Journal of Clinical Epidemiology最新文献

{"title":"Measurement differences explain much of the variation in adherence and persistence after ischemic stroke, and standardized estimates are lower: a systematic review with meta-regression.","authors":"Youli Jiang, Jingfang Chen, Linlin Liu, Wan Ling Lee, Rongjia Pan, Qiuyang Qian, Xing Tan, Ao Li, Yanfeng Li, Qingshi Zhao","doi":"10.1016/j.jclinepi.2026.112571","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2026.112571","url":null,"abstract":"<p><strong>Objective: </strong>Continued use of secondary prevention medications after ischemic stroke or transient ischemic attack is an important component of long-term management. Reported estimates of adherence and persistence vary considerably across studies, limiting comparison and interpretability. Although some variation may reflect differences in patient behavior, inconsistencies in operational definitions and measurement approaches are also likely to contribute. We sought to examine sources of heterogeneity and to derive standardized estimates using a common reference measurement framework.</p><p><strong>Study design and setting: </strong>We searched bibliographic databases, dissertations, and trial registries from inception to September 10, 2025, for routine-care studies reporting adherence or persistence to secondary prevention medications after ischemic stroke or transient ischemic attack. Cutoff-based proportions were extracted. We used 3-level hierarchical Bayesian models to characterize heterogeneity and multivariable meta-regression to evaluate associations with measurement specifications, follow-up window, medication class, region, and study-level characteristics. From the fitted model, we derived estimates standardized to a prespecified reference specification: pharmacy or administrative data, moderate definition stringency, and a 9- to 15-month follow-up window.</p><p><strong>Results: </strong>The review included 141 studies; 101 (432 estimates; 976,020 participants) contributed to the quantitative synthesis. Unstandardized pooled estimates suggested that 74.1% of patients were adherent and 76.8% were persistent. Heterogeneity was substantial, with explained variation concentrated more in the measurement-related Assessment and Administration domains than in reported Patient characteristics. Under the common reference specification, the model-based estimates were lower, at 53.7% for adherence and 48.2% for persistence. Standardized persistence declined from 63.3% at 1 to 4 months to 28.1% beyond 30 months. Adjusted estimates were generally lower in Asia; persistence was numerically lowest for anticoagulants, although credible intervals were wide and overlapping.</p><p><strong>Conclusion: </strong>A large proportion of the heterogeneity reported in medication adherence and persistence after ischemic stroke or transient ischemic attack appears to be attributable to methodological non-equivalence in how these outcomes are defined and measured. When evaluated within a standardized framework, suboptimal medication continuation appears more common than conventional pooled estimates indicate. Meaningful surveillance and benchmarking require longitudinal, standardized, and transparent measures of medication continuation rather than reliance on discharge prescribing alone.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"112571"},"PeriodicalIF":5.8,"publicationDate":"2026-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149247458","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":"When Clinical Prediction Models Meet Clinical Judgment: A Framework for Classifying Prediction Approaches.","authors":"Felix Kerscher, Ilse P Peringa, Eline G M Cox, Marvin Neumann, Iwan C C van der Horst, Rob R Meijer, Jacqueline Koeze","doi":"10.1016/j.jclinepi.2026.112572","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2026.112572","url":null,"abstract":"<p><strong>Background and objective: </strong>There is an ever increasing interest in using clinical prediction models to improve diagnostic and prognostic accuracy. However, the literature often conflates distinct prediction approaches, resulting in ambiguous findings and slowing scientific progress. This commentary aims to clarify the various ways in which physicians use clinical prediction models and highlight the implications of these approaches for prediction accuracy by drawing on an existing framework from the judgment and decision-making literature.</p><p><strong>Methods: </strong>We promote a framework distinguishing between four distinct prediction approaches: clinical judgment, mechanical judgment, clinical synthesis, and mechanical synthesis. We apply this framework to recent studies and illustrate how it distinguishes between previously conflated approaches.</p><p><strong>Results: </strong>Our analysis demonstrates that current research often obscures meaningful differences between the prediction approaches, thereby impeding improvement in patient care. The framework provides conceptual clarity and highlights clinical synthesis, in which the physician incorporates the model output into their own judgment, as a practical yet under-researched approach.