Journal of Clinical Epidemiology最新文献

{"title":"Priority-setting criteria for clinical practice guideline development on rare genetic neurodevelopmental disorders: a Delphi study within the European Reference Network (ERN) ITHACA.","authors":"Mirthe Jasmijn Klein Haneveld, Michiel Sebastiaan Oerbekke, Katalin Szakszon, Martina Cornelia Cornel, Charlotte Maria Wilhelmina Gaasterland, Agnies Marguerite Van Eeghen","doi":"10.1016/j.jclinepi.2025.111761","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2025.111761","url":null,"abstract":"<p><strong>Objective: </strong>The prioritization of clinical practice guideline (CPG) efforts is particularly challenging for rare genetic neurodevelopmental disorders given the large number of (ultra)rare conditions and limited resources. We aimed to establish criteria for the priority-setting of CPG topics within the European Reference Network (ERN) ITHACA (Intellectual disability, TeleHealth, Autism and Congenital Anomalies) based on stakeholder input.</p><p><strong>Study design and setting: </strong>Sets of priority-setting criteria for aetiology-specific CPGs and shared health topic CPGs (across aetiologies) were generated using a two-phase consensus process. The first phase consisted of initial criteria generation, internal feedback from the ERN-ITHACA Executive Committee and Patient Advisory Board, and stakeholder input through an open survey. The second phase consisted of a two-round modified Delphi and consensus meeting with an expert panel consisting of patient advocates, clinicians, and methodologists.</p><p><strong>Results: </strong>The final sets of priority-setting criteria included absence of existing guidance, high burden for affected individuals and families, and specific health risks requiring adaptation from usual care. Additionally, complexity and treatment availability were included for aetiology-specific CPGs and common occurrence and societal burden were included for CPGs for shared health topics. Availability and interest of clinical experts and patient organizations were considered required to produce CPGs; shared health topics addressed through dedicated CPGs need to be universal across aetiologies.</p><p><strong>Conclusion: </strong>Aligning with stakeholder perspectives in priority-setting is required to allocate scarce resources to the development of high-priority CPGs for rare conditions. Priority-setting criteria specific to the rare condition context were identified. CPG development was considered a particular priority important for complex conditions and/or healthcare and where care is non-standard. Practice variation was not selected as a priority-setting criterion.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"111761"},"PeriodicalIF":7.3,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143671670","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":"A scoping review identifies comments suggesting modifications to PRISMA-P 2015.","authors":"Camilla Hansen Nejstgaard, Nina Sondrup, An-Wen Chan, Kerry Dwan, David Moher, Matthew J Page, Larissa Shamseer, Lesley A Stewart, Asbjørn Hróbjartsson","doi":"10.1016/j.jclinepi.2025.111760","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2025.111760","url":null,"abstract":"<p><strong>Objectives: </strong>To identify, summarise, and analyse published comments relevant to the PRISMA-P (Preferred Items for Reporting Systematic reviews and Meta-Analyses Protocols) 2015 reporting guideline for systematic review protocols, with special emphasis on suggestions for guideline modifications.</p><p><strong>Methods: </strong>We included documents (e.g., empirical studies and social media posts) that included comments relevant to PRISMA-P 2015. We searched bibliographic databases (e.g., Embase, MEDLINE, Scopus, from January 1^st 2015 to February 2^nd 2024) and other sources (e.g., BMJ rapid responses, BMC Blog Network, from January 1^st 2015 to April 22^nd 2024). Two authors independently assessed documents for inclusion, extracted data, and categorised comments. We categorised comments as 'suggestion for modification to the wording of an existing PRISMA-P 2015 item', 'suggestion for a new item', 'suggestion for deletion of an existing PRISMA-P 2015 item', or 'additional comment'. We categorised each comment into themes and provided a summary and examples of the proposed suggestions. We analysed the characteristics of the suggestions by describing the rationale and comparing with existing PRISMA-P 2015 guidance.</p><p><strong>Results: </strong>We assessed full text of 1,912 potentially eligible documents and included 28 documents with 38 comments. Eleven comments suggested modifications to existing guideline items. Multiple comments proposed modifications to items related to eligibility criteria (three comments made different suggestions, e.g., one comment suggested to include reporting guidance relating to retracted papers) and data synthesis (three comments made different suggestions, e.g., one comment suggested to add reporting guidance relating to prediction intervals for random-effects meta-analyses). There were 11 comments suggesting new items. The data items section of PRISMA-P 2015 received the most comments (five comments made different suggestions, e.g., three comments suggested to add content on pre-specifying whether authors plan to extract information on funding and conflicts of interest among the included studies). None of the included comments suggested to delete items or content. Most of the suggestions provided a rationale directly in the document and around two-thirds of the suggestions referred to content in addition to PRISMA-P 2015 or asked for more extensive guidance than what is included.