Clinical Trials最新文献

{"title":"Bayesian analysis in confirmatory clinical trials: A narrative review and discussion of current practice.","authors":"Rebecca M Turner, Conor D Tweed, Trinh Duong, Deborah Ford, Michelle N Clements, Mahesh Kb Parmar, Anna Turkova, Ian R White","doi":"10.1177/17407745261437669","DOIUrl":"10.1177/17407745261437669","url":null,"abstract":"<p><strong>Background: </strong>Bayesian methods allow trial investigators to combine evidence obtained within a clinical trial with relevant evidence that is available outside the trial. Bayesian analyses are now widely used in the drug development process, to inform internal 'go/no-go' decisions about planned studies, for example when deciding whether a drug should proceed from phase II to a phase III trial. However, Bayesian analyses are not commonly used for analysis of phase III (confirmatory) trials.</p><p><strong>Methods: </strong>In this article, we performed a narrative review of confirmatory trials using Bayesian methods for their primary analysis, to explore which types of trials chose Bayesian methods, why they chose a Bayesian analysis and how the methods were used. We reviewed published papers over a 6-year period and explored the characteristics of trials using Bayesian methods for their primary analysis, their reasons for choosing a Bayesian analysis, whether any informative priors were used and if so how they were informed. Next, we selected four trials from the review as case studies and presented their motivation for using Bayesian methods and their Bayesian analyses in more detail.</p><p><strong>Results: </strong>Our narrative review found that the number of Bayesian methods in confirmatory clinical trials has approximately doubled over the past 6 years, reflecting growing familiarity among investigators. Ninety-four papers were eligible for inclusion, presenting results from 69 separate trials. The most common reason given for choosing Bayesian methods was to make direct probability statements about the superiority and/or futility of the interventions evaluated; this was mentioned for 49% of trials. Flexibility in adapting the design or use of Bayesian stopping rules was another very common motivation, cited for 47% of trials. Borrowing information through informative priors was cited for a much smaller proportion (16%) of trials. The majority of trials (75%) specified vague or weakly informative priors for all parameters.</p><p><strong>Conclusion: </strong>Among the reasons given for choosing Bayesian methods, we consider the use of informative priors or making direct probability statements to be the strongest motivations for a Bayesian analysis, because there are no equivalent frequentist approaches. Making direct probability statements was the most common motivation provided, while informative priors were not often used. In settings with recruitment difficulties, we recommend considering borrowing relevant information, to gain power and precision. In all confirmatory trial settings, we recommend that Bayesian approaches are used only with careful justification, investigators make clear whether the methods and priors were pre-planned, and alternative frequentist approaches are considered.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"404-412"},"PeriodicalIF":2.4,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13451585/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147632198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A randomized control trial of re-designed and shorter research informed consent forms to improve comprehension.","authors":"Ezekiel J Emanuel, Samantha Lopez-Rico, Merjan Lijerón Ozisik, Eli Silvert","doi":"10.1177/17407745261429936","DOIUrl":"10.1177/17407745261429936","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background/aims: &lt;/strong&gt;Informed consent forms are an essential component of ethical clinical research. However, they are failing. They are long, legalistic, and written at an 11th-grade reading level. Consequently, many participants have poor comprehension of the research they are considering. Our objective is to assess participant comprehension and satisfaction across three informed consent forms of different lengths and formats including one based on the Food and Drug Administration's (FDA) 2024 draft summary template.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;In total, 334 healthy participants from AmeriSpeak's online survey panel were recruited via email and AmeriSpeak's member portal, oversampling less educated individuals and those from racial and ethnic minority groups. Participants were randomized to three informed consent forms-long, medium, and short-and were asked to imagine hypothetically being a patient considering joining a study. They were given a brief introduction on the purpose of informed consent forms and of this project's goal to evaluate comprehension, satisfaction, and willingness to join the described hypothetical study but were not told the hypothesis or that there were three different informed consent forms. The long informed consent form (21 pages) was used in an actual international Bristol Myers Squibb study concerning a stroke prevention regimen. The long informed consent form contained longer paragraphs and lists and was written just below an 11th-grade level. The long informed consent form was modified to create the medium (14 pages) and short informed consent forms (3 pages), which both used simpler words, shorter sentences, less passive voice, tables, and other patient-friendly edits to achieve below sixth-grade reading levels. The short informed consent form was adapted from the Food and Drug Administration's 2024 draft summary template.