Gastrointestinal Acute Radiation Syndrome: Mechanisms, Models, Markers, and Medical Countermeasures.

There have been a number of reported human exposures to high dose radiation, resulting from accidents at nuclear power plants (e.g., Chernobyl), atomic bombings (Hiroshima and Nagasaki), and mishaps in industrial and medical settings.

Quantitative Brain Amyloid PET.

Since the development of amyloid tracers for PET imaging, there has been interest in quantifying amyloid burden in the brains of patients with Alzheimer disease. Quantitative amyloid PET imaging is poised to become a valuable approach in disease staging, theranostics, monitoring, and as an outcome measure for interventional studies. Yet, there are significant challenges and hurdles to overcome before it can be implemented into widespread clinical practice.

The impact of misclassification errors on the performance of biomarkers based on next-generation sequencing, a simulation study.

The development of next-generation sequencing (NGS) opens opportunities for new applications such as liquid biopsy, in which tumor mutation genotypes can be determined by sequencing circulating tumor DNA after blood draws. However, with highly diluted samples like those obtained with liquid biopsy, NGS invariably introduces a certain level of misclassification, even with improved technology. Recently, there has been a high demand to use mutation genotypes as biomarkers for predicting prognosis and treatment selection.

US FDA public meeting: identification of concepts and terminology for multicomponent biomarkers.

The US FDA convened a virtual public workshop with the goals of obtaining feedback on the terminology needed for effective communication of multicomponent biomarkers and discussing the diverse use of biomarkers observed across the FDA and identifying common issues. The workshop included keynote and background presentations addressing the stated goals, followed by a series of case studies highlighting FDA-wide and external experience regarding the use of multicomponent biomarkers, which provided context for panel discussions focused on common themes, challenges and preferred terminology. The final panel discussion integrated the main concepts from the keynote, background presentations and case studies, laying a preliminary foundation to build consensus around the use and terminology of multicomponent biomarkers.

Bayesian Sample Size Planning Tool for Phase I Dose-Finding Trials.

Purpose: Through Bayesian inference, we propose a method called BayeSize as a reference tool for investigators to assess the sample size and its associated scientific property for phase I clinical trials.

Methods: BayeSize applies the concept of effect size in dose finding, assuming that the maximum tolerated dose can be identified on the basis of an interval surrounding its true value because of statistical uncertainty. Leveraging a decision framework that involves composite hypotheses, BayeSize uses two types of priors, the fitting prior (for model fitting) and sampling prior (for data generation), to conduct sample size calculation under the constraints of statistical power and type I error.

A targeted simulation-extrapolation method for evaluating biomarkers based on new technologies in precision medicine.

New technologies for novel biomarkers have transformed the field of precision medicine. However, in applications such as liquid biopsy for early tumor detection, the misclassification rates of next generation sequencing and other technologies have become an unavoidable feature of biomarker development. Because initial experiments are usually confined to specific technology choices and application settings, a statistical method that can project the performance metrics of other scenarios with different misclassification rates would be very helpful for planning further biomarker development and future trials.

Perspectives on statistical strategies for the regulatory biomarker qualification process.

Qualification of a biomarker for use in a medical product development program requires a statistical strategy that aligns available evidence with the proposed context of use (COU), identifies any data gaps to be filled and plans any additional research required to support the qualification. Accumulating, interpreting and analyzing available data is outlined, step-by-step, illustrated by a qualified enrichment biomarker example and a safety biomarker in the process of qualification. The detailed steps aid requestors seeking qualification of biomarkers, allowing them to organize the available evidence and identify potential gaps.

Hi3 + 3: A model-assisted dose-finding design borrowing historical data.

Background: In phase I clinical trials, historical data may be available through multi-regional programs, reformulation of the same drug, or previous trials for a drug under the same class. Statistical designs that borrow information from historical data can reduce cost, speed up drug development, and maintain safety.

Purpose: Based on a hybrid design that partly uses probability models and partly uses algorithmic rules for decision making, we aim to improve the efficiency of the dose-finding trials in the presence of historical data, maintain safety for patients, and achieve a level of simplicity for practical applications.

Cutaneous Radiation Injuries: Models, Assessment and Treatments.

Many cases of human exposures to high-dose radiation have been documented, including individuals exposed during the detonation of atomic bombs in Hiroshima and Nagasaki, nuclear power plant disasters (e.g., Chernobyl), as well as industrial and medical accidents.

