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Cited by 6Pharmaceutical studies and practicesStatistical Methods in Clinical TrialsAcute Lymphoblastic Leukemia research

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Clinical trial simulations in paediatric oncology: A feasibility study from the Innovative Therapies for Children with Cancer Consortium

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Janssen, Julie M., Zwaan, C. Michel, Schellens, Jan H.M., Beijnen, Jos H., Huitema, Alwin D.R.·2017·European Journal of Cancer
DOI 10.1016/j.ejca.2017.07.050
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Abstract

Introduction Paediatric dose-finding studies are challenging to perform due to ethical reasons, the limited number of available patients and restricted number of blood samples. In certain cases, the adult pharmacokinetic (PK) exposure can be used as target for dose finding in paediatrics. The aim of this study was to investigate the performance of a paediatric phase I dose-finding clinical trial in silico. Methods Using an adult pharmacokinetic model, clinical trial simulations were performed to determine the power of a proposed clinical trial design. Power was defined as the fraction of 1000 trials with an area under the plasma concentration-time curve at steady-state (AUC 0-24,SS) within ±20% of the adult geometric mean AUC 0-24,SS. Different scenarios were compared to optimise the design of the trial. To show the potential of this framework for similar compounds, the current simulation method was also evaluated with adult and paediatric data from literature on sunitinib. Results At the starting dose of 300 mg/m 2, the power of the trial design was 66.9%. Power did not improve by dose escalation to 350 mg/m 2 (65.3%). Power increased to 78.9% with inclusion of 10 patients per trial. Paediatric sunitinib PK data were adequately predicted from adult data with a mean prediction error of 1.80%. Conclusion The performance of PK-based clinical trials in paediatrics can be predicted and optimised through PK modelling and simulation. Application of this approach enables clinical trials in paediatrics to be performed as efficiently as possible while protecting the child from unnecessary harm.

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Metadata

Authors
Janssen, J. M., Zwaan, C. M., Schellens, J. H. M., Beijnen, J. H., & Huitema, A. D. R.
Affiliations
  • The Netherlands Cancer Institute (NL)
  • Erasmus MC - Sophia Children’s Hospital (NL)
  • Utrecht University (NL)
Corresponding author
Janssen, Julie M.
ORCID
Venue
European Journal of Cancer
Publisher
Elsevier BV
Published
2017-11
Volume
85
Pages
78-85
ISSN
0959-8049 (ISSN-L)
DOI
10.1016/j.ejca.2017.07.050
OpenAlex
W2752416376
Cited by
6
References
0
Citations by year
2026: 1 · 2023: 1 · 2022: 1 · 2020: 2 · 2018: 1
FWCI
0.90
Type
journal article
Language
en
Open access
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • European Journal of Cancer (publishedVersion)
  • PubMed (publishedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
  • Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
  • Utrecht University Repository (Utrecht University) (submittedVersion)
Topics
  • Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Health Sciences › Medicine › Hematology › Acute Lymphoblastic Leukemia research
Keywords
pediatric oncology, clinical trial simulation, pharmacokinetic modeling, statistical power, sunitinib, pediatric drug development
MeSH terms
Sunitinib, Adult, Age Factors, Antineoplastic Agents, Child, Computer Simulation, Feasibility Studies, Humans, Indoles, Models, Biological, Pediatrics, Pyrroles, Research Design, Clinical Trials, Phase I as Topic, Risk Assessment, Protein Kinase Inhibitors, Drug Dosage Calculations, Patient Safety

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