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The medium informed consent form (mean score of 79.3%) scored significantly higher on comprehension than the long informed consent form (65.7% mean score, p &lt; 0.001) or the short informed consent form (69.3% mean score, p = 0.006). Compared to the long informed consent form, fewer medium informed consent form participants found their informed consent form \"too long\" or \"too detailed.\" Compared to the long and medium informed consent forms, more short informed consent form participants reported wanting more information on study procedures.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;The medium-length informed consent form, written at a sixth-grade reading level, with shorter words and sentences, tables, and enhanced formatting, produced significantly better comprehension than longer or shorter informed consent forms. The short informed consent form produced the same level of comprehension as a long informed consent form used in approved clinical trials. Researchers, pharmaceutical companies, and institutional review boards should adopt these informed co","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"421-429"},"PeriodicalIF":2.4,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13451594/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147572699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The evolving role of placebo in non-inferiority trials: A scoping review.","authors":"Spencer Cho, Shaheer Nadeem, Valentina Ly, Iman Alhafez, Tim Ramsay, Pil Joo","doi":"10.1177/17407745261430850","DOIUrl":"10.1177/17407745261430850","url":null,"abstract":"<p><strong>Background: </strong>Non-inferiority trials can be used for efficacy endpoints or safety endpoints, with indirect and direct comparison to placebo. A less common application of this design involves using placebo as the proposed intervention to challenge standard practices that lack evidence of efficacy. However, the methodology of using a placebo in a non-inferiority trial is poorly described in the literature. We performed a scoping review to map how placebo is utilized in randomized controlled trials with a non-inferiority design, with particular attention to studies positioning placebo as a proposed alternative to existing, but unproven, interventions.</p><p><strong>Methods: </strong>We conducted a scoping review of randomized controlled trials using non-inferiority designs with a placebo arm, searching six databases without date or language restrictions. Eligible studies were primary randomized controlled trials with at least one placebo arm evaluated under a non-inferiority hypothesis. Data extraction focused on study characteristics, design elements, rationale for non-inferiority design and margin, and analytical practices.</p><p><strong>Results: </strong>Of 6897 studies screened, 94 met inclusion criteria. Three primary study types were identified: safety (63%), deprescription (20%), and shorter-course (13%) trials. There has been increased use of deprescription and shorter-course studies since 2017. One-third (35%) hypothesized that placebo was non-inferior to active treatment, predominantly in deprescription and shorter-course trials focused on antibiotic use. Most studies (94%) applied non-inferiority analysis to primary outcomes, yet only 22% provided a rationale for non-inferiority design, and despite 96% prespecifying non-inferiority margin, only 41% justified the margin. While 71% used intention-to-treat analysis, only 53% conducted per-protocol analysis. Graphical representation of non-inferiority margins and confidence intervals was reported in 23% of studies.</p><p><strong>Conclusion: </strong>Placebo is increasingly used in non-inferiority trials aimed at evaluating the necessity of standard interventions, including safety, deprescription, and shorter-course designs. However, many trials lack critical methodological transparency. Future studies should clearly justify non-inferiority designs and margins, use both intention-to-treat and per-protocol analyses, and adhere to the Consolidated Standards of Reporting Trials reporting guidelines to enhance interpretability and rigor.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"439-446"},"PeriodicalIF":2.4,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13451599/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147621770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and monitoring of randomized trials in vision research with binary endpoints.","authors":"Guoqing Diao, Qiang Zhang, Toshimitsu Hamasaki, Scott R Evans","doi":"10.1177/17407745261468235","DOIUrl":"10.1177/17407745261468235","url":null,"abstract":"<p><strong>Background: </strong>Randomized eye trials often involve both eyes if eligible from a patient. Few studies have investigated the design properties of randomized eye trials with binary endpoints, for instance, the sample size/power determination, leaving a significant gap in the literature. In addition, proper interim data-monitoring plans, which are essential for a successful design, are not available for eye trials with binary endpoints.