Journal of Clinical Epidemiology最新文献

{"title":"PedsQL Generic Core Scales was more discriminative while EQ-5D-Y-5L was more responsive in a longitudinal study of multiethnic Asian children and adolescents with heart disease","authors":"Mihir Gandhi ,&nbsp;Ching Kit Chen ,&nbsp;Dyan Zhewei Zhang ,&nbsp;Chun Fan Lee ,&nbsp;Nan Luo ,&nbsp;Yin Bun Cheung","doi":"10.1016/j.jclinepi.2025.111982","DOIUrl":"10.1016/j.jclinepi.2025.111982","url":null,"abstract":"<div><h3>Objectives</h3><div>This study compared the measurement properties of five pediatric health-related quality of life (HRQoL) instruments—three preference-based (3-level EQ-5D-Y [EQ-5D-Y-3L], 5-level EQ-5D-Y [EQ-5D-Y-5L], and Child Health Utility 9D [CHU9D]) and two nonpreference-based (Pediatric Quality of Life Inventory [PedsQL] Generic Core Scales and PedsQL Cardiac Module)—in a multiethnic Asian cohort of children and adolescents with heart disease to guide their use in clinical and health technology assessments (HTAs).</div></div><div><h3>Methods</h3><div>A total of 221 children aged 8–18 years from two tertiary hospitals in Singapore completed all instruments at baseline, with follow-up at 1 and 12 months. We assessed validity, internal consistency, test–retest reliability, and responsiveness.</div></div><div><h3>Results</h3><div>Of participants, 85% had congenital heart disease, 9% arrhythmia, and 6% heart failure. Ceiling effects were high for EQ-5D-Y-3L (49.3%) and EQ-5D-Y-5L (47.5%) but lower for CHU9D (15.4%). PedsQL dimensions showed acceptable internal consistency (Cronbach's α ≥ 0.70), except for school functioning (α = 0.52) and treatment adherence (α = 0.56). Preference-based instruments demonstrated good convergent validity with the PedsQL Generic Core Scales (≥75% of hypotheses met). Known-group validity was the strongest for PedsQL Generic Core Scales, followed by EQ-5D-Y instruments and CHU9D. Test–retest reliability was satisfactory (intraclass correlation coefficient [ICC] ≥0.70), except EQ-5D-Y-3L utility (ICC = 0.68). Responsiveness was the highest for EQ-5D-Y-5L (standardized response mean = 0.50), followed by EQ-5D-Y-3L and CHU9D; PedsQL instruments were minimally responsive.</div></div><div><h3>Conclusion</h3><div>The PedsQL Generic Core Scales is suitable for cross-sectional outcome assessment requiring discrimination between HRQoL levels. EQ-5D-Y-5L shows superior responsiveness and is recommended for intervention studies requiring preference-based outcomes. CHU9D demonstrates low ceiling effects and good reliability, but less discriminative ability than EQ-5D-Y instruments. Instrument selection should align with clinical and HTA objectives.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"188 ","pages":"Article 111982"},"PeriodicalIF":5.2,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145139577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Letter to the editor: Predicting obstetric anal sphincter injury in the first and second vaginal delivery and after a cesarean delivery: development and validation of an intrapartal model.","authors":"Parth Aphale, Shashank Dokania, Himanshu Shekhar","doi":"10.1016/j.jclinepi.2025.111963","DOIUrl":"10.1016/j.jclinepi.2025.111963","url":null,"abstract":"","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"111963"},"PeriodicalIF":5.2,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144977732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conflict of interest policies for editors and peer reviewers in medical journals: cross-sectional study","authors":"Christoffer Bruun Korfitsen ,&nbsp;Helena Van Beersel Krejčíková ,&nbsp;Camilla Hansen Nejstgaard ,&nbsp;Isabelle Boutron ,&nbsp;Lisa Bero ,&nbsp;Asbjørn Hróbjartsson ,&nbsp;Andreas Lundh","doi":"10.1016/j.jclinepi.2025.111980","DOIUrl":"10.1016/j.jclinepi.2025.111980","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Objectives&lt;/h3&gt;&lt;div&gt;Editors and peer reviewers of research articles may have conflicts of interest that impact their evaluations. We aimed to characterize medical journals' conflict of interest policies for editors and peer reviewers.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Study Design and Setting&lt;/h3&gt;&lt;div&gt;In this cross-sectional study, we randomly sampled 277 medical journals from Clarivate Journal Citation Reports. Two authors independently retrieved public conflict of interest policies and disclosures for editors and peer reviewers from journal websites and retrieved publishers' policies when journals also referred to them (January to June 2024). We used content analysis to analyze policies and multivariable mixed-effects logistic regressions to estimate the associations between journal characteristics and having a policy.