BMC Medical Research Methodology最新文献

{"title":"Overcoming challenges in prevalence meta-analysis: the case for the Freeman-Tukey transform.","authors":"Jazeel Abdulmajeed, Tawanda Chivese, Suhail A R Doi","doi":"10.1186/s12874-025-02527-z","DOIUrl":"10.1186/s12874-025-02527-z","url":null,"abstract":"<p><strong>Background: </strong>Traditional statistical methods assume normally distributed continuous variables, making them unsuitable for analysis of prevalence proportions. To address this problem, two commonly utilized variance-stabilizing transformations (logit and Freeman-Tukey) are empirically evaluated in this study to provide clarity on the optimal choice among these transforms for researchers.</p><p><strong>Methods: </strong>Simulated datasets were created using multiple Monte Carlo simulations, with varying input parameters to examine transformation estimator performance under varying scenarios. Additionally, the research delved into how sample size and proportion influenced the variability of the Freeman-Tukey transform. Performance was evaluated for both single prevalence proportions (coverage, interval width and variation over sample size) as well as for meta-analysis of prevalence (absolute mean deviation of pooled proportions, coverage and interval width).</p><p><strong>Results: </strong>For extreme proportions we found that the Freeman-Tukey transform provides better coverage and narrower intervals compared to the logit transformation, and for non-extreme proportions, both transformations demonstrated similar performance in terms of single proportions. The variability of Freeman-Tukey transformed proportions with sample size is only seen when the range of proportions under scrutiny are very small (~ 0.005), and the variability of the Freeman-Tukey transform's value occurs in the third decimal place (0.007). In meta-analysis, the Freeman-Tukey transformation consistently showed lower absolute deviation from the population parameter, with narrower confidence intervals, and improved coverage compared to the same meta-analyses using the logit transformation.</p><p><strong>Conclusion: </strong>The results suggest that the Freeman-Tukey transform is to be preferred over the logit transformation in the meta-analysis of prevalence.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"89"},"PeriodicalIF":3.9,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11971753/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143787742","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":"Evaluation of intervention systematic reviews on chronic non-communicable diseases and lifestyle risk factors in low-middle income countries: meta-research.","authors":"Beatriz Hadassa Silva Cano, Giulianna Faypher Morena Vieira da Silva, Gustavo Dias Bottari, Eduarda Letícia Balbinot, Maria Laura Rodrigues Uggioni, Leonardo Roever, Maria Inês da Rosa, Antonio José Grande","doi":"10.1186/s12874-025-02501-9","DOIUrl":"10.1186/s12874-025-02501-9","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Systematic Reviews (SRs) rigorously synthesize findings on a theme, but some articles with this design are redundant due to errors and conflicts. Meta-research aims to rigorously analyze research, assessing SRs' methodological quality and result reliability. This study evaluates SRs' overall quality in low- and middle-income countries (LMICs) on chronic non-communicable Diseases (NCDs) and key modifiable risk factors, using assessment tools.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A search strategy was conducted in the following databases: MEDLINE (via PubMed), Embase, (via Elsevier), Cochrane Library, and Grey Literature for published studies from January 1, 2014 - April 5, 2024. SRs addressing the association between at least one of the four most important modifiable behavioral risk factors (tobacco use, inadequate diet, alcohol consumption, and physical inactivity) and chronic NCDs in populations classified as LMICs according to the 'World Bank list of countries' were included. The selected studies were imported into the EndNote 20 software and analyzed using a form for the extraction of their main data and four tools were chosen to assess each of the most important domains of scientific evidence: Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) for article writing; Template for Intervention Description and Replication (TIDieR) for intervention description; A Measurement Tool for Evaluating Systematic Reviews (AMSTAR-2) for methodological assessment; and Grading of Recommendations, Assessment, Development and Evaluation (GRADE) for certainty of evidence.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Nine studies were included in this analysis. The average Overall Score on the PRISMA 2020 checklist was 13.5 for articles published before 2020 and 25.67 for those published after 2020. TIDieR analysis revealed complete correspondence (100%) for item 'Brief Name', while other items, like 'Why' (89%), and 'What', 'Who Provided', and 'How' (78%), were partially met but significantly so. Regarding AMSTAR-2 criteria, only one study fulfilled all critical items, meeting item 7 by providing a detailed list of excluded studies and justifying each exclusion motive. Additionally, among critical items applicable to multiple articles, only item 11 was consistently fulfilled by all studies. In the final classification, one article achieved a moderate quality rating, three were critically low quality, and five had low quality among the nine evaluated articles. In the GRADE tool evaluation, limitations resulted in estimations for only 19 outcomes and 8 intervention-exposure sets.