Clinical Trials最新文献

{"title":"From the ASPREE investigators: Response to Wittes et al.","authors":"John J McNeil, Andrew M Tonkin, Anne B Newman, Jeff D Williamson, Robyn L Woods, Andrew T Chan, Geoffrey A Donnan, Christopher M Reid, Mark R Nelson, Sara E Espinoza, Walter P Abhayaratna, Raj C Shah, Peter Gibbs, Michael E Ernst, Nigel P Stocks, Lawrence J Beilin, Brenda Kirpach, Joanne Ryan, Rory Wolfe, Anne M Murray, Karen L Margolis","doi":"10.1177/17407745251344560","DOIUrl":"10.1177/17407745251344560","url":null,"abstract":"","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"468-470"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12318158/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144567251","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":"Nature-inspired metaheuristics for optimizing dose-finding and computationally challenging clinical trial designs.","authors":"Weng Kee Wong, Yevgen Ryeznik, Oleksandr Sverdlov, Ping-Yang Chen, Xinying Fang, Ray-Bing Chen, Shouhao Zhou, J Jack Lee","doi":"10.1177/17407745251346396","DOIUrl":"10.1177/17407745251346396","url":null,"abstract":"<p><p>Metaheuristics are commonly used in computer science and engineering to solve optimization problems, but their potential applications in clinical trial design have remained largely unexplored. This article provides a brief overview of metaheuristics and reviews their limited use in clinical trial settings. We focus on nature-inspired metaheuristics and apply one of its exemplary algorithms, the particle swarm optimization (PSO) algorithm, to find phase I/II designs that jointly consider toxicity and efficacy. As a specific application, we demonstrate the utility of PSO in designing optimal dose-finding studies to estimate the optimal biological dose (OBD) for a continuation-ratio model with four parameters under multiple constraints. Our design improves existing designs by protecting patients from receiving doses higher than the unknown maximum tolerated dose and ensuring that the OBD is estimated with high accuracy. In addition, we show the effectiveness of metaheuristics in addressing more computationally challenging design problems by extending Simon's phase II designs to more than two stages and finding more flexible Bayesian optimal phase II designs with enhanced power.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"422-429"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12318163/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144616590","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":"Afternoon discussion: Statistical issues in clinical trials conference on dose finding.","authors":"Anna Heath, Kelley M Kidwell","doi":"10.1177/17407745251350598","DOIUrl":"10.1177/17407745251350598","url":null,"abstract":"<p><p>The adoption of innovative, model-based, and computationally intensive clinical trial designs is challenged by barriers including clinician engagement, regulatory acceptance, dissemination beyond major research institutions, and patient accrual. This session explored strategies to overcome these barriers. Key approaches discussed included the development of user-friendly software and interactive platforms to enhance transparency, open sharing of algorithms, and recognition of software contributions in academic publishing. Building collaborations with stakeholders predisposed to innovation, fostering interdisciplinary communication, and producing complementary methodological and clinical publications were emphasized as essential steps. Practical considerations for trials with small sample sizes included the use of adaptive designs, individualized trials, and alternative optimization strategies when traditional theoretical assumptions are infeasible. A major theme of the discussion was the importance of model assumptions in innovative designs. Questions were raised about the sensitivity of results to these assumptions and the robustness of methods, particularly under limited sample sizes. Addressing this requires extensive simulation studies across varied scenarios to assess operating characteristics. The focus should be on achieving clinically meaningful goals-such as identifying effective dose regions-rather than perfect model specification. Speakers emphasized the need to acknowledge and, when feasible, test assumptions post hoc, integrating such verification as secondary objectives in trial design. An iterative scientific process was encouraged, recognizing that trials not only serve immediate clinical goals but also advance broader scientific understanding. Assumptions provide a principled foundation for methodology, but thoughtful scrutiny of their realism was urged, given the risk of relying on overly strong or untestable premises. The potential of metaheuristic algorithms was highlighted for efficiently identifying optimal designs across different model assumptions, supporting robustness evaluations. Practical implementation should adapt optimal designs to stakeholder needs while preserving acceptable statistical efficiency. In sum, advancing the adoption of innovative designs requires improved communication, infrastructure, and methodological transparency, alongside careful evaluation of model assumptions and robustness.