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;After excluding 27 journals, we included 250 medical journals in English, of which 177 (71%) had a conflict of interest policy for editors and 174 (70%) for peer reviewers. Of journals with a policy, 137 (77%) and 129 (74%) described disclosure requirements, 160 (90%) and 163 (94%) described management strategies, 124 (70%) and 106 (61%) described policy enforcement strategies, and 17 (10%) and 15 (9%) described processes for appealing decisions. All 4 concepts were addressed in 16 (9%) policies for editors and in 11 (6%) for peer reviewers. Having a policy for editors was associated with higher journal impact factor (adjusted odds ratio (OR): 1.28; 95% confidence interval (CI): 1.05–1.56) and Committee on Publication Ethics membership (OR: 3.50; 95% CI: 1.42–8.65). Having a policy for peer reviewers was associated with higher journal impact factor (OR: 1.16; 95% CI: 0.97–1.37) and open access journal (OR: 4.59; 95% CI: 1.11–18.93). For a subgroup of journals referring to their publishers' policy, the content was concordant for 5 (11%) of 45 journals for editors and 4 (9%) of 47 journals for peer reviewers. Of 250 journals, 14 (6%) had public declarations of interest from editors, and 3 (1%) from peer reviewers.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusion&lt;/h3&gt;&lt;div&gt;More than two-thirds of medical journals have conflict of interest policies for editors and reviewers; however, policies vary in comprehensiveness. There is potential to improve the content of conflict of interest policies and the transparency of interests in medical journals.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Plain Language Summary&lt;/h3&gt;&lt;div&gt;Before a scientific study is published as a research paper in a medical journal, it is evaluated by the journal editors and other researchers, known as peer reviewers. This process is used to assess and ensure the quality and trustworthiness of the research and to assist editors in deciding whether to publish the paper. Editors and peer reviewers, however, are not necessarily neutral and may have personal interests that can influence their opinions. For example, they may have personal relationships with the study authors or hav","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"188 ","pages":"Article 111980"},"PeriodicalIF":5.2,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145114462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reusing clinical trial data to consolidate and advance medical knowledge","authors":"Giulia Varvarà ,&nbsp;Cora Burgwinkel ,&nbsp;Clara Locher ,&nbsp;Joseph S. Ross ,&nbsp;Ulrich Mansmann ,&nbsp;Florian Naudet","doi":"10.1016/j.jclinepi.2025.111984","DOIUrl":"10.1016/j.jclinepi.2025.111984","url":null,"abstract":"<div><div>While data sharing holds great potential to maximize the value of research and reduce waste, these benefits can only be fully realized if shared data are also effectively reused. Yet, data reuse remains limited, and there is a notable lack of clear guidelines to support data reusers. Reusing existing data enables a wide range of valuable activities, including validating previous findings, identifying errors, conducting individual patient data meta-analyses, performing secondary analyses, and developing or testing new methods. However, the validity of such work depends on strict adherence to reproducible research practices—arguably even more so in the context of secondary use. Data reuse also involves practical constraints and specific challenges, such as addressing feasibility issues, which must be anticipated and managed from the outset. Researchers should remain aware of these considerations throughout the entire lifecycle of a reuse study. Ideally, this process should be supported by hands-on training tailored to the specific demands of data reuse. To that end, we propose a set of guiding principles to foster responsible and meaningful reuse of existing datasets—including, but not limited to, assembling a skilled multidisciplinary team, anticipating infrastructure and interoperability challenges, maintaining transparency throughout the research process, and incentivizing all stakeholders involved.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"188 ","pages":"Article 111984"},"PeriodicalIF":5.2,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145114527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Planning retention strategies in clinical trials-a qualitative interview study with members of trial teams.","authors":"Ellen Murphy, Sharon McCann, Frances Shiely, Katie Gillies","doi":"10.1016/j.jclinepi.2025.111979","DOIUrl":"10.1016/j.jclinepi.2025.111979","url":null,"abstract":"<p><strong>Objectives: </strong>To address poor participant retention, trial teams often use retention strategies. Evidence on the planning of retention strategies in trials is limited. Based on our previously conducted research, and other existing literature, it is unclear whether retention strategies are prospectively or retrospectively planned by trialists. Our objective was to investigate this.