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;The results demonstrated that the writing of recent scientific articles meets most of the PRISMA 2020 criteria, with a checklist being the most used tool. Interventions and exposure were also very well reported, with the TIDieR checklist not being cited in any study as a guiding tool. AMSTAR-2 revealed a methodologi","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"90"},"PeriodicalIF":3.9,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11972496/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143787737","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":"Public engagement with science: an inclusive approach to innovate in health research with real-world data.","authors":"Adalton Dos Anjos Fonseca, Valentina Martufi, Walisson Angélico de Araújo, Denise Moraes Pimenta, Acácia Mayra Pereira de Lima, Juliana Araújo Prata de Faria, Danilo Luis Cerqueira Dias, Eduarda Ferreira Dos Anjos, Maria Del Pillar Flores Quispe, Gisela Rodrigues Piloto, Vivian Mitiko Queiroz Lima, Felipe Ferré, Marcos Antônio Gêmeos Almeida Sampaio, Erika de Souza Lopes, Blanda Helena de Mello, Diego Cavalcante Teixeira Daltro, Mariana Rodrigues Sebastião de Almeida, Raiza Tourinho Lima, Elzo Pereira Pinto Junior, Mauricio L Barreto, Maria Yury T Ichihara","doi":"10.1186/s12874-025-02530-4","DOIUrl":"10.1186/s12874-025-02530-4","url":null,"abstract":"<p><strong>Background: </strong>Public engagement with science (PES) initiatives in health research that use big data to analyze social inequalities in health requires strategies and methods adapted to the contexts of countries in the Global South. This paper aims to examine how, in Brazil - a country with a strong tradition of social participation in research and public policymaking-two research projects from a center that utilizes administrative and real-world data incorporate inclusion and diversity as key elements to connect knowledge production with real-world challenges.</p><p><strong>Methods: </strong>The study analyzes how two Cidacs research projects - one related to Primary Health Care (PHC) and the other to Data Interoperability-involved members of the public throughout their implementation. Both projects jointly engaged 18 participants, including community representatives, health professionals, and public sector managers. A case report approach is being employed in this paper to systematically document PES experiences based on a predefined script, covering context, methodology, activities, audiences, and ethical aspects. Data were collected through participant observation and listening during engagement activities, which facilitated dialogue between participants and researchers, as well as through follow-up questionnaires and subsequent discussions. This paper itself emerged from this collaborative process, including with some PES participants as co-authors.</p><p><strong>Results: </strong>The participants' collaboration impacted the researchers' decisions, providing a closer understanding of the challenges faced by the participants in their daily work in relation to each of the research themes. Furthermore, these discussions resulted in the establishment of partnerships for new initiatives. The participants highlighted that, in addition to the opportunity to contribute to the development of scientific research, they acquired new knowledge from their contact with the research teams.</p><p><strong>Conclusions: </strong>The diversity of social groups and the inclusion of different perspectives in research projects mobilized by PES have the potential to promote innovations in research processes and results, as well as have social impact. The potential for applicability of scientific information is expanded since it is more connected to the real world, and the participants themselves drive the dissemination process.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"88"},"PeriodicalIF":3.9,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11970009/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143787756","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":"Defining expert opinion in clinical guidelines: insights from 98 scientific societies - a methodological study.","authors":"Blin Nagavci, Zsófia Gáspár, Botond Lakatos","doi":"10.1186/s12874-025-02534-0","DOIUrl":"10.1186/s12874-025-02534-0","url":null,"abstract":"<p><strong>Background: </strong>The use of Expert Opinion (EO) in clinical guidelines is highly variable and lacks standardization, leading to ongoing controversy. A clear and universally accepted definition of EO is also lacking. To date, no research has systematically assessed how guideline-developing societies conceptualize and apply EO. This study aims to map methodological manuals, evaluate their rationale for EO use, examine its foundations, and synthesize a comprehensive definition.