Recent advances in clinical trial design considerations in Thera"nostics".

Theranostics in drug development is an evolving framework, known as combining 'thera' (a therapeutic drug) with 'nostics' (a diagnostic imaging drug) and with the latter being mostly used to select patient for evaluation of safety and efficacy of an investigational therapeutics. However, when a diagnostic imaging drug is still investigational, patient selection performance of a nostics imaging has not been demonstrated. Clinical trials conducted to assess the effect of an investigational therapeutics in a theranostics setting may focus only on the therapeutics development and not necessarily require definitive truth standard or reference standard to also assess patient selection performance of an investigational diagnostic imaging drug.

The i3+3 design for phase I clinical trials.

The traditional rule-based design, 3 + 3, has been shown to be less likely to achieve the objectives of dose-finding trials when compared with model-based designs. We propose a new rule-based design called i3 + 3, which is based on simple but more advanced rules that account for the variabilities in the observed data. We compare the operating characteristics for the proposed i3 + 3 design with other popular phase I designs by simulation.

Commentary on "Applying CHW method to 2-in-1 design: gain or lose".

While 2-in-1 designs give a flexibility to make a clinical trial either an information generation Phase 2 trial or a full scale confirmatory Phase 3 trial, flexible sample size designs can naturally fit into the 2-in-1 design framework. This study is to show that the CHW design can be blended into a 2-in-1 design to improve the adaptive performance of the design. Commenting on the usual 2-in-1 design, we demonstrated that the CHW design can achieve the goal of a 2-in-1 design with satisfactory statistical power and efficient average sample size for a targeted range of the treatment effect.

Evaluation of the extent of adaptation to sample size in clinical trials for cardiovascular and CNS diseases.

A planned adaptation to sample size in an ongoing trial aims at providing an opportunity to modify design assumptions made at the trial planning stage. Reassessment of sample size in an ongoing trial may be performed in a non-comparative or a comparative fashion, either with or without use of external data that surface. We review the completed new drug applications (NDAs) and biologic license applications (BLAs) submitted since 2000 to cardio-renal, neurology and psychiatry drug products divisions of Center for Drug Evaluation and Research, U.

A Bayesian interval dose-finding design addressingOckham's razor: mTPI-2.

There has been an increasing interest in using interval-based Bayesian designs for dose finding, one of which is the modified toxicity probability interval (mTPI) method. We show that the decision rules in mTPI correspond to an optimal rule under a formal Bayesian decision theoretic framework. However, the probability models in mTPI are overly sharpened by the Ockham's razor, which, while in general helps with parsimonious statistical inference, leads to undesirable decisions from safety perspective.

Treatment effect heterogeneity for univariate subgroups in clinical trials: Shrinkage, standardization, or else.

Treatment effect heterogeneity is a well-recognized phenomenon in randomized controlled clinical trials. In this paper, we discuss subgroup analyses with prespecified subgroups of clinical or biological importance. We explore various alternatives to the naive (the traditional univariate) subgroup analyses to address the issues of multiplicity and confounding.

An integrated dose-finding tool for phase I trials in oncology.

In the past 25 years, the 3+3 design has been the most popular approach for planning phase I dose-finding trials in oncology. During the same time period, major development of more efficient model-based designs has been made by statistical researchers aiming to improve the clinical practice of dose finding in oncology. Despite the effort, 3+3 is still the most frequently used designs in practice.

Statistical challenges in a regulatory review of cardiovascular and CNS clinical trials.

There are several challenging statistical problems identified in the regulatory review of large cardiovascular (CV) clinical outcome trials and central nervous system (CNS) trials. The problems can be common or distinct due to disease characteristics and the differences in trial design elements such as endpoints, trial duration, and trial size. In schizophrenia trials, heavy missing data is a big problem.

Multiplicity in confirmatory clinical trials: a case study with discussion from a JSM panel.

An invited panel session was conducted in the 2012 Joint Statistical Meetings, San Diego, California, USA, to stimulate the discussion on multiplicity issues in confirmatory clinical trials for drug development. A total of 11 expert panel members were invited and 9 participated. Prior to the session, a case study was previously provided to the panel members to facilitate the discussion, focusing on the key components of the study design and multiplicity.