</p><p><strong>Study design and setting: </strong>One-to-one semistructured interviews, online or in person, were conducted with trialists in the United Kingdom and Ireland to gain better insights into planning retention strategies across various trialists viewpoints. Purposive snowball sampling was used to recruit interviewees. Data were analyzed using framework analysis. This approach was chosen to aid in identifying similarities and differences in patterns in the data within and between different groups of trialists interviewed, for example, Trial Managers, Research Nurses, Principal Investigators etc. RESULTS: Twenty-four trialists were interviewed, including trial managers, study co-ordinators, principal investigators, research nurses, a head of trial operations, a clinical trial unit director, a clinical trial monitor, a co-investigator, and a clinical trials practitioner. Findings show that the development of retention strategies in trials is mostly done proactively during the design and planning stages of the trial, that is, during trial design and protocol development. Participant retention, however, is an ongoing process, and if retention rates are problematic, additional strategies are reactively planned and implemented. Strategies tend to be chosen by the core trial management team, and the choice of strategy is mainly guided by prior experience. A variety of different formal strategies (explicitly and intentionally planned strategies that are often more structured, such as reminders or incentives) are used to facilitate ongoing participant retention. Informal strategies (not explicitly or intentionally planned), such as building rapport with participants and having motivated and invested trial staff, are also highlighted as being important to facilitating retention in trials.</p><p><strong>Conclusion: </strong>Most trialists proactively plan and implement retention strategies during the design and planning stages of the trial but are also responsive to poor retention rates as the trial is ongoing. Currently, retention strategies are chosen based on prior experience of using the strategy. More formal evaluation of effectiveness is needed to help facilitate evidence-based decision-making when choosing retention strategies.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"111979"},"PeriodicalIF":5.2,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145114497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical model assessment in published dose-response meta-analyses is suboptimal: evidence from a methodological review and reanalysis of 242 datasets","authors":"Marimuthu Sappani ,&nbsp;Shofiqul Islam ,&nbsp;Rohan D'Souza ,&nbsp;Joseph Beyene","doi":"10.1016/j.jclinepi.2025.111981","DOIUrl":"10.1016/j.jclinepi.2025.111981","url":null,"abstract":"<div><h3>Objectives</h3><div>Dose-response meta-analysis (DRMA) is a crucial clinical and epidemiological research tool for synthesizing exposure-risk relationships. Despite its growing use, facilitated by the availability of statistical software, the appropriateness of the underlying statistical methods has not been thoroughly explored. This study aims to evaluate the reporting quality of key statistical measures in DRMA and compare their performance using empirical datasets.</div></div><div><h3>Study Design and Setting</h3><div>We performed a systematic literature search to identify relevant studies, from which we extracted datasets and study characteristics. We fitted linear, quadratic polynomial and restricted cubic spline (RCS) models with fixed and non-fixed knots selection procedures. Key measures assessed included non-linearity, goodness-of-fit (GoF), model comparison, and the impact of outlying studies on statistical results. We compared <em>P</em><em>-</em>values for non-linearity, GoF test for each model pair, and used the Akaike information criterion for model comparison. We evaluated the influence of individual studies on non-linearity and GoF using a leave-one-out (LOO) approach.</div></div><div><h3>Results</h3><div>We included 146 unique DRMA studies, from which 242 datasets were extracted with median (interquartile range) of 9 (7, 14) individual studies. While the non-linearity test was conducted in 102/124 (82.3%) studies, other measures were infrequently reported. Only 13/146 (10.0%) studies assessed GoF, 10/79 (12.7%) provided model comparison results, and 46/146 (31.5%) examined the impact of outlying studies. Our reanalysis of 242 datasets demonstrated that the RCS model with a non-fixed knots selection procedure identified more non-linearity (110/242, 45.5%) and fitted well (205/242, 84.7%) than other models. The LOO approach showed that conclusions regarding non-linearity and GoF changed in approximately 50% of cases after excluding a single study, regardless of the model used.</div></div><div><h3>Conclusion</h3><div>Our analysis reveals suboptimal attention to key statistical issues in published DRMA studies. RCS with non-fixed knots selection have shown potential advantages than a few other alternative modeling approaches. To strengthen the credibility of meta-analytic findings, it is advisable for researchers to integrate both clinical judgment and rigorous statistical model evaluation in their analyses. The LOO assessment underscores the necessity for methods that can identify and accommodate outlying studies in DRMA.