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"452-457"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144505000","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":"Experiences with low-intervention clinical trials-the new category under the European Union Clinical Trials Regulation.","authors":"Amos J de Jong, Helga Gardarsdottir, Yared Santa-Ana-Tellez, Anthonius de Boer, Mira Gp Zuidgeest","doi":"10.1177/17407745241309293","DOIUrl":"10.1177/17407745241309293","url":null,"abstract":"<p><p>Background/AimsLow-intervention clinical trials have been established under the European Union Clinical Trials Regulation (EU 536/2014) which aims to simplify the conduct of clinical trials with authorized medicinal products. There is limited experience with conducting low-intervention trials. Therefore, this study aims to report on experiences and perceived (dis)advantages of low-intervention trials.MethodsWe surveyed representatives of all individual clinical trials registered on the public website of the European Union Clinical Trials Information System between 31 January 2022 and 1 December 2023 that evaluated authorized investigational medicinal products and had at least one investigative site in the European Union. These representatives were approached between June 2023 and January 2024.ResultsWe received 70 responses (response rate 21%). Of the respondents, 31 represented a trial registered as low-intervention trial, and 39 represented a trial not registered as a low-intervention trial (hereafter \"regular trials\"). Simplified clinical trial monitoring and an easier regulatory approval process were perceived as the main advantages of low-intervention trials, with respectively 44% and 34% of the respondents indicating this to be an advantage in low-intervention trials. However, the respondents experienced that stringent and unclear regulatory requirements impeded the conduct of low-intervention trials. Respondents involved with regular trials indicated that 39% of the regular trials met the criteria of a low-intervention trial but were not registered as such, among others due to unfamiliarity with this trial category.ConclusionsWe argue that the simplified procedures for low-intervention trials should be more detailed-for example in regulatory guidance-in the future to further simplify the conduct of clinical trials with authorized investigational medicinal products.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"494-500"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12318156/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143022383","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":"Seamless monotherapy-combination phase I dose-escalation model-based design.","authors":"Libby Daniells, Thomas Jaki, Alimu Dayimu, Nikos Demiris, Basu Bristi, Stefan Symeonides, Pavel Mozgunov","doi":"10.1177/17407745251350604","DOIUrl":"10.1177/17407745251350604","url":null,"abstract":"<p><p>Phase I dose-escalation studies for a single-agent and combination of anti-cancer agents have explored various model-based designs to guide identification of a maximum tolerated dose and recommended phase II dose. This work describes a parallel approach to dose escalation to expedite identification of maximum tolerated doses both for an anti-cancer agent as monotherapy and in combination with another agent. We develop a three-parameter Bayesian logistic regression model that allows for more efficient use of information between monotherapy and combination parts of the study. The model allows the monotherapy and combination data to drive dose escalation of the combination of treatments, reflecting the known dose-toxicity relationship between the monotherapy and combination setting. Through a thorough simulation study in which the proposed model is compared to two comparative approaches, the three-parameter Bayesian logistic regression model is shown to accurately select doses in the target toxicity interval, performing similar to comparative approaches in terms of proportion of target dose/combination selection, while more than halving the proportion of doses selected that were greater than the target toxicity, thereby improving safety concerns.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"430-441"},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12318161/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144616592","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":"Policy recommendations for implementing registries to minimize over-volunteering in Phase I clinical trials.","authors":"Roberto Abadie, Jill A Fisher, Shadreck Mwale, François Bompart, François Hirsch","doi":"10.1177/17407745251360649","DOIUrl":"https://doi.org/10.1177/17407745251360649","url":null,"abstract":"<p><p>Thousands of healthy volunteers enroll in Phase I clinical trials annually, often motivated by financial gain. Some engage in \"over-volunteering\"-participating in multiple studies simultaneously or ignoring washout periods. While serious adverse