Clinical Trials最新文献

{"title":"Commentary on Wittes et al: Aspirin for primary prevention of CV events - Rationally robust? Statistically significant? Clinically convincing?","authors":"John Gf Cleland, Danyaal Anzar","doi":"10.1177/17407745251324865","DOIUrl":"10.1177/17407745251324865","url":null,"abstract":"","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"462-465"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12318157/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143751496","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":"Military influences on the evolution of clinical trials throughout history.","authors":"Kamil Malshy, Alexis Steinmetz, Kit Yuen, Jathin Bandari, Ronald Rabinowitz","doi":"10.1177/17407745241309054","DOIUrl":"10.1177/17407745241309054","url":null,"abstract":"<p><p>Clinical trials of drugs, procedures, and other therapies play a crucial role in advancing medical science by evaluating the safety, efficacy, and optimal use of medical interventions. The design and implementation of these trials have evolved significantly over time, reflecting advancements in medicine, ethics, and methodology. Early historical examples, such as King Nebuchadnezzar II's and his captives' dietary experiment and Ambroise Paré's treatment of gunshot wounds, laid some foundational principles of trial design. The momentum of clinical trial development increased notably with James Lind's 1747 trial for scurvy and continued to progress during World War I with innovations in blood transfusion techniques. World War II (WWII) marked a pivotal moment with breakthroughs in oncology, including the development of the first modern chemotherapeutic agents derived from mustard gas and the introduction of the randomized controlled trial, credited to British epidemiologist Austin Bradford Hill, which revolutionized trial design. More recent conflicts, such as those in Vietnam, Iraq, and Afghanistan, have driven advancements in trauma care, heroin addiction treatment, and hemorrhage management. In response to historical abuses committed by the Nazis during WWII, the evolution of clinical trials has increasingly emphasized ethical standards, particularly informed consent, starting with the Doctors' Trial and the Nuremberg Code. This article discusses how military needs and wartime innovations have shaped modern clinical research, highlighting the interplay between military imperatives and medical progress. Ultimately, clinical trials play an essential role in advancing medical science and improving patient outcomes.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"501-508"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143001576","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":"Dose-response characterization: A key to success in drug development.","authors":"Frank Bretz, Björn Bornkamp, Thomas Dumortier","doi":"10.1177/17407745251350289","DOIUrl":"10.1177/17407745251350289","url":null,"abstract":"<p><p>Dose selection is a key component of drug development, yet inadequate dose-response characterization remains a major challenge, contributing to late-stage attrition and post-marketing regulatory commitments. Effective dose-response characterization for both efficacy and safety supports benefit-risk assessments of therapeutic interventions and relies on two main elements: Trial design and trial analysis. In trial design, selecting an appropriate dose range, determining the number of dose levels, and ensuring proper dose spacing are essential to capture both the steep and plateau regions of a dose-response curve. Adaptive trial designs provide additional flexibility to address uncertainties during trial planning and execution, increasing the chances of identifying optimal doses and improving trial efficiency. In trial analysis, modeling approaches support dose-response characterization by utilizing data across dose levels to fit a continuous curve rather than analyzing each dose level separately. Model-based methods, such as Emax modeling or MCP-Mod (which combines multiple comparison procedures and modeling), incorporate assumptions about the dose-response relationship to improve the precision of dose-response and target dose estimation. Additional precision can often be achieved by modeling dose-exposure-response relationships, recognizing that exposure (e.g. drug concentration in the plasma) often mediates the relationship between dose and clinical response. Dose-exposure response models may also enable the prediction of dose-response relationships of alternative regimens (e.g. when applying a different frequency of administration than the tested ones). This article reviews key considerations for the design and analysis of dose-response trials, focusing on strategies to improve decision-making and regulatory alignment.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"384-392"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144583299","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":"Examining the bias-efficiency tradeoff from incorporation of nonconcurrent controls in platform trials: A simulation study example from the adaptive COVID-19 treatment trial.","authors":"Tyler Bonnett, Gail E Potter, Lori E Dodd","doi":"10.1177/17407745251313928","DOIUrl":"10.1177/17407745251313928","url":null,"abstract":"<p><strong>Background: </strong>Platform trials typically feature a shared control arm and multiple experimental treatment arms. Staggered entry and exit of arms splits the control group into two cohorts: those randomized during the same period in which the experimental arm was open (concurrent controls) and those randomized outside that period (nonconcurrent controls). Combining these control groups may offer increased statistical power but can lead to bias if analyses do not account for time trends in the response variable. Proposed methods of adjustment for time may increase type I error rates when time trends impact arms unequally or when large, sudden changes to the response rate occur. However, there has been limited exploration of the degree of type I error inflation one can plausibly expect in real-world scenarios.