Practical considerations for the implementation of adaptive designs for oncology Phase I dose-finding trials

The EC90 of remifentanil for inhibiting endotracheal intubation responses under anesthesia induction with ciprofol: study protocol for a dose-finding trial with the biased-coin design

BACKGROUND

Tracheal intubation may cause significant hemodynamic responses. Many drugs have been shown to be effective in modifying these cardiovascular responses, including remifentanil, fentanyl, sufentanil, and alfentanil. However, the 90% effect-site concentration (EC90) of remifentanil required to control cardiovascular responses to tracheal intubation when combined with ciprofol remains unclear. The purpose of this study was to determine the EC90 of remifentanil inhibiting cardiovascular responses to tracheal intubation during anesthesia induction with ciprofol using biased-coin design up-and-down sequential method (BC-UDM).

METHODS

This is a prospective sequential allocation dose-finding study. American Society of Anesthesiologists physical status (ASA) I-II elective surgical patients receiving target-controlled infusion (TCI) of remifentanil effect-site concentration (Ce), followed by ciprofol and rocuronium for anesthesia, were enrolled. The cardiovascular response to tracheal intubation was defined as positive when mean arterial pressure (MAP) or heart rate (HR) is 15% higher than the baseline value. Using the BC-UDM, the Ce of remifentanil was determined based on the cardiovascular response to tracheal intubation of the previous patient. The EC90 and 90% confidence intervals (90% CIs) were estimated by R-Foundation centered isotonic regression and the pooled adjacent violators algorithm with bootstrapping.

DISCUSSION

The results of this study sought to demonstrate EC90 of remifentanil blunting sympathetic responses to tracheal intubation during anesthesia index (Ai)-guided ciprofol anesthesia using BCD-UDM. It may help to minimize the cardiovascular responses to tracheal intubation.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR2300078275. Registered on December 3, 2023.

Adaptive Bayesian information borrowing methods for finding and optimizing subgroup-specific doses

In precision oncology, integrating multiple cancer patient subgroups into a single master protocol allows for the simultaneous assessment of treatment effects in these subgroups and promotes the sharing of information between them, ultimately reducing sample sizes and costs and enhancing scientific validity. However, the safety and efficacy of these therapies may vary across different subgroups, resulting in heterogeneous outcomes. Therefore, identifying subgroup-specific optimal doses in early-phase clinical trials is crucial for the development of future trials. In this article, we review various innovative Bayesian information-borrowing strategies that aim to determine and optimize subgroup-specific doses. Specifically, we discuss Bayesian hierarchical modeling, Bayesian clustering, Bayesian model averaging or selection, pairwise borrowing, and other relevant approaches. By employing these Bayesian information-borrowing methods, investigators can gain a better understanding of the intricate relationships between dose, toxicity, and efficacy in each subgroup. This increased understanding significantly improves the chances of identifying an optimal dose tailored to each specific subgroup. Furthermore, we present several practical recommendations to guide the design of future early-phase oncology trials involving multiple subgroups when using the Bayesian information-borrowing methods.

Methodological Development of Combination Drug and Radiotherapy in Basic and Clinical Research

Newer technical improvements in radiation oncology have been rapidly implemented in recent decades, allowing an improved therapeutic ratio. The development of strategies using local and systemic treatments concurrently, mainly targeted therapies, has however plateaued. Targeted molecular compounds and immunotherapy are increasingly being incorporated as the new standard of care for a wide array of cancers. A better understanding of possible prior methodology issues is therefore required and should be integrated into upcoming early clinical trials including individualized radiotherapy-drug combinations. The outcome of clinical trials is influenced by the validity of the preclinical proofs of concept, the impact on normal tissue, the robustness of biomarkers and the quality of the delivery of radiation. Herein, key methodological aspects are discussed with the aim of optimizing the design and implementation of future precision drug-radiotherapy trials.