Assessment of endpoint definitions in curative-intent trials for mucosal head and neck squamous cell carcinomas: Head and Neck Cancer International Group consensus recommendations.

Robust time-to-event endpoint definitions are crucial for the assessment of treatment effect and the clinical value of trial interventions. Here, the Head and Neck Cancer International Group investigated endpoint use in phase 3 trials and trials considered potentially practice-changing published between 2008 and 2021 in the curative-intent setting for patients with mucosal head and neck squamous cell carcinoma. Of the 92 trials reviewed, we show that all core components of endpoint reporting were heterogeneous, including definitions of common terms, such as overall survival and progression-free survival. Our report highlights the urgent need for harmonisation of fundamental components of clinical trial endpoints and the engagement of all stakeholders to ensure the transparent reporting of endpoint details.

Assessment of endpoint definitions in recurrent and metastatic mucosal head and neck squamous cell carcinoma trials: Head and Neck Cancer International Group consensus recommendations.

Transparent and precise endpoint definitions are a crucial aspect of clinical trial conduct and reporting, and are used to communicate the benefit of an intervention. Previous studies have identified inconsistencies in endpoint definitions across oncological clinical trials. Here, the Head and Neck Cancer International Group assessed endpoint definitions from phase 3 trials or trials considered practice-changing for patients with recurrent or metastatic mucosal head and neck squamous cell carcinoma, published between 2008 and 2021. We identify considerable and global heterogeneity in endpoint definitions, which undermines the interpretation of results and development of future studies. We show how fundamental components of even incontrovertible endpoints such as overall survival vary widely, highlighting an urgent need for increased rigour in reporting and harmonisation of endpoints.

Considerations for using potential surrogate endpoints in cancer screening trials.

The requirement of large-scale expensive cancer screening trials spanning decades creates considerable barriers to the development, commercialisation, and implementation of novel screening tests. One way to address these problems is to use surrogate endpoints for the ultimate endpoint of interest, cancer mortality, at an earlier timepoint. This Review aims to highlight the issues underlying the choice and use of surrogate endpoints for cancer screening trials, to propose criteria for when and how we might use such endpoints, and to suggest possible candidates. We present the current landscape and challenges, and discuss lessons and shortcomings from the therapeutic trial setting. It is hugely challenging to validate a surrogate endpoint, even with carefully designed clinical studies. Nevertheless, we consider whether there are candidates that might satisfy the requirements defined by research and regulatory bodies.

Electroencephalographic Indices for Clinical Endpoints during Propofol Anesthesia in Infants: An Early-phase Propofol Biomarker-finding Study.

BACKGROUND: Unlike expired sevoflurane concentration, propofol lacks a biomarker for its brain effect site concentration, leading to dosing imprecision particularly in infants. Electroencephalography monitoring can serve as a biomarker for propofol effect site concentration, yet proprietary electroencephalography indices are not validated in infants. The authors evaluated spectral edge frequency (SEF95) as a propofol anesthesia biomarker in infants. It was hypothesized that the SEF95 targets will vary for different clinical stimuli and an inverse relationship existed between SEF95 and propofol plasma concentration. METHODS: This prospective study enrolled infants (3 to 12 months) to determine the SEF95 ranges for three clinical endpoints of anesthesia (consciousness-pacifier placement, pain-electrical nerve stimulation, and intubation-laryngoscopy) and correlation between SEF95 and propofol plasma concentration at steady state. Dixon's up-down method was used to determine target SEF95 for each clinical endpoint. Centered isotonic regression determined the dose-response function of SEF95 where 50% and 90% of infants (ED50 and ED90) did not respond to the clinical endpoint. Linear mixed-effect model determined the association of propofol plasma concentration and SEF95. RESULTS: Of 49 enrolled infants, 44 evaluable (90%) showed distinct SEF95 for endpoints: pacifier (ED50, 21.4 Hz; ED90, 19.3 Hz), electrical stimulation (ED50, 12.6 Hz; ED90, 10.4 Hz), and laryngoscopy (ED50, 8.5 Hz; ED90, 5.2 Hz). From propofol 0.5 to 6 µg/ml, a 1-Hz SEF95 increase was linearly correlated to a 0.24 (95% CI, 0.19 to 0.29; P < 0.001) µg/ml decrease in plasma propofol concentration (marginal R2 = 0.55). CONCLUSIONS: SEF95 can be a biomarker for propofol anesthesia depth in infants, potentially improving dosing accuracy and utilization of propofol anesthesia in this population.