</p><p><strong>Methods: </strong>We use data from the Adaptive COVID-19 Treatment Trial (ACTT) to mimic a realistic platform trial with a remdesivir control arm. We compare four strategies for estimating the effect of interferon beta-1a (the ACTT-3 experimental arm) relative to remdesivir (data from ACTT-1, ACTT-2, and ACTT-3) on recovery and death by day 29: utilizing concurrent controls only (the prespecified analysis), pooling all remdesivir arm data without adjustment (the \"unadjusted-pooled\" analysis), adjusting for time as a categorical variable, and a Bayesian hierarchical model implementation which adjusts for time trends using smoothing techniques (the \"Bayesian time machine\"). We compare type I error rates and relative efficiency of each method in simulation settings based on observed ACTT remdesivir arm data.</p><p><strong>Results: </strong>The unadjusted-pooled approach provided substantially different estimates of the effect of interferon beta-1a relative to remdesivir compared with the concurrent-only and model-based approaches, indicating that changes in recovery and death rates over time were not ignorable across different stages of ACTT. The model-based approaches rely on an assumption of constant treatment effects for each arm in the platform relative to control; error rates more than doubled in settings where this was not satisfied. Relative efficiency of the model-based approaches compared with the concurrent-only analysis was moderate.</p><p><strong>Conclusions: </strong>In simulation settings where key model assumptions were not met, potential efficiency gains from incorporation of nonconcurrent controls were outweighed by the risk of substantial type I error rate inflation. This leads us to advise against these strategies for primary analyses in confirmatory clinical trials, aligning with current FDA guidance advising against comparisons to nonconcurrent controls in COVID-19 settings. The model-based adjustment methods may be useful in other settings, but we recommend performing the concurrent-only analysis as a reference for assessing the degree to which nonconcurrent controls drive results.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"471-481"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143374120","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":"Comparison of adaptive seamless Phase 2/3 designs for dose selection in clinical trials with multiple endpoints.","authors":"Man Jin","doi":"10.1177/17407745251338592","DOIUrl":"10.1177/17407745251338592","url":null,"abstract":"<p><p>Adaptive seamless Phase 2/3 designs provide possible pathways to expedite drug development by combining dose selection and confirmatory evaluation on the selected dose with the control group in the same trial. Various methods have been developed to demonstrate the potential advantages compared to conventional development plan with separate Phase 2 and 3 trials. More practical and complicated situations occur when we want to achieve the goal of combining dose selection and confirmatory evaluation in clinical trials with multiple endpoints. Examples of multiple endpoints include multiple efficacy endpoints needed in the final stage for regulatory submissions. In this article, a few inferential adaptive seamless Phase 2/3 designs have been proposed which can combine dose selection and confirmatory stage in clinical trials evaluating multiple endpoints, including adaptive graph-based multiple testing procedure, adaptive seamless design with graph-based combination test, and seamless design with rank-based Dunnett-adjusted test. Simulations are conducted to confirm the control of the familywise type I error rate with an illustrated example design and assess the power. These designs can preserve the familywise type I error rate, and adaptive graph-based multiple testing procedure is more powerful than the others.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"405-412"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144141624","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":"Proceedings of the University of Pennsylvania 16th annual conference on statistical issues in clinical trials: Optimizing dose selection across the clinical trials spectrum.","authors":"Mary E Putt, Pamela A Shaw","doi":"10.1177/17407745251346836","DOIUrl":"10.1177/17407745251346836","url":null,"abstract":"","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"381-383"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12318153/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144257534","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":"Dose finding in early-phase human immunodeficiency virus type 1 prevention monoclonal antibody clinical trials.","authors":"Yunda Huang, Bo Zhang, Lily Zhang, Bryan T Mayer, Troy Martin, William Hahn, Ollivier Hyrien, Huub C Gelderblom","doi":"10.1177/17407745251347280","DOIUrl":"10.1177/17407745251347280","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Human immunodeficiency virus type 1 remains a major public health burden with 39 million people living with human immunodeficiency virus type 1 and 1.3 million new diagnoses in 2023, despite the recent approval of multiple antiretroviral-based prevention products. While the development of a safe and effective human immunodeficiency virus type 1 vaccine remains the ultimate goal for controlling the worldwide pandemic, progress has been hindered by unprecedented challenges, including the extraordinary genetic diversity of human immunodeficiency virus type 1, the inability of current vaccines to induce broadly reactive antibody responses, and the lack of clear immune correlates of protection to serve as benchmarks for vaccine development. Passive administration of broadly neutralizing monoclonal antibodies that are engineered versions of naturally occurring antibodies has emerged