</p><p><strong>Conclusions: </strong>The prediction accuracy achieved in practice depends on how physicians use clinical prediction models. Greater recognition and use of the proposed framework can improve future research by properly classifying prediction approaches, fostering more accurate research syntheses, and supporting the more effective and fair application of clinical prediction models in practice.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"112572"},"PeriodicalIF":5.8,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149228902","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":"Appraisal of Recent Intervention-Focused Umbrella Reviews Reveals Major Methodological Weaknesses: A Meta-Epidemiological Study.","authors":"Pawel Posadzki, Penny Whiting, Lisa Hartling, Dawid Pieper, Edoardo Aromataris, Javier Bracchiglione, Edzard Ernst, Ram Bajpai, Kavi Mathiyalagan, Hanan Khalil, Ritin Fernandez, Paolo Fusar-Poli, Zachary Munn, John P A Ioannidis","doi":"10.1016/j.jclinepi.2026.112569","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2026.112569","url":null,"abstract":"<p><strong>Background: </strong>Umbrella reviews (URs) are frequently used to provide high-level syntheses of evidence to inform clinical practice, policy, and guideline development. However, the methodological quality (MQ) and adherence to reporting standards of recent intervention-focused URs is understudied.</p><p><strong>Objective: </strong>To evaluate a random sample of recently published URs of interventions in health/medicine across several potential domains of MQ. Secondary objectives were to evaluate adherence to the Preferred Reporting Items for Overviews of Reviews (PRIOR) guideline and other recognised methodological guidance (e.g., Cochrane Handbook, JBI Manual).</p><p><strong>Methods: </strong>PubMed, Cochrane Library and Epistemonikos were searched in January 2026 for URs of interventions. We selected a random sample of 100 URs in health and/or medicine published between January 2024 and January 2026. Data were extracted pertaining to the following domains: identification and selection of systematic reviews (SRs), overlap of primary studies, bias inherited from included SRs, data extraction and evidence mapping, synthesis and interpretation bias, and reporting and transparency.</p><p><strong>Results: </strong>Of the 100 URs, 69% lacked a complete search strategy (median=4, IQR: 3-6 databases). Eligibility criteria were insufficiently reported in 96% of URs. Quantification of overlap was unclear in 77%, and only 11% considered overlap in synthesis. Only 21% of URs adhered to PRIOR. AMSTAR II was used in 77%, with AMSTAR I and JBI at 5% each. In 48%, inherited risk of bias from the SRs was high. Only 9% described how outdated or superseded SRs were managed and none managed discordant review conclusions. Outcome definitions were inconsistent in 71%, while only 9% avoided selective extraction of outcomes or analyses. Handling of multiple meta-analyses was unclear in 96%, and 71% selectively emphasised statistically significant results. Only 25% clearly described handling of heterogeneity and small-study effects, and 24% used evidence grading. 19% failed to register a protocol, and only 10% justified deviations from planned methods. Finally, 84% did not explicitly acknowledge umbrella-level limitations.</p><p><strong>Conclusions: </strong>We identified multiple methodological weaknesses in recent URs of interventions. Existing assessment tools appear only partially fit for purpose to assess the quality of the URs. Adherence to available guidance during the conduct and reporting of these recent URs is poor.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"112569"},"PeriodicalIF":5.8,"publicationDate":"2026-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149225434","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":"Systematic, contextual, and individual influences drive trialists' behaviour relating to greener trial design and delivery - A qualitative study.","authors":"Frank You, Taylor Coffey, Daniel Powell, Paula R Williamson, Katie Gillies","doi":"10.1016/j.jclinepi.2026.112568","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2026.112568","url":null,"abstract":"<p><strong>Objectives: </strong>To identify the key behavioural determinants that influence how people working in clinical trials ('trialists') design and deliver greener trials.</p><p><strong>Study design and setting: </strong>We conducted semi-structured focus groups and interviews with trialists involved in the design and conduct of clinical trials in the UK. Participants were recruited from a preceding survey, supplemented by purposive sampling through established trial networks and professional groups. Data collection was guided by the Theoretical Domains Framework (TDF) where analysis combined deductive TDF coding with inductive thematic development.