Accrual Suspensions in Seamless Phase II/III Trials: A Review of NRG Oncology Trials.

Purpose: A phase II/III trial is a type of phase III trial that has embedded in it an intermediate phase II go/no-go decision as to whether to continue the accrual to the phase III sample size. We examine the design characteristics and experience of a well-defined set of National Cancer Institute phase II/III trials, with special emphasis on designed accrual suspensions while awaiting the data to become mature enough for the phase II analysis. This experience is used to highlight the potential of using a calendar backstop to avoid an inordinately long accrual suspension.

Phase III Evaluation of Treatment Combinations in Three-Arm Trials.

Phase III trials that randomly assign patients to a control treatment (C), an experimental treatment (A), or a combination treatment (AB) should be designed with the goal to recommend the best treatment: AB (if it is better than A and C), A (if it is better than C, and AB is not better than A), or C (if neither AB nor A is better than C). However, this goal can be challenging to achieve with statistical confidence. We performed a survey of cancer trials published in five journals from January 2018 to May 2024 to assess the trial designs being used in this setting and found that three quarters of them did not have a provision for a formal comparison of the AB treatment arm with the A treatment arm, a possible shortcoming.

Two-to-One Randomization: Rarely Advisable.

In a randomized clinical trial, instead of allocating patients equally between the treatment arms, some trials in oncology assign a higher proportion of patients to receive the experimental treatment arm (eg, a two-to-one randomization). In this commentary, we first briefly review the common reasons given for the use of a two-to-one randomization and provide some examples of trials using these designs. We then explain why the risk-benefit ratio of this approach may not be favorable as is commonly assumed.

Design of randomized clinical trials with a binary endpoint: Conditional versus unconditional analyses of a two-by-two table.

When designing a randomized clinical trial to compare two treatments, the sample size required to have desired power with a specified type 1 error depends on the hypothesis testing procedure. With a binary endpoint (e.g.

Avoiding Delays in Reporting Time-to-Event Randomized Trials: Calendar Backstops and Other Approaches.

New oncology therapies that extend patients' lives beyond initial expectations and improving later-line treatments can lead to complications in clinical trial design and conduct. In particular, for trials with event-based analyses, the time to observe all the protocol-specified events can exceed the finite follow-up of a clinical trial or can lead to much delayed release of outcome data. With the advent of multiple classes of oncology therapies leading to much longer survival than in the past, this issue in clinical trial design and conduct has become increasingly important in recent years.

Backfilling Patients in Phase I Dose-Escalation Trials Using Bayesian Optimal Interval Design (BOIN).

In recent years, there has been increased interest in incorporation of backfilling into dose-escalation clinical trials, which involves concurrently assigning patients to doses that have been previously cleared for safety by the dose-escalation design. Backfilling generates additional information on safety, tolerability, and preliminary activity on a range of doses below the maximum tolerated dose (MTD), which is relevant for selection of the recommended phase II dose and dose optimization. However, in practice, backfilling may not be rigorously defined in trial protocols and implemented consistently.

Timing and Reporting of Secondary Overall Survival End Points for Phase III Trials in Advanced/Metastatic Disease.

Recent therapeutic advances have led to improved patient survival in many cancer settings. Although prolongation of survival remains the ultimate goal of cancer treatment, the availability of effective salvage therapies could make definitive phase III trials with primary overall survival (OS) end points difficult to complete in a timely manner. Therefore, to accelerate development of new therapies, many phase III trials of new cancer therapies are now designed with intermediate primary end points (eg, progression-free survival in the metastatic setting) with OS designated as a secondary end point.

Dose optimization during drug development: whether and when to optimize.

The goal of dose optimization during drug development is to identify a dose that preserves clinical benefit with optimal tolerability. Traditionally, the maximum tolerated dose in a small phase I dose escalation study is used in the phase II trial assessing clinical activity of the agent. Although it is possible that this dose level could be altered in the phase II trial if an unexpected level of toxicity is seen, no formal dose optimization has routinely been incorporated into later stages of drug development.

Augmenting randomized clinical trial data with historical control data: Precision medicine applications.

As precision medicine becomes more precise, the sizes of the molecularly targeted subpopulations become increasingly smaller. This can make it challenging to conduct randomized clinical trials of the targeted therapies in a timely manner. To help with this problem of a small patient subpopulation, a study design that is frequently proposed is to conduct a small randomized clinical trial (RCT) with the intent of augmenting the RCT control arm data with historical data from a set of patients who have received the control treatment outside the RCT (historical control data).