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"188 ","pages":"Article 111981"},"PeriodicalIF":5.2,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145114518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Updating the PRISMA reporting guideline for network meta-analysis: a scoping review","authors":"Areti Angeliki Veroniki ,&nbsp;Andrea C. Tricco ,&nbsp;Daniella Rangira ,&nbsp;Joanne E. McKenzie ,&nbsp;Tianjing Li ,&nbsp;Sharon E. Straus ,&nbsp;Maureen Smith ,&nbsp;Ferrán Catalá-López ,&nbsp;Dianna Wolfe ,&nbsp;Vera Nincic ,&nbsp;Menelaos Konstantinidis ,&nbsp;Juan Franco ,&nbsp;David Tovey ,&nbsp;Sai Surabi Thirugnanasampanthar ,&nbsp;Jasmeen Dourka ,&nbsp;Rachel Warren ,&nbsp;George Wells ,&nbsp;Adrienne Stevens ,&nbsp;Brian Hutton","doi":"10.1016/j.jclinepi.2025.111985","DOIUrl":"10.1016/j.jclinepi.2025.111985","url":null,"abstract":"<div><h3>Background and Objective</h3><div>This scoping review is the first step in the process of updating the 2015 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for network meta-analysis (NMA). It builds up on a 2014 scoping review by our team and aims to enhance the usability, completeness, and transparency of NMA reporting for diverse audiences, including patients and the public. The updated extension will align with PRISMA 2020 and will address gaps in reporting, such as documenting methods for assessing NMA homogeneity and transitivity, defining intervention nodes in a network of studies, and considering advances in statistical modeling with NMA.</div></div><div><h3>Methods</h3><div>We registered the study protocol with the Open Science Framework and published it in Joanna Briggs Institute (JBI) Evidence Synthesis. We searched multiple databases and gray literature sources, and screened studies in duplicate. Data extraction was also conducted in duplicate using a standardized form, focusing on study characteristics, authors' reporting recommendations, and proposed additions to PRISMA-NMA and/or PRISMA 2020.</div></div><div><h3>Results</h3><div>Sixty-one studies met eligibility criteria, including 23 guidance documents and 38 overviews of reviews assessing the completeness or quality of NMA reporting. We identified 37 additional reporting items relevant to NMAs, which will inform the next stage of the PRISMA-NMA update (a Delphi consensus process).</div></div><div><h3>Conclusion</h3><div>Our findings support the urgent need to update the PRISMA-NMA guideline. Addressing persistent reporting gaps and incorporating recent methodological developments is critical to improving the transparency, reproducibility, and trustworthiness of NMAs.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"188 ","pages":"Article 111985"},"PeriodicalIF":5.2,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145114533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developing risk prediction models for type 2 diabetes and assessing the role of circulating metabolic biomarkers in five independent Finnish cohorts with over 22,000 individuals","authors":"Eetu Kiviniemi ,&nbsp;Ville Karhunen ,&nbsp;Markus Perola ,&nbsp;Johannes Kettunen ,&nbsp;Mikko J. Sillanpää","doi":"10.1016/j.jclinepi.2025.111978","DOIUrl":"10.1016/j.jclinepi.2025.111978","url":null,"abstract":"<div><h3>Objectives</h3><div>Type 2 diabetes (T2D) is a serious public health risk. It is not well known whether large scale omics data could help improve the risk prediction. We combined the use of metabolic variables with modern model selection methods to develop risk prediction models for T2D. We then assessed the incremental improvement in model performance produced by the metabolic variables, when compared to a clinical baseline.</div></div><div><h3>Methods</h3><div>We used five cohorts with a total of 493 cases and 21,755 controls to develop and validate risk prediction models for T2D. We first constructed a baseline model using 15 clinical variables, and then assessed the incremental improvement provided by a set of 154 metabolic variables to the prediction, using multiple different statistical methods. Model performance was assessed in terms of discrimination and calibration in multiple validation cohorts.</div></div><div><h3>Results</h3><div>The baseline model reached area under the receiver operating characteristic curve values between 0.832 and 0.913 in the validation cohorts. On adding the metabolic measures, the highest area under the receiver operating characteristic curve values reached in the validation cohorts were between 0.840 and 0.915, a small but not clinically relevant improvement over the baseline model. Most of the constructed models were miscalibrated in the validation cohorts.</div></div><div><h3>Conclusion</h3><div>The baseline model with clinical variables achieved a very good discrimination in predicting T2D. Models with metabolic variables were not able to meaningfully improve on it, as the high level set by the baseline left little room for improvement. The constructed models generalize to new independent data quite well in terms of discrimination, but relatively poorly in terms of calibration.