Considerations for master protocols using external controls

The aim of this review was to highlight why the use of master protocols trial design is particularly useful for radiotherapy intervention trials where complex setup pathways (including quality assurance, user training, and integrating multiple modalities of treatment) may hinder clinical advances. We carried out a systematic review according to Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, reviewing the findings using a landscape analysis. Results were summarized descriptively, reporting on trial characteristics highlighting the benefits, limitations, and challenges of developing and implementing radiotherapy master protocols, with three case studies selected to explore these issues in more detail. Twelve studies were suitable for inclusion (4 platform trials, 3 umbrella trials, and 5 basket trials), evaluating a mix of solid tumor sites in both curative and palliative settings. The interventions were categorized into 1) novel agent and radiotherapy combinations; 2) radiotherapy dose personalization; and 3) device evaluation, with a case study provided for each intervention. Benefits of master protocol trials for radiotherapy intervention include protocol efficiency for implementation of novel radiotherapy techniques; accelerating the evaluation of novel agent drug and radiotherapy combinations; and more efficient translational research opportunities, leading to cost savings and research efficiency to improve patient outcomes. Master protocols offer an innovative platform under which multiple clinical questions can be addressed within a single trial. Due to the complexity of radiotherapy trial setup, cost and research efficiency savings may be more apparent than in systemic treatment trials. Use of this research approach may be the change needed to push forward oncological innovation within radiation oncology.

Cancer medicine continues to evolve into a more molecularly based discipline with many new treatments being developed aimed at specific cancer-related pathways and genetic alterations. In order to meet the challenges of the evolving science, new clinical trial designs and approaches for treatment trials are needed to evaluate the promise of these potential therapies. The National Cancer Institute (NCI) with the national NCI Clinical Trials Network (NCTN) Groups will launch two clinical research initiatives in lung cancer in 2014 that demonstrate innovative approaches to the design and conduct of clinical trials. The first initiative is the ALCHEMIST trial (Adjuvant Lung Cancer Enrichment Marker Identification and Sequencing Trial) which is aimed at patients with lung adenocarcinoma that has been entirely removed by surgery. In this study, samples of tumor tissue from thousands of patients will be tested for two specific genetic alterations, one in the EGFR gene, and the other in the ALK gene. These alterations are not common; about 10% of the lung cancer patient population in the US will have tumors with alterations in the EGFR gene and 5% will have alterations in the ALK gene. Rather than conduct a single trial for each alteration, the screening component of the ALCHEMIST trial will screen patients for both alterations at the same time. The ALCHEMIST is connected to 2 specific NCI-supported NCTN Group clinical treatment trials that are each testing a targeted agent specific for one of the alterations in conjunction with adjuvant therapy. Patients found to have tumors containing one of the alterations will be offered enrollment onto the appropriate clinical treatment trial. Every patient in the ALCHEMIST trial, including those without an EGFR or ALK alteration, will also be studied for cancer risk characteristics and their tumor tissue will be analyzed in a research genomics initiative conducted by the NCI Center for Cancer Genomics (CCG). This effort will employ next-generation sequencing technology to capitalize on the foundation of the CCG's earlier effort, the Cancer Genome Atlas. The second initiative, the Advanced Squamous Cell Carcinoma Lung Master Protocol, is a public-private effort made possible through collaboration with stakeholders including the NCI, NCTN Groups, FDA, NIH Foundation, the Friends of Cancer patient advocacy group, and the pharmaceutical industry. By pooling resources to screen tumor samples from about a thousand patients per year with advanced squamous cell carcinoma for multiple genetic alterations, this master protocol will enable several, randomized, phase II clinical trials with promising new agents to take place in parallel within a single study management framework. Agents will be evaluated rapidly and either be further evaluated in a phase III clinical trial or replaced by other new agents for phase II evaluation, without having to develop individual trials de novo each time. Compared with the usual process of developing clinical trials, these two new design approaches will hopefully allow more patients to be enrolled in trials with agents targeted for important molecular characteristics specific for their tumors and the trials will yield clinically useful results more rapidly. Citation Format: Margaret M. Mooney, Jack Welch, Jeffrey S. Abrams. Clinical trial design and master protocols in NCI clinical treatment trials. [abstract]. In: Proceedings of the AACR-IASLC Joint Conference on Molecular Origins of Lung Cancer; 2014 Jan 6-9; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2014;20(2Suppl):Abstract nr IA08.