</p><p><strong>Conclusion: </strong>The issues raised provide context to authors, peer reviewers, editors, and readers of systematic review protocols using PRISMA-P 2015 and inform the planned update of the guideline.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"111760"},"PeriodicalIF":7.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665362","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":"Methods resources for authors new to conducting systematic reviews with network meta-analysis: A Scoping Review.","authors":"Lize-Mari Swanepoel, Amanda Brand, Andrit Lourens, Anel Schoonees, Michael McCaul","doi":"10.1016/j.jclinepi.2025.111759","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2025.111759","url":null,"abstract":"<p><strong>Objectives: </strong>To support systematic reviewers new to network meta-analysis (NMA), we (i) identified and described published methods resources for conducting systematic reviews (SRs) with NMA of randomized controlled trials (RCTs); (ii) mapped the resources to the typical steps for conducting NMA's; and (iii) identified NMA guidance gaps.</p><p><strong>Study design and setting: </strong>We performed a scoping review and comprehensively searched major databases, grey literature sources and websites for methods resources that described or informed any steps in conducting SRs with NMA to guide review authors, particularly those new to the method. Title, abstract and full text screening were conducted independently in duplicate using Covidence. NMA resources were narratively described and tabulated by guidance type, review steps and topic and mapped to the steps of conducting a systematic review with NMA.</p><p><strong>Results: </strong>We considered documents in the 2011-2025 date range and included 90; the majority (39%) were published between 2021-2025. Most were classified as guides/guidance (29%), methods/methodology (22%) or reviews (27%). We found that the rate of published guidance around most steps of NMA increased or remained stable over time. Most resources for software were guidance for R and Stata. Guidance documents on assumptions and certainty of evidence were abundant (in excess of 13 documents per topic), while fewer guidance documents were available on elements of protocol development and presentation of results. We mapped methods resources across steps in conducting SRs with NMA, identifying areas with sparse guidance.</p><p><strong>Conclusion: </strong>This scoping review provides a comprehensive reference for conducting SRs using NMA, especially for those new to the methods. It highlights the significant increase in guidance since 2011, particularly on evidence certainty and NMA assumptions, and the availability of user-friendly web tools. Future work should focus on advanced NMA guidance and decision tools to aid reviewers in further navigating NMA complexities.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"111759"},"PeriodicalIF":7.3,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665363","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 strategies to analyze local control after radiotherapy.","authors":"Tetsuo Saito, Kenta Murotani, Takeshi Kodaira, Naoto Shikama, Yoshinori Ito, Naoki Nakamura, Takashi Mizowaki, Yoshikazu Kagami","doi":"10.1016/j.jclinepi.2025.111758","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2025.111758","url":null,"abstract":"<p><p>Historically, local progression, an outcome of effectiveness in curative radiotherapy, has not always been statistically analyzed with the same method. This article aims to elucidate the validity and relative usefulness of statistical strategies to analyze local control. In an application example, data were analyzed from a phase III trial comparing different radiation schedules for glottic cancer. The superiority of experimental treatment over standard treatment in local control was detected by a competing risks model but not detected in the analysis of local progression-free survival by a standard survival model. The use of a composite outcome, local progression-free survival, is suboptimal in that local progression and death are equally treated as the events of interest. In the analysis of local progression-free rate, by censoring death, the cumulative incidence of local progression is overestimated. We recommend the consistent use of the cumulative incidence of local progression as the endpoint to assess local control after radiotherapy.