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"188 ","pages":"Article 111978"},"PeriodicalIF":5.2,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145102890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Citizen science as an approach for engaging underrepresented communities in codevelopment of health research","authors":"Codie A. Primeau ,&nbsp;Alison M. Hoens ,&nbsp;Stephanie Therrien ,&nbsp;Linda C. Li","doi":"10.1016/j.jclinepi.2025.111977","DOIUrl":"10.1016/j.jclinepi.2025.111977","url":null,"abstract":"<div><h3>Objectives</h3><div>Engaging patients and public in health research ensures results remain relevant and responsive to community needs. However, meaningful engagement with underrepresented communities remains challenging, and this lack of representation can perpetuate ongoing inequities in health research. Citizen science offers a flexible methodological approach to prioritize active and meaningful patient and public engagement, including from underrepresented communities, where community voices are included throughout the research process. This commentary explores how a citizen science approach can be applied to enhance engagement of underrepresented communities and support co-developing research questions that reflect community needs.</div></div><div><h3>Study Design and Setting</h3><div>We present a case example of an ongoing project working with 2S/LGBTQQIA+ communities to codevelop a health research program centered around chronic pain using citizen science. The project includes a nationwide online platform, group workshops, and consensus approaches, with activities guided by an Advisory Committee of 2S/LGBTQQIA+ individuals. We describe the European Citizen Science Association's ten principles of citizen science, their application in the example .</div></div><div><h3>Results</h3><div>The case example demonstrates how citizen science can be used to codevelop a research program that reflects community needs, balancing large-scale public engagement with collaborative cocreation. Prioritizing active community engagement throughout the research process promotes transparency and inclusion, setting a new standard for collaborative research.</div></div><div><h3>Conclusion</h3><div>Citizen science holds significant potential for broader application across diverse health domains, offering an innovative alternative to traditional methods of priority-setting, and provides a flexible framework for engaging underrepresented communities to advance health equity.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"188 ","pages":"Article 111977"},"PeriodicalIF":5.2,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145092819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Grading of Recommendations, Assessment, Development, and Evaluation Notes 6: three strategies to determine the clinically important thresholds for outcomes in evidence-based guideline development","authors":"Xiaomei Yao ,&nbsp;Jun Xia ,&nbsp;Marisa Deodat ,&nbsp;Peiyao Wang ,&nbsp;Yaping Chang ,&nbsp;Yingying Luo ,&nbsp;Linong Ji","doi":"10.1016/j.jclinepi.2025.111976","DOIUrl":"10.1016/j.jclinepi.2025.111976","url":null,"abstract":"<div><h3>Objectives</h3><div>In evidence-based clinical practice guidelines (CPGs), the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach is commonly used to evaluate the certainty of evidence to develop recommendations. The recently published GRADE guidance papers suggested using a confidence interval approach as the primary criterion to assess the imprecision and inconsistency domains. This involves predetermining three clinically important thresholds, ie, small, moderate, and large effects. Establishing thresholds for outcomes is helpful when judging the strength of the corresponding recommendation. Recognizing that setting these thresholds poses a significant challenge for many CPG developers, we aim to delineate three methods for determining clinically important thresholds.</div></div><div><h3>Study Design and Setting</h3><div>During the development of a diabetes-related CPG, we identified three practical strategies to increase the likelihood of finding clinically significant thresholds in the literature.</div></div><div><h3>Results</h3><div>The three strategies are as follows: First, the minimally important difference or minimal clinically important difference found within the literature can be regarded as a small clinically important threshold. Second, the effect size used to calculate the sample size in a randomized controlled trial can serve as a small threshold for the same outcome, and occasionally may serve as moderate or even large threshold. Third, the different magnitudes of effect between two groups in trials conducted for government drug approval can guide the determination of three thresholds for any outcomes, especially for safety-related outcomes in a CPG.</div></div><div><h3>Conclusion</h3><div>This study presents three approaches that can be utilized to guide the establishment of three clinically important thresholds in the evaluation of the imprecision and inconsistency domains in certainty assessments of evidence and to inform judgement about the strength of the corresponding recommendation.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"188 ","pages":"Article 111976"},"PeriodicalIF":5.2,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145076594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}