Postmarketing surveillance is useful to collect safety data in real‐world clinical settings. In this study, we applied postmarketing real‐world data on a mechanistic model analysis for neutropenic profiles of eribulin in patients with recurrent or metastatic breast cancer. Demographic and safety data were collected using an active surveillance method from eribulin‐treated recurrent or metastatic breast cancer patients. Changes in neutrophil counts over time were analyzed using a mechanistic pharmacodynamic model. Pathophysiological factors that might affect the severity of neutropenia were investigated, and neutropenic patterns were simulated for different treatment schedules. Clinical and laboratory data were collected from 401 patients (5199 neutrophil count measurements) who had not received granulocyte colony‐stimulating factor and were eligible for pharmacodynamic analysis. The estimated mean parameters were as follows: mean transit time = 104.5 h, neutrophil proliferation rate constant = 0.0377 h−1, neutrophil elimination rate constant = 0.0295 h−1, and linear coefficient of drug effect = 0.0413 mL/ng. Low serum albumin levels and low baseline neutrophil counts were associated with severe neutropenia. The probability of grade ≥3 neutropenia was predicted to be 69%, 27%, and 27% for patients on standard, biweekly, and triweekly treatment scenarios, respectively, based on virtual simulations using the developed pharmacodynamic model. In conclusion, this is the first application of postmarketing surveillance data to a model‐based safety analysis. This analysis of safety data reflecting authentic clinical settings will provide useful information on the safe use and potential risk factors of eribulin.
Objective: Increased risk of atherosclerotic cardiovascular disease in subjects with type 2 diabetes is linked to elevated levels of triglyceride-rich lipoproteins and their remnants. The metabolic effects of PCSK9 (proprotein convertase subtilisin/kexin 9) inhibitors on this dyslipidemia were investigated using stable-isotope-labeled tracers. Approach and Results: Triglyceride transport and the metabolism of apos (apolipoproteins) B48, B100, C-III, and E after a fat-rich meal were investigated before and on evolocumab treatment in 13 subjects with type 2 diabetes. Kinetic parameters were determined for the following: apoB48 in chylomicrons; triglyceride in VLDL 1 (very low-density lipoprotein) and VLDL 2 ; and apoB100 in VLDL 1 , VLDL 2 , IDL (intermediate-density lipoprotein), and LDL (low-density lipoprotein). Evolocumab did not alter the kinetics of apoB48 in chylomicrons or apoB100 or triglyceride in VLDL 1 . In contrast, the fractional catabolic rates of VLDL 2 -apoB100 and VLDL 2 -triglyceride were both increased by about 45%, which led to a 28% fall in the VLDL 2 plasma level. LDL-apoB100 was markedly reduced by evolocumab, which was linked to metabolic heterogeneity in this fraction. Evolocumab increased clearance of the more rapidly metabolized LDL by 61% and decreased production of the more slowly cleared LDL by 75%. ApoC-III kinetics were not altered by evolocumab, but the apoE fractional catabolic rates increased by 45% and the apoE plasma level fell by 33%. The apoE fractional catabolic rates was associated with the decrease in VLDL 2 - and IDL-apoB100 concentrations. Conclusions: Evolocumab had only minor effects on lipoproteins that are involved in triglyceride transport (chylomicrons and VLDL 1 ) but, in contrast, had a profound impact on lipoproteins that carry cholesterol (VLDL 2 , IDL, LDL). Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02948777.
Background: Japanese regulation imposes a mandatory post-marketing observational cohort study for new chemical entities and biological products. The primary purpose is collection of safety data in actual clinical settings by an active surveillance approach. In this study, we utilized the observational safety data of eribulin for model-based pharmacodynamic analysis to investigate more detailed safety profile of eribulin in patients with recurrent or metastatic breast cancer (RBC/MBC). Methods: The demographics and safety data were collected from RBC/MBC patients who were treated with eribulin by an active surveillance method. Since dose-limiting toxicity of eribulin is neutropenia, we analyzed the time course of neutrophil counts using a mechanistic pharmacodynamic model. Plasma concentrations of eribulin were simulated by a population pharmacokinetic model developed by Majid et al. (J. Clin. Pharmacol. 2014). All analyses were performed by Phoenix64 NLME1.3 (Certara). Estimated pharmacodynamic parameters were mean transit time (MTT [h]), proliferation rate constant of neutrophils (Kprol [1/h]), elimination rate constant of neutrophils (Kout [1/h]), feedback constant (Gamma) and linear coefficient of drug effect (Slope [mL/ng]). Results: Clinical and laboratory data of 607 patients who were not given granulocyte colony stimulating factor were collected from July through December 2011. Among them, 406 patients with a total of 5204 neutrophil count measurements were eligible for mechanistic pharmacodynamic analysis. The estimated mean parameters for eribulin were: MTT=45.4 [h], Kprol=0.1111 [1/h], Kout=0.2074 [1/h], Gamma=0.317 and Slope=0.0254 [mL/ng]. Pathophysiological factors (age, ECOG performance status, serum albumin level, and previous treatment history of cytotoxic agents) that can affect severity of neutropenia were investigated by Chi-squared test, and albumin level was supposed to influence the proliferation of progenitor cells. Conclusions: The present study reports the first example that observational data collected by a post-marketing cohort study can be successfully applied to a model-based safety analysis. Different from pre-marketing clinical trials which strictly limit the eligible population, the use of post-marketing data is useful to investigate extensive safety profiles of eribulin in patients with broader backgrounds. The obtained safety profile of real-world clinical settings will provide clinically useful information for the treatment of breast cancer using eribulin. Citation Format: Takahisa Kawamura, Valentina Fermanelli, Toshiaki Takahashi, Yukinori Sakata, Toshiyuki Matsuoka, Mika Ishii, Yusuke Tanigawara. Mechanistic pharmacodynamic analysis on safety profiles of eribulin in patients with breast cancer using data obtained by post-marketing observational study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5052. doi:10.1158/1538-7445.AM2017-5052
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