Journal of Clinical Epidemiology最新文献

{"title":"Review of methods to deal with the misalignment of times of eligibility, start of follow-up, and treatment assignment in studies explicitly aimed at emulating target trials","authors":"Matthew McIntyre , Sally Yaacoub , Elodie Perrodeau , Raphael Porcher , Viet-Thi Tran","doi":"10.1016/j.jclinepi.2025.111898","DOIUrl":"10.1016/j.jclinepi.2025.111898","url":null,"abstract":"<div><h3>Objectives</h3><div>Real world evidence based on observational data from cohorts, registries, and health-care databases are increasingly used to assess the effectiveness of therapeutic interventions, often using the target trial emulation framework. One challenge when analyzing observational data are risks of biases due to misalignment of times of eligibility, start of follow-up, and treatment assignment. We aimed to describe the methods used to generate alignment or to account for misalignment in studies explicitly aimed at emulating target trials, and to estimate the proportion of studies for which a low-cost change would limit the risk of biases associated with misalignment of the times.</div></div><div><h3>Study Design and Setting</h3><div>We analyzed 199 studies explicitly aiming at emulating a target trial identified in a previous systematic review from Hansford et al. Two reviewers extracted the times of eligibility, start of follow-up, and treatment assignment and the methods used by authors to generate alignment or to account for misalignment of time points.</div></div><div><h3>Results</h3><div>Out of the 199 studies, 181 (91%) reported the times of eligibility, start of follow-up, and treatment assignment. All time points were aligned for 93/181 (51%), with 73 using no specific method, 18 emulating a sequence of target trials, and 2 using other methods to generate alignment. In contrast, 88/181 (49%) studies had misalignment of time points, of which 29 used a method to correct for misalignment during analysis (24 studies used a cloning, censoring, and weighting approach; 4 randomly allocated patients with early events; and 1 randomly allocated all participants to the study groups with subsequent censoring when they deviated from the allocated intervention). Out of 59/88 (67%) studies that did not use any method to address nonalignment, 46/59 (78%) could have applied low-cost changes to account for misalignment.</div></div><div><h3>Conclusion</h3><div>Approximately, half of the studies explicitly aiming to emulate a target trial had alignment of times of eligibility, start of follow-up, and treatment assignment, either by design or using a method generating alignment. Among studies with misalignment, about 67% did not account for it in the analysis among which 78% could have applied low-cost changes to reduce bias.</div></div><div><h3>Plain Language Summary</h3><div>Researchers increasingly use real-world evidence from sources like routinely collected or claims data to assess the efficacy and safety of therapeutic interventions (medications, surgery, physiotherapy, etc). To prevent design errors when analyzing these data, researchers follow a framework called “target trial emulation”. A crucial aspect of this framework is to ensure that three key time points of the study are aligned during analysis: the times at which 1) participants in the database are assessed for eligibility in the study (ie, when do we choose to include them","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"185 ","pages":"Article 111898"},"PeriodicalIF":5.2,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610189","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":"Anchor-based predictive modeling and receiver operating characteristic curve estimates of patient acceptable symptom state for the forgotten joint score in total knee arthroplasty patients stratified by age and gender","authors":"Glory Uche Abugu ,&nbsp;Nicholas Holloway ,&nbsp;Philip Riches ,&nbsp;Jon Clarke ,&nbsp;Mario Ettore Giardini ,&nbsp;Swati Chopra","doi":"10.1016/j.jclinepi.2025.111897","DOIUrl":"10.1016/j.jclinepi.2025.111897","url":null,"abstract":"<div><h3>Objectives</h3><div>This study aimed to estimate patient acceptable symptom state (PASS) thresholds in the Forgotten Joint Score (FJS) 1 year following primary total knee arthroplasty (PTKA) while investigating the impact of patients’ characteristics on PASS thresholds.</div></div><div><h3>Study Design and Setting</h3><div>This cohort study used data from patients who underwent PTKA at a public hospital in Scotland between April 2021 and December 2022. Assessment of FJS (0-100, high-low knee awareness) was completed 1 year postoperatively. A single-item question about satisfaction with the operated knee was completed at 1 year and served as the anchor for estimating PASS thresholds. Anchor-based predictive modeling (adjusted and unadjusted) and receiver operating characteristic (ROC) curve methods were used to determine PASS thresholds. The impact of patient characteristics on PASS threshold values was investigated by calculating stratified PASS values based on gender and age groups.