Pharmacodynamic Model-Based Safety Management of Eribulin-Induced Myelosuppression in Patients With Breast Cancer.

BACKGROUND: Neutropenia is a major dose-limiting toxicity of cancer chemotherapy. Semimechanistic mathematical models have been applied to describe the time course of neutrophil counts. The objectives of this study were to develop a mathematical model describing changes in neutrophil counts during eribulin treatment, to apply the empirical Bayes method to predict the probability of developing neutropenia ≥ grade 3 during eribulin treatment in each patient, and to propose the implementation of this mathematical tool in clinical practice for individual safety management. METHODS: The present model analysis and subsequent external evaluation were performed using the data of 481 patients with breast cancer, previously obtained from a postmarketing surveillance (training set) and a phase 2 clinical study (validation set). The model we previously reported (Kawamura et al 2018) was modified to improve its predictive capability. The individual time course of neutrophil changes during the treatment period was predicted by the empirical Bayes method using the observed neutrophil counts at baseline and the first measurement after the first eribulin dose. To evaluate the predictability of this method, the predicted neutrophil counts were compared with those of the observed values. RESULTS: The developed model provided good individual predictions, as indicated by the goodness-of-fit plots between the predicted and observed neutrophil counts, especially for a lower neutrophil count range. Days required to reach the nadir after the dose were also well-predicted. The sensitivity, specificity, and accuracy of the prediction of neutropenia grade ≥3 were 76%, 53%, and 71%, respectively. CONCLUSIONS: We developed a mathematical method for predicting and managing the risk of neutropenia during eribulin treatment. This method is generally applicable to other cases of chemotherapy-induced neutropenia and can be a new practical tool for individual safety management.

Effects of Evolocumab on the Postprandial Kinetics of Apo (Apolipoprotein) B100- and B48-Containing Lipoproteins in Subjects With Type 2 Diabetes.

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 VLDL1 (very low-density lipoprotein) and VLDL2; and apoB100 in VLDL1, VLDL2, IDL (intermediate-density lipoprotein), and LDL (low-density lipoprotein). Evolocumab did not alter the kinetics of apoB48 in chylomicrons or apoB100 or triglyceride in VLDL1. In contrast, the fractional catabolic rates of VLDL2-apoB100 and VLDL2-triglyceride were both increased by about 45%, which led to a 28% fall in the VLDL2 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 VLDL2- and IDL-apoB100 concentrations. CONCLUSIONS: Evolocumab had only minor effects on lipoproteins that are involved in triglyceride transport (chylomicrons and VLDL1) but, in contrast, had a profound impact on lipoproteins that carry cholesterol (VLDL2, IDL, LDL). Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02948777.

Pharmacodynamic analysis of eribulin safety in breast cancer patients using real-world postmarketing surveillance data.

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.