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"111758"},"PeriodicalIF":7.3,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143639842","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":"Calculating Follow-Up Completeness: a comparison of multiple methods under different simulated scenarios and a use-case.","authors":"Carlijn C E M van der Ven, M Arfan Ikram, Frank J A van Rooij, Jolanda Kluin, Johanna J M Takkenberg, Kevin M Veen","doi":"10.1016/j.jclinepi.2025.111757","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2025.111757","url":null,"abstract":"<p><strong>Background: </strong>Completeness of follow-up is a crucial aspect of data quality in cohort studies and clinical trials. This study aims to provide an overview of different methods to calculate follow-up completeness. Additionally, the performance of these methods is tested in several scenarios using simulated datasets and a use-case, with the aim of guiding researchers in selecting the most appropriate method for their data.</p><p><strong>Methods: </strong>The literature was searched for methods of quantification of follow-up completeness. These methods were investigated in simulated datasets, in which the true completeness of follow-up was known. A total of 27 different scenarios were investigated, based on different survival distributions, total proportions of drop-out of participants and different time points of drop-out. The methods were also investigated using real-world mortality data from the population-based Rotterdam Study cohort. Kaplan-Meier curves were used in order to depict observed survival, and completeness of follow-up was calculated in percentages using a freely available GitHub package developed by our research group.</p><p><strong>Results: </strong>In total, six methods were found in the literature for quantification of follow-up completeness. Overall, two methods (the Simplified Person-Time Method and the modified Clark's Completeness Index C*) were closest to the true follow-up completeness in the 27 scenarios.</p><p><strong>Conclusions: </strong>Researchers should make attempts to report follow-up completeness. This simulation study may assist researchers in selecting the most appropriate method to calculate follow-up completeness in different scenarios.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"111757"},"PeriodicalIF":7.3,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143639839","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":"A meta-research study finds unclear impact of institutional conflicts of interest on conclusions of studies investigating volume-outcome relationships.","authors":"Charlotte M Kugler, Kaethe Goossen, Elie A Akl, Dawid Pieper","doi":"10.1016/j.jclinepi.2025.111756","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2025.111756","url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to explore institutional conflicts of interest (COIs) in volume-outcome studies investigating whether higher hospital volume is associated with better patient outcomes.</p><p><strong>Study design and setting: </strong>We used a sample of studies (n=68) included in a systematic review on the hospital volume-outcome relationship in total knee arthroplasty. For studies in which at least one of the study authors was affiliated with a hospital, we contacted the study authors by email to obtain their institutional volume and to survey them about their opinion on institutional COIs. We categorized the studies' conclusions (positive vs. non-positive) and authors' hospital volume (high, intermediate, low). We compared conclusions for high vs. intermediate/low hospital volume categories RESULTS: Of 29 hospital-affiliated authors contacted, 20 replied. Authors from high-volume institutions were more likely to conclude that a hospital volume-outcome relationship existed compared to authors from intermediate- or low-volume institutions, although this was not statistically significant (odds ratio, OR: 2.0; 95% confidence interval, CI: 0.21; 18.7). Six out of 17 authors (35%) believed that institutional factors such as the case volume were (very) likely to influence the study design, analysis, or conclusions of research in the field of volume-outcome studies; 4/17 (24%) were neutral; and 7/17 (41%) believed that this was (very) unlikely.</p><p><strong>Conclusion: </strong>This is the first study explicitly investigating institutional financial interests with benefit through increasing services provided by the institution. The findings suggest the possibility that institutional COI may influence the conclusions of volume-outcome studies, although the results are inconclusive. Surveyed authors had divergent opinions on whether institutional factors are likely to influence research integrity. Further research is needed to investigate institutional COIs.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"111756"},"PeriodicalIF":7.3,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143631049","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":"Methodological Challenges in Pilot Trials of Herbal Medicine: Barriers to Evidence-Based Practice.","authors":"Yixuan Li, Ziwen Xu, Peipei Du, Jierong Gao, Sijin Wang, Xu Pang, Chenyu Ren, Yan Liu, Chi Zhang","doi":"10.1016/j.jclinepi.2025.111754","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2025.111754","url":null,"abstract":"<p><strong>Objective: </strong>The growing popularity of herbal medicine (HM) underscores the need for high-quality clinical trials to support its evidence-based integration. Pilot trials are essential for addressing methodological challenges in this field. This study evaluates the design quality, feasibility, and reporting of HM pilot trials, with a focus on their capacity to inform future full-scale studies.