Clinical Relevance of High Plasma Trough Levels of the Kinase Inhibitors Crizotinib, Alectinib, Osimertinib, Dabrafenib, and Trametinib in NSCLC Patients.

BACKGROUND: the study aims to evaluate whether high plasma trough levels of the kinase inhibitors (K.I.s) crizotinib, alectinib, osimertinib, dabrafenib, and trametinib were associated with a higher risk of toxicity in non-small-cell lung cancer patients. METHODS: In this retrospective cohort study, patients with non-small-cell lung cancer treated with the selected K.I.s were included if at least one plasma trough level at steady state (C min,ss ) was available. Data were extracted from electronic medical records and laboratory databases. The high group for each K.I. was defined as 10% of patients with the highest first C min,ss . The remaining patients were placed in the non-high group. The frequency of dose-limiting toxicities (DLTs), defined as adverse events leading to dose reduction, dose interruption, or permanent discontinuation, was compared between the 2 groups. RESULTS: A total of 542 patients were included in the different K.I. groups. A high C min,ss of crizotinib (n = 96), alectinib (n = 105), osimertinib (n = 227), dabrafenib (n = 52), and trametinib (n = 62) correlated with a C min,ss ≥490, ≥870, ≥405, ≥150, and ≥25 ng/mL, respectively. DLTs were more common in the alectinib high group than in the alectinib non-high group (64% vs. 29%, P = 0.036). Liver toxicity was observed in 4 (36%) patients in the high group and 5 (5%) patients in the non-high group ( P = 0.007). For other K.I.s, no significant differences were observed in the frequency of DLTs between the high and non-high groups. CONCLUSIONS: For alectinib, high C min,ss was correlated with a higher risk of DLT. No differences in the frequency of DLTs were observed between the high and non-high groups for crizotinib, osimertinib, dabrafenib, and trametinib.

The influence of body mass index on the tolerability and effectiveness of full-weight-based paclitaxel chemotherapy in women with early-stage breast cancer.

PURPOSE: To investigate the influence of body mass index (BMI) on the tolerability and effectiveness of full-weight-based paclitaxel chemotherapy in early breast cancer patients. METHODS: Early-stage breast cancer patients who received (neo)adjuvant weekly paclitaxel 80 mg/m2 chemotherapy were included in this retrospective study. Patients were divided into three groups based on their BMI: lean, overweight, and obese. Logistic regression was used to assess for association between BMI with administered relative dose intensity (RDI) < 85%. The occurrence of treatment modifications and the pathological response on neoadjuvant chemotherapy were compared between BMI categories. RESULTS: Four hundred (400) patients were included in this study; 200 (50%) lean, 125 (31%) overweight, and 75 (19%) obese patients. The adjusted odds ratio to receive RDI < 85% for BMI was 1.02 (p value, .263). Treatment modifications occurred in 115 (58%), 82 (66%), and 52 (69%) patients in the respective BMI categories (p value = .132). Peripheral neuropathy was observed in 79 (40%), 58 (46%), and 41 (55%) patients in the lean, overweight, and obese group (p value = .069), whereas hematologic toxicity was observed in 31 (16%), 10 (8%), and 4 (5%) patients (p value = .025). Pathological complete response was observed in 22 (17%), 11 (14%), and 6 (13%) patients in the respective BMI categories (p value = .799). CONCLUSION: BMI did not significantly influence the tolerability and effectiveness of full-weight-based paclitaxel chemotherapy. Therefore, the results of this study align with current guideline recommendations of using full-weight-based paclitaxel chemotherapy in obese patients.

Are novel oral oncolytics underdosed in obese patients?

PURPOSE: Data on the effects of obesity on drug exposure of oral targeted oncolytics is scarce. Therefore, the aim of this study was to investigate the influence of body weight and body mass index (BMI) on trough levels of oral oncolytics with an exposure-response relationship. The oral oncolytics of interest were abiraterone, alectinib, cabozantinib, crizotinib, imatinib, pazopanib, sunitinib and trametinib. METHODS: This retrospective cohort study included patients treated with the selected oral oncolytics at the standard dose, with a measured trough level at steady state and with available body weight. The Spearman's correlation test was used to determine the correlation between body weight and trough levels. The Fisher's exact text was used to compare the frequency of inadequate trough levels between BMI categories. RESULTS: 1265 patients were included across the different oral oncolytics. A negative correlation coefficient was observed between weight and trough levels for crizotinib (n = 75), imatinib (n = 201) and trametinib (n = 310), respectively, ρ = - 0.41, ρ = - 0.24 and ρ = - 0.23, all with a p-value < 0.001. For crizotinib, a higher percentage of patients with a body weight > 100 kg had inadequate trough levels. No statistically significant differences were observed in the frequency of inadequate trough levels between BMI categories. CONCLUSION: Higher body weight was only correlated with lower plasma trough levels for crizotinib, imatinib, and trametinib. Therefore, patients with a high body weight may require dose escalation to obtain adequate target levels when treated with these oral oncolytics.

