Professional health of instructor-officers with different service experience.

Objective: Aim: To investigate the levels and indicators of professional deformation in instructor-officers with different service experience as a negative factor in their professional health.

Patients And Methods: Materials and Methods: The research, which was conducted in 2022-2023, involved 136 instructor-officers of the National Academy of Internal Affairs aged 25-55 years with different service experience (up to 5 years - 21 people, 5-10 years - 45 people, 10-15 years - 42 people, over 15 years - 28 people).

Results: Results: The dynamics of the levels of professional deformation in instructor-officers of higher educational institutions depending on the experience of their service activities have been determined, and the peculiarities of the manifestation of key professional and psychological indicators that affect their professional health in the course of their service activities have been revealed.

Motivational orientations of students towards internet dependent behavior and measures for its prevention.

Objective: Aim: The aim is to study the motivation of students towards Internet dependent behavior and develop practical recommendations for improving a set of measures for its prevention.

Patients And Methods: Materials and Methods: The research involved 154 students of the National Academy of Internal Affairs. Research methods: analysis and generalization of literature sources, questionnaire, statistical methods.

Tumor-Agnostic Approvals: Insights and Practical Considerations.

Since the first approval of a tumor-agnostic indication in 2017, a total of seven tumor-agnostic indications involving six drugs have received approval from the FDA. In this paper, the master protocol subteam of the Statistical Methods in Oncology Scientific Working Group, Biopharmaceutical Session, American Statistical Association, provides a comprehensive summary of these seven tumor-agnostic approvals, describing their mechanisms of action; biomarker prevalence; study design; companion diagnostics; regulatory aspects, including comparisons of global regulatory requirements; and health technology assessment approval. Also discussed are practical considerations relating to the regulatory approval of tumor-agnostic indications, specifically (i) recommendations for the design stage to mitigate the risk that exceptions may occur if a treatment is initially hypothesized to be effective for all tumor types and (ii) because drug development continues after approval of a tumor-agnostic indication, recommendations for further development of tumor-specific indications in first-line patients in the setting of a randomized confirmatory basket trial, acknowledging the challenges in this area.

Statistical Considerations on the Use of RWD/RWE for Oncology Drug Approvals: Overview and Lessons Learned.

Despite increasing utilization of real-world data (RWD)/real-world evidence (RWE) in regulatory submissions, their application to oncology drug approvals has seen limited success. Real-world data is most commonly summarized as a benchmark control for a single arm study or used to augment the concurrent control in a randomized clinical trial (RCT). While there has been substantial research on usage of RWD/RWE, our goal is to provide a comprehensive overview of their use in oncology drug approval submissions to inform future RWD/RWE study design.

Statistical and Operational Considerations for 2-Stage Adaptive Designs with Simultaneous Evaluation of Overall and Marker-Selected Populations in Oncology Confirmatory Trials.

In biomarker enrichment study designs that start with an all-comer population, simultaneous evaluation of the entire and the marker-selected populations can be more desirable than pre-specifying the testing order, when the degree of marker predictiveness is uncertain. While there has been substantial research on this approach, our goal is to provide a complete overview and guidance in all aspects of this approach, including the interim analysis potentially using different endpoints, combination tests with associated multiplicity control, and the final treatment effect estimation. Regulatory/operational aspects and actual cases demonstrating the potential advantage of this approach are also described.

Accuracy and Safety of Novel Designs for Phase I Drug-Combination Oncology Trials.

Despite numerous innovative designs having been published for phase I drug-combination dose finding trials, their use in real applications is rather limited. As a working group under the American Statistical Association Biopharmaceutical Section, our goal is to identify the unique challenges associated with drug combination, share industry's experiences with combination trials, and investigate the pros and cons of the existing designs. Toward this goal, we review seven existing designs and distinguish them based on the criterion of whether their primary objectives are to find a single maximum tolerated dose (MTD) or the MTD contour (i.

Sources of Safety Data and Statistical Strategies for Design and Analysis: Transforming Data Into Evidence.

Background: Safety evaluation is a key aspect of medical product development. It is a continual and iterative process requiring thorough thinking, and dedicated time and resources.

Methods: In this article, we discuss how safety data are transformed into evidence to establish and refine the safety profile of a medical product, and how the focus of safety evaluation, data sources, and statistical methods change throughout a medical product's life cycle.

Sources of Safety Data and Statistical Strategies for Design and Analysis: Clinical Trials.

Background: There has been an increased emphasis on the proactive and comprehensive evaluation of safety endpoints to ensure patient well-being throughout the medical product life cycle. In fact, depending on the severity of the underlying disease, it is important to plan for a comprehensive safety evaluation at the start of any development program. Statisticians should be intimately involved in this process and contribute their expertise to study design, safety data collection, analysis, reporting (including data visualization), and interpretation.