</p><p><strong>Methods: </strong>Systematic searches for clinical guidelines were conducted in PubMed to identify guideline-developing societies, supplemented by additional searches. Systematic searches were then conducted to identify methodological manuals from these societies. Screening was performed independently by two reviewers, and data extraction was conducted using piloted forms. Findings were summarized through narrative evidence synthesis using descriptive statistics.</p><p><strong>Results: </strong>A total of 473 national and international societies were identified, and methodological manuals from 98 societies were mapped and analysed. These manuals included 61 handbooks, 29 journal articles, and 8 websites. EO is mentioned in 65 (66%) manuals, with substantial variation in its utilization and terminology. EO is primarily used in two contexts: (1) filling evidence gaps (72%), and (2) interpreting existing evidence (8%). In the remaining 20%, EO use is unclear. Five main foundations could be identified as a potential basis for EO (clinical experience, indirect evidence, low-quality evidence, mechanism-based reasoning, and expert evidence/witnesses). Based on these findings, a novel comprehensive definition of EO was synthesized.</p><p><strong>Conclusions: </strong>EO is widely used to address evidence gaps and interpret ambiguous evidence, underscoring its importance in guideline development. However, the variability in its application and conceptualization across societies highlights the need for standardization. We propose a comprehensive EO definition as a first step towards standardization to improve consistency, transparency, and clinical decision-making.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"87"},"PeriodicalIF":3.9,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11963610/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143771256","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":"Combining treatment effects from mixed populations in meta-analysis: a review of methods.","authors":"Lorna Wheaton, Sandro Gsteiger, Stephanie Hubbard, Sylwia Bujkiewicz","doi":"10.1186/s12874-025-02507-3","DOIUrl":"10.1186/s12874-025-02507-3","url":null,"abstract":"<p><strong>Background: </strong>Meta-analysis is a useful method for combining evidence from multiple studies to detect treatment effects that could perhaps not be identified in a single study. While traditionally meta-analysis has assumed that populations of included studies are comparable, over recent years the development of precision medicine has led to identification of predictive genetic biomarkers which has resulted in trials conducted in mixed biomarker populations. For example, early trials may be conducted in patients with any biomarker status with no subgroup analysis, later trials may be conducted in patients with any biomarker status and subgroup analysis, and most recent trials may be conducted in biomarker-positive patients only. This poses a problem for traditional meta-analysis methods which rely on the assumption of somewhat comparable populations across studies. In this review, we provide a background to meta-analysis methods allowing for synthesis of data with mixed biomarker populations across trials.</p><p><strong>Methods: </strong>For the methodological review, PubMed was searched to identify methodological papers on evidence synthesis for mixed populations. Several identified methods were applied to an illustrative example in metastatic colorectal cancer.</p><p><strong>Results: </strong>We identified eight methods for evidence synthesis of mixed populations where three methods are applicable to pairwise meta-analysis using aggregate data (AD), three methods are applicable to network meta-analysis using AD, and two methods are applicable to network meta-analysis using AD and individual participant data (IPD). The identified methods are described, including a discussion of the benefits and limitations of each method.</p><p><strong>Conclusions: </strong>Methods for synthesis of data from mixed populations are split into methods which use (a) AD, (b) IPD, and (c) both AD and IPD. While methods which utilise IPD achieve superior statistical qualities, this is at the expense of ease of access to the data. Furthermore, it is important to consider the context of the decision problem in order to select the most appropriate modelling framework.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"86"},"PeriodicalIF":3.9,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11963434/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143771235","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":"Reducing risk of bias in interventional studies during their design and conduct: a scoping review.","authors":"Zhilin Ren, Angela Claire Webster, Kylie Elizabeth Hunter, Jiexin Zhang, Yi Yao, Ava Grace Tan-Koay, Aidan Christopher Tan","doi":"10.1186/s12874-025-02467-8","DOIUrl":"10.1186/s12874-025-02467-8","url":null,"abstract":"<p><strong>Background: </strong>Interventional studies are intended to provide robust evidence. Yet poorly designed or conducted studies may bias research results and skew resulting evidence. While there have been advances in the assessment of risk of bias, it is unclear how to intervene against risks of bias during study design and conduct.