Use of win time for ordered composite endpoints in clinical trials.

Consider the choice of outcome for overall treatment benefit in a clinical trial which measures the first time to each of several clinical events. We describe several new variants of the win ratio that incorporate the time spent in each clinical state over the common follow-up, where clinical state means the worst clinical event that has occurred by that time. One version allows restriction so that death during follow-up is most important, while time spent in other clinical states is still accounted for. Three other variants are described; one is based on the average pairwise win time, one creates a continuous outcome for each participant based on expected win times against a reference distribution and another that uses the estimated distributions of clinical state to compare the treatment arms. Finally, a combination testing approach is described to give robust power for detecting treatment benefit across a broad range of alternatives. These new methods are designed to be closer to the overall treatment benefit/harm from a patient's perspective, compared to the ordinary win ratio. The new methods are compared to the composite event approach and the ordinary win ratio. Simulations show that when overall treatment benefit on death is substantial, the variants based on either the participants' expected win times (EWTs) against a reference distribution or estimated clinical state distributions have substantially higher power than either the pairwise comparison or composite event methods. The methods are illustrated by re-analysis of the trial heart failure: a controlled trial investigating outcomes of exercise training.

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., response), the trial results can be displayed in a 2 × 2 table. If one does the analysis conditional on the number of positive responses, then using Fisher's exact test has an actual type 1 error less than or equal to the specified nominal type 1 error. Alternatively, one can use one of many unconditional "exact" tests that also preserve the type 1 error and are less conservative than Fisher's exact test. In particular, the unconditional test of Boschloo is always at least as powerful as Fisher's exact test, leading to smaller required sample sizes for clinical trials. However, many statisticians have argued over the years that the conditional analysis with Fisher's exact test is the only appropriate procedure. Since having smaller clinical trials is an extremely important consideration, we review the general arguments given for the conditional analysis of a 2 × 2 table in the context of a randomized clinical trial. We find the arguments not relevant in this context, or, if relevant, not completely convincing, suggesting the sample-size advantage of the unconditional tests should lead to their recommended use. We also briefly suggest that since designers of clinical trials practically always have target null and alternative response rates, there is the possibility of using this information to improve the power of the unconditional tests.

Familywise error for multiple time-to-event endpoints in a group sequential design.

We investigate the familywise error rate (FWER) for time-to-event endpoints evaluated using a group sequential design with a hierarchical testing procedure for secondary endpoints. We show that, in this setup, the correlation between the log-rank test statistics at interim and at end of study is not congruent with the canonical correlation derived for normal-distributed endpoints. We show, both theoretically and by simulation, that the correlation also depends on the level of censoring, the hazard rates of the endpoints, and the hazard ratio. To optimize operating characteristics in this complex scenario, we propose a simulation-based method to assess the FWER which, better than the alpha-spending approach, can inform the choice of critical values for testing secondary endpoints.

An information-theoretic approach for the assessment of a continuous outcome as a surrogate for a binary true endpoint based on causal inference: Application to vaccine evaluation.

Within the causal association paradigm, a method is proposed to assess the validity of a continuous outcome as a surrogate for a binary true endpoint. The methodology is based on a previously introduced information-theoretic definition of surrogacy and has two main steps. In the first step, a new model is proposed to describe the joint distribution of the potential outcomes associated with the putative surrogate and the true endpoint of interest. The identifiability issues inherent to this type of models are handled via sensitivity analysis. In the second step, a metric of surrogacy new to this setting, the so-called individual causal association is presented. The methodology is studied in detail using theoretical considerations, some simulations, and data from a randomized clinical trial evaluating an inactivated quadrivalent influenza vaccine. A user-friendly R package Surrogate is provided to carry out the evaluation exercise.