Clinical Benefit Scales and Trial Design: Some Statistical Issues.

Recently developed clinical-benefit outcome scales by the European Society for Medical Oncology and the American Society of Clinical Oncology allow standardized objective evaluation of outcomes of randomized clinical trials. However, incorporation of clinical-benefit outcome scales into trial designs highlights a number of statistical issues: the relationship between minimal clinical benefit and the target treatment-effect alternative used in the trial design, designing trials to assess long-term benefit, potential problems with using a trial endpoint that is not overall survival, and how to incorporate subgroup analyses into the trial design. Using the European Society for Medical Oncology Magnitude of Clinical Benefit Scale as a basis for discussion, we review what these issues are and how they can guide the choice of trial-design target effects, appropriate endpoints, and prespecified subgroup analyses to increase the chances that the resulting trial outcomes can be appropriately evaluated for clinical benefit.

Time trends with response-adaptive randomization: The inevitability of inefficiency.

Response-adaptive randomization, which changes the randomization ratio as a randomized clinical trial progresses, is inefficient as compared to a fixed 1:1 randomization ratio in terms of increased required sample size. It is also known that response-adaptive randomization leads to biased treatment effects if there are time trends in the accruing outcome data, for example, due to changes in the patient population being accrued, evaluation methods, or concomitant treatments. Response-adaptive-randomization analysis methods that account for potential time trends, such as time-block stratification or re-randomization, can eliminate this bias.

A Problematic Biomarker Trial Design.

Efficient biomarker-driven randomized clinical trials are a key tool for implementing precision oncology. A commonly used biomarker phase III design is focused on testing the treatment effect in biomarker-positive and overall study populations. This approach may result in recommending new treatments to biomarker-negative patients when these treatments have no benefit for these patients.

Are restricted mean survival time methods especially useful for noninferiority trials?

Background: Restricted mean survival time methods compare the areas under the Kaplan-Meier curves up to a time for the control and experimental treatments. Extraordinary claims have been made about the benefits (in terms of dramatically smaller required sample sizes) when using restricted mean survival time methods as compared to proportional hazards methods for analyzing noninferiority trials, even when the true survival distributions satisfy proportional hazardss.

Methods: Through some limited simulations and asymptotic power calculations, the authors compare the operating characteristics of restricted mean survival time and proportional hazards methods for analyzing both noninferiority and superiority trials under proportional hazardss to understand what relative power benefits there are when using restricted mean survival time methods for noninferiority testing.

Evaluation of the contribution of randomised cancer clinical trials evaluating agents without documented single-agent activity.

Background: With the development of targeted agents, the approach to combination cancer therapy has evolved to focus on identifying ways in which pathway inhibition by one agent may enhance the activity of other agents. In theory, this implies that under this new paradigm, agents are no longer required to show single-agent activity, as the pathway inhibited by the targeted agent may only have a therapeutic effect when given with other agents. This raises the question of the extent to which anticancer agents without single-agent activity can contribute to effective combination regimens.

Phase III Precision Medicine Clinical Trial Designs That Integrate Treatment and Biomarker Evaluation.

Recent advances in biotechnology and cancer genomics have afforded enormous opportunities for development of more effective anticancer therapies. A key thrust of this modern drug development paradigm is successful identification of predictive biomarkers that can distinguish patients who might be sensitive to new targeted therapies. To respond to this challenge, a number of phase III cancer trial designs integrating biomarker-based objectives have been proposed and implemented in oncology drug development.

Moving Molecular Profiling to Routine Clinical Practice: A Way Forward?

Molecular profiling of a patient's tumor to guide targeted treatment selection offers the potential to advance patient care by improving outcomes and minimizing toxicity (by avoiding ineffective treatments). However, current development of molecular profile (MP) panels is often based on applying institution-specific or subjective algorithms to nonrandomized patient cohorts. Consequently, obtaining reliable evidence that molecular profiling is offering clinical benefit and is ready for routine clinical practice is challenging.

Single-Arm Phase II Trials of Combination Therapies: A Review of the CTEP Experience 2008-2017.

Designing and interpreting single-arm phase II trials of combinations of agents is challenging because it can be difficult, based on historical data, to identify levels of activity for which the combination would be worth pursuing. We identified Cancer Therapy Evaluation Program single-arm combination trials that were activated in 2008-2017 and tabulated their design characteristics and results. Positive trials were evaluated as to whether they provided credible evidence that the combination was better than its constituents.