</p><p><strong>Objective: </strong>To identify interventions to reduce or predict risk of bias in interventional studies during their design and conduct.</p><p><strong>Search strategy: </strong>For this scoping review, we searched three electronic bibliographic databases (MEDLINE, Embase, and Cochrane Library) and nine grey literature sources and Google from in September 2024. This was supplemented by a natural language processing fuzzy matching search of the top 2000 relevant publications in the electronic bibliographic databases. Publications were included if they described the implementation and effectiveness of an intervention during study design or conduct aimed at reducing risk of bias in interventional studies. The characteristics and effect of the interventions were recorded.</p><p><strong>Result: </strong>We identified, and reviewed the title and abstracts of, a total of 41,793 publications, reports, documents and grey literature, with 24,677 from electronic bibliographic databases and 17,140 from grey literature sources. There were 67 publications from bibliographic databases and 24 items from grey literature that were considered potentially eligible for inclusion, and the full-text of these were reviewed. Only three studies met the inclusion criteria. The first intervention was offering education and training to researchers during study design. This training included the implementation of a more rigorous participant screening process and systematic participant tracking program that reduced loss to follow-up and missing data, particularly for long-term follow-up trials. The second intervention was introducing an independent clinical events committee during study conduct. This was intended to mitigate bias due to conflicts of interest affecting the analysis and interpretation of results. The third intervention was to provide participants with financial incentives in randomized controlled trials, so that participants could more actively accomplish the requirements of the trials.</p><p><strong>Conclusion: </strong>Despite the major impact of risk of bias on study outcomes, there are few empirical interventions to address this during study design or conduct.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"85"},"PeriodicalIF":3.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11963288/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143762941","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":"Longitudinal tracking of healthcare professionals: a methodological scoping review.","authors":"Yingxi Zhao, Xuan Li, Attakrit Leckcivilize, Mike English","doi":"10.1186/s12874-025-02533-1","DOIUrl":"10.1186/s12874-025-02533-1","url":null,"abstract":"<p><strong>Background: </strong>Tracking and understanding the progress and experiences of health workers and the outcomes of workforce decisions are essential for evidence-based workforce planning. In this scoping review, we aim to identify longitudinal studies that prospectively tracked healthcare professionals and that specifically focused on workforce issues such as career preferences, choices, and working conditions, and summarise the different approaches and methods used for tracking.</p><p><strong>Methods: </strong>We searched MEDLINE, Embase, Global Health, PsycINFO, CINAHL, Education Resource Information Center (ERIC), EconLit and the Cochrane Library for articles published between 2000-2022 that longitudinally tracked doctors, nurses, midwives, physician associates/assistants. We further compared articles and conducted a back-and-forward citation search to identify longitudinal tracking studies which sometimes have multiple published articles. We developed a typology of the different tracking approaches, and summarised the major areas assessed and tracked by different studies.</p><p><strong>Results: </strong>We identified and analysed 263 longitudinal tracking studies. Based on population recruitment and follow-up methods, we grouped studies into seven categories (cohort studies, multiple-cohort studies, baseline and data linkage studies, baseline and short repeated measure studies, baseline-only studies, data linkage-only studies and repeated survey studies). The majority of studies included used a cohort or multiple-cohort design (n = 180), and several others also used data linkage (n = 45) and repeated measure approaches (n = 24). Sixty-two studies recruited participants while they were students and followed them until they became the active workforce, and nearly half of the included studies started directly from the active workforce stage. Most of the included studies examined workforce issues including employment status, preference or intention (to leave/remain/migrate, specific speciality or location etc.), and work environment, however there was a lack of widely used measurement tools for workforce issues. Additionally, nearly 40% examined wellbeing issues and a subset (20%) examined physical health in the context of workforce-related issues.