Two-stage randomized clinical trials with a right-censored endpoint: Comparison of frequentist and Bayesian adaptive designs.

Adaptive randomized clinical trials are of major interest when dealing with a time-to-event outcome in a prolonged observation window. No consensus exists either to define stopping boundaries or to combine p $$ p $$ values or test statistics in the terminal analysis in the case of a frequentist design and sample size adaptation. In a one-sided setting, we compared three frequentist approaches using stopping boundaries relying on α $$ \alpha $$ -spending functions and a Bayesian monitoring setting with boundaries based on the posterior distribution of the log-hazard ratio. All designs comprised a single interim analysis with an efficacy stopping rule and the possibility of sample size adaptation at this interim step. Three frequentist approaches were defined based on the terminal analysis: combination of stagewise statistics (Wassmer) or of p $$ p $$ values (Desseaux), or on patientwise splitting (Jörgens), and we compared the results with those of the Bayesian monitoring approach (Freedman). These different approaches were evaluated in a simulation study and then illustrated on a real dataset from a randomized clinical trial conducted in elderly patients with chronic lymphocytic leukemia. All approaches controlled for the type I error rate, except for the Bayesian monitoring approach, and yielded satisfactory power. It appears that the frequentist approaches are the best in underpowered trials. The power of all the approaches was affected by the violation of the proportional hazards (PH) assumption. For adaptive designs with a survival endpoint and a one-sided alternative hypothesis, the Wassmer and Jörgens approaches after sample size adaptation should be preferred, unless violation of PH is suspected.

Applying Exercise Capacity and Physical Activity as Single vs Composite Endpoints for Trials of Cardiac Rehabilitation Interventions: Rationale, Use-case, and a Blueprint Method for Sample Size Calculation.

OBJECTIVE: To conceptualize a composite primary endpoint for parallel-group RCTs of exercise-based cardiac rehabilitation (CR) interventions and to explore its application and statistical efficiency. DESIGN: We conducted a statistical exploration of sample size requirements. We combined exercise capacity and physical activity for the composite endpoint (CE), both being directly related to reduced premature mortality in patients with cardiac diseases. Based on smallest detectable and minimal clinically important changes (change in exercise capacity of 15 W and change in physical activity of 10 min/day), the CE combines 2 dichotomous endpoints (achieved/not achieved). To examine statistical efficiency, we compared sample size requirements based on the CE to single endpoints using data from 2 completed CR trials. SETTING: Cardiac rehabilitation phase III. PARTICIPANTS: Patients in cardiac rehabilitation. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE(S): Exercise capacity (Pmax assessed by incremental cycle ergometry) and physical activity (daily minutes of moderate to vigorous physical activity assessed by accelerometry). RESULTS: Expecting, for example, a 10% between-group difference and improvement in the clinical outcome, the CE would increase sample size by up to 21% or 61%, depending on the dataset. When expecting a 10% difference and designing an intervention with the aim of non-deterioration, the CE would allow to reduce the sample size by up to 55% or 70%. CONCLUSIONS: Trialists may consider the utility of the CE for future studies in exercise-based CR to reduce sample size requirements. However, perhaps surprisingly at first, the CE could also lead to an increased sample size needed, depending on the observed baseline proportions in the trial population and the aim of the intervention.

The database makes the poison: How the selection of datasets in QSAR models impacts toxicant prediction of higher tier endpoints.

As the United States and the European Union continue their steady march towards the acceptance of new approach methodologies (NAMs), we need to ensure that the available tools are fit for purpose. Critics will be well-positioned to caution against NAMs acceptance and adoption if the tools turn out to be inadequate. In this paper, we focus on Quantitative Structure Activity-Relationship (QSAR) models and highlight how the training database affects quality and performance of these models. Our analysis goes to the point of asking, "are the endpoints extracted from the experimental studies in the database trustworthy, or are they false negatives/positives themselves?" We also discuss the impacts of chemistry on QSAR models, including issues with 2-D structure analyses when dealing with isomers, metabolism, and toxicokinetics. We close our analysis with a discussion of challenges associated with translational toxicology, specifically the lack of adverse outcome pathways/adverse outcome pathway networks (AOPs/AOPNs) for many higher tier endpoints. We recognize that it takes a collaborate effort to build better and higher quality QSAR models especially for higher tier toxicological endpoints. Hence, it is critical to bring toxicologists, statisticians, and machine learning specialists together to discuss and solve these challenges to get relevant predictions.