A joint model of longitudinal pharmacokinetic and time-to-event data to study exposure-response relationships: a proof-of-concept study with alectinib.

PURPOSE: In exposure-response analyses of oral targeted anticancer agents, longitudinal plasma trough concentrations are often aggregated into a single value even though plasma trough concentrations can vary over time due to dose adaptations, for example. The aim of this study was to compare joint models to conventional exposure-response analyses methods with the application of alectinib as proof-of-concept. METHODS: Joint models combine longitudinal pharmacokinetic data and progression-free survival data to infer the dependency and association between the two datatypes. The results from the best joint model and the standard and time-dependent cox proportional hazards models were compared. To normalize the data, alectinib trough concentrations were normalized using a sigmoidal transformation to transformed trough concentrations (TTC) before entering the models. RESULTS: No statistically significant exposure-response relationship was observed in the different Cox models. In contrast, the joint model with the current value of TTC in combination with the average TTC over time did show an exposure-response relationship for alectinib. A one unit increase in the average TTC corresponded to an 11% reduction in progression (HR, 0.891; 95% confidence interval, 0.805-0.988). CONCLUSION: Joint models are able to give insights in the association structure between plasma trough concentrations and survival outcomes that would otherwise not be possible using Cox models. Therefore, joint models should be used more often in exposure-response analyses of oral targeted anticancer agents.

Impact of bariatric surgery on oral anticancer drugs: an analysis of real-world data.

PURPOSE: The number of patients with bariatric surgery who receive oral anticancer drugs is rising. Bariatric surgery may affect the absorption of oral anticancer drugs. Strikingly, no specific drug dosing recommendations are available. We aim to provide practical recommendations on the application of oral anticancer drugs in patients who underwent bariatric surgery. METHODS: Patients with any kind of bariatric surgery were extracted retrospectively in a comprehensive cancer center. In addition, a flowchart was proposed to assess the risk of inadequate exposure to oral anticancer drugs in patients who underwent bariatric surgery. Subsequently, the flowchart was evaluated retrospectively using routine Therapeutic drug monitoring (TDM) samples. RESULTS: In our analysis, 571 cancer patients (0.4% of 140.000 treated or referred patients) had previous bariatric surgery. Of these patients, 78 unique patients received 152 oral anticancer drugs equaling an overall number of 30 unique drugs. The 30 different prescribed oral anticancer drugs were categorized as low risk (13%), medium risk (67%), and high risk (20%) of underdosing. TDM plasma samples of 25 patients (82 samples) were available, of which 21 samples post-bariatric surgery (25%) were below the target value. CONCLUSIONS: The proposed flowchart can support optimizing the treatment with orally administered anticancer drugs in patients who underwent bariatric surgery. We recommend performing TDM in drugs that belong to BCS classes II, III, or IV. If more risk factors are present in BCS classes II or IV, a priori switches to other drugs may be advised. In specific cases, higher dosages can be provided from the start (e.g., tamoxifen).

Treatment patterns and survival outcomes of patients admitted to the intensive care unit due to immune-related adverse events of immune checkpoint inhibitors.

