Model‐Based Prediction of Irinotecan‐Induced Grade 4 Neutropenia in Advanced Cancer Patients: Influence of Demographic and Clinical Factors

Abstract

Severe neutropenia is the major dose‐liming toxicity of irinotecan‐based chemotherapy. The objective was to assess to what extent a population pharmacokinetic/pharmacodynamic model including patient‐specific demographic/clinical characteristics, individual pharmacokinetics, and absolute neutrophil counts (ANCs) can predict irinotecan‐induced grade 4 neutropenia. A semimechanistic population pharmacokinetic/pharmacodynamic model was developed to describe neutrophil response over time in 197 patients with cancer receiving irinotecan. For covariate analysis, sex, race, age, pretreatment total bilirubin, and body surface area were evaluated to identify significant covariates on system‐related parameters (mean transit time (MTT) and ɣ) and sensitivity to neutropenia effects of irinotecan and SN‐38 (SLOPE). The model‐based simulation was performed to assess the contribution of the identified covariates, individual pharmacokinetics, and baseline ANC alone or with incremental addition of weekly ANC up to 3 weeks on predicting irinotecan‐induced grade 4 neutropenia. The time course of neutrophil response was described using the model assuming that irinotecan and SN‐38 have toxic effects on bone marrow proliferating cells. Sex and pretreatment total bilirubin explained 10.5% of interindividual variability in MTT. No covariates were identified for SLOPE and γ. Incorporating sex and pretreatment total bilirubin (area under the receiver operating characteristic curve (AUC‐ROC): 50%, 95% CI 50–50%) or with the addition of individual pharmacokinetics (AUC‐ROC: 62%, 95% CI 53–71%) in the model did not result in accurate prediction of grade 4 neutropenia. However, incorporating ANC only at baseline and week 1 in the model achieved a good prediction (AUC‐ROC: 78%, 95% CI 69–88%). These results demonstrate the potential applicability of a model‐based approach to predict irinotecan‐induced neutropenia, which ultimately allows for personalized intervention to maximize treatment outcomes.

Model‐Based Prediction of Irinotecan‐Induced Grade 4 Neutropenia in Cancer Patients: Influence of Incorporating Germline Genetic Factors in the Model

“…Previously, we demonstrated the improvement in prediction of irinotecan-induced grade 4 neutropenia using a model-based framework incorporating individual pharmacokinetics and patient demographic and clinical characteristics associated with neutrophil response to irinotecan leveraging immediately post-treatment data. 4 This new study extended the previous study by exploring how patient genetic characteristics influence the prediction of irinotecan-induced grade 4 neutropenia when added to: (i) baseline demographics and clinical characteristics, (ii) individual pharmacokinetics (plasma concentrations of irinotecan and its metabolites), and (iii) baseline and/or weekly measured absolute neutrophil counts (ANCs) during the treatment.…”

“…Data from 197 patients with advanced solid tumors or lymphoma receiving irinotecan [5][6][7][8][9][10] in our previous study 4 were analyzed. Patient characteristics are described elsewhere.…”

“…Patient characteristics are described elsewhere. 4 All studies, including this study, were approved by local institutional review boards, and all patients provided written informed consent. This study adhered to the Declaration of Helsinki guidelines.…”

“…The structural pharmacokinetic/pharmacodynamic model is described in our previous study. 4 Step 2 -Evaluation of demographic/clinical factors associated with random effects (η SLOPE , η MTT , and η ɣ ) using stepwise forward inclusion. As described in our previous study, 4 the inclusion of sex and pretreatment total bilirubin on MTT resulted in a significant decrease in objective function value (OFV; ∆-2LL < −3.84, P < 0.05) in the stepwise forward inclusion procedure.…”

Temporal offset association between the number of irinotecan-related adverse reactions and pharmacogenomic studies: A cross-correlation analysis

“…It is undeniable that the number of ADRs is not only affected by the single factor of UGT1A1 gene polymorphism, but also by various factors such as changes in the recommended treatment regimen by the guideline, liposome-encapsulated form and so on ( Assiri and Noor, 2020 , Karas et al, 2022 , Milano et al, 2022 ). However, this study provides large-scale real world data support for the important role of UGT1A1 genotype in guiding irinotecan dose in clinical practice, which helps to promote the inclusion of mandatory genetic testing in guideline ( Karas & Innocenti 2022 ), and is worthy of reference for other drugs.…”