Exposure-response relationship of cabozantinib in patients with metastatic renal cell carcinoma treated in routine care.

BACKGROUND: Interindividual pharmacokinetic variability may influence the clinical benefit or toxicity of cabozantinib in metastatic renal cell carcinoma (mRCC). We aimed to investigate the exposure-toxicity and exposure-response relationship of cabozantinib in unselected mRCC patients treated in routine care. METHODS: This ambispective multicenter study enrolled consecutive patients receiving cabozantinib in monotherapy. Steady-state trough concentration (Cmin,ss) within the first 3 months after treatment initiation was used for the PK/PD analysis with dose-limiting toxicity (DLT) and survival outcomes. Logistic regression and Cox proportional-hazards models were used to identify the risk factors of DLT and inefficacy in patients, respectively. RESULTS: Seventy-eight mRCC patients were eligible for the statistical analysis. Fifty-two patients (67%) experienced DLT with a median onset of 2.1 months (95%CI 0.7-8.2). In multivariate analysis, Cmin,ss was identified as an independent risk factor of DLT (OR 1.46, 95%CI [1.04-2.04]; p = 0.029). PFS and OS were not statistically associated with the starting dose (p = 0.81 and p = 0.98, respectively). In the multivariate analysis of PFS, Cmin, ss > 336 ng/mL resulted in a hazard ratio of 0.28 (95%CI, 0.10-0.77, p = 0.014). By contrast, Cmin, ss > 336 ng/mL was not statistically associated with longer OS. CONCLUSION: Early plasma drug monitoring may be useful to optimise cabozantinib treatment in mRCC patients treated in monotherapy, especially in frail patients starting at a lower than standard dose.

Dihydropyrimidine dehydrogenase gene variants for predicting grade 4-5 fluoropyrimidine-induced toxicity: FUSAFE individual patient data meta-analysis.

BACKGROUND: Dihydropyrimidine dehydrogenase (DPD) deficiency is the main known cause of life-threatening fluoropyrimidine (FP)-induced toxicities. We conducted a meta-analysis on individual patient data to assess the contribution of deleterious DPYD variants *2A/D949V/*13/HapB3 (recommended by EMA) and clinical factors, for predicting G4-5 toxicity. METHODS: Study eligibility criteria included recruitment of Caucasian patients without DPD-based FP-dose adjustment. Main endpoint was 12-week haematological or digestive G4-5 toxicity. The value of DPYD variants *2A/p.D949V/*13 merged, HapB3, and MIR27A rs895819 was evaluated using multivariable logistic models (AUC). RESULTS: Among 25 eligible studies, complete clinical variables and primary endpoint were available in 15 studies (8733 patients). Twelve-week G4-5 toxicity prevalence was 7.3% (641 events). The clinical model included age, sex, body mass index, schedule of FP-administration, concomitant anticancer drugs. Adding *2A/p.D949V/*13 variants (at least one allele, prevalence 2.2%, OR 9.5 [95%CI 6.7-13.5]) significantly improved the model (p < 0.0001). The addition of HapB3 (prevalence 4.0%, 98.6% heterozygous), in spite of significant association with toxicity (OR 1.8 [95%CI 1.2-2.7]), did not improve the model. MIR27A rs895819 was not associated with toxicity, irrespective of DPYD variants. CONCLUSIONS: FUSAFE meta-analysis highlights the major relevance of DPYD *2A/p.D949V/*13 combined with clinical variables to identify patients at risk of very severe FP-related toxicity.

Model-Informed Precision Dosing of Intravenous Busulfan in Thai Pediatrics Undergoing Hematopoietic Stem Cell Transplantation.

BACKGROUND: Conditioning bifunctional agent, busulfan, is commonly used on children before hematopoietic stem cell transplantation. Currently, at the Ramathibodi hospital, Bangkok, Thailand, initial dosing is calculated according to age and body surface area, and 7 samples per day are used for therapeutic drug monitoring (TDM). This study aimed to identify the best strategies for individual dosages a priori from patient characteristics and a posteriori based on TDM. METHODS: The pharmacokinetic data set consisted of 2018 plasma concentrations measured in 135 Thai (n = 135) pediatric patients (median age = 8 years) and were analyzed using a population approach. RESULTS: Body weight, presence of malignant disease, and genetic polymorphism of Glutathione S-transferase Alpha-1 (GSTA1) were predictors of clearance. The optimum sampling times for TDM concentration measurements were 0.25, 2, and 5 hours after a 3-hour infusion. This was sufficient to obtain a Bayesian estimate of clearance a posteriori. Simulations showed the poor performance of a priori formula-based dose calculations with 90% of patients demonstrating a 69%-151% exposure interval around the target. This interval shrank to 85%-124% if TDM was carried out only at day 1 and to 90%-116% with TDM at days 1 and 3. CONCLUSIONS: This comprehensive study reinforces the interest of TDM in managing interindividual variability in busulfan exposure. Therapeutic drug monitoring can reliably be implemented from 3 samples using the Bayesian approach, preferably over 2 days. If using the latter is not possible, the formulas developed herein could present an alternative in Thai patients.

Can we identify patients carrying targeted deleterious DPYD variants with plasma uracil and dihydrouracil? A GPCO-RNPGx retrospective analysis.

