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

The impact of structural uncertainty on cost-effectiveness models for adjuvant endocrine breast cancer treatments: The need for disease-specific model standardization and improved guidance

__Abstract__ Introduction: Structural uncertainty relates to differences in model structure and parameterization. For many published health economic analyses in oncology, substantial differences in model structure exist, leading to differences in analysis outcomes and potentially impacting decision-making processes. The objectives of this analysis were (1) to identify differences in model structure and parameterization for cost-effectiveness analyses (CEAs) comparing tamoxifen and anastrazole for adjuvant breast cancer (ABC) treatment; and (2) to quantify the impact of these differences on analysis outcome metrics. Methods: The analysis consisted of four steps: (1) review of the literature for identification of eligible CEAs; (2) definition and implementation of a base model structure, which included the core structural components for all identified CEAs; (3) definition and implementation of changes or additions in the base model structure or parameterization; and (4) quantification of the impact of changes in model structure or parameterizations on the analysis outcome metrics life-years gained (LYG), incremental costs (IC) and the incremental cost-effectiveness ratio (ICER). Results: Eleven CEA analyses comparing anastrazole and tamoxifen as ABC treatment were identified. The base model consisted of the following health states: (1) on treatment; (2) off treatment; (3) local recurrence; (4) metastatic disease; (5) death due to breast cancer; and (6) death due to other causes. The base model estimates of anastrazole versus tamoxifen for the LYG, IC and ICER were 0.263 years, €3,647 and €13,868/LYG, respectively. In the published models that were evaluated, differences in model structure included the addition of different recurrence health states, and associated transition rates were identified. Differences in parameterization were related to the incidences of recurrence, local recurrence to metastatic disease, and metastatic disease to death. The separate impact of these model components on the LYG ranged from 0.207 to 0.356 years, while incremental costs ranged from €3,490 to €3,714 and ICERs ranged from €9,804/LYG to €17,966/LYG. When we re-analyzed the published CEAs in our framework by including their respective model properties, the LYG ranged from 0.207 to 0.383 years, IC ranged from €3,556 to €3,731 and ICERs ranged from €9,683/LYG to €17,570/LYG. Conclusion:

Does Older Age Lead to Higher Risk for Neutropenia in Patients Treated with Paclitaxel?

Purpose: There is ongoing concern regarding increased toxicity from paclitaxel in elderly patients, particularly of severe neutropenia. Yet, data so far is controversial and this concern is not supported by a clinically relevant age-dependent difference in pharmacokinetics (PK) of paclitaxel. This study assessed whether age is associated with increased risk for paclitaxel-induced neutropenia. Methods: Paclitaxel plasma concentration-time data, pooled from multiple different studies, was combined with available respective neutrophil count data during the first treatment cycle. Paclitaxel pharmacokinetic-pharmacodynamic (PK-PD) d

Toxicity of pemetrexed during renal impairment explained-Implications for safe treatment

Item does not contain fulltextPemetrexed is an important component of first line treatment in patients with non-squamous non-small cell lung cancer. However, a limitation is the contraindication in patients with renal impairment due to hematological toxicity. Currently, it is unknown how to safely dose pemetrexed in these patients. The aim of our study was to elucidate the relationship between pemetrexed exposure and toxicity to support the development of a safe dosing regimen in patients with renal impairment. A population pharmacokinetic/pharmacodynamic analysis was performed based on phase II study results in three patients with renal dysfunction, supplemented with data from 106 patients in early clinical studies. Findings were externally validated with data of different pemetrexed dosing regimens. Alternative dosing regimens were evaluated using the developed model. We found that pemetrexed toxicity was driven by the time above a toxicity threshold concentration. The threshold for vitamin-supplemented patients was 0.110 mg/mL (95% CI: 0.092-0.146 mg/mL). It was observed that in patients with renal impairment (estimated glomerular filtration rate [eGFR]: <45 mL/min) the approved dose of 500 mg/m(2) would yield a high probability of severe neutropenia in the range of 51.0% to 92.6%. A pemetrexed dose of 20 mg for patients (eGFR: 20 mL/min) is shown to be neutropenic-equivalent to the approved dose in patients with adequate renal function (eGFR: 90 mL/min), but would result in an approximately 13-fold lower area under the concentration-time curve. The pemetrexed exposure-toxicity relationship is explained by a toxicity threshold and substantially different from previously thought. Without prophylaxis for toxicity, it is unlikely that a therapeutic dose can be safely administered to patients with renal impairment

Exposure-response analyses of anaplastic lymphoma kinase inhibitors crizotinib and alectinib in non-small cell lung cancer patients