This article discusses and compares statistical designs of basket trial, from both frequentist and Bayesian perspectives. Baskets trials are used in oncology to study interventions that are developed to target a specific feature (often genetic alteration or immune phenotype) that is observed across multiple tissue types and/or tumor histologies. Patient heterogeneity has become pivotal to the development of non-cytotoxic treatment strategies. Treatment targets are often rare and exist among several histologies, making prospective clinical inquiry challenging for individual tumor types. More generally, basket trials are a type of master protocol often used for label expansion. Master protocol is used to refer to designs that accommodates multiple targets, multiple treatments, or both within one overarching protocol. For the purpose of making sequential decisions about treatment futility, Simon’s two-stage design is often embedded within master protocols. In basket trials, this frequentist design is often applied to independent evaluations of tumor histologies and/or indications. In the tumor agnostic setting, rarer indications may fail to reach the sample size needed for even the first evaluation for futility. With recent innovations in Bayesian methods, it is possible to evaluate for futility with smaller sample sizes, even for rarer indications. Novel Bayesian methodology for a sequential basket trial design based on predictive probability is introduced. The Bayesian predictive probability designs allow interim analyses with any desired frequency, including continual assessments after each patient observed. The sequential design is compared with and without Bayesian methods for sharing information among a collection of discrete, and potentially non-exchangeable tumor types. Bayesian designs are compared with Simon’s two-stage minimax design.

Contemporary advances in the understanding of the molecular and immunologic basis of metastatic lung cancer have firmly changed its treatment paradigm to a personalized, biomarker-driven approach. However, the majority of lung-cancer patients [especially lung squamous cell carcinoma (LUSC)] still do not have effective targeted therapeutic options. Master protocols, such as Lung-MAP, represent an innovative clinical trial approach designed to accelerate evaluation of novel biomarker-driven therapies. Lung-MAP is an umbrella trial for advanced LUSC and has been active since 2014. Cumulative experience from this overarching, multi-institution master protocol has demonstrated that centralized, real-time biomarker screening is feasible and substudy modularity is essential for protocol adaptability in a rapidly changing treatment landscape. In addition, screening and efficacy results from Lung-MAP affirm that LUSC has several putative drivers but remains difficult to effectively treat with targeted therapy. Master protocols are a feasible and efficient approach for evaluating biomarker-driven therapies in lung cancer. As we begin to target less common genomic and immunotherapy subtypes, centrally coordinated clinical trial designs such as Lung-MAP are necessary to rapidly deliver effective therapies to patients, whereas also maximizing the quality of research data obtained.

Master protocols in clinical trials: a universal Swiss Army knife?


 Advancements in genomic and precision medicine have changed the way oncology clinical trials are designed. Compared to the traditional single tumour-based trial, master protocols, which are often classified as basket, umbrella, or platform trials, conduct studies on multiple subgroups under a single overarching protocol.
 This paper summarizes the discussion held during CADTH’s second webinar, which examined issues around health technology assessment of evidence generated using these trial designs.
 In this workshop, several experts were invited to present on the clinical, health economic, patient value, and ethical aspects associated with these new study designs. The discussion section of this paper summarizes the major points raised by the presenters, as well as questions from the audience and answers from the presenters.

In this chpater, we review the standards and guidelines for adaptive trial designs and master protocols. Methodological rigour and transparent reporting are required in all clinical trials. Adaptive trial designs and master protocols are no exception. The standard reporting guidelines and risk-of-bias assessments for conventional trials can be applied to adaptive trial designs and master protocols. Adaptive trial designs have pre-planned adaptations and analysis plans that are specified in a formal way that outline how the data will be used to guide the design. Planning of adaptive clinical trials, basket trials, umbrella trials, and platform trials will require early engagement with the stakeholders and methodologists to think through potential hurdles and challenges of the statistical design and its implementation.