effects are rare, the experimental nature of Phase I trials, which for \"first-in-human\" studies are designed to trigger adverse events under controlled conditions, makes risks uncertain and unpredictable-a concern that might be compounded by concealed trial participation, which may further increase the likelihood of adverse events. Over-volunteering may also distort trial results through undetected drug interactions. To address this, France, Malaysia, and the UK have implemented national registries to track enrollments and enforce washout periods. Private, for-profit registries, like India's biometric-based system and the US-based Verified Clinical Trials, are used by some clinical research units, mostly private contract research organizations, but their use is not universal and mandatory within countries. Overall, most countries still lack mandatory systems, highlighting the need for broader oversight to protect volunteers and ensure reliable research outcomes. This article discusses the need for and barriers to implementing effective registries and argues that widespread adoption of such registries is critical to protect healthy volunteers from risk of harm while also enhancing trial results' transparency, reliability, and integrity, thereby contributing to developing safer and more effective drugs.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745251360649"},"PeriodicalIF":2.2,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144728482","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":"Salvaging information from paused or stopped clinical studies.","authors":"Davey Smith, Thomas Fleming, Sara Gianella, Elizabeth Halloran, Sharon Hillier, Ira Longini, Laura Smeaton, Victor DeGruttola","doi":"10.1177/17407745251353429","DOIUrl":"10.1177/17407745251353429","url":null,"abstract":"","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745251353429"},"PeriodicalIF":2.2,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12331140/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144616591","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":"Approaches to ensure quality of information provision and consent processes for vaccine clinical trial participation in Sub-Saharan Africa: A scoping review.","authors":"Aitana Juan-Giner, Elena Carrillo-Alvarez, Cristina Enguita-Fernàndez","doi":"10.1177/17407745251346134","DOIUrl":"https://doi.org/10.1177/17407745251346134","url":null,"abstract":"<p><p>Background/AimsTo respect the rights and wellbeing of research participants, these should receive information at all stages of the trial, and procedures should be put in place to ensure a valid consent that promotes an informed, autonomous and voluntary decision-making. This review focuses on the extent and type of evidence available in relation to best practices in the information provision and consent processes for vaccine trials conducted in Sub-Saharan Africa.MethodsAncillary studies or evaluations assessing the information and/or consent processes used in vaccine trials implemented in Sub-Saharan Africa were eligible. The databases PubMed, CINAHL, Scopus, Web of Science, African Index Medicus Google Scholar and ProQuest dissertations and thesis citation index and Open Access Theses and Dissertations were searched, without time limits. Following a deductive approach, relevant data were extracted using an extraction tool and categorised into themes.ResultsThe review included 46 sources reporting results from 37 studies implemented in 13 Sub-Saharan African countries. The studies covered: community engagement (n = 8); informants (n = 7); messages (n = 7); communication tools (n = 3); community groups (n = 4); consent process (n = 11); comprehension (n = 19) and dissemination of results (n = 4). They mostly represented the views of participants or parents of trial participants; researchers and trial site personnel; and community members and representatives, including those with formal informational roles. The studies showed gaps in information and consent processes leading to a lack of understanding and confusion or suspicion. The involvement of community members in information giving was essential. These were able to communicate in culturally-appropriate ways and also increase trust in the trial.ConclusionsThe studies highlight complexities involved in the information and consent processes for vaccine trials implemented in Sub-Saharan Africa. These processes would benefit from a stronger consideration to the context where research takes place, including culture, language, non-biomedical conceptions and power imbalances. The views from ethics review boards were mostly absent.