</p><p><strong>Study design and setting: </strong>A comprehensive collection of herbal medicine HM pilot trials was conducted using PubMe, Web of Science and Embase, based on predefined inclusion criteria. Data were extracted on trial characteristics, reporting quality, and progression to full-scale studies. To gather additional information on follow-up studies, authors of selected trials were contacted directly by email. Adherence to CONSORT guidelines for pilot trials was evaluated, and Poisson regression was applied to identify factors influencing reporting completeness.</p><p><strong>Results: </strong>A total of 123 HM pilot trials were reviewed, predominantly from Asia (78.1%). Trials most commonly addressed respiratory (14.6%), nervous (14.6%), and reproductive systems (13.0%). Key gaps in reporting included feasibility assessments (13.1%), sample size rationale (47.2%), and randomization methods (35.8%). Herbal medicine-specific details, including ingredient processing, quality control, and safety assessments, were inconsistently reported. Among the trials, 4 (3.3%) progressed to full-scale studies. Factors such as trial registration (IRR = 1.20, 95% CI: 1.11-1.30) and protocol publication (IRR = 1.16, 95% CI: 1.08-1.24) were positively associated with reporting completeness. Moreover, an analysis of the origin of herbal medicines revealed that modern HM trials were 4.7 times more likely to progress to full-scale studies compared to traditional HM trials (OR = 4.70, 95% CI: 0.37-252.91), although the result did not reach statistical significance (p = 0.300).</p><p><strong>Conclusion: </strong>Herbal medicine pilot trials, as they stand, are not yet equipped to reliably guide full-scale studies. Core issues in methodological rigor, particularly in feasibility assessment, sample size justification, and randomization processes, limit their effectiveness and integration into evidence-based practice. A dedicated checklist that merges pilot study standards with the unique needs of HM trials is essential.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"111754"},"PeriodicalIF":7.3,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143626778","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":"Suboptimal Practices in Harm Reporting: A Meta-Epidemiological Study on Metrics, Recurrence and Exposure Duration in Clinical Trials.","authors":"Qiao Huang, Wen Wang, Liang Zheng, Yue-Xian Shi, Long Ge, Xian-Tao Zeng, Ying-Hui Jin","doi":"10.1016/j.jclinepi.2025.111755","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2025.111755","url":null,"abstract":"<p><strong>Objective: </strong>The CONSORT Harms 2022 statement emphasizes the necessity for clinical trials to clearly address the duration of follow-up and recurrence of adverse events in safety analysis, highlighting the importance of using appropriate measures for a comprehensive risk assessment. This study aimed to provide guidance on metrics in harm profile reporting and evaluating current practices in clinical trials against the CONSORT Harms 2022 recommendations.</p><p><strong>Study design and setting: </strong>We have summarized characteristics of four reporting metrics-cumulative incidence rate, cumulative event rate, exposure-adjusted incidence rate, and exposure-adjusted event rate. To evaluate the current reporting patterns, we conducted a meta-epidemiological study of 116 clinical trials published in four top-tier medical journals from September 1, 2023, to December 31, 2023.</p><p><strong>Results: </strong>The cumulative incidence rate was the most frequently used metric (81.03%), followed by a simple count (16.38%), exposure-adjusted event rate (3.45%), exposure-adjusted incidence rate (2.59%), and cumulative event rate (0.86%). 105 trials (91.38%) employed a single measure and 10 trials (8.62%) incorporated two different measures. Only 14 trials (12.07%) gave explicit evidence for the reporting of recurrent adverse events and 6 trials (5.17%) explicitly stated their rationale for not considering recurrence. Adjustments for exposure duration were notably absent in trials with unequal drop-out rates and exposure times.</p><p><strong>Conclusion: </strong>Recurrence of adverse events and varied exposure duration were inadequately addressed in current practices. Future trials should adopt transparent and sophisticated metrics in reporting them to capture a multidimensional and reliable representation of harm profiles.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"111755"},"PeriodicalIF":7.3,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143598331","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":"Exploring the effect of COVID-19 restrictions on the Social Functioning Scale in a clinical trial of Antipsychotic Reduction: using multiple imputation to target a hypothetical estimand.","authors":"Louise Marston, Joanna Moncrieff, Stefan Priebe, Suzie Cro, Victoria R Cornelius","doi":"10.1016/j.jclinepi.2025.111753","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2025.111753","url":null,"abstract":"<p><strong>Objective: </strong>Many trials are affected by unforeseen events after recruitment has commenced. The aim of this study is to explore a hypothetical strategy for dealing with an intercurrent event that occurred during trial follow-up; COVID-19 restrictions.