Development of a Therapeutic Drug Monitoring Strategy for the Optimization of Vincristine Treatment in Pediatric Oncology Populations in Africa : Therapeutic Drug Monitoring

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Focus Series: Therapeutic Drug Monitoring in Oncology

Development of a Therapeutic Drug Monitoring Strategy for the Optimization of Vincristine Treatment in Pediatric Oncology Populations in Africa

Van der Heijden, Lisa T. PharmD*,†; Nijstad, A. Laura PharmD‡,§; Uittenboogaard, Aniek MD; Beijnen, Jos H. PharmD, PhD*,†,¦; Dorlo, Thomas P.C. MSc, PhD*,†,**; Kaspers, Gertjan J.L. MD, PhD¶,††,‡‡; Huitema, Alwin D.R. PharmD, PhD*,†,‡,§

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Therapeutic Drug Monitoring 45(3):p 354-363, June 2023. | DOI: 10.1097/FTD.0000000000001090

Abstract

Background: 

Recent studies have reported ethnic differences in vincristine exposure and outcomes such as toxicity. This resulted in the hypothesis of subtherapeutic dosing in African children. To optimize individual treatment, a strategy to identify subtherapeutic exposure using therapeutic drug monitoring is essential. The aim of the current study was to develop a strategy for therapeutic drug monitoring of vincristine in African children to meet the following criteria: (1) identify patients with low vincristine exposure with sufficient sensitivity (>70%), (2) determine vincristine exposure with a limited sampling strategy design of 3 samples, and (3) allow all samples to be collected within 4 hours after administration.

Methods: 

An in silico simulation study was performed using a previously described population pharmacokinetic model and real-life demographic dataset of Kenyan and Malawian pediatric oncology patients. Two different therapeutic drug monitoring strategies were evaluated: (1) Bayesian approach and (2) pharmacometric nomogram. The sampling design was optimized using the constraints described above. Sensitivity analysis was performed to investigate the influence of missing samples, erroneous sampling times, and different boundaries on the nomogram weight bands.

Results: 

With the Bayesian approach, 43.3% of the estimated individual exposure values had a prediction error of ≥20% owing to extremely high shrinkage. The Bayesian approach did not improve with alternative sampling designs within sampling constraints. However, the pharmacometric nomogram could identify patients with low vincristine exposure with a sensitivity, specificity, and accuracy of 75.1%, 76.4%, and 75.9%, respectively. The pharmacometric nomogram performed similarly for different weight bands.

Conclusions: 

The pharmacometric nomogram was able to identify patients with low vincristine exposure with high sensitivity, with 3 blood samples collected at 1, 1.5, and 4 hours after administration. Missing samples should be avoided, and the 3 scheduled samples should be collected within 15, 5, and 15 minutes of 1, 1.5, and 4 hours after administration, respectively.

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