Crizotinib and alectinib are anaplastic lymphoma kinase (ALK)-inhibitors indicated for the treatment of ALK-positive metastatic non-small cell lung cancer (NSCLC). At the currently used fixed doses, interindividual variability in exposure is high. The aim of this study was to investigate whether minimum plasma concentrations (C-min) of crizotinib and alectinib are related to efficacy and toxicity. An observational study was performed, in which ALK-positive NSCLC patients who were treated with crizotinib and alectinib and from whom pharmacokinetic samples were collected in routine care, were included in the study. Exposure-response analyses were explored using previously proposed C(min)thresholds of 235 ng/mL for crizotinib and 435 ng/mL for alectinib. Forty-eight crizotinib and 52 alectinib patients were included. For crizotinib, median progression-free survival (mPFS) was 5.7 vs. 17.4 months for patients with C-min = 235 ng/mL, respectively (P = 0.08). In multivariable analysis, C-min = 435 ng/mL, respectively (P = 0.04). Multivariable analysis resulted in an HR of 4.29 (95% CI, 1.33-13.90,P = 0.015). In conclusion, PFS of crizotinib and alectinib treated NSCLC patients is prolonged in patients with C-min >= 235 ng/mL and 435 ng/mL, respectively. Therefore, therapeutic drug monitoring should be part of routine clinical management for these agents.Pathogenesis and treatment of chronic pulmonary disease

Predictive ability of a semi-mechanistic model for neutropenia in the development of novel anti-cancer agents: two case studies

Abstract In cancer chemotherapy neutropenia is a common dose-limiting toxicity. An ability to predict the neutropenic effects of cytotoxic agents based on proposed trial designs and models conditioned on previous studies would be valuable. The aim of this study was to evaluate the ability of a semi-mechanistic pharmacokinetic/pharmacodynamic (PK/PD) model for myelosuppression to predict the neutropenia observed in Phase I clinical studies, based on parameter estimates obtained from prior trials. Pharmacokinetic and neutropenia data from 5 clinical trials for diflomotecan and from 4 clinical trials for indisulam were used. Data were analyzed and simulations were performed using the population approach with NONMEM VI. Parameter sets were estimated under the following scenarios: (a) data from each trial independently, (b) pooled data from all clinical trials and (c) pooled data from trials performed before the tested trial. Model performance in each of the scenarios was evaluated by means of predictive (visual and numerical) checks. The semi-mechanistic PK/PD model for neutropenia showed adequate predictive ability for both anti-cancer agents. For diflomotecan, similar predictions were obtained for the three scenarios. For indisulam predictions were better when based on data from the specific study, however when the model parameters were conditioned on data from trials performed prior to a specific study, similar predictions of the drug related-neutropenia profiles and descriptors were obtained as when all data were used. This work provides further indication that modeling and simulation tools can be applied in the early stages of drug development to optimize future trials

Hot flashes are not predictive for serum concentrations of tamoxifen and its metabolites

Background: Tamoxifen has dramatically reduced the recurrence and mortality rate of estrogen receptor positive breast cancer. However, the efficacy of tamoxifen varies between individuals and 40% of patients will have a recurrence despite adjuvant tamoxifen treatment. Factors that predict tamoxifen efficacy would be helpful for optimizing treatment. Serum concentrations of the active metabolite, endoxifen, may be positively related to treatment outcome. In addition, hot flashes are suggested to be positively associated with tamoxifen treatment outcome. Methods: We investigated in a series of 109 patients whether the frequency and severity of hot flashes were related to concentrations of tamoxifen and its metabolites. A serum sample of all patients was analyzed for the concentration of tamoxifen, N-desmethyltamoxifen, endoxifen and 4-hydroxytamoxifen, as well as for estradiol concentrations and several single nucleotide polymorphisms in CYP2D6. Additionally, these patients completed a questionnaire concerning biometric data and treatment side effects. Results: We found no evidence supporting an association between concentrations of tamoxifen or metabolites and either the frequency or severity of hot flashes in the covariate unadjusted analyses. However, including interactions with menopausal status and pre-treatment hot flash (PTHF) history indicated that post-menopausal women with PTHF experienced an increasing frequency of hot flashes with increasing serum concentrations of tamoxifen and its metabolites. This finding was not altered when adjusting for potential confounding factors (duration of tamoxifen treatment, CYP2D6 phenotype, estradiol serum concentration, age and body mass index). In addition we observed a positive association between body mass index and both hot flash frequency (p = 0.04) and severity (p < 0.0001). We also observed that patients with lower estradiol levels reported more severe hot flashes (p = 0.02). Conclusions: No univariate associations were observed between concentrations of active tamoxifen metabolites and either the frequency or severity of hot flashes during treatment. However, the frequency of hot flashes may be exacerbated by higher serum concentrations of tamoxifen and its metabolites in post-menopausal women with a history of hot flashes prior to tamoxifen treatment