as a potential complement to current human immunodeficiency virus type 1 prevention modalities. These antibodies are isolated from people with human immunodeficiency virus type 1 and can neutralize a broad range of human immunodeficiency virus type 1 viruses. Importantly, advances in antibody engineering have improved the pharmacokinetics of these monoclonal antibodies, offering potential for lower levels and/or less frequent monoclonal antibody dosing with greater feasibility and accessibility for human immunodeficiency virus type 1 prevention. Evaluating monoclonal antibody candidates in human immunodeficiency virus type 1 prevention trials, dose-finding and optimization requires a careful balance between virus-neutralization coverage, cost considerations, and practical constraints. To achieve this, pharmacokinetic modeling of antibody concentrations over time, combined with pharmacodynamics modeling of the relationship between neuralization titers and prevention efficacy, serves as a core of the statistical framework. In addition, for human immunodeficiency virus type 1 monoclonal antibodies administered to individuals without human immunodeficiency virus type, neutralization titers can be reliably predicted from antibody concentrations, owning to the preservation of neutralization function post-administration of these monoclonal antibodies. Within this framework, the antibody-mediated prevention efficacy trials of VRC01, an human immunodeficiency virus type 1 monoclonal antibody, and a meta-analysis of 16 different monoclonal antibodies in non-human primates provided consistent evidence that neutralization titer is a potential pharmacodynamics biomarker of monoclonal antibody prevention efficacy. These findings support the use of integrated pharmacokinetics/pharmacodynamics modeling as a foundation for dose finding of human immunodeficiency virus type 1 monoclonal antibodies. However, in the context of combination monoclonal antibody regimens, additional challenges arise. The total dose cost, operational feasibility, and the influence of dosing ratios on neutraliz","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"442-451"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12370288/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144567250","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":"Adaptive promising zone design for sequential parallel comparison design with continuous outcomes.","authors":"Xinlin Lu, Guogen Shan","doi":"10.1177/17407745241309056","DOIUrl":"10.1177/17407745241309056","url":null,"abstract":"<p><strong>Introduction: </strong>The sequential parallel comparison design has emerged as a valuable tool in clinical trials with high placebo response rates. To further enhance its efficiency and effectiveness, adaptive strategies, such as sample size adjustment and allocation ratio modification can be employed.</p><p><strong>Methods: </strong>We compared the performance of Jennison and Turnbull's method and the Promising Zone approach for sample size adjustment in a two-phase sequential parallel comparison design study. We also evaluated the impact of allocation ratio adjustments using Neyman and Optimal allocation strategies. Various scenarios were simulated to assess the effects of different design parameters, including weight in the test statistic, initial randomization ratio, and interim analysis timing.</p><p><strong>Results: </strong>The Promising Zone approach demonstrated superior or comparable power to Jennison and Turnbull's method at equivalent expected sample sizes while maintaining the intuitive property that more promising interim results lead to smaller required follow-up sample sizes. However, the Promising Zone approach may require a larger maximum possible sample size in some cases. The addition of allocation ratio adjustments offered minimal improvements overall, but showed potential benefits when the variance in the treatment group was larger than that in the placebo group. We also applied our findings to a real-world example from the AVP-923 trial in patients with Alzheimer's disease-related agitation, demonstrating the practical implications of adaptive sequential parallel comparison designs in clinical research.</p><p><strong>Discussion: </strong>Adaptive strategies can significantly enhance the efficiency of sequential parallel comparison designs. The choice between sample size adjustment methods should consider trade-offs between power, expected sample size, and maximum adjusted sample size. Although allocation ratio adjustments showed limited overall impact, they may be beneficial in specific scenarios. Future research should explore the application of these adaptive strategies to binary and survival outcomes in sequential parallel comparison designs.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"482-493"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12290032/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143036899","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":"Response to Cleland and Anzar.","authors":"Janet Wittes, David L DeMets, KyungMann Kim, Dennis G Maki, Marc A Pfeffer, J Michael Gaziano, Panagiota Kitsantas, Charles H Hennekens, Sarah K Wood","doi":"10.1177/17407745251324843","DOIUrl":"10.1177/17407745251324843","url":null,"abstract":"","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"466-467"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143751501","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":"Sixteenth Annual University of Pennsylvania conference on statistical issues in clinical trial/optimizing dose-finding across the clinical trials spectrum (morning panel discussion).","authors":"Ken Cheung, Elizabeth Garrett-Mayer","doi":"10.1177/17407745251351291","DOIUrl":"10.1177/17407745251351291","url":null,"abstract":"","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"413-421"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144567252","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}