OBJECTIVES: Dihydropyrimidine dehydrogenase (DPD) deficiency is the main cause of severe fluoropyrimidine-related toxicities. The best strategy for identifying DPD-deficient patients is still not defined. The EMA recommends targeted DPYD genotyping or uracilemia (U) testing. We analyzed the concordance between both approaches. METHODS: This study included 19,376 consecutive French patients with pre-treatment plasma U, UH2 and targeted DPYD genotyping (*2A, *13, D949V, *7) analyzed at Eurofins Biomnis (2015-2022). RESULTS: Mean U was 9.9 ± 10.1 ng/mL (median 8.7, range 1.6-856). According to French recommendations, 7.3 % of patients were partially deficient (U 16-150 ng/mL) and 0.02 % completely deficient (U≥150 ng/mL). DPYD variant frequencies were *2A: 0.83 %, *13: 0.17 %, D949V: 1.16 %, *7: 0.05 % (2 homozygous patients with U at 22 and 856 ng/mL). Variant carriers exhibited higher U (median 13.8 vs. 8.6 ng/mL), and lower UH2/U (median 7.2 vs. 11.8) and UH2/U2 (median 0.54 vs. 1.37) relative to wild-type patients (p<0.00001). Sixty-six% of variant carriers exhibited uracilemia <16 ng/mL, challenging correct identification of DPD deficiency based on U. The sensitivity (% patients with a deficient phenotype among variant carriers) of U threshold at 16 ng/mL was 34 %. The best discriminant marker for identifying variant carriers was UH2/U2. UH2/U2<0.942 (29.7 % of patients) showed enhanced sensitivity (81 %) in identifying deleterious genotypes across different variants compared to 16 ng/mL U. CONCLUSIONS: These results reaffirm the poor concordance between DPD phenotyping and genotyping, suggesting that both approaches may be complementary and that targeted DPYD genotyping is not sufficiently reliable to identify all patients with complete deficiency.

Identification of non-adherence to adjuvant letrozole using a population pharmacokinetics approach in hormone receptor-positive breast cancer patients.

BACKGROUND: Letrozole, an aromatase inhibitor metabolised via CYP2A6 and CYP3A4/5 enzymes, is used as adjuvant therapy for women with hormone receptor (HR)-positive early breast cancer. The objective of this study was to quantify the impact of CYP2A6 genotype on letrozole pharmacokinetics (PK), to identify non-adherent patients using a population approach and explore the possibility of a relationship between non-adherence and early relapse. METHODS: Breast cancer patients enrolled in the prospective PHACS study (ClinicalTrials.gov NCT01127295) and treated with adjuvant letrozole 2.5 mg/day were included. Trough letrozole concentrations (Css,trough) were measured every 6 months for 3 years by a validated LC-MS/MS method. Concentration-time data were analysed using non-linear mixed effects modelling. Three methods were evaluated for identification of non-adherent subjects using the base PK model. RESULTS: 617 patients contributing 2534 plasma concentrations were included and led to a one-compartment PK model with linear absorption and elimination. Model-based methods identified 28 % of patients as non-adherent based on high fluctuations of their Css,trough compared to 3 % based on patient declarations. The covariate analysis performed in adherent subjects revealed that CYP2A6 intermediate (IM) and slow metabolisers (SM) had 21 % (CI95 % = 12 - 30 %) and 46 % (CI95 % = 41 - 51 %) lower apparent clearance, respectively, compared to normal and ultrarapid metabolisers (NM+UM). Early relapse (19 patients) was not associated with model-estimated, concentration-based or declared adherence in the total population (p = 0.41, p = 0.37 and p = 0.45, respectively). CONCLUSIONS: These findings will help future investigations focusing on the exposure-efficacy relationship for letrozole in adjuvant setting.

Nonlinear Mixed-Effects Model of Z-Endoxifen Concentrations in Tamoxifen-Treated Patients from the CEPAM Cohort.

Tamoxifen is widely used in patients with hormone receptor-positive breast cancer. The polymorphic enzyme CYP2D6 is primarily responsible for metabolic activation of tamoxifen, resulting in substantial interindividual variability of plasma concentrations of its most important metabolite, Z-endoxifen. The Z-endoxifen concentration thresholds below which tamoxifen treatment is less efficacious have been proposed but not validated, and prospective trials of individualized tamoxifen treatment to achieve Z-endoxifen concentration thresholds are considered infeasible. Therefore, we aim to validate the association between Z-endoxifen concentration and tamoxifen treatment outcomes, and identify a Z-endoxifen concentration threshold of tamoxifen efficacy, using pharmacometric modeling and simulation. As a first step, the CYP2D6 Endoxifen Percentage Activity Model (CEPAM) cohort was created by pooling data from 28 clinical studies (> 7,000 patients) with measured endoxifen plasma concentrations. After cleaning, data from 6,083 patients were used to develop a nonlinear mixed-effect (NLME) model for tamoxifen and Z-endoxifen pharmacokinetics that includes a conversion factor to allow inclusion of studies that measured total endoxifen but not Z-endoxifen. The final parent-metabolite NLME model confirmed the primary role of CYP2D6, and contributions from body weight, CYP2C9 phenotype, and co-medication with CYP2D6 inhibitors, on Z-endoxifen pharmacokinetics. Future work will use the model to simulate Z-endoxifen concentrations in patients receiving single agent tamoxifen treatment within large prospective clinical trials with long-term survival to identify the Z-endoxifen concentration threshold below which tamoxifen is less efficacious. Identification of this concentration threshold would allow personalized tamoxifen treatment to improve outcomes in patients with hormone receptor-positive breast cancer.