BMC Medical Research Methodology最新文献

{"title":"Mapping power in community engagement: methodological reflections from health emergencies.","authors":"Luisa Enria, Giulia Loffreda, Angus F Tengbeh, Abass S Kamara, Alie D Timbo, Karin Diaconu, Sophie Witter","doi":"10.1186/s12874-026-02905-1","DOIUrl":"10.1186/s12874-026-02905-1","url":null,"abstract":"<p><p>Community engagement is increasingly seen as a key component of public health responses to health emergencies. Recent outbreaks, from Ebola in West Africa to COVID-19 across the world, have highlighted the importance of working through existing structures and identifying trusted local leaders who can help response workers design context-appropriate interventions. However, community engagement efforts often rely on homogenous understandings of 'community' that underestimate the significance of power. This creates a risk of exclusionary practices. In this article, we discuss the use of participatory power mapping workshops as a useful method to identify who has authority and who is trusted by whom, and consider its implications for how we think about trust-building during emergencies. We detail the implementation of this method using participatory workshops conducted in Sierra Leone. We show how these workshops provided granular insights on authority structures and the relationship between power and trust. These discussions highlighted that trust is not homogeneous nor static, and helped kickstart conversations about the role of citizens not simply as recipients of health interventions but also as active participants in how health interventions are designed and delivered. Tracing power dynamics with and within communities can help develop allows us to make power visible in health interventions, maintaining a critical lens on how interventions themselves intervene dynamically on its distribution. In practice, a systematic application of this methodology can encourage more diversified community engagement efforts, and potentially set the foundations for citizen-led collective action around health emergency resilience.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13471247/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148270261","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":"Basket and umbrella trials in pediatric precision medicine: a systematic review of designs, opportunities, and challenges.","authors":"Mohd Rashid Khan, Mariarita Stendardo, Silvia Bressan, Luca Vedovelli, Paola Berchialla, Ileana Baldi, Dario Gregori, Danila Azzolina","doi":"10.1186/s12874-026-02914-0","DOIUrl":"10.1186/s12874-026-02914-0","url":null,"abstract":"<p><strong>Background: </strong>Personalized medicine, driven by genomic insights, has catalyzed the emergence of innovative clinical trial designs such as basket and umbrella trials. These designs are particularly suited for evaluating targeted therapies in biomarker-defined subgroups and rare pediatric conditions where traditional trials face challenges of small sample sizes and disease heterogeneity.</p><p><strong>Objectives: </strong>This systematic review aimed to characterize and synthesize the current literature on basket and umbrella trial designs in pediatric drug development, with a focus on their methodological, regulatory, and statistical aspects.</p><p><strong>Methods: </strong>A systematic search was conducted in the electronic databases PubMed, Scopus, and Web of Science to identify all literature related to basket and umbrella trials. A text mining analysis using unsupervised machine learning technique was performed with relevant articles to automatically identify the primary topics within publications on basket and umbrella trials. A systematic search of PubMed, Scopus, and Web of Science identified 1867 records. After screening and eligibility assessment, 28 studies were included in the final review. Topic modelling using Latent Dirichlet Allocation (LDA) was performed on 76 pertinent articles to identify dominant themes. Statistical convergence, topic coherence, and classification accuracy (> 85%) were validated.</p><p><strong>Results: </strong>A systematic search of PubMed, Scopus, and Web of Science identified 1867 records. After screening and eligibility assessment, 28 studies were included in the final review. Basket trial designs were more prevalent than umbrella trials, particularly in early-phase oncology and rare disease research. Topic modelling using Latent Dirichlet Allocation (LDA) was performed on 76 relevant articles to identify dominant themes. Statistical convergence, topic coherence, and classification accuracy (> 85%) were validated.</p><p><strong>Conclusions: </strong>Basket and umbrella trials offer substantial advantages for pediatric drug development by increasing trial efficiency, enabling precision targeting, and supporting adaptive decision-making. Their success depends on robust statistical planning, careful use of Bayesian methods, and attention to regulatory guidance.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13527913/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148270284","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":"Contemporary practices in scoping review protocol registration: a meta-research analysis of high-impact health journals (2024-2025).","authors":"Fernando César Paraizo Borges, Raissa Tabosa Ferreira, Kevin Henrique Azevedo Duarte, Clarice Wanderley de Sousa, Ana Beatriz Maia Fernandes, Manuella Rocha Boaventura Pinheiro, Thereza Eduarda Medeiros Pimentel, Gustavo Andrade de Oliveira, Manuela Queiroz Reis, Maria Heloísa Pignataro Lange, Maycon Willian Fontes da Costa, Giovanna Kettlen Mendes Silva, Bruno Fontenele Carvalho, Fabio Gamboa Ritto, João Vitor Dos Santos Canellas","doi":"10.1186/s12874-026-02919-9","DOIUrl":"10.1186/s12874-026-02919-9","url":null,"abstract":"<p><strong>Background: </strong>Scoping reviews are widely used across the health sciences to map evidence, clarify concepts, and identify knowledge gaps. Although protocol development and registration are increasingly encouraged, empirical evidence describing contemporary registration practices remains limited.