</p><p><strong>Study design and setting: </strong>Secondary analysis of a randomised controlled trial in schizophrenia, comparing antipsychotic reduction versus maintenance medication on the Social Functioning Scale (SFS) score at 12 months' follow-up. A hypothetical analysis strategy was used to estimate the treatment effect in a COVID-19 restriction-free world. Outcome data were set to missing and multiple imputation was used to replace values affected by COVID-19.</p><p><strong>Results: </strong>The trial randomised 253 participants, 187 participants had an SFS score at 12 months, 75 of those were collected during COVID-19 restrictions. In the original complete case regression analysis, targeting a treatment policy estimand, the treatment effect was estimated to be 0.51 (95%CI -1.33, 2.35) points higher in the reduction group. After multiple imputation, targeting the hypothetical estimand, the mean SFS score was -3.01 (95%CI -7.22, 1.20) points lower in the reduction group, but varied with different assumptions about the timing of events and in sensitivity analyses to increase the size of difference between randomised groups.</p><p><strong>Conclusion: </strong>We demonstrated how the intervention effect can change when estimating the intervention effect in a pandemic world (treatment policy estimand) versus a pandemic restriction-free world (hypothetical estimand) and that estimates are sensitive to imputation and input assumptions. Trialists should be aware of potential intercurrent events and plan the analysis to take them into account.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"111753"},"PeriodicalIF":7.3,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143588016","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":"Measuring the environmental impact of health interventions in randomised controlled trials - a scoping review.","authors":"Beatriz Goulao, Dwayne Boyers, Oscar Forbes, Kristin Konnyu","doi":"10.1016/j.jclinepi.2025.111751","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2025.111751","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Healthcare accounts for 4% of the overall greenhouse gas emissions worldwide. Reducing carbon emissions is a key strategic aim for health systems in multiple countries. To achieve this, environmental data needs to be considered in health decision making. Clinical trials are a key element to inform clinical practice, but to what extent they have considered environmental outcomes in their design, analysis and interpretation is unclear. We conducted a scoping review of environmental outcomes in clinical trials, including protocols, to assess what outcomes are being collected, how and why, and to what extent environmental outcomes influence interpretation of the clinical findings by trial authors.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We developed a search strategy in Embase, MEDLINE and Cochrane library to identify eligible English language studies with no date restrictions. Inclusion criteria were healthcare randomised controlled trials (RCTs) that collected, or protocols of RCTs that planned to collect, environmental outcomes in their abstracts. Two researchers conducted abstract and full text screening independently. We single extracted data using a pre-agreed and piloted data extraction form. Any uncertainties in extraction were discussed as a group until an agreement was reached. We summarised quantitative data using descriptive statistics and analysed verbatim text of qualitative data into summary categories that were agreed by the team.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;We identified 1,318 abstracts, from which 27 full texts were screened, and 16 RCTs (or protocols of RCTs) were included in our review. Nine studies were published from 2022; nine reported environmental outcomes in secondary publications; seven were in the nutrition field followed by oncology (n=2) and anaesthesiology (n=2). The primary reason for including environmental outcomes was to confirm that the intervention reduced emissions (n=12), rather than focusing on broader goals of lowering carbon emissions or environmental considerations in health systems. Included trials assessed various environmental impacts of the studied interventions including carbon footprint, greenhouse gas emissions, or wider environmental impacts. Most trials used life cycle assessments, or publicly available carbon footprint data, to calculate their environmental outcomes. The analysis was not pre-specified in eight trials; all trials but one undertook separate analyses for clinical and environmental outcomes. In all but two cases, environmental and clinical outcomes were in agreement (in favour of, or against, the intervention). Patient and public involvement was rarely reported (n= 3). Five trials presented examples or contextual information to aid interpretation of the environmental outcome results.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Discussion: &lt;/strong&gt;Including environmental outcomes in RCTs appears to be increasing in prominence, although the role of these outcomes in clinical decision maki","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"111751"},"PeriodicalIF":7.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143588019","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}