</p><p><strong>Methods: </strong>We propose a unified design for vision research with binary endpoints that accommodate all possible design options while accounting for correlations between the two eyes of the same patient. We derive closed-form formulas for the sample size and power calculations under the generalized linear mixed model framework. We also describe how to properly calculate the information fractions during interim monitoring, which is an essential component used to determine the efficacy/futility boundaries or calculate the alpha-spending function, as the standard technique may not apply.</p><p><strong>Results: </strong>We conduct extensive simulation studies to examine the performance of the proposed unified design for clustered binary data in randomized eye trials and compare it with the existing specific individual design. The simulation results demonstrate that the proposed methods perform well in practical settings. We provide an application to the Age-Related Eye Disease Study.</p><p><strong>Conclusion: </strong>We propose a unified design that accommodates all scenarios in eye trials with binary outcomes, including one-eye, paired, two-eye, mixture of one-eye and two-eye, and hybrid designs, and develop appropriate interim analysis plans. A proper study design and interim monitoring using the proposed methods in these studies can help study investigators make informed decisions.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745261468235"},"PeriodicalIF":2.4,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13410960/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148590730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"17th Annual University of Pennsylvania Conference on statistical issues in clinical trials - Covariate adjustment in randomized clinical trials: New methods and applications (Morning panel discussion).","authors":"Mary E Putt","doi":"10.1177/17407745261442581","DOIUrl":"10.1177/17407745261442581","url":null,"abstract":"","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"263-271"},"PeriodicalIF":2.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147970835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shaping the future of clinical trials through strategic foresight.","authors":"Sharon Lee, Jeff McIntyre, Tracey Robertson, Kimberley Kallsen, Martin Bauer, Rossana Berardi, Christian Boisvert-Huneault, Emmanuelle Clerisme-Beaty, Christopher P Denton, Eric Fakra, Jan Geissler, David Goldstein, Kazuo Hasegawa, Manya Lind, Patricia LoRusso, Keith Perry, Claas Röhl, Jose Francisco Kerr Saraiva, Nidhi Swarup, Aron Szpisjak, Allan Flyvbjerg","doi":"10.1177/17407745251414680","DOIUrl":"10.1177/17407745251414680","url":null,"abstract":"<p><strong>Background/aims: </strong>Global megatrends, including population growth, interconnectedness and artificial intelligence, are already shaping the clinical trials industry, and will do so for decades to come. Innovations from technology companies, greater collaboration with patients and caregivers, and increased diversity in clinical trials could transform clinical trials of the future. However, the industry has typically been slow to adopt new technologies, and certain barriers could stifle innovation and allow health inequalities to persist. Our aim was to explore the trends shaping clinical trials and identify initiatives that can be started now to move toward a future where patients are actively involved in clinical trial design and decision-making, and technologies like artificial intelligence are integrated responsibly and ethically into clinical trials.</p><p><strong>Methods: </strong>We used strategic foresight methodology to explore the trends that will shape the future of clinical trials and how the trajectory of these trends could lead to different future scenarios We then identified initiatives that could help us move toward our desired scenario.</p><p><strong>Results: </strong>We identified four possible scenarios for the future of clinical trials based on two key trends: data sharing and adaptation of regulatory frameworks. While the future will see collection of large amounts of data from different sources, such as databases and wearable devices, their usefulness could be limited if data remain in silos, limited by strict regulations and a lack of trust in data privacy. Alternatively, data may be integrated more efficiently into clinical trials if regulators adapt proactively to new technologies and patients are empowered to take control over their data, for example. We identified initiatives that can be started now to achieve our vision. Pharmaceutical companies, academic researchers, non-governmental organizations (including patient organizations), regulatory authorities, policymakers, technology companies and innovative service providers must join forces and work on initiatives to integrate technology into trials, enable data sharing, harmonize regulations across regions, co-design trials with patients and caregivers, strengthen decentralized trial capabilities and promote diversity in trials.