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. These recommendations and practical considerations may provide insights for the future development of drugs for tumor-agnostic indications.

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. We will review examples of applications and summarize the strengths and weaknesses of each example identified by regulatory agencies. A few noteworthy case studies will be reviewed in detail. Operational aspects of RWD/RWE study design/analysis will be also discussed.

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.e., multiple MTDs). Numerical studies, based on either industry-specified fixed scenarios or randomly generated scenarios, are performed to assess their relative accuracy, safety, and ease of implementation. We show that the algorithm-based 3+3 design has poor performance and often fails to find the MTD. The performance of model-based combination trial designs is mixed: some demonstrate high accuracy of finding the MTD but poor safety, while others are safe but with compromised identification accuracy. In comparison, the model-assisted designs, such as BOIN and waterfall designs, have competitive and balanced performance in the accuracy of MTD identification and patient safety, and are also simple to implement, thus offering an attractive approach to designing phase I drug-combination trials. By taking into consideration the design's operating characteristics, ease of implementation and regulation, the need for advanced infrastructures, as well as the risk of regulatory acceptance, our paper offers practical guidance on the selection of a suitable dose-finding approach for designing future combination trials.

The value of microRNA-122 in the diagnosis of coronary heart disease

Funding Acknowledgements

Type of funding sources: None.

Background. Patients with ischemic heart diseases form the majority group of cardiac diseases. Studies on the roles and mechanisms of microRNAs taking part in cardiac pathophysiology have become the focus of research worldwide.

Purpose. To elucidate whether microRNAs could be markers of atherosclerotic lesions, and further explore the mechanism of microRNAs in ischemic heart diseases. 

Methods. In general, 40 patients were investigated in our Clinic. Blood tests, echocardiography (with two-dimensional speckle tracking echocardiography), ECG, coronary angiograms, microRNA detection were conducted. The patients were divided into two groups, i.e., a control group (Group A) without atherosclerotic lesion and a group with proven coronary artery disease (Group В). The data were analyzed using SPSS Statistics 20.0

Results. According to the level of circulating microRNA, a significant association between miR-122 and coronary artery lesion was identified (р=0.033). The results are shown in Figure 1. Besides, the positive moderate correlation was also revealed (r= 0.337, р=0.036). These data show miR-122 as a robust biomarker for predicting atherosclerosis lesions, and it plays certain role in pathogenesis of atherosclerosis.

Conclusion. Particularly, microRNA-122 fulfils the criteria of good biomarkers due to their key-role in severity assessment. The correlation between obtained coronary artery lesion results and epigenetic markers was found. The circulating microRNA has also improved the predictive power for diagnostics of ischemic heart disease, which is crucially important for patients and possible biochemical markers for control of treatment. Abstract Figure.

Statistical Issues and Recommendations for Clinical Trials Conducted During the COVID-19 Pandemic

Abstract-The COVID-19 pandemic has had and continues to have major impacts on planned and ongoing clinical trials. Its effects on trial data create multiple potential statistical issues. The scale of impact is unprecedented, but when viewed individually, many of the issues are well defined and feasible to address. A number of strategies and recommendations are put forward to assess and address issues related to estimands, missing data, validity and modifications of statistical analysis methods, need for additional analyses, ability to meet objectives and overall trial interpretability.

[MULTI-FACTOR MODEL OF FINANCING PREVENTION AND TREATMENT OF DIROPHILARIOSIS (BASIC PRINCIPLES AND INDICATORS OF EFFICIENCY)]

The aim of the study was to substantiate the effectiveness and feasibility of the practical application of the multifactorial model of financing the prevention and treatment of dirofilariasis, its principles and methodological approaches. The basic principles of the multifactor model - an integrated approach, a combination of public and private financing, ensuring continuity of financing, discreteness of expenses; methodology for determining the effectiveness of the use of financial resources on the calculation of the return on costs for the prevention and treatment of dirofilariasis were justified. The effectiveness of local budget spending on the treatment of territories of the Kharkov region from mosquitoes on the base on the proposed principles and methodology was analyzed. As a result of the study, it has been proven the limited budgetary funds do not allow the implementation of long-term comprehensive programs for the prevention and treatment of dirofilariasis. The use of a multifactorial model of financing will allow overcoming budgetary constraints, significantly increasing the financial resources of the fight against dirofilariasis, optimizing the expenditures of state and local budgets, and ensuring targeted use of funds from the state, territorial communities, enterprises and the population.

[COMPARATIVE ANALYSIS OF THE COST OF TREATMENT OF ECHINOCOCCOSIS BY THERAPEUTIC AND SURGICAL METHODS (BASED ON THE STEP-DOWN METHODOLOGY)]

The aim of the study was to carry out a comparative economic analysis of the costs of therapeutic and surgical treatment of liver echinococcosis based on the developed methodological approaches and principles for calculating the cost of complex medical services in accordance with the «step-down» methodology. The model for calculating the cost of complex medical services for the treatment of echinococcosis was justified. The sum of costs of outpatient and inpatient units that directly provide medical care (direct costs) to the costs of support centers (indirect costs) was adjusted, which among simple medical services based on the chosen criterion were distributed. Calculation of costing items out on the basis of the direct-cost costing method was carried. Based on the proposed model, a comparative analysis of the cost of treatment of liver echinococcosis using therapeutic and surgical methods was carried out. As a result of the study, it was proved that the therapeutic method is less expensive than the surgical method. This is the basis to recommend it for wider use in medical practice, especially in cases when there is a problem of choosing the method of treatment of echinococcosis. Cost optimization is facilitated by a combination of surgical intervention and therapeutic treatment.