</p><p><strong>Conclusion: </strong>We described a large number of different healthcare professional longitudinal tracking studies. In order for longitudinal tracking to contribute to effective workforce planning, we recommend employing a mix of cohort and data linkage approaches to collect data across the different stages of the workforce 'working lifespan', and using and continuing to test standardised measurement instruments to better capture experiences related to workforce and wellbeing.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"83"},"PeriodicalIF":3.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11959867/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143762937","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":"Understanding multimorbidity: insights with graphical models.","authors":"Erika Banzato, Alberto Roverato, Alessandra Buja, Giovanna Boccuzzo","doi":"10.1186/s12874-025-02536-y","DOIUrl":"10.1186/s12874-025-02536-y","url":null,"abstract":"<p><strong>Background: </strong>The use of graphical models in the multimorbidity context is increasing in popularity due to their intuitive visualization of the results. A comprehensive understanding of the model itself is essential for its effective utilization and optimal application. This article is a practical guide on the use of graphical models to better understand multimorbidity. It provides a tutorial with a focus on the interpretation of the model structure and of the parameter values. In this study, we analyze data related to a cohort of 214,401 individuals, who were assisted by the Local Health Unit of the province of Padova (north-eastern Italy), collecting information from hospital discharge forms.</p><p><strong>Methods: </strong>We explain some fundamental concepts, with special attention to the difference between marginal and conditional associations. We emphasize the importance of considering multimorbidity as a network, where the variables involved are part of an interconnected system of interactions, to correct for spurious effects in the analysis. We show how to analyze the network structure learned from the data by introducing and explaining some centrality measures. Finally, we compare the model obtained by adjusting for population characteristics with the results of a stratified analysis.</p><p><strong>Results: </strong>Using examples from the estimated model, we demonstrate the key differences between marginal and conditional associations. Specifically, we show that, marginally, all variables appear associated, while this is not the case when considering conditional associations, where many variables appear to be conditionally independent given the others. We present the results from the analysis of centrality indices, revealing that cardiovascular diseases occupy a central position in the network, unlike more peripheral conditions such as sensory organ diseases. Finally, we illustrate the differences between networks estimated in subpopulations, highlighting how disease associations vary across different groups.</p><p><strong>Conclusion: </strong>Graphical models are a versatile tool for analyzing multimorbidity, offering insights into disease associations while controlling for the effects of other variables. This paper provides an overview of graphical models without focusing on detailed methodology, highlighting their utility in understanding network structures and potential subgroup differences, such as gender-related variations in multimorbidity patterns.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"84"},"PeriodicalIF":3.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11959969/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143762945","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":"Navigating challenges in pediatric trial conduct: integrating bayesian sequential design with semiparametric elicitation for handling primary and secondary endpoints.","authors":"Danila Azzolina, Ileana Baldi, Silvia Bressan, Mohd Rashid Khan, Liviana Da Dalt, Dario Gregori, Paola Berchialla","doi":"10.1186/s12874-025-02484-7","DOIUrl":"10.1186/s12874-025-02484-7","url":null,"abstract":"<p><strong>Background: </strong>This study presents a Bayesian Adaptive Semiparametric approach designed to address the challenges of pediatric randomized controlled trials (RCTs). The study focuses on efficiently handling primary and secondary endpoints, a critical aspect often overlooked in pediatric trials. This methodology is particularly pertinent in scenarios where sparse or conflicting prior data are present, a common occurrence in pediatric research, particularly for rare diseases or conditions.</p><p><strong>Method: </strong>Our approach considers Bayesian adaptive design, enhanced with B-Spline Semiparametric priors, allowing for the dynamic updating of priors with ongoing data. This improves the efficiency and accuracy of the treatment effect estimation. The Semiparametric prior inherent flexibility makes it suitable for pediatric populations, where responses to treatment can be highly variable. The design operative characteristics were assessed through a simulation study, motivated by the real-world case of the REnal SCarring Urinary infEction Trial (RESCUE).