In oncology drug development, indication selection and optimal dose identification are the primary objectives for the early phase of clinical trials and could significantly impact the probability of success. Master protocols, e.g., basket trial, umbrella trial, and platform trial, have become popular in practice considering the connection of trial designs with multiple indications and treatment candidates. They also enable the optimization of operational resources and maximize the capability of data-driven decision-making. However, most of the available designs are developed with the efficacy endpoint only for treatment effect estimation and testing, without consideration of the safety end point. Thus, it often lacks a comprehensive quantitative framework to allow optimal treatment selection, which could put future development at risk. We propose an optimal Bayesian platform trial design with multiple end points (PMED) to characterize the overall benefit-risk profile. The design is further extended to allow treatment and indication selection within and across arms, with continuous monitoring on multiple interim analyses for futility. In addition, we propose dynamic borrowing across arms to increase the efficiency and accuracy of estimation given the level of similarity across arms. A hierarchical hypothesis structure is utilized to achieve optimal indication and treatment combination selection by controlling family-wise error. Through simulation studies, we show that PMED is a robust design under the studied scenarios with superb power and controlled family-wise error rate.

BackgroundTo address the heterogeneity of response to therapies, the oncology field is moving toward precision medicine (PM), with therapy tailored to a patient‘s disease. Biomarker assessment is now critical when...

Statistical considerations of phase 3 umbrella trials allowing adding one treatment arm mid-trial

PURPOSEMaster protocols represent transformations, enabling multiple therapies or diseases under a single protocol. These designs streamline therapeutic development by reducing redundancies. Suited for evolving fields such as oncology and global emergencies such as the COVID-19 pandemic, master protocols have been exemplified by studies such as RECOVERY, Solidarity, and I-SPY 2, which accelerated effective treatment identification (with I-SPY 2 focused on molecular subtypes). Recent oncology examples, such as MORPHEUS, evaluate immunotherapy combinations with shared controls. Despite advantages, their application in early-phase oncology remains underutilized amid growing regulatory emphasis on randomization for robust evidence.METHODSUS Food and Drug Administration (FDA) Oncology Center of Excellence (OCE) initiatives, such as Project Optimus and Project FrontRunner, emphasize randomization in early-phase oncology trials. However, these initiatives pose challenges, including larger sample sizes, patient and physician reluctance to randomization, and high failure rates from poor accrual. To address these, this article adapts master protocol designs to consolidate early-phase trials for novel therapeutics sharing a common backbone therapy, integrating hybrid controls from published standard-of-care data to minimize randomization to the control arm.RESULTSBy consolidating trials under a shared standard-of-care control arm, the proposed master protocol design reduces total sample size by as much as 55% when compared with independent trials (with control arm sizes 2.4-2.9 times lower), lowers costs and duration, and enhances enrollment through reduced randomization to controls. Incorporating hybrid controls from prior studies and sharing information among arms with common background standard-of-care further improve efficiency, increasing power (reaching 90% overall) while controlling type I error rates acceptable levels.CONCLUSIONMaster protocol designs with hybrid controls and Bayesian information sharing enable the efficient integration of randomization into early-phase oncology trials, enhancing efficiency, cost-effectiveness, and patient-centricity while aligning with FDA OCE initiatives.

MotivationPlatform designs - master protocols that allow for new treatment arms to be added over time - have gained considerable attention in recent years. Between 2001 and 2019, 16 platform trials were initiated globally. The COVID-19 pandemic seems to have provided a new motivation for these designs. We conducted a rapid review to quantify and describe platform trials used in COVID-19. MethodsWe cross-referenced PubMed, ClinicalTrials.gov, and the Cytel COVID-19 Clinical Trials Tracker to identify platform trials, defined by their stated ability to add future arms. ResultsWe identified 58 COVID-19 platform trials globally registered between January 2020 and May 2021. According to trial registries, 16 trials have added new therapies (median 3, IQR 4) and 11 have dropped arms (median 3, IQR 2.5). About 50% of trials publicly share their protocol, and 31 trials (53%) intend to share trial data. Forty-nine trials (84%) explicitly report adaptive features, and 21 trials (36%) state Bayesian methods. ConclusionsDuring the pandemic, there has been a surge in the number of platform trials compared to historical use. While transparency in statistical methods and clarity of data sharing policies needs improvement, platform trials appear particularly well-suited for rapid evidence generation. Trials secured funding quickly and many succeeded in adding new therapies in a short time period, thus demonstrating the potential for these trial designs to be implemented beyond the pandemic. The evidence gathered here may provide ample insight to further inform operational, statistical, and regulatory aspects of future platform trial conduct.