</div></div><div><h3>Results</h3><div>A total of 1832 PTKAs were performed between April 2021 and December 2022, of which 1359 (74%) had complete data comprising the study cohort. The median age and body mass index of patients included in the study were 70 years and 31.2 <span><math><mrow><msup><mrow><mtext>kg</mtext><mo>/</mo><mi>m</mi></mrow><mn>2</mn></msup></mrow></math></span>, respectively, with 54% being females. The proportion of satisfied patients was 84%. A moderate positive correlation between FJS and patient satisfaction was found (<em>r</em> = 0.64, <em>P</em> &lt; .001), which supports the validity of the external anchor. PASS thresholds for the entire cohort were 31 (ROC method) and ∼33 points (predictive modeling method). Larger PASS values were found for male patients and patients aged ≥70 years compared to their female and younger counterparts. The adjusted predictive modeling estimate was 15.3; given that the data do not meet the assumption of normal distribution, we consider this threshold might be biased and must be interpreted with circumspection.</div></div><div><h3>Conclusion</h3><div>A postoperative FJS of ≥33 points can be used as a reference guide to evaluate successful achievement of a “forgotten joint” in a Scottish population. Patients’ characteristics impact PASS estimates and should be considered when interpreting outcome scores.</div></div><div><h3>Plain Language Summary</h3><div>After knee replacement surgery, patients want their new knee to feel natural. The FJS measures how much a person notices their artificial knee in daily life. The score goes from 0 to 100, with higher numbers meaning the knee feels more natural. We studied data from over 1300 patients in Scotland using modern statistical methods. Our results show that most patients need a score of at least 33 to feel satisfied with their knee 1 year after surgery, while men and people aged ≥70 years seem to need higher scores.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"185 ","pages":"Article 111897"},"PeriodicalIF":7.3,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144602174","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 microsimulation model based on healthcare pathways to estimate the impact of COVID-19 pandemic–induced delays on breast cancer mortality","authors":"A.M. Fraslin ,&nbsp;T. Stockholm ,&nbsp;T. Filleron ,&nbsp;A. Bertaut ,&nbsp;A. Blanc-Lapierre ,&nbsp;J. Marghadi ,&nbsp;A. Aupérin ,&nbsp;J. Bonastre","doi":"10.1016/j.jclinepi.2025.111896","DOIUrl":"10.1016/j.jclinepi.2025.111896","url":null,"abstract":"<div><h3>Objectives</h3><div>This study aimed to develop a microsimulation model to estimate the impact of a care disruption during the COVID-19 pandemic on breast cancer mortality using an administrative database.</div></div><div><h3>Study Design and Setting</h3><div>Patient flows and pathways were assessed from the French hospital discharge database for four French cancer centers for patients with breast cancer from 2018 to 2021. Patients' return dynamics were compared to time series predictions to determine flow differences. Forecasted and observed patients were matched through healthcare pathways to account for possible delay heterogeneity among patients with breast cancer. Healthcare pathways were modeled and analyzed as sequences of states defined based on hospital treatments. Unmatched patients were reconsidered for matching the next month, with incrementing delays. We derived the number of expected additional cancer deaths at 5 years and the associated relative mortality rate using hazard ratios (HRs) associated with delays extracted from the literature. A deterministic sensitivity analysis was performed on HRs. Confidence intervals were computed for each outcome based on 1000 bootstrap replications.</div></div><div><h3>Results</h3><div>A forecasted population of 8125 patients with incident breast cancer was analyzed. An overall decrease of 20.8% in flows was estimated during the first lockdown. For the year following the beginning of the lockdown, 24.8% of patients were expected to receive delayed care, resulting in a 4.6% excess cancer mortality rate at 5 years among the 8125 forecasted patients.</div></div><div><h3>Conclusion</h3><div>Using an innovative approach based on patient-level data from an administrative database, our study further strengthens previous estimates of excess breast cancer mortality following the COVID-19 pandemic.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"185 ","pages":"Article 111896"},"PeriodicalIF":7.3,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144576887","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":"Comparison of AI-assisted and human-generated plain language summaries for Cochrane reviews: protocol for a randomized trial (HIET-1)","authors":"Declan Devane ,&nbsp;Johanna Pope ,&nbsp;Paula Byrne ,&nbsp;Evan Forde ,&nbsp;Steven Woloshin ,&nbsp;Eileen Culloty ,&nbsp;Darren Dahly ,&nbsp;Ingeborg Hess Elgersma ,&nbsp;Heather Munthe-Kaas ,&nbsp;Conor Judge ,&nbsp;Martin O'Donnell ,&nbsp;Finn Krewer ,&nbsp;Sandra Galvin ,&nbsp;Nikita Burke ,&nbsp;Theresa Tierney ,&nbsp;KM Saif-Ur-Rahman ,&nbsp;Tom Conway ,&nbsp;James Thomas","doi":"