</p><p><strong>Result: </strong>We demonstrate that Semiparametric prior parametrization exhibits an improved tendency to correctly declare the treatment effect at the study conclusion, even if recruitment challenges, uncertainty, and prior-data conflict arise. Moreover, the Semiparametric prior design demonstrates an improved ability in truly stopping for futility, with this tendency varying with the sample size and discontinuation rates. Approaches based on Parametric priors are more effective in detecting treatment efficacy during interim assessments, particularly with larger sample sizes.</p><p><strong>Conclusion: </strong>Our findings indicate that these methods are especially effective in managing the complexities of pediatric trials, where prior data may be limited or contradictory. The flexibility of Semiparametric prior design in incorporating new evidence proves advantageous in addressing recruitment challenges and making informed decisions with restricted data.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"82"},"PeriodicalIF":3.9,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11956446/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143751054","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":"Investigator-initiated versus industry-sponsored trials - visibility and relevance of randomized controlled trials in clinical practice guidelines (IMPACT).","authors":"Manuel Hecht, Anette Blümle, Harald Binder, Martin Schumacher, Nadine Binder","doi":"10.1186/s12874-025-02535-z","DOIUrl":"10.1186/s12874-025-02535-z","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The goal of evidence-based medicine is to make clinical decisions based on the best available, relevant evidence. For this to be possible, studies such as randomized controlled trials (RCTs), which are widely considered to provide the best evidence of all forms of primary research, must be visible and have an impact on clinical practice guidelines. We further investigated the impact of publicly and commercially sponsored RCTs on clinical practice guidelines by measuring direct and indirect impactful citations and the time to guideline impact.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We considered the sample from the IMPACT study, where a total of 691 RCTs (120 German investigator-initiated trials (IITs), 200 international IITs, 171 German industry-sponsored trials (ISTs) and 200 international ISTs) was sampled from registries (DFG-/BMBF-Websites, the German Clinical Trials Register, and from ClinicalTrials.gov) and followed prospectively. First, all eligible IITs were sampled. Then, ISTs were randomly selected while ensuring balance across certain trial characteristics. Next, the corresponding publications in the form of original research articles were identified. A search was then conducted for (1) systematic reviews (SRs) citing these articles and (2) clinical practice guidelines (CPGs) that cited either the original articles or the SRs. The methods and results of this effort were already published. In this investigation we aimed to better characterize the impact of RCTs in CPGs. Therefore, we identified all citations of the original articles and SRs in the citing CPGs and classified them into impactful and non-impactful. This allowed us to calculate an estimate for the guideline impact of a trial. In addition, we estimated the time-to-guideline-impact, defined as the time to a direct and indirect impactful citation in a CPG. Direct means that the publication of a trial was cited in the main text of a CPG. Indirect means that the publication was cited and included in the findings of a SR and the SR was cited in the main text of a CPG. We also investigated to what extent pre-defined study characteristics influenced the guideline impact using multivariable negative binomial regression as well as the time-to-guideline impact using multivariable Cox proportional hazards regression.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Overall, 22% of RCTs impacted a CPG. For international ISTs, only 15% of trials had an impact in CPGs. Overall, of the 405 associated guidelines, 331 were impacted. Larger trials were associated with more impactful main text citations in CPGs and earlier time-to-guideline impact, while international industry-sponsored trials were associated with smaller impact on CPGs and longer time-to-guideline impact. IITs funded by governmental bodies in Germany reached an impact on CPGs that is on par with German ISTs or international IITs and ISTs.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;This study demonstrated that a considerable n","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"80"},"PeriodicalIF":3.9,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11948659/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143717993","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}