</p><p><strong>Results: </strong>Three focus groups and nine interviews with a total of 23 participants including diverse roles, such as Clinical Trials Unit (CTU) directors, trial managers, statisticians, Quality Assurance staff, and researchers, were conducted. We identified 34 belief statements across all 14 TDF domains which were synthesised into five overarching themes: 1. Developing and promoting a culture for greener trials; 2. Weighing up the anticipated benefits against the unknowns; 3. Tensions between intrinsic and extrinsic priorities; 4. Degree of control over the enablement of greener trials; and 5. Negotiating gaps to address individual uncertainties. The study found that trialists' actions were shaped by a range of behavioural mechanisms. Cultural and contextual constraints, competing priorities, and limited organisational support were key challenges; while leadership, funders' expectations, and existing sustainability practices were identified as potential opportunities.</p><p><strong>Conclusion: </strong>This study provides an in-depth theory-informed behavioural analysis of the challenges and opportunities for making clinical trials greener. These findings provide a basis for designing behaviour change strategies to support trialists' adoption of greener trials.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"112568"},"PeriodicalIF":5.8,"publicationDate":"2026-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149225369","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":"Identifying the behavioural determinants of trialists for the design and delivery of greener trials - A cross-sectional survey study.","authors":"Frank You, Taylor Coffey, Daniel Powell, Paula R Williamson, Katie Gillies","doi":"10.1016/j.jclinepi.2026.112567","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2026.112567","url":null,"abstract":"<p><strong>Objectives: </strong>To understand the behavioural determinants of people working in clinical trials ('trialists') to support greener trials which, in this survey, refer to those being designed and delivered without unnecessary, disproportionate, or unexamined carbon emissions.</p><p><strong>Study design: </strong>AND SETTING: We conducted an online cross-sectional survey of trialists involved in the design, conduct, analysis, or reporting of clinical trials. Recruitment targeted established trial networks in the UK and Ireland supplemented by social media and snowball sampling. Data collected included demographics, attitudes to climate change risk (ACCRs), perceived capability, opportunity and motivation in relation to design and delivery of greener trials through application of the 'Capabilities, Opportunities, Motivations - Behaviour' (COM-B) model, and self-reported behavioural specification for greener trials.</p><p><strong>Results: </strong>We received 88 responses mainly from the UK and Ireland. Respondents, on average, were concerned about climate change. Most respondents considered the carbon impact of their professional activities at least sometimes. Most respondents reported high levels of psychological capability and reflective motivation, but less agreement on social opportunity, physical opportunity, and automatic motivation when considering the design and delivery of greener trials. Several key actors (e.g., trial staff, funders) and actions (e.g., institutional incentives, green technologies) were proposed by respondents as important targets for change.</p><p><strong>Conclusion: </strong>This study investigated trialists' perspectives on the design and delivery of greener trials through a behavioural lens. Our findings highlight key behavioural determinants that could be targets for future intervention development. In addition, our results demonstrate the range of actors and actions that are important in the clinical trial ecosystem to ensure greener trials become routine. Behavioural models offer valuable insights for guiding the development of relevant strategies for change.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"112567"},"PeriodicalIF":5.8,"publicationDate":"2026-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149217349","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":"Validation studies of ICD-10 diagnostic codes for identifying common causes of hospitalization: a scoping review.","authors":"Heather I Henderson, Alexander C Commanday, Zhihua Liu, Kendall N McClellan, Lindsay E Browne, Amanda E Moy, Carol Golin, Claire E Farel, Darren A DeWalt, Joseph J Eron, Sonia Napravnik","doi":"10.1016/j.jclinepi.2026.112570","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2026.112570","url":null,"abstract":"<p><strong>Background: </strong>International Classification of Diseases, Tenth Revision (ICD-10) diagnosis codes are widely used to identify clinical conditions in administrative health data for epidemiologic research, surveillance, and health services evaluation. However, the validity of ICD-10-coded diagnoses varies across conditions and healthcare settings, and validation studies differ substantially in design, case definitions, and reporting practices.