</p><p><strong>Methods: </strong>This study aimed to evaluate current practices in scoping review protocol registration and reporting in high-impact health sciences journals published between 2024 and 2025. We conducted an empirical meta-research study of scoping reviews published in first-quartile journals according to the Journal Citation Reports and indexed in PubMed. Data were extracted independently using a standardized form and included protocol registration status, registry platform, public accessibility, peer-reviewed protocol publication, reported protocol components, and methodological guidance cited. Descriptive analyses were used to assess registration patterns and methodological consistency. Multivariable logistic regression models were fitted to explore factors associated with protocol registration reporting and the presence of a peer-reviewed protocol.</p><p><strong>Results: </strong>Among 2,546 screened records, 1,267 scoping reviews underwent full data extraction. Overall, 549 reviews reported a registered protocol, of which 483 were publicly accessible and included in the analysis. Protocol registration was identified in 43.3% of scoping reviews, while peer-reviewed protocol publication was rare (5.1%). Most protocols were registered on the Open Science Framework (OSF) (n = 478). Protocol content frequently included core methodological elements but also reported additional items beyond those addressed in the JBI Manual for Evidence Synthesis. Although many methodological documents were cited, only two provided explicit guidance for scoping review protocol development. Post hoc analyses identified substantial heterogeneity in protocol registration practices across journals, publishers, and corresponding author countries, suggesting that registration practices are influenced by a combination of editorial policies, local research cultures, and differing methodological perspectives.</p><p><strong>Conclusion: </strong>Protocol registration practices in scoping reviews remain heterogeneous across high-impact health sciences journals. The findings demonstrate substantial variability in protocol content, registration approaches, and use of methodological guidance, while reinforcing ongoing methodological discussions regarding protocol registration and standardization in scoping reviews.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13528004/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148270276","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":"Estimating the hazard ratio of excess mortality using a microsimulation framework with golden section search calibration: a methodological primer.","authors":"Reda Rhellab, Maximiliaan L Notenboom, Jonathan R G Etnel, Jolanda Kluin, Ewout W Steyerberg, Johanna J M Takkenberg, Kevin M Veen","doi":"10.1186/s12874-026-02910-4","DOIUrl":"10.1186/s12874-026-02910-4","url":null,"abstract":"<p><strong>Background: </strong>Excess mortality in a population with a disease can be defined as extra mortality observed compared to the matched-general population, and expressed as a hazard ratio (HR). While excess hazard models and cure models exist, these commonly need patient-level data. In this paper, we show a method for estimation of excess mortality with aggregated data.</p><p><strong>Methods: </strong>We detail the estimation of excess mortality in a microsimulation framework using the golden section search algorithm. This iterative algorithm identifies a local minimum within a predefined search interval. The overall excess mortality and residual excess (remaining mortality after accounting for modelled events) is estimated by calibrating microsimulation-derived survival curves to observed patient-sample survival curves. R code is provided. We apply the method to a study of aortic valve repair in non-elderly adults.</p><p><strong>Results: </strong>The method enabled efficient estimation of excess mortality, expressed as overall and time-dependent hazard ratios through a piecewise function. The estimated excess mortality HR in the case-study was 2.70 without accounting from modelled events and 2.43 while accounting for modelled events, and the HR increased over time (1.23; 2.32; 5.50 at 0-60 months, 61-120 months and 121-188 months, respectively).</p><p><strong>Conclusions: </strong>This microsimulation framework provides an accessible, efficient method for estimating time-varying excess mortality hazard ratios, allowing for estimation of residual excess mortality, which excludes mortality due to modelled events, using only aggregated input data.