Introduction: Differentiation between glioma grade 2 and 3 was performed based on histological findings. The current grade is an important prognostic factor due to its widespread use, economic efficiency, and data accumulation, but analog elements remain and the genetic marker is unknown. The concept of Lower-grade glioma including G2/3 is spreading. On the other hand, WHO grade is the criteria of clinical trials, and evidence is established for G2 with low risk and high risk, G3 alone or with G4. In Japan, JCOG 1303 and 1016 have been implemented for high-risk G2 and G3, respectively and will be finished next year. Therefore, we examined the feasibility and design of novel clinical trial for patients with grade 2/3 glioma. Method: With reference to clinical trials of high evidence level and public database registration, we researched trials, arms, and designs for each of 3 genotypes, oligodendroglioma (OD), astrocytoma IDH mutant and IDH wild (A-IDHm, A-IDHw). Results: The standard arm common to all genotypes is follow-up (EORTC22845) for G2 low-risk, and chemoradiotherapy (CRT) for G3. Standard arm for G2 high risk, depending on a genotype, is follow-up (EORTC22845), radiation alone (A-IDHm and IDHw, A-IDHw: RTOG9802 subanalysis), or PCV chemoradiotherapy (OD and A-IDHm: 9802). Furthermore, the standard arm and the test arm were replaced by the matrix-like method on each genotype. Results in the G2/3-targeted trial, there was no standard arm all in the three genotypes. In addition, there were a design of master protocols for many genotype and a design that has arms of randomization and observation. Conclusion: Applying the master protocol, the possibility of novel G2/3 target trial in which the arms existing in MATRIX form was suggested. With the improvement of the genetic analysis infrastructure, prospective observational research and a well-designed intervention research plan for each genotype are required.

Oncology clinical trials are undergoing transformation to evaluate targeted therapies addressing a wider variety of biologically defined cancer subgroups. Multiarm basket and umbrella trials conducted under master protocols have become more prominent mechanisms for the clinical evaluation of promising new biologically driven anticancer therapies that are integral to precision oncology medicine. These new trial designs permit efficient clinical evaluation of multiple therapies in a variety of histologically and biologically defined cancers. These complex trials require extensive planning and attention to many factors, including choice of biomarker assay platform, mechanism for processing clinicopathologic and biomarker data to assign patients to substudies, and statistical design, monitoring, and analysis of substudies. Trial teams have expanded to include expertise in the interface between biology, clinical oncology, bioinformatics, and statistics. Strategies for the design, conduct, and analysis of these complex trials will continue to evolve to meet new challenges and opportunities in precision oncology medicine.

Randomized clinical trials are considered the milestones of clinical research in oncology, and guided the development and approval of new compounds so far. In the last few years, however, molecular and genomic profiling led to a change of paradigm in therapeutic algorithms of many cancer types, with the spread of different biomarker-driven therapies (or targeted therapies). This scenario of “personalized medicine” revolutionized therapeutic strategies and the methodology of the supporting clinical research. New clinical trial designs are emerging to answer to the unmet clinical needs related to the development of these targeted therapies, overcoming the “classical” structure of randomized studies. Innovative trial designs able to evaluate more than one treatment in the same group of patients or many groups of patients with the same treatment (or both) are emerging as a possible future standard in clinical trial methodology. These are identified as “master protocols”, and include umbrella, basket and platform trials. In this review, we described the main characteristics of these new trial designs, focusing on the opportunities and limitations of their use in the era of personalized medicine.