</p><p><strong>Objective: </strong>To characterize validation studies of ICD-10-based case definitions for eight common causes of hospitalization and identify methodological factors affecting the interpretation and comparability of reported performance estimates.</p><p><strong>Design: </strong>PubMed and Embase (2005-2025) were searched for systematic reviews and primary studies validating ICD-10-coded diagnoses for the following conditions: heart failure, osteoarthritis, pneumonia, diabetes mellitus, acute myocardial infarction, chronic obstructive pulmonary disease, acute kidney injury, and stroke. Data on study characteristics, case definitions, reference standards, and performance metrics were extracted and descriptively summarized.</p><p><strong>Results: </strong>We identified 116 unique primary publications through 11 systematic reviews and our database search. Stroke and heart failure had the largest evidence base, whereas few validation studies were identified for several conditions. More than one-third of studies reported only positive predictive value, typically reflecting a study design that verified algorithm-identified cases and therefore precluded estimation of sensitivity and specificity. When reported, specificity was generally high, whereas sensitivity varied considerably; however, differences in study design limited comparability of estimates. Incorporating laboratory results, procedures, medications, or other electronic health record data often improved the performance of ICD-10-based case definitions.</p><p><strong>Conclusions: </strong>Validation studies of ICD-10-coded diagnoses are highly heterogeneous in design and reporting, limiting direct comparison across studies. Many rely on designs that only estimate positive predictive value and therefore provide incomplete assessments of validity. Standardized, population-based validation studies measuring both sensitivity and specificity are needed to improve the reliability and reproducibility of administrative health data for epidemiologic research, surveillance, and quality improvement.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"112570"},"PeriodicalIF":5.8,"publicationDate":"2026-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149217276","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 critical review of clinical prediction models in oncology: is this SEERious research?","authors":"Biruk Tsegaye, Jie Ma, Jadwiga Fryc, Zahina Yasmin, Melissa Brookfield, Richard D Riley, Paula Dhiman, Gary S Collins","doi":"10.1016/j.jclinepi.2026.112566","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2026.112566","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Objectives: &lt;/strong&gt;The National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) cancer registry covers almost half the United States population. Clinical prediction models developed using the SEER cancer registry have rapidly grown in number. We sought to characterise and examine the extent to which this body of work reflects formulaic research practices, reflected by a lack of clear objectives, substandard methods and practices with limited scientific value.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Study design and setting: &lt;/strong&gt;We conducted a systematic review of clinical prediction model development studies using the SEER data. MEDLINE via PubMed was searched for studies published between January 1 and August 10, 2023. Studies were included if they developed a clinical prediction model using two or more predictors from the SEER database. Data extraction covered study context, intended use, predictor characteristics, reporting guideline adherence, external validation practices, and the rationale provided for using SEER.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Of 436 eligible studies, 94% (n=412) had first authors affiliated with institutions in China, while 3% (n=14) were from the United States. Developed models mostly targeted lung (11%) and breast (10%) cancers, and most focussed on prognosis (87%). Cox regression was the predominant modelling approach (59%), and nomograms were the most common presentation format (77%). Reporting guideline adherence was low (13%), and study protocols were rarely mentioned (3%). Nearly one third of models included patients' race as a predictor (32%). Of the China-affiliated studies, only 6% reported an intended clinical setting, and 3% specified the intended country of use. Discussion of the suitability of SEER was absent in 87% of included studies. Among China-affiliated studies, 22% carried out external validation using data from China. Over a ten-year period, expanding our search strategy identified more than 4,000 SEER-based prediction model studies indexed in MEDLINE, with annual output growing from 37 in 2016 to over 700 in 2023.