Sources of Safety Data and Statistical Strategies for Design and Analysis: Real World Insights.

Background: Although randomized controlled clinical trials provide necessary information and serve as the basis for regulatory decision making, a significant gap exists between the evidence these trials provide and what the biomedical community needs. It is recognized that a wealth of data are routinely collected outside clinical trials. Such real-world data (RWD) are not of comparable quality, it does not have similar immunity from bias and confounding as data collected in randomized clinical trials, but it might offer additional understanding of the benefit-risk, provide new insights to different stakeholders, and aid in regulatory decision making.

Bridging data across studies using frequentist and Bayesian estimation.

In drug development programs, an experimental treatment is evaluated across different populations and/or disease types using multiple studies conducted in countries around the world. In order to show the efficacy and safety in a specific population, a bridging study may be required. There are therapeutic areas for which enrolling patients to a trial is very challenging.

Comparing oncology clinical programs by use of innovative designs and expected net present value optimization: Which adaptive approach leads to the best result?

Designing an oncology clinical program is more challenging than designing a single study. The standard approaches have been proven to be not very successful during the last decade; the failure rate of Phase 2 and Phase 3 trials in oncology remains high. Improving a development strategy by applying innovative statistical methods is one of the major objectives of a drug development process.

Joint modeling of time to recurrence and cancer stage at recurrence in oncology trials.

This research was motivated by a clinical trial with bladder cancer patients who went through a surgery and were followed up for cancer recurrence. One of the main objectives of the trial was to evaluate the time to cancer recurrence in patients in control and experimental groups. At the time of recurrence, the disease stage was also evaluated.

Practical designs for Phase I combination studies in oncology.

Phase I trials evaluating the safety of multidrug combinations are becoming more common in oncology. Despite the emergence of novel methodology in the area, it is rare that innovative approaches are used in practice. In this article, we review three methods for Phase I combination studies that are easy to understand and straightforward to implement.

Nine-year change in statistical design, profile, and success rates of Phase II oncology trials.

We investigated nine-year trends in statistical design and other features of Phase II oncology clinical trials published in 2005, 2010, and 2014 in five leading oncology journals: Cancer, Clinical Cancer Research, Journal of Clinical Oncology, Annals of Oncology, and Lancet Oncology. The features analyzed included cancer type, multicenter vs. single-institution, statistical design, primary endpoint, number of treatment arms, number of patients per treatment arm, whether or not statistical methods were well described, whether the drug was found effective based on rigorous statistical testing of the null hypothesis, and whether the drug was recommended for future studies.

Adaptive Design Applied to Identification of the Minimum Effective Dose in Schizophrenia: Simulations of Scientific and Commercial Value.

The International Society for CNS Clinical Trials and Methodology (ISCTM) Adaptive Design Working Group (IADWG) designed a case study simulation exercise to compare the value of traditional versus adaptive design approaches to phase II clinical trial design in schizophrenia in statistical and economic terms. Operational characteristics of both designs were compared across 7 likely dose-response curves. Based on IADWG members' recent research experience in schizophrenia, estimates of expected net present value (eNPV) for the molecule were compared for the traditional and adaptive designs.

Adaptive Clinical Trials: Overview of Early-Phase Designs and Challenges.

In this paper, we describe developments in adaptive design methodology and discuss implementation strategies and operational challenges in early phase adaptive clinical trials. The BATTLE trial - the first completed, biomarker-based, Bayesian adaptive randomized study in lung cancer - is presented as a case study to illustrate main ideas and share learnings.

Advances in Statistical Approaches Oncology Drug Development.

We describe some recent developments in statistical methodology and practice in oncology drug development from an academic and an industry perspective. Many adaptive designs were pioneered in oncology, and oncology is still at the forefront of novel methods to enable better and faster Go/No-Go decision making while controlling the cost.

Selection of hypothesis weights and ordering when testing multiple hypotheses in clinical trials.

This article discusses the problem of selecting free parameters of multiple testing procedures in confirmatory Phase III clinical trials with multiple objectives, including hypothesis weights and hypothesis ordering. We identify classes of multiple testing procedures that provide different interpretations of these parameters. This includes basic single-step procedures (Bonferroni procedure) that employ fixed hypothesis weights, as well as more powerful stepwise procedures (Holm, fallback, and chain procedures) that reweight the hypotheses during the testing process.

Improving Oncology Clinical Programs by Use of Innovative Designs and Comparing Them via Simulations.

The design of an oncology clinical program is much more challenging than the design of a single study. The standard approach has been proven to be not very successful during the past decade; the failure rate of phase 3 studies in oncology is about 66%. Improving the development strategy by applying innovative statistical methods is one of the major objectives for study teams designing and supporting oncology clinical programs.