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13504745/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148263393","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":"Recruiting children and young people with vision impairment for clinical research - experience from the SeeMyLife study.","authors":"Lisa Gittel, Robert P Finger, Verena Richter, Asmaa Cadi, Nicole Beck, Alice Colombo, Arvydas Gelžinis, Erika Gustafierro, Francesca Incagli, Agnė Kručaitė, Martina Lanza, Matilde Leonardi, Bart P Leroy, Dominika Nowakowska, Katarzyna Nowomiejska, Francesco Parmeggiani, Valérie Pelletier, Anais Philippe, Maria Eleonora Reffo, Yaël Slaghmuylder, Agnese Suppiej, Chloé Laeng, Reda Žemaitienė, Hélène Dollfus, Jan H Terheyden","doi":"10.1186/s12874-026-02915-z","DOIUrl":"10.1186/s12874-026-02915-z","url":null,"abstract":"<p><strong>Background: </strong>Effective participant recruitment is crucial for the success of clinical trials, yet little is known about facilitators and barriers to recruitment in pediatric populations with visual impairment. Understanding which methods yield the highest participant engagement can help optimize recruitment efforts and improve study outcomes. Thus, we assessed factors associated with recruitment in the SeeMyLife study, a European multi-center cohort study about quality of life and participation of children and young people with visual impairment.</p><p><strong>Methods: </strong>Data on the perceived effectiveness of recruitment strategies were collected from principal investigators, study coordinators, clinical and research staff using an online survey. Additional information on recruitment approaches was obtained through document analysis of study-related communications, including e-mails and meeting minutes. Descriptive statistics were used to summarize recruitment rates and perceived effectiveness scores. Open-ended responses regarding recruitment challenges were analyzed thematically to identify common barriers and facilitators.</p><p><strong>Results: </strong>Seventeen clinical and research staff members from six countries participated in the survey and shared their insights and experience with participant recruitment. In total, study staff reported using twelve distinct recruitment sources to enhance participant enrolment. These sources were grouped into three broad categories: healthcare settings, community engagement and educational settings, and professional and system-level approaches. The recruitment of participants using the hospital information system was perceived as the most effective recruitment strategy, used by 71% of respondents. Other highly ranked sources included pediatric visual rehabilitation centers, patient associations, and affiliated university ophthalmology departments, where staff actively presented the study to their patients and referred eligible participants. Commonly reported recruitment challenges included restrictive inclusion criteria, limited parental responsiveness, concerns about the impact of study participation on children's well-being, and institutional barriers.</p><p><strong>Conclusions: </strong>Successful strategies for enrolling children and young people with visual impairment into clinical research include direct interactions between clinical staff and families, likely due to established trust, easier identification of eligible participants, and clearer communication about the study. In contrast, recruitment approaches outside clinical care settings were perceived as less effective. These findings highlight the importance of integrating recruitment efforts within established healthcare networks when conducting pediatric vision impairment research.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"26 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13270738/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148263376","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 use and methodological reporting of large language models in qualitative research: a scoping review.","authors":"Christian Kempny, Julian Frings, Paul Rust, Sven Meister, Leonard Fehring","doi":"10.1186/s12874-026-02913-1","DOIUrl":"10.1186/s12874-026-02913-1","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Large language models (LLMs) are being integrated into qualitative research processes, yet the scope, function, and reporting quality of their use remain poorly understood. Existing reporting guidelines for qualitative research, including for example the Consolidated Criteria for Reporting Qualitative Research (COREQ), provide minimal guidance for documenting LLM use. This scoping review provides an overview of the emerging use of LLMs applications in qualitative research and assesses the associated reporting practices.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A scoping review was conducted following the PRISMA-ScR guidelines and the Joanna Briggs Institute methodological framework. Five databases (PubMed, CINAHL, PsycINFO, Business Source Premier, and Scopus) were searched for peer-reviewed empirical studies published between January 2020 and May 2025 that employed at least one LLM in a substantive qualitative research stage. The search yielded 5,049 records, of which 4,201 remained after duplicate removal. Studies were screened independently by multiple reviewers, and data were extracted using a standardized template capturing study metadata, methodological characteristics, and comprehensive LLM implementation details.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Seventy-five studies were included. OpenAI GPT models dominated the field, appearing in 93% of studies. LLMs were applied across the full spectrum of qualitative research, with coding assistance (n = 43) and theme identification (n = 41) as the most common applications. Thematic analysis was the predominant qualitative method (n = 38), and content analysis (n = 12). Technical reporting was highly inconsistent: only 13 studies reported temperature settings, 12 documented context length, and 4 provided top_p values. Approximately half of studies (45%, n = 34) did not specify the deployment configuration (API, web interface, or local), and 75% (n = 56) reported no parameter settings at all. While 61% of studies provided complete or partial prompts, 13% reported no prompting details. Agreement rates between LLM and human coders ranged from 36% to 99%, reflecting substantial variation related to task complexity, prompt engineering quality, and validation rigor. Nearly all studies (95%) discussed ethical considerations, and 97% incorporated human verification of AI outputs.