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Access to data alone does not justify model development. Most prediction models developed using SEER lack a clearly reported rationale, defined target population, an intended clinical purpose, and fail to address whether the models produced with the SEER data are appropriate for populations outside the United States. Readers should treat SEER-based prediction model studies with appropriate scepticism until evidence of rigorous methodology and clinical relevance is demonstrated. Many studies have limited scientific value and exhibit hallmarks of formulaic research created solely to boost researcher's resumé. Journals, peer reviewers, and data custodians all have a responsibility to ensure high research standards for studies exploiting widely available datasets, as the growing volume of such output places editorial and peer review systems un","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"112566"},"PeriodicalIF":5.8,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149197556","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":"Flipping death-to-survival event coding shifted pooled risk ratios and GRADE imprecision ratings in 2,071 Cochrane meta-analyses.","authors":"Yasushi Tsujimoto, Yuki Kataoka, Yusuke Tsutsumi, Ryuhei So, Toshi A Furukawa","doi":"10.1016/j.jclinepi.2026.112553","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2026.112553","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;When meta-analyzing a dichotomous outcome such as death or survival, reviewers must decide which side of the outcome to code as the event. In a single study, death and survival are two sides of the same dichotomous outcome, and the choice does not change the result. However, in a meta-analysis using the risk ratio, this choice affects the weight given to each study. Pooling deaths and pooling survivors need not give equivalent results. We evaluated how flipping the event coding of death or survival outcomes affects pooled risk ratios, precision, and GRADE imprecision judgments across Cochrane reviews.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Study design and setting: &lt;/strong&gt;We conducted a meta-epidemiological study of Cochrane reviews with death or survival outcomes that used risk ratios or odds ratios as the effect measure. For each meta-analysis, we created a flipped version of the reported 2 x 2 data by replacing event counts with total minus events. We then calculated pooled risk ratios for the original and flipped data using random-effects Mantel-Haenszel methods. The flipped pooled risk ratio was re-expressed as its reciprocal on the original scale and compared with the original as a ratio of risk ratios. We compared statistical significance, confidence intervals, and GRADE imprecision ratings between original and flipped analyses. We repeated the analysis using odds ratios and examined subgroups by total sample size, baseline control event rate, and single-zero or double-zero studies.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 2,071 meta-analyses were included. The median ratio of risk ratios was 1.17 (IQR 1.05 to 1.42), showing that flipping moved the pooled risk ratio toward the null in most meta-analyses. Statistical significance changed in 199 (9.6%). GRADE imprecision changed in 1,211 (58%): worsening in 672 (32%) and improving in 539 (26%). Using odds ratios instead of risk ratios showed a far smaller divergence. The discrepancies were apparent in meta-analyses with single-zero or double-zero studies, low baseline control event rates, small total sample sizes, or large original effect sizes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;Flipping the event coding of death or survival outcomes changed risk ratio results and GRADE imprecision judgments considerably, especially in sparse or small meta-analyses. Systematic reviewers should use odds ratios instead of risk ratios when primary studies did not originally use a consistent event coding.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Plain language summary: &lt;/strong&gt;When researchers combine results from multiple clinical trials (a meta-analysis) to see whether a treatment changes the risk of death, they must first decide whether to count deaths or survivors as the \"event.\" In a single trial, this choice does not matter. We found that in a meta-analysis, it can matter a great deal: recoding deaths as survivors (or vice versa) changed the combined result, whether it was statistically significant, and how confident rev","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"112553"},"PeriodicalIF":5.8,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149197498","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":"Reporting of Financial Relationships in Primary Studies Included in Systematic Reviews of Interventions for Common Diagnoses.","authors":"Marek Czajkowski, Louise Olsson","doi":"10.1016/j.jclinepi.2026.112565","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2026.112565","url":null,"abstract":"<p><strong>Objective: </strong>Although systematic reviews (SRs) are recommended to report authors' financial disclosures and funding sources from primary studies, the completeness of such reporting is not well known. This study examines the reporting of financial disclosures in primary studies included in SRs of interventions for six common conditions of public health importance.