Estimated Glomerular Filtration Rate Slope as an Endpoint in Cardiovascular Trials.

PURPOSE OF REVIEW: End stage kidney disease can be a slow process and it may be challenging to achieve required follow-up for sufficient events. Therefore, a surrogate kidney endpoint, such as estimated glomerular filtration rate (eGFR) slope maybe attractive to assess the kidney in cardiovascular trials, especially heart failure (HF). RECENT FINDINGS: eGFR slope can generate informative results in a shorter follow-up period, has decreased risk of type-2 error, and is less sensitive to eGFR shifts compared with other surrogate kidney endpoints (eGFR decline≥40% or doubling creatinine). However, eGFR slope has its limitations with acute effects, heterogeneity in slope calculation/reporting, and deviations from linearity. eGFR slope is a kidney endpoint which may be well-suited for HF trials. Cross-collaborated guideline recommendations are needed to optimize the use of eGFR slope as a kidney endpoint in patients with HF.

Cancer Stage Compared With Mortality as End Points in Randomized Clinical Trials of Cancer Screening: A Systematic Review and Meta-Analysis.

Importance: Randomized clinical trials of cancer screening typically use cancer-specific mortality as the primary end point. The incidence of stage III-IV cancer is a potential alternative end point that may accelerate completion of randomized clinical trials of cancer screening. Objective: To compare cancer-specific mortality with stage III-IV cancer as end points in randomized clinical trials of cancer screening. Design, Setting, and Participants: This meta-analysis included 41 randomized clinical trials of cancer screening conducted in Europe, North America, and Asia published through February 19, 2024. Data extracted included numbers of participants, cancer diagnoses, and cancer deaths in the intervention and comparison groups. For each clinical trial, the effect of screening was calculated as the percentage reduction between the intervention and comparison groups in the incidence of participants with cancer-specific mortality and stage III-IV cancer. Exposures: Randomization to a cancer screening test or to a comparison group in a clinical trial of cancer screening. Main Outcomes and Measures: End points of cancer-specific mortality and incidence of stage III-IV cancer were compared using Pearson correlation coefficients with 95% CIs, linear regression, and fixed-effects meta-analysis. Results: The included randomized clinical trials tested benefits of screening for breast (n = 6), colorectal (n = 11), lung (n = 12), ovarian (n = 4), prostate (n = 4), and other cancers (n = 4). Correlation between reductions in cancer-specific mortality and stage III-IV cancer varied by cancer type (I2 = 65%; P = .02). Correlation was highest for trials that screened for ovarian (Pearson ρ = 0.99 [95% CI, 0.51-1.00]) and lung (Pearson ρ = 0.92 [95% CI, 0.72-0.98]) cancers, moderate for breast cancer (Pearson ρ = 0.70 [95% CI, -0.26 to 0.96]), and weak for colorectal (Pearson ρ = 0.39 [95% CI, -0.27 to 0.80]) and prostate (Pearson ρ = -0.69 [95% CI, -0.99 to 0.81]) cancers. Slopes from linear regression were estimated as 1.15 for ovarian cancer, 0.75 for lung cancer, 0.40 for colorectal cancer, 0.28 for breast cancer, and -3.58 for prostate cancer, suggesting that a given magnitude of reduction in incidence of stage III-IV cancer produced different magnitudes of change in incidence of cancer-specific mortality (P for heterogeneity = .004). Conclusions and Relevance: In randomized clinical trials of cancer screening, incidence of late-stage cancer may be a suitable alternative end point to cancer-specific mortality for some cancer types, but is not suitable for others. These results have implications for clinical trials of multicancer screening tests.

Simultaneous Inference of Multiple Binary Endpoints in Biomedical Research: Small Sample Properties of Multiple Marginal Models and a Resampling Approach.