CYP3A4*22 genotype-guided dosing of kinase inhibitors in cancer patients

IntroductionA genetic variant explaining a part of the exposure of many kinase inhibitors (KIs) is the single nucleotide polymorphism (SNP) CYP3A4*22, resulting in less CYP3A4 enzyme activity. The primary aim of this study was to investigate if the systemic exposure is non-inferior after a dose reduction of KIs metabolized by CYP3A4 in CYP3A4*22 carriers compared to patients without this SNP (i.e., wildtype patients) receiving the standard dose.MethodsIn this multicenter, prospective, non-inferiority study, patients were screened for the presence of CYP3A4*22. Patients with the CYP3A4*22 SNP received a 20-33% dose reduction. At steady state, a pharmacokinetic (PK) analysis was performed and compared to the PK results from wildtype patients treated with the registered dose using a two-stage individual patient data meta-analysis approach.ResultsIn total, 207 patients were included in the final analysis. The CYP3A4*22 SNP was found in 16% of the patients in the final analysis (n = 34). Most of the included patients received imatinib (37%) or pazopanib (22%) treatment. The overall geometric mean ratio (GMR) comparing the exposure of the CYP3A4*22 carriers to the exposure of the wildtype CYP3A4 patients was 0.89 (90% confidence interval: 0.77-1.03).ConclusionNon-inferiority could not be proven for dose reduction of KIs metabolized by CYP3A4 in CYP3A4*22 carriers compared to the registered dose in wildtype patients. Therefore, an up-front dose reduction based upon the CYP3A4*22 SNP for all KIs does not seem an eligible new way of personalized therapy.Personalised Therapeutic

Impact of CYP3A4*22 on Pazopanib Pharmacokinetics in Cancer Patients

Background and Objective: As pazopanib plasma trough concentrations are correlated with treatment outcome, we explored whether single nucleotide polymorphisms in the elimination pathway of pazopanib affect systemic pazopanib concentrations. Methods: The decreased function alleles CYP3A4 15389 C > T (*22), ABCB1 3435 C >T, ABCG2 421 C >A, and ABCG2 34G >A were analyzed within a recently developed population-pharmacokinetic model. Results: Incorporation of CYP3A4*22 in the model resulted in a 35% lower clearance for variant carriers (0.18 vs. 0.27 L/h; difference in objective function value: − 9.7; p < 0.005). Simulated median trough concentrations of cancer patients with CYP3A4*22 with 600 mg once daily or 800 mg once daily were 31 and 35 mg/L, respectively. The simulated trough concentrations for the population excluding the CYP3A4*22 carriers after 600 mg once daily or 800 mg once daily were 18 and 20 mg/L, respectively. Conclusion: This analysis shows that CYP3A4*22 heterozygotes have a substantial lower pazopanib clearance and that dose adjustments based on CYP3A4*22 status could be considered

Linked Pharmacometric-Pharmacoeconomic Modeling and Simulation in Clinical Drug Development

Market access and pricing of pharmaceuticals are increasingly contingent on the ability to demonstrate comparative effectiveness and cost-effectiveness. As such, it is widely recognized that predictions of the economic potential of drug candidates in development could inform decisions across the product life cycle. This may be challenging when safety and efficacy profiles in terms of the relevant clinical outcomes are unknown or highly uncertain early in product development. Linking pharmacometrics and pharmacoeconomics, such that outputs from pharmacometric models serve as inputs to pharmacoeconomic models, may provide a framework for extrapolating from early-phase studies to predict economic outcomes and characterize decision uncertainty. This article reviews the published studies that have implemented this methodology and used simulation to inform drug development decisions and/or to optimize the use of drug treatments. Some of the key practical issues involved in linking pharmacometrics and pharmacoeconomics, including the choice of final outcome measures, methods of incorporating evidence on comparator treatments, approaches to handling multiple intermediate end points, approaches to quantifying uncertainty, and issues of model validation are also discussed. Finally, we have considered the potential barriers that may have limited the adoption of this methodology and suggest that closer alignment between the disciplines of clinical pharmacology, pharmacometrics, and pharmacoeconomics, may help to realize the potential benefits associated with linked pharmacometric-pharmacoeconomic modeling and simulation