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Discussion: &lt;/strong&gt;LLMs have been adopted across qualitative research workflows, yet critical methodological details are frequently underreported, undermining comparability. The findings highlight an urgent need for dedicated reporting guidelines, such as the COREQ + LLM extension, to ensure that LLM-assisted qualitative research meets standards of transparency, rigor, and interpretive depth. Future research should address the predominance of proprietary models, the limited evidence for non-English contexts, and the need for systematic comparison of models, prompting strategies, and validation ap","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"26 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13270661/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148257346","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 dynamic perspective on clinical treatment evaluation using dynamic structural equation modeling.","authors":"Shuncheng He, Wooyeol Lee","doi":"10.1186/s12874-026-02921-1","DOIUrl":"10.1186/s12874-026-02921-1","url":null,"abstract":"<p><strong>Background: </strong>Conventional evaluations of psychological treatment effects have primarily focused on changes in average symptom levels, thereby overlooking intra-individual variability. However, evidence from intensive longitudinal data demonstrates that psychological states fluctuate dynamically over time, suggesting that treatment effects may manifest not only in mean levels but also in temporal instability. It is imperative to acknowledge the impact of variability on treatment efficacy, particularly in the context of clinical intervention research. Failure to account for this variability can lead to the misinterpretation of treatment outcomes, potentially compromising the accuracy of research findings.</p><p><strong>Methods: </strong>The proposed methodology, under a randomized controlled trial design, is intended to facilitate the dynamic assessment of clinical treatment. The present method is based on a dynamic structural equation model framework, which allows individual-specific residual variances to be contingent on treatment allocation, thereby facilitating the direct evaluation of the impact of treatment on psychological instability. The proposed framework is illustrated with an empirical case, and the performance of dynamic treatment assessment parameters is systematically evaluated under different conditions using Monte Carlo simulations.</p><p><strong>Results: </strong>Empirical evidence has demonstrated the efficacy of the dynamic structural equation model in capturing variations in dynamic treatment effects between experimental and control groups. The simulation results further indicate that this method provides accurate parameter recovery and stable estimates under various conditions, thereby supporting its robustness and flexibility for simulating dynamic treatment effects in intensive longitudinal data settings.</p><p><strong>Conclusions: </strong>The present study proposes a novel perspective on dynamic treatment evaluation based on a dynamic structural equation model framework. By conceptualizing residual variance as a dynamic outcome, this framework facilitates a more nuanced comprehension of clinical change and offers a significant extension to conventional treatment-evaluation methods in randomized controlled trials.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13501713/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148257302","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":"Automated tools for evidence quality assessment: a scoping review.","authors":"Jiayi Huang, Xinxin Deng, Liying Zhou, Junliang Tao, Cui Liang, Kehu Yang, Xiuxia Li","doi":"10.1186/s12874-026-02868-3","DOIUrl":"10.1186/s12874-026-02868-3","url":null,"abstract":"<p><strong>Background: </strong>Evidence quality assessment is critical for informed public health decision-making, but manual approaches are time-consuming and subject to variability. Automated support tools have been proposed to improve efficiency and consistency, yet their current status has not been comprehensively or systematically mapped.</p><p><strong>Objective: </strong>To identify or map the characteristics, performance, and limitations of existing automated tools for evidence quality assessment.</p><p><strong>Methods: </strong>Following the JBI methodology and PRISMA-ScR checklist, we searched 6 English and 4 Chinese databases from their inception to February 9, 2025, to identify studies evaluating automated tools for evidence quality assessment. Eligible studies included original research on tool development, application, or validation. Study characteristics (e.g., year, country, design, tool type, technical features, reliability, and validity) were extracted and summarized descriptively.</p><p><strong>Results: </strong>Twenty studies were included, most from the United Kingdom (30%), Canada (25%), and Australia (15%). Observational designs predominated (75%), with only 10% randomized controlled trials (RCTs). Twelve distinct tools were identified, of which 65% were publicly available. 