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

Neutropenia is the major dose-limiting toxicity of irinotecan-based therapy. The objective of this study was to assess whether inclusion of germline genetic variants into a population pharmacokinetic/pharmacodynamic model can improve prediction of irinotecan-induced grade 4 neutropenia and identify novel variants of clinical value. A semimechanistic population pharmacokinetic/pharmacodynamic model was used to predict neutrophil response over time in 197 patients receiving irinotecan. Covariate analysis was performed for demographic/clinical factors and 4,781 genetic variants in 84 drug response- and toxicity-related genes to identify covariates associated with neutrophil response. We evaluated the predictive value of the model for grade 4 neutropenia reflecting different clinical scenarios of available data on identified demographic/clinical covariates, baseline and post-treatment absolute neutrophil counts (ANCs), individual pharmacokinetics, and germline genetic variation. Adding 8 genetic identified covariates (rs10929302 (UGT1A1), rs1042482 (DPYD), rs2859101 (HLA-DQB3), rs61754806 (NR3C1), rs9266271 (HLA-B), rs7294 (VKORC1), rs1051713 (ALOX5), and ABCB1 rare variant burden) to a model using only baseline ANCs improved prediction of irinotecan-induced grade 4 neutropenia from area under the receiver operating characteristic curve (AUC-ROC) of 50-64% (95% confidence interval (CI), 54-74%). Individual pharmacokinetics further improved the prediction to 74% (95% CI, 64-84%). When weekly ANC was available, the identified covariates and individual pharmacokinetics yielded no additional contribution to the prediction. The model including only ANCs at baseline and at week 1 achieved an AUC-ROC of 78% (95% CI, 69-88%). Germline DNA genetic variants may contribute to the prediction of irinotecan-induced grade 4 neutropenia when incorporated into a population pharmacokinetic/pharmacodynamic model. This approach is generalizable to drugs that induce neutropenia and ultimately allows for personalized intervention to enhance patient safety.

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

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 É£) 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.

All You Need to Know About UGT1A1 Genetic Testing for Patients Treated With Irinotecan: A Practitioner-Friendly Guide.

Irinotecan is an anticancer agent widely used for the treatment of solid tumors, including colorectal and pancreatic cancers. Severe neutropenia and diarrhea are common dose-limiting toxicities of irinotecan-based therapy, and UGT1A1 polymorphisms are one of the major risk factors of these toxicities. In 2005, the US Food and Drug Administration revised the drug label to indicate that patients with UGT1A1*28 homozygous genotype should receive a decreased dose of irinotecan. However, UGT1A1*28 testing is not routinely used in the clinic, and specific reasons include lack of access to concise information on this wide issue as well as mixed recommendations by regulatory and professional entities. To assist oncologists in assessing whether and when to use UGT1A1 genetic testing in patients receiving irinotecan-based therapies, this article provided (1) essential knowledge of UGT1A1 polymorphisms; (2) an update on the impact of UGT1A1 polymorphisms on efficacy and toxicity of contemporary irinotecan-based regimens; (3) dosing adjustments based upon the UGT1A1 genotypes, and (4) recommendations from currently available guidelines from the US and international scientific consortia and major oncology societies.

Integration of DNA sequencing with population pharmacokinetics to improve the prediction of irinotecan exposure in cancer patients.

BACKGROUND: Irinotecan (CPT-11) is an anticancer agent widely used to treat adult solid tumours. Large interindividual variability in the clearance of irinotecan and SN-38, its active and toxic metabolite, results in highly unpredictable toxicity. METHODS: In 217 cancer patients treated with intravenous irinotecan single agent or in combination, germline DNA was used to interrogate the variation in 84 genes by next-generation sequencing. A stepwise analytical framework including a population pharmacokinetic model with SNP- and gene-based testing was used to identify demographic/clinical/genetic factors that influence the clearance of irinotecan and SN-38. RESULTS: Irinotecan clearance was influenced by rs4149057 in SLCO1B1, body surface area, and co-administration of 5-fluorouracil/leucovorin/bevacizumab. SN-38 clearance was influenced by rs887829 in UGT1A1, pre-treatment total bilirubin, and EGFR rare variant burden. Within each UGT1A1 genotype group, elevated pre-treatment total bilirubin and/or presence of at least one rare variant in EGFR resulted in significantly lower SN-38 clearance. The model reduced the interindividual variability in irinotecan clearance from 38 to 34% and SN-38 clearance from 49 to 32%. CONCLUSIONS: This new model significantly reduced the interindividual variability in the clearance of irinotecan and SN-38. New genetic factors of variability in clearance have been identified.