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745251346134"},"PeriodicalIF":2.2,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144505001","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":"An open-source SQL database schema for integrated clinical and translational data management in clinical trials.","authors":"Umar Niazi, Charlotte Stuart, Patricia Soares, Vincent Foure, Gareth Griffiths","doi":"10.1177/17407745241304331","DOIUrl":"10.1177/17407745241304331","url":null,"abstract":"<p><p>Unlocking the power of personalised medicine in oncology hinges on the integration of clinical trial data with translational data (i.e. biospecimen-derived molecular information). This combined analysis allows researchers to tailor treatments to a patient's unique biological makeup. However, current practices within UK Clinical Trials Units present challenges. While clinical data are held in standardised formats, translational data are complex, diverse, and requires specialised storage. This disparity in format creates significant hurdles for researchers aiming to curate, integrate and analyse these datasets effectively. This article proposes a novel solution: an open-source SQL database schema designed specifically for the needs of academic trial units. Inspired by Cancer Research UK's commitment to open data sharing and exemplified by the Southampton Clinical Trials Unit's CONFIRM trial (with over 150,000 clinical data points), this schema offers a cost-effective and practical 'middle ground' between raw data and expensive Secure Data Environments/Trusted Research Environments. By acting as a central hub for both clinical and translational data, the schema facilitates seamless data sharing and analysis. Researchers gain a holistic view of trials, enabling exploration of connections between clinical observations and the molecular underpinnings of treatment response. Detailed instructions for setting up the database are provided. The open-source nature and straightforward design ensure ease of implementation and affordability, while robust security measures safeguard sensitive data. We further showcase how researchers can leverage popular statistical software like R to directly query the database. This approach fosters collaboration within the academic discovery community, ultimately accelerating progress towards personalised cancer therapies.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"374-377"},"PeriodicalIF":2.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12092935/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142884787","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 framework for sequential monitoring of individual N-of-1 trials and combining results across a series of sequentially monitored N-of-1 trials.","authors":"Subodh Selukar, David K Prince, Susanne May","doi":"10.1177/17407745241304284","DOIUrl":"10.1177/17407745241304284","url":null,"abstract":"<p><strong>Background: </strong>N-of-1 trials compare two or more treatment options for a single participant. These trials have been used to study options for chronic conditions such as arthritis and attention deficit hyperactivity disorder. In addition, they have been suggested as a means to study interventions in rare populations that may not be tractable to include in standard clinical trials, such as treatment options for HIV-positive patients in need of organ transplant. Sequential monitoring of accruing data has been well-studied in traditional clinical trials, but these methods have not yet been implemented in N-of-1 trials. However, the option to validly stop an N-of-1 trial early could deliver faster decisions that could directly improve the patient's health.</p><p><strong>Methods: </strong>In this work, we propose and evaluate a framework to (1) facilitate sequential monitoring in individual N-of-1 trials with a continuous outcome and (2) combine results across a series of already-completed sequentially monitored N-of-1 trials. By employing the block structure common to N-of-1 trials, we suggest that existing approaches to sequential monitoring may be employed when data from one N-of-1 trial are analyzed with a linear mixed-effects model. To combine results across a series of already-completed sequentially monitored N-of-1 trials, we propose combining the naive estimates from constituent trials in a random-effects model with inverse-variance weighting. We evaluate these proposals via simulation.</p><p><strong>Results: </strong>We find that type 1 error can be substantially inflated for N-of-1 trials with a small number of planned blocks but can reach the nominal rate for trials with more planned blocks or those with larger numbers of periods per block or by using a <math><mrow><mi>t</mi></mrow></math>-value correction. For those settings with acceptable type 1 error, sequential monitoring results in similar power and on average earlier stopping compared with trials with no sequential monitoring. And, as expected, we find that including a larger number of constituent trials in a series reduces the mean-squared error of the combined point estimator.</p><p><strong>Conclusion: </strong>Under suitable design considerations, our proposed framework for sequential monitoring can support clinicians in providing important decisions earlier, on average, for patients engaged in N-of-1 trials.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"257-266"},"PeriodicalIF":2.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12094905/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142913822","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}