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Pharmacometrics-Based Considerations for the Design of a Pharmacogenomic Clinical Trial Assessing Irinotecan Safety

PURPOSE: Pharmacometric models provide useful tools to aid the rational design of clinical trials. This study evaluates study design-, drug-, and patient-related features as well as analysis methods for their influence on the power to demonstrate a benefit of pharmacogenomics (PGx)-based dosing rega...

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Detalles Bibliográficos
Autores principales: Minichmayr, Iris K., Karlsson, Mats O., Jönsson, Siv
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8057977/
https://www.ncbi.nlm.nih.gov/pubmed/33733372
http://dx.doi.org/10.1007/s11095-021-03024-w
Descripción
Sumario:PURPOSE: Pharmacometric models provide useful tools to aid the rational design of clinical trials. This study evaluates study design-, drug-, and patient-related features as well as analysis methods for their influence on the power to demonstrate a benefit of pharmacogenomics (PGx)-based dosing regarding myelotoxicity. METHODS: Two pharmacokinetic and one myelosuppression model were assembled to predict concentrations of irinotecan and its metabolite SN-38 given different UGT1A1 genotypes (poor metabolizers: CL(SN-38): -36%) and neutropenia following conventional versus PGx-based dosing (350 versus 245 mg/m(2) (-30%)). Study power was assessed given diverse scenarios (n = 50–400 patients/arm, parallel/crossover, varying magnitude of CL(SN-38), exposure-response relationship, inter-individual variability) and using model-based data analysis versus conventional statistical testing. RESULTS: The magnitude of CL(SN-38) reduction in poor metabolizers and the myelosuppressive potency of SN-38 markedly influenced the power to show a difference in grade 4 neutropenia (<0.5·10(9) cells/L) after PGx-based versus standard dosing. To achieve >80% power with traditional statistical analysis (χ(2)/McNemar’s test, α = 0.05), 220/100 patients per treatment arm/sequence (parallel/crossover study) were required. The model-based analysis resulted in considerably smaller total sample sizes (n = 100/15 given parallel/crossover design) to obtain the same statistical power. CONCLUSIONS: The presented findings may help to avoid unfeasible trials and to rationalize the design of pharmacogenetic studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11095-021-03024-w.