INTRODUCTION: Severe immune-related adverse events (irAEs) due to immune checkpoint inhibitors (ICIs) can lead to admission to the intensive care unit (ICU). In this retrospective study, we determined the incidence, treatment patterns and survival outcomes of this patient population at a comprehensive cancer center. METHODS: All patients admitted to the ICU due to irAEs from ICI treatment between January 2015 and July 2022 were included. Descriptive statistics were reported on patient characteristics and treatment patterns during hospital admission. Overall survival (OS) from the time of ICU discharge to death was estimated using the Kaplan-Meier method. RESULTS: Over the study period, 5561 patients received at least one ICI administration, of which 32 patients (0.6%) were admitted to the ICU due to irAEs. Twenty patients were treated with anti-PD-1 plus anti-CTLA-4 treatment, whereas 12 patients were treated with ICI monotherapy. The type of irAEs were de novo diabetes-related ketoacidosis (n = 8), immune-related gastrointestinal toxicity (n = 8), myocarditis or myositis (n = 10), nephritis (n = 3), pneumonitis (n = 2), and myelitis (n = 1). The median duration of ICU admission was 3 days (interquartile range: 2-6 days). Three patients died during ICU admission. The median OS of the patients who were discharged from the ICU was 18 months (95% confidence interval, 5.0-NA). CONCLUSION: The incidence of irAEs leading to ICU admission in patients treated with ICI was low in this study. ICU mortality due to irAEs was low and a subset of this patient population even had long-term survival.

Representativeness of Phase III Trial for Osimertinib in Pretreated Advanced EGFR-Mutated Non-small-cell Lung Cancer Patients and Treatment Outcomes in Clinical Practice.

BACKGROUND: Overall survival (OS) data of osimertinib in pretreated non-small-cell lung cancer (NSCLC) in real-world practice is limited, and treatment benefits for patients not represented in the pivotal trials (ineligible) are unclear. OBJECTIVE: To determine the representativeness of the AURA3 trial for NSCLC patients treated with osimertinib in a real-world setting and to determine outcomes of patients who were represented in the AURA3 trial (eligible) and those who were ineligible. METHODS: Advanced NSCLC patients receiving post first-line osimertinib were included in this retrospective study and were divided into two groups based on eligibility criteria of the AURA3 trial. Progression-free survival (PFS) and OS were estimated using the Kaplan-Meier method. Cox models were used to estimate the association of eligibility criteria with OS. RESULTS: 328 patients were included; 126 (38%) patients were eligible and 202 (62%) patients were ineligible. The most common ineligibility reasons were the number of earlier treatment lines and an Eastern Cooperative Oncology Group performance status (ECOG PS) > 1. PFS of eligible and ineligible patients was not statistically different (8.0 vs. 5.8 months, p = 0.062). Eligible patients had a longer OS (24.0 vs. 15.4 months, p = 0.001) compared to ineligible patients. ECOG PS was the best predictor for OS. An ECOG PS of 1 was already associated with poorer survival compared to an ECOG PS of 0 (hazard ratio 1.54; p = 0.016). CONCLUSION: The majority of the study population was not represented in the AURA3 trial. Survival outcomes of eligible patients are in concordance with the AURA3 trial, while OS of ineligible patients was significantly shorter compared to eligible patients.

Longitudinal nonlinear mixed effects modeling of EGFR mutations in ctDNA as predictor of disease progression in treatment of EGFR-mutant non-small cell lung cancer.

Correlations between increasing concentrations of circulating tumor DNA (ctDNA) in plasma and disease progression have been shown. A nonlinear mixed effects model to describe the dynamics of epidermal growth factor receptor (EGFR) ctDNA data from patients with non-small cell lung cancer (NSCLC) combined with a parametric survival model were developed to evaluate the ability of these modeling techniques to describe ctDNA data. Repeated ctDNA measurements on L858R, exon19del, and T790M mutants were available from 54 patients with EGFR mutated NSCLC treated with erlotinib or gefitinib. Different dynamic models were tested to describe the longitudinal ctDNA concentrations of the driver and resistance mutations. Subsequently, a parametric time-to-event model for progression-free survival (PFS) was developed. Predicted L858R, exon19del, and T790M concentrations were used to evaluate their value as predictor for disease progression. The ctDNA dynamics were best described by a model consisting of a zero-order increase and first-order elimination (19.7/day, 95% confidence interval [CI] 14.9-23.6/day) of ctDNA concentrations. In addition, time-dependent development of resistance (5.0 × 10-4 , 95% CI 2.0 × 10-4 -7.0 × 10-4 /day) was included in the final model. Relative change in L858R and exon19del concentrations from baseline was identified as most significant predictor of disease progression (p = 0.001). The dynamic model for L858R, exon19del, and T790M concentrations in ctDNA and time-to-event model adequately described the observed concentrations and PFS data in our clinical cohort. In addition, it was shown that nonlinear mixed effects modeling is a valuable method for the analysis of longitudinal and heterogeneous biomarker datasets obtained from clinical practice.