In biomedical research, the simultaneous inference of multiple binary endpoints may be of interest. In such cases, an appropriate multiplicity adjustment is required that controls the family-wise error rate, which represents the probability of making incorrect test decisions. In this paper, we investigate two approaches that perform single-step p $p$ -value adjustments that also take into account the possible correlation between endpoints. A rather novel and flexible approach known as multiple marginal models is considered, which is based on stacking of the parameter estimates of the marginal models and deriving their joint asymptotic distribution. We also investigate a nonparametric vector-based resampling approach, and we compare both approaches with the Bonferroni method by examining the family-wise error rate and power for different parameter settings, including low proportions and small sample sizes. The results show that the resampling-based approach consistently outperforms the other methods in terms of power, while still controlling the family-wise error rate. The multiple marginal models approach, on the other hand, shows a more conservative behavior. However, it offers more versatility in application, allowing for more complex models or straightforward computation of simultaneous confidence intervals. The practical application of the methods is demonstrated using a toxicological dataset from the National Toxicology Program.

Surrogate endpoints: a key concept in clinical epidemiology.

Surrogate endpoints are biomarkers or intermediate outcomes that are used as substitutes for clinical outcomes of interest, often to expedite research or decision-making. In contrast, patient-important (or patient-centered) outcomes are health outcomes that are of direct relevance and importance to patients themselves; clinical trials may have measured the impact of the intervention on other endpoints related to, but different from, those of primary importance to patients. This article aims to elaborate on the use and understanding of surrogate endpoints. There should be a well-understood and scientifically grounded relationship between the surrogate (replacement) and the patient-important (target) endpoint it is intended to represent. It should be biologically plausible that changes in the surrogate will consistently and predictably reflect changes in the patient-important endpoint. The surrogate endpoint should show a threshold effect, meaning that a specific change (or state) in the surrogate with an intervention (relative to the comparator) is associated with a predictable (change in the) patient-important outcome. This helps establish a meaningful cutoff or target for the treatment effect on the surrogate endpoint. While surrogate endpoints offer advantages in certain situations, it is important to remember that their use requires careful validation to ensure they reliably predict the true clinical outcome. The validity of "surrogate endpoints" should be supported by robust scientific evidence and rigorous evaluation before these can be considered and labeled as surrogate endpoints.

In-Depth Retinal Sensitivity Assessment With the MP3 Type S Microperimeter: A Methods Study.

Purpose: Retinal sensitivity is frequently listed as an end point in clinical trials, often with long working practices. The purpose of this methods study was to provide a new workflow and reduced test time for in-depth characterization of retinal sensitivity. Methods: A workflow for the MP3-S microperimeter with detailed functional characterization of the retina under photopic, mesopic, and scotopic conditions was evaluated. Grids of 32 and 28 test positions for photopic/mesopic and scotopic, respectively, were tested in 12 healthy individuals and compared with an established 68-point grid for test time, mean sensitivity (MS), and bivariate contour ellipse area (BCEA). Results: The mean test time (range; ±SD) was 10.5 minutes (8.4-14.9; ±2.0) in the 68-point grid and 4.3 minutes (3.8-5.0; ±0.4) in the 32-point grid, which was significantly different (P < 0.0001). The mean of difference in test time (±SD; 95% confidence interval) was 6.1 minutes (±2.0; 4.6-7.6). MS and BCEA were significantly correlated between grids (r = 0.89 and 0.74; P = 0.0005 and 0.014, respectively). Mean test time of subjects who underwent the full protocol (n = 4) was 2.15 hours. Conclusions: The protocol suggested herein appears highly feasible with in-depth characterization of retinal function under different testing conditions and in a short test time. Translational Relevance: The protocol described herein allows for characterization of the retina under different testing conditions and in a short test time, which is relevant due to its potential for patient prognostication and follow-up in clinical settings and also given its increasing role as a clinical trial end point.

The Finkelstein-Schoenfeld Test: A Note on Some Overlooked Issues Concerning Power.

In this note, we express our viewpoint regarding power considerations, via simulation studies, in clinical study design using hierarchical composite endpoint and Finkelstein-Schoenfeld test.