58% of the tools were developed for RCTs, while 50% remained experimental and required human oversight. Reported outcomes focused on sensitivity, specificity, precision, efficiency, and consistency. Despite promising results, external validity and scalability were limited.</p><p><strong>Conclusion: </strong>Automated tools for evidence quality assessment show potential to enhance efficiency and consistency but remain restricted in applicability. Current tools are often tailored to clinical trials and require human supervision. Broader adaptation and rigorous validation are needed before such tools can be widely integrated into public health decision-making.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13495222/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148257305","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 predictive power of first recruits to commercial trial performance.","authors":"Martin J Batty, James M S Wason, David J Ward, Effrossyni Gkrania-Klotsas","doi":"10.1186/s12874-026-02907-z","DOIUrl":"10.1186/s12874-026-02907-z","url":null,"abstract":"<p><strong>Background: </strong>The United Kingdom has a history of world-leading health research, showcased most recently in its response to the Covid pandemic. However, while the UK's performance in academic clinical research remains strong, its global position in the delivery of commercial research has declined. In 2023 Lord O'Shaughnessy reviewed the barriers and drivers to the delivery of commercial trials, identifying 27 recommendations to improve commercial trial performance. Highlighted within the report was the importance of the UK being globally competitive in the delivery of its trials, including study set up and approval times.</p><p><strong>Methods: </strong>A dataset from the National Institute for Health and Care Research (NIHR), containing 28,188 site observations from 5,421 unique commercial studies provided data on first recruits to commercial studies spanning a 15-year period from 2010 to 2024. Where there were issues with data quality or reliability, data were cleaned, leaving 23,622 observations from 4,849 studies for analysis. Logistic regression and generalised linear mixed effects models were applied to determine whether sites that recruited their first participant to commercial studies more quickly had a higher probability of recruiting to time and target.</p><p><strong>Results: </strong>Sites that recruited their first participant more quickly were significantly more likely to recruit to time and target (RTT); (odds ratio per one-month increase in time 0.88, 95% CI 0.87 to 0.89, p < 0.0001). The model suggests that the predicted probability of RTT for a site falls to < 50% if it takes more than 8 months to recruit its first participant. A secondary analysis showed a highly significant increase in probability of a site meeting RTT if they recruited the 'first' Global, European or UK participants onto a study (odds ratio 2.96, 95% CI 2.20 to 4.05, p < 0.0001).</p><p><strong>Conclusions: </strong>Sites that recruit first participants more quickly are more likely to recruit to time and target in commercial studies. This is likely to lead to them being selected by sponsors to participate in subsequent studies, increasing research opportunities for their patients and revenue for their organisation. Achieving quicker firsts requires proactive planning and coordination by R&D departments and study teams. Setting up sites in a timely manner is a key determinant of successful study delivery and a key component of the UK government's 10-Year Health Plan for England and Life Sciences Sector Plan.</p><p><strong>Trial registration: </strong>Not applicable.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13488190/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148249066","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":"Semiparametric accelerated failure time models with time-varying covariates under partly interval censoring.","authors":"Aishwarya Bhaskaran, Ding Ma, Benoit Liquet, Angela Hong, Stephane Heritier, Serigne N Lo, Jun Ma","doi":"10.1186/s12874-026-02916-y","DOIUrl":"10.1186/s12874-026-02916-y","url":null,"abstract":"<p><p>In survival analysis, accelerated failure time (AFT) models are often used as an alternative to the Cox model. A benefit of the AFT model is that it provides a direct link between covariates and event times, and therefore offers meaningful interpretations of the regression coefficients directly on the event times. This paper is motivated by a randomised clinical trial dataset on advanced melanoma patients, in which the event times are interval-censored and one of the covariates in the model is time-varying. To allow direct assessment of the effects of covariates on the event time, we aim to fit an AFT model. However, there are no readily available computational packages for AFT models with time-varying covariates and interval censoring. In this paper, we propose a maximum penalised likelihood approach for fitting such models. The effectiveness of our method is demonstrated through extensive simulations. Also, an application to the above mentioned melanoma dataset is used to demonstrate practical utility of our method.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":" ","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13487988/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148249032","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}