[THE ITERATIVE APPROACH TO PRICING LABORATORY SERVICES FOR THE PROVISION OF MEDICAL AID (COPROPROCYCOSOPHICAL EXAMINATION ON LYAMBLIOSIS)]

The purpose of the study was to substantiate the theoretical and methodical principles of pricing for laboratory services in the diagnosis of giardiasis, taking into account their iterability and peculiarities of parasitic research methods. The methods of laboratory study of gum disease of native smear, treated with Lyulol solution, and ether-formalin enrichment on the criteria of their quality and effectiveness are analyzed. On the basis of the study of the effectiveness of the first and repeated analyzes, the conclusion on the iterative nature of laboratory studies of giardiasis and the effectiveness of the use of an iterative approach to the determination of prices for laboratory services is substantiated. The approaches to pricing laboratories providing diagnostic services for giardiasis in Ukraine are analyzed. The necessity of applying the price trajectory for laboratory diagnosis of giardiasis on the basis of multiplicity of researches (interactive approach) and the determination of the minimum and maximum price levels (the minimax approach) is proved. The main factors of pricing for laboratory diagnostics of giardiasis are identified and characterized: iterative research, economic efficiency, social value, value for the patient, competitiveness and reputation.

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.

METHODS

In this manuscript, we review the challenges associated with the analysis of safety endpoints and describe the safety data that are available to influence the design and analysis of premarket clinical trials.

RESULTS

We share our recommendations for the statistical and graphical methodologies necessary to appropriately analyze, report, and interpret safety outcomes, and we discuss the advantages and disadvantages of safety data obtained from clinical trials compared to other sources.

CONCLUSIONS

Clinical trials are an important source of safety data that contribute to the totality of safety information available to generate evidence for regulators, sponsors, payers, physicians, and patients. This work is a result of the efforts of the American Statistical Association Biopharmaceutical Section Safety Working Group.

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. The oncology sub-team on Adaptive Program under the Drug Information Association Adaptive Design Scientific Working Group (DIA ADSWG) evaluated hypothetical oncology programs with two competing treatments and published the work in the Therapeutic Innovation and Regulatory Science journal in January 2014. Five oncology development programs based on different Phase 2 designs, including adaptive designs and a standard two parallel arm Phase 3 design were simulated and compared in terms of the probability of clinical program success and expected net present value (eNPV). In this article, we consider eight Phase2/Phase3 development programs based on selected combinations of five Phase 2 study designs and three Phase 3 study designs. We again used the probability of program success and eNPV to compare simulated programs. For the development strategies, we considered that the eNPV showed robust improvement for each successive strategy, with the highest being for a three-arm response adaptive randomization design in Phase 2 and a group sequential design with 5 analyses in Phase 3.

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. Because the stage of cancer at recurrence significantly impacts future treatment and patient prognosis of survival, analyzing the time to cancer recurrence and the stage at recurrence jointly provides more clinically relevant information than analyzing the time to recurrence alone. In this paper, we propose a stochastic model for the joint distribution of time to recurrence and cancer stage that (1) accounts for the recurrence caused by cancer cells surviving a treatment or a surgery and for the recurrence caused by spontaneous carcinogenesis, and (2) incorporates parameters that have biological meaning. To estimate the parameters, we use the maximum-likelihood method combined with the EM algorithm. To demonstrate the performance of our modeling, we evaluate the data from a clinical trial in patients with bladder cancer. We also use simulations to assess the sensitivity of the method.

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. Therefore, it is of interest to utilize the available historical information from previous studies. However, treatment effect may vary across different subpopulations/disease types; therefore, directly utilizing outcomes from historical studies may result in a biased estimation of treatment effect under investigation in the target trial. In this article, we propose novel approaches using both frequentist and Bayesian frameworks that allow borrowing information from historical studies while accounting for relevant patient's covariates via a propensity-based weighting. We evaluate the operating characteristics of the proposed methods in a simulation study and demonstrate that under certain conditions these methods may lead to improved estimation of a treatment effect.

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.

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. We demonstrate the operating characteristics of the designs through illustration in a single trial, as well as through extensive simulation studies, with the aim of increasing the use of novel approaches in Phase I combination studies. Design specifications and software capabilities are also discussed.

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.

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.

Using C60 fullerenes for photodynamic inactivation of mosquito iridescent viruses

This article describes the photodynamic inactivation of mosquito iridescent virus (MIV) Aedes flavescens in the presence of water-soluble C(60) fullerenes. It has been observed that the photodynamic inactivation of MIV for about 1 h reduces the infectious titre of the virus in large wax-moth larvae Galleria mellonella to 4.5 lg ID(50)/mL. The influence of the C(60) concentration on its anti-viral activity was tested in the concentration range from 1 to 0.001 mg/mL. It has been found that C(60) is able to inactivate the iridovirus even in low concentrations. Consequently, the findings of this work suggest that photoexcited C(60) fullerenes can be successfully used for the inactivation of iridoviruses in biological systems.

Molecule length-induced reentrant self-organization of alkanes in monolayers adsorbed on Au(111)

We report the observation by scanning tunneling microscopy of the reentrant self-organization of n-alkanes (C(n)H(2n+2)) in monolayers adsorbed on Au(111) induced by a variation of the chain length. In the investigated range of lengths ( 10</=n</=38 with even n values), the presence of self-assembled monolayers which consist of a close-packed arrangement of molecules lying flat on the surface is evidenced except for alkanes with 18</=n</=26. The unexpected transition between ordered and disordered phases is related to the mismatch between Au(111) lattice and the CH2-group period along the chain.