Randomized Phase III Study of Amcenestrant Plus Palbociclib Versus Letrozole Plus Palbociclib in Estrogen Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Advanced Breast Cancer: Primary Results From AMEERA-5.

Purpose: AMEERA-5 investigated amcenestrant (oral selective estrogen receptor [ER] degrader) plus palbociclib versus letrozole plus palbociclib as first-line treatment for ER-positive/human epidermal growth factor receptor 2-negative (ER+/HER2-) advanced/metastatic breast cancer (aBC).

Materials And Methods: In AMEERA-5 (ClinicalTrials.gov identifier: NCT04478266), a double-blind, double-dummy, international phase III trial, adult pre-/post-menopausal women and men without previous systemic therapy for ER+/HER2- aBC were randomly assigned 1:1 to amcenestrant 200 mg once daily + standard palbociclib dosage (125 mg once daily, 21 days on/7 days off) or letrozole 2.

Development and validation of a predictive model to guide the use of plerixafor in pediatric population.

Plerixafor, a CXCR4 receptor antagonist, reduces the binding and chemotaxis of hematopoietic stem cells to the bone marrow stroma, resulting in predictable peak of cluster of differentiation 34 (CD34) cells in the peripheral blood (PB) approximately 10 h after its administration. We developed a model that could predict the CD34 harvest volume on the first day of apheresis (AP-CD34) based on PB-CD34 counts immediately prior to commencing apheresis in pediatric population. In all, data from 45 pediatric patients from the MOZAIC study who received either granulocyte colony-stimulating factor (G-CSF) alone or G-CSF plus plerixafor were included.

Utility-Based Dose Selection for Phase II Dose-Finding Studies.

Background And Objectives: Dose selection is a key feature of clinical development. Poor dose selection has been recognized as a major driver of development failure in late phase. It usually involves both efficacy and safety criteria.

Matching-adjusted indirect comparisons: Application to time-to-event data.

The Matching-Adjusted Indirect Comparison method (MAIC) is a recent methodology that allows to perform indirect comparisons between two drugs assessed in two different studies, where individual patients data are available in only one of the two studies, the data of the other one being available in an aggregate format only. In this work, we have assessed the properties of the MAIC method and compared, through simulations, several ways of practical implementation of the method. We conclude that it is more efficient to match the treatment arms separately (match the two drugs to compare on one hand, and the control arms on the other hand) and use the Lasso technique to select the covariates for the matching step is better than matching a maximal set of covariates.

Design optimization for dose-finding trials: a review.

Dose selection is one of the most difficult and crucial decisions to make during drug development. As a consequence, the dose-finding trial is a major milestone in the drug development plan and should be properly designed. This article will review the most recent methodologies for optimizing the design of dose-finding studies: all of them are based on the modeling of the dose-response curve, which is now the gold standard approach for analyzing dose-finding studies instead of the traditional ANOVA/multiple testing approach.