</p><p><strong>Conclusion: </strong>Through a collaborative cross-industry effort that prioritizes proactive patient involvement and responsible use of technology, we can shape a clinical trial ecosystem that is inclusive, ethical and ready for the future. We urge all stakeholders to act now on these initiatives to positively influence the future of clinical trials.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"309-319"},"PeriodicalIF":2.4,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13242527/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147288978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proceedings of the University of Pennsylvania 17th annual conference on statistical issues in clinical trials: Covariate adjustment in randomized clinical trials: new methods and applications.","authors":"Mary E Putt","doi":"10.1177/17407745261434940","DOIUrl":"10.1177/17407745261434940","url":null,"abstract":"","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"237-239"},"PeriodicalIF":2.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147608276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adjusting for covariates in randomized clinical trials for drugs and biological products.","authors":"Daniel Rubin","doi":"10.1177/17407745251405770","DOIUrl":"10.1177/17407745251405770","url":null,"abstract":"<p><p>In May 2023, the US Food and Drug Administration released a guidance document on adjusting for covariates in randomized clinical trials for drugs and biological products. This article provides a summary of motivations for the US Food and Drug Administration guidance document, recommendations in the guidance document, considerations for covariate adjustment in large trials and small trials, and additional topics beyond the scope of the guidance document that may benefit from greater consensus on best practices. A covariate-adjusted prespecified primary analysis can have advantages over an unadjusted analysis and is generally acceptable to the US Food and Drug Administration.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"259-262"},"PeriodicalIF":2.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145862469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Covariate adjustment in randomized trials: An overview.","authors":"Stuart J Pocock","doi":"10.1177/17407745261434564","DOIUrl":"10.1177/17407745261434564","url":null,"abstract":"<p><p>This article aims to provide a practical overview of the various methods of covariate adjustment in randomized clinical trials leading to recommendation for future practice. Topics covered are baseline adjustment for a quantitative outcome (analysis of covariance), consequences of covariate adjustment for different types of outcome (quantitative, binary, time-to-event), surveys of covariate adjustment as done in published trials, regulatory guidance on covariate adjustment, how big is the gain in statistical power (a simulation study), some pertinent examples in cardiovascular trials, center-adjusted analyses (are they worthwhile?), a brief mention of some alternative approaches to covariate adjustment, other uses of covariates (eg risk models). We conclude that modest gains in statistical power are achieved by adjustment for covariates that influence prognosis.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"240-247"},"PeriodicalIF":2.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147688427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On flexible covariate adjustment under covariate-constrained randomization.","authors":"Bingkai Wang, Fan Li","doi":"10.1177/17407745261423479","DOIUrl":"10.1177/17407745261423479","url":null,"abstract":"<p><p>Covariate-constrained randomization is an effective treatment allocation procedure for controlling imbalance across multiple baseline covariates in randomized trials. Motivated by the GroupPMPlus cluster randomized trial, we introduce the asymptotic theory for a broad class of estimators, known as M-estimators, under covariate-constrained randomization. Here, M-estimators refer to estimators obtained by optimizing an objective function, such as a log-likelihood function, and include commonly used methods such as analysis of covariance and linear mixed models. We show that M-estimators remain consistent in this setting but can exhibit non-Gaussian asymptotic distributions depending on the specification. Using examples of common M-estimators, we delineate conditions under which covariate-constrained randomization can be safely ignored in statistical analysis. Our results extend to stratified covariate-constrained randomization and semiparametric efficient estimators based on data-adaptive machine learning methods. We illustrate these theoretical findings using the GroupPMPlus study to evaluate the causal effect of a psychological treatment on mental health outcomes following a disaster.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"282-288"},"PeriodicalIF":2.4,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12965748/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147347409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}