Optimal Sampling Strategies for Irinotecan (CPT-11) and its Active Metabolite (SN-38) in Cancer Patients.

Irinotecan (CPT-11) is an anticancer agent widely used in the treatment of a variety of adult solid tumors. The objective of this study was to develop an optimal sampling strategy model that accurately estimates pharmacokinetic parameters of CPT-11 and its active metabolite, SN-38. This study included 221 patients with advanced solid tumors or lymphoma receiving CPT-11 single or combination therapy with 5-fluorouracil (5-FU)/leucovorin (LV) (FOLFIRI) plus bevacizumab from 4 separate clinical trials. Population pharmacokinetic analysis of CPT-11 and SN-38 was performed by non-linear mixed effects modeling. The optimal sampling strategy model was developed using D-optimality with expected distribution approach. The pharmacokinetic profiles of CPT-11 and SN-38 were best described by a 3- and 2-compartment model, respectively, with first-order elimination. Body surface area and co-administration with 5-FU/LV plus bevacizumab were significant covariates (p < 0.01) for volumes of the central compartment of CPT-11 and SN-38, and clearance of CPT-11. Pre-treatment total bilirubin and co-administration with 5-FU/LV and bevacizumab were significant covariates (p < 0.01) for clearance of SN-38. Accurate and precise predictive performance (r2 > 0.99, -2 < bias (%ME) < 0, precision (% RMSE) < 12) of both CPT-11 and SN-38 was achieved using: (i) 6 fixed sampling times collected at 1.5, 3.5, 4, 5.75, 22, 23.5 hours post-infusion; or (ii) 1 fixed time and 2 sampling windows collected at 1.5, [3-5.75], [22-23.5] hours post-infusion. The present study demonstrates that an optimal sampling design with three blood samples achieves accurate and precise pharmacokinetic parameter estimates for both CPT-11 and SN-38.

Definition and Validation of a Novel Metric of Erythropoiesis-Stimulating Agent Response in Hemodialysis Patients.

Erythropoiesis-stimulating agents (eg, epoetin alfa) are the primary treatment for anemia in patients with end-stage renal disease. Hemoglobin variability in and out of a narrow target range is common and associated with higher morbidity and mortality risk. More robust erythropoiesis-stimulating agent response metrics are needed to define optimal dosing and their association with clinical outcomes. In this cross-sectional, single-center, retrospective study, 49 patients with end-stage renal disease on hemodialysis were followed over 12 months. To quantify hemoglobin deviations outside the target range (10-12 g/dL), the area under the curve of hemoglobin versus time over a 12-month period (AUC-HGB) was calculated using the trapezoidal rule. Patients were categorized into 4 responder groups based on AUC-HGB quartiles. Comparative analyses of demographic and clinical characteristics between responder groups were performed. Correlations between AUC-HGB, erythropoietin resistance index, and time within therapeutic range were calculated. There were no significant differences in laboratory and dialysis parameters between responder groups except hemoglobin concentration and epoetin alfa dose. There was a negative correlation between AUC-HGB and time within therapeutic range (r = -.92; P < .001) and hemoglobin concentration (r = -.85; P < .01), indicating internal validity of the metric. There was a positive correlation between AUC-HGB and erythropoietin resistance index (r = .70; P < .001) indicating external validity. The poor response group received a higher median epoetin alfa dose (160 U/kg/week) compared to the excellent response group (68.8 U/kg/week; P < .001) with a similar number of dose changes between the groups. AUC-HGB is a valid marker of epoetin alfa response and should be considered in future analyses of larger populations.