems Pharmacology, Leiden Academic Centre for Drug Research, Leiden University Leiden, The Netherlands.

ABSTRACT
Quantitative model-based analyses are helpful to support decision-making in drug development. In oncology, disease progression/clinical outcome (DPCO) models have been used for early predictions of clinical outcome, but most of such approaches did not include adverse events or dose intensity. In addition, cost-effectiveness evaluations of investigational compounds are becoming increasingly important. Here, we developed an integrated model-based framework including relevant treatment effects for patients with castration-resistant prostate cancer treated with the anticancer agent eribulin. The framework included (i) a DPCO model relating prostate-specific antigen (PSA) dynamics to survival; (ii) models for adverse events including dose-limiting neutropenia and other graded toxicities; (iii) a model for Eastern Cooperative Oncology Group (ECOG) performance score; (iv) a model for dropout; (v) the consideration of cost effectiveness. The model allowed simulation of realistic treatment courses. Subsequently, simulations evaluating alternative treatment protocols or patient characteristics were performed in order to derive inferences on expected efficacy and cost effectiveness.

No MeSH data available.


Related in: MedlinePlus