</p><p><strong>Methods: </strong>In this cross-sectional methodological study, all primary studies included in 17 previously identified SRs with low risk of bias were retrieved. Declarations of financial conflicts of interest (COI), industry funding, and authors' industry affiliation were extracted from the primary studies and compared with reporting in the SRs. The SRs were stratified according to the disclosure status of financial COI among their authors.</p><p><strong>Results: </strong>Out of 300 identified randomized controlled trials (RCTs), financial COI were declared by at least one author in 131 (44%), but none were reported in the SRs. Industry funding was declared in 185 (62%) RCTs and reported for 112 (37%) in the SRs. At least one author was affiliated with industry in 141 (47%) RCTs and reported for 2 (1%) RCTs in the SRs. Altogether, 206 (69%) RCTs declared any form of financial relationship with industry compared with 113 (38%) reported in the SRs. SRs with at least one author declaring financial COI included a higher proportion of RCTs declaring any financial relationship with industry (82% vs 51%).</p><p><strong>Conclusions: </strong>Financial COI in RCTs were not reported in this sample of clinically relevant SRs, and funding information was also inadequately reported. This methodological shortcoming hinders readers' ability to fully assess the findings of the SRs.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"112565"},"PeriodicalIF":5.8,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149197547","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":"Development and internal validation of the NOTICE assessment as a non-biological measure of prenatal nicotine, tobacco, and cannabis use and exposure.","authors":"Elizabeth A Burmeister, Min-Tz Weng, Kathryn J Steadman, Jared A Miles, Qiuda Zheng, Angela Ratsch","doi":"10.1016/j.jclinepi.2026.112552","DOIUrl":"https://doi.org/10.1016/j.jclinepi.2026.112552","url":null,"abstract":"<p><strong>Objectives: </strong>Accurate measurement of tobacco, nicotine and cannabis use and exposure during pregnancy is essential for research and clinical care, yet existing perinatal surveillance relies on simplified self-report that inadequately captures exposure patterns. Biological assays provide objective measurement but are invasive, costly, limited to short detection windows, and impractical for repeated or population-level use. This study aimed to develop and internally validate the Nicotine, Tobacco and Cannabis Use and Exposure (NOTICE) assessment as a low-burden, non-biological behavioural tool for use and exposure during pregnancy.</p><p><strong>Study design and setting: </strong>In a longitudinal cohort of Australian First Nations pregnant women, repeated NOTICE assessments were collected across pregnancy alongside exhaled carbon monoxide, saliva cotinine, and urinary free cotinine and total 11-Nor-9-carboxy-Δ9-tetrahydrocannabinol (THC-COOH), with and without creatinine correction. Weekly self-use and exposure scores were combined into a weighted, standardised composite score. Discriminative validity relative to biochemical reference standards was assessed using receiver operating characteristic analysis. Area under the curve (AUC) estimates with bias-corrected and accelerated bootstrap confidence intervals clustered by participant were calculated. Population-averaged associations were examined using generalised estimating equations.</p><p><strong>Results: </strong>The composite NOTICE score demonstrated very high discrimination for tobacco and nicotine exposure relative to creatinine-corrected cotinine ≥5 ng/mg cr (AUC = 0.99; 95% CI 0.98-1.00) and high discrimination for cannabis exposure relative to creatinine-corrected THC-COOH ≥80 ng/mg cr (AUC = 0.92; 95% CI 0.83-1.00). Discrimination was stable across alternative biomarker thresholds and consistently superior to exposure-only measures. Weekly scores demonstrated better discriminative performance than daily scores.</p><p><strong>Conclusion: </strong>NOTICE is a low-burden behavioural assessment that demonstrates strong criterion-based alignment with established biochemical reference standards for measuring tobacco, nicotine and cannabis use and exposure during pregnancy. By integrating active use and environmental exposure across products and timeframes, the tool supports repeated measurement and surveillance of exposure patterns in settings where routine biological testing is impractical.</p>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":" ","pages":"112552"},"PeriodicalIF":5.8,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149185788","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}