Using Bayesian statistics in confirmatory clinical trials in the regulatory setting: a tutorial review.

Bayesian statistics plays a pivotal role in advancing medical science by enabling healthcare companies, regulators, and stakeholders to assess the safety and efficacy of new treatments, interventions, and medical procedures. The Bayesian framework offers a unique advantage over the classical framework, especially when incorporating prior information into a new trial with quality external data, such as historical data or another source of co-data. In recent years, there has been a significant increase in regulatory submissions using Bayesian statistics due to its flexibility and ability to provide valuable insights for decision-making, addressing the modern complexity of clinical trials where frequentist trials are inadequate. For regulatory submissions, companies often need to consider the frequentist operating characteristics of the Bayesian analysis strategy, regardless of the design complexity. In particular, the focus is on the frequentist type I error rate and power for all realistic alternatives. This tutorial review aims to provide a comprehensive overview of the use of Bayesian statistics in sample size determination, control of type I error rate, multiplicity adjustments, external data borrowing, etc., in the regulatory environment of clinical trials. Fundamental concepts of Bayesian sample size determination and illustrative examples are provided to serve as a valuable resource for researchers, clinicians, and statisticians seeking to develop more complex and innovative designs.

A flexible dose-response modeling framework based on continuous toxicity outcomes in phase I cancer clinical trials.

BACKGROUND: The past few decades have seen remarkable developments in dose-finding designs for phase I cancer clinical trials. While many of these designs rely on a binary toxicity response, there is an increasing focus on leveraging continuous toxicity responses. A continuous toxicity response pertains to a quantitative measure represented by real numbers. A higher value corresponds not only to an elevated likelihood of side effects for patients but also to an increased probability of treatment efficacy. This relationship between toxicity and dose is often nonlinear, necessitating flexibility in the quest to find an optimal dose. METHODS: A flexible, fully Bayesian dose-finding design is proposed to capitalize on continuous toxicity information, operating under the assumption that the true shape of the dose-toxicity curve is nonlinear. RESULTS: We conduct simulations of clinical trials across varying scenarios of non-linearity to evaluate the operational characteristics of the proposed design. Additionally, we apply the proposed design to a real-world problem to determine an optimal dose for a molecularly targeted agent. CONCLUSIONS: Phase I cancer clinical trials, designed within a fully Bayesian framework with the utilization of continuous toxicity outcomes, offer an alternative approach to finding an optimal dose, providing unique benefits compared to trials designed based on binary toxicity outcomes.

Clinical Outcomes in Dogs Undergoing Cholecystectomy via a Transverse Incision: A Meta-Analysis of 121 Animals Treated between 2011 and 2021.

Although many studies have been conducted on the use of median and transverse incisions in various surgeries in the field of human medicine, related studies in veterinary medicine are lacking. This study aimed to present treatment options for dogs requiring cholecystectomy by reporting the pros and cons of 121 cholecystectomies performed via transverse incision at our hospital over 10 years. In most included cases, nonelective cholecystectomy was performed in an unstable emergency situation. The perioperative mortality rate was 23.14%, which was not significantly different from that of cholecystectomy performed via the conventional midline approach. However, the overall operation time (46.24 ± 6.13 min; range 35-65 min) was shortened by securing an adequate surgical field of view. The transverse incision approach facilitates fast and accurate surgery without increasing the fatality rate in small-breed dogs, in whom securing an adequate surgical field of view is difficult. Thus, transverse incision should be actively considered in dogs undergoing cholecystectomy due to emergency conditions, such as bile leakage or biliary tract obstruction, since prolonged anesthesia can be burdensome. This study may improve cholecystectomy outcomes in small-breed dogs with difficult-to-secure surgical fields.

Factors Affecting the Outcome of Medical Treatment in Cats with Obstructive Ureteral Stones Treated with Tamsulosin: 70 Cases (2018-2022).

The incidence of diseases associated with feline ureteral obstruction is increasing; however, non-surgical treatment options are limited. This study evaluated the outcome of medical treatment in cats with obstructive ureteral stones treated with tamsulosin and identified potential factors predicting spontaneous stone passage. We retrospectively reviewed 70 client-owned cats treated at the Western Referral Animal Medical Center, Seoul, Korea, from 2018 to 2022. All the cats had obstructive ureterolithiasis and were treated using tamsulosin. The baseline characteristics of the cats, stone diameter and location, and stone passage outcomes were analyzed. Stone passage occurred in 22 cats; the remaining 48 cats showed no change in stone locations. Sex, creatinine, and diameter and location of stones were potential risk factors associated with successful stone passage, but age, weight, and side of the stone were not. No serious adverse events related to tamsulosin treatment were observed. This is the first study to identify the risk factors predictive of the spontaneous stone passage of cats with obstructive ureterolithiasis after tamsulosin treatment. Tamsulosin could be an alternative treatment for ureteral obstruction in male cats with smaller distal ureteral stones and low baseline serum creatinine levels. These findings could help develop guidelines for treating feline ureterolithiasis.

Optimization of dose selection using multiple surrogates of toxicity as a continuous variable in phase I cancer trial.

In phase I trials, it is the top priority of clinicians to effectively treat patients and minimize the chance of exposing them to subtherapeutic and overly toxic doses, while exploiting patient information. Motived by this practical consideration, we revive the one parameter linear dose-finder developed in 1970s to accommodate a continuous toxicity response in the phase I cancer clinical trials, which is called the two parameters linear dose-finder (2PLD). The 2PLD is a fully Bayesian model that assumes a linear relationship between toxicity response and dose. We suggest a dose search algorithm based on the 2PLD to exploit the grades of toxicities from multiple adverse events to align with Common Toxicity Criteria for Adverse Events provided by the National Cancer Institute. The proposed search procedure suggests an optimal dose to each patient by using accrued patients' information while controlling the posterior probability of overdose. The heterogeneity of patients in dose reaction is addressed by making a fully Bayesian inference about the standard deviation of toxicity responses. The 2PLD can be an attractive tool for clinical scientists due to its parsimonious description of a toxicity-dose curve and medical interpretation as well as an automatic posterior computation. We illustrate the performance of this design using simulation data to identify the maximum tolerated dose.

Directionally dependent multi-view clustering using copula model.

Recent developments in high-throughput methods have resulted in the collection of high-dimensional data types from multiple sources and technologies that measure distinct yet complementary information. Integrated clustering of such multiple data types or multi-view clustering is critical for revealing pathological insights. However, multi-view clustering is challenging due to the complex dependence structure between multiple data types, including directional dependency. Specifically, genomics data types have pre-specified directional dependencies known as the central dogma that describes the process of information flow from DNA to messenger RNA (mRNA) and then from mRNA to protein. Most of the existing multi-view clustering approaches assume an independent structure or pair-wise (non-directional) dependence between data types, thereby ignoring their directional relationship. Motivated by this, we propose a biology-inspired Bayesian integrated multi-view clustering model that uses an asymmetric copula to accommodate the directional dependencies between the data types. Via extensive simulation experiments, we demonstrate the negative impact of ignoring directional dependency on clustering performance. We also present an application of our model to a real-world dataset of breast cancer tumor samples collected from The Cancer Genome Altas program and provide comparative results.

Estimation of COVID-19 spread curves integrating global data and borrowing information.

Currently, novel coronavirus disease 2019 (COVID-19) is a big threat to global health. The rapid spread of the virus has created pandemic, and countries all over the world are struggling with a surge in COVID-19 infected cases. There are no drugs or other therapeutics approved by the US Food and Drug Administration to prevent or treat COVID-19: information on the disease is very limited and scattered even if it exists. This motivates the use of data integration, combining data from diverse sources and eliciting useful information with a unified view of them. In this paper, we propose a Bayesian hierarchical model that integrates global data for real-time prediction of infection trajectory for multiple countries. Because the proposed model takes advantage of borrowing information across multiple countries, it outperforms an existing individual country-based model. As fully Bayesian way has been adopted, the model provides a powerful predictive tool endowed with uncertainty quantification. Additionally, a joint variable selection technique has been integrated into the proposed modeling scheme, which aimed to identify possible country-level risk factors for severe disease due to COVID-19.

Continuous electrolytic decarbonation and recovery of a carbonate salt solution from a metal-contaminated carbonate solution.

This work studied the characteristic changes of a continuous electrolytic decarbonation and recovery of a carbonate salt solution from a metal-contaminated carbonate solution with changes of operational variables in an electrolytic system which consisted of a cell-stacked electrolyzer equipped with a cation exchange membrane and a gas absorber. The system could completely recover the carbonate salt solution from a uranyl carbonato complex solution in a continuous operation. The cathodic feed rate could control the carbonate concentration of the recovered solution and it affected the most transient pH drop phenomenon of a well type within the gas absorber before a steady state was reached, which caused the possibility of a CO(2) gas slip from the gas absorber. The pH drop problem could be overcome by temporarily increasing the OH(-) concentration of the cathodic solution flowing down within the gas absorber only during the time required for a steady state to be obtained in the case without the addition of outside NaOH. An overshooting peak of the carbonate concentration in the recovered solution before a steady state was observed, which was ascribed to the decarbonation of the initial solution filled within the stacked cells by a redundant current leftover from the complete decarbonation of the feeding carbonate solution.

Precipitation characteristics of uranyl ions at different pHs depending on the presence of carbonate ions and hydrogen peroxide.

This work studied the dissolution of uranium dioxide and precipitation characteristics of uranyl ions in alkaline and acidic solutions depending on the presence of carbonate ions and H2O2 in the solutions at different pHs controlled by adding HNO3 or NaOH in the solution. The chemical structures of the precipitates generated in different conditions were evaluated and compared by using XRD, SEM, TG-DT, and IR analyses together. The sizes and forms of the precipitates in the solutions were evaluated, as well. The uranyl ions were precipitated in the various forms, depending on the solution pH and the presences of hydrogen peroxide and carbonate ions in the solution. In a 0.5 M Na2CO3 solution with H2O2, where the uranyl ions formed mixed uranyl peroxy-carbonato complexes, the uranyl ions were precipitated as a uranium peroxide of UO4(H20)4 at pH 3-4, and precipitated as a clarkeite of Na2U2Ox(OH)y(H2O)z above pH 13. In the same carbonate solution without H2O2, where the uranyl ions formed uranyl tris-carbonato complex, the uranyl ions were observed to be precipitated as a different form of clarkeite above pH 13. The precipitate of uranyl ions in a nitrate solution without carbonate ions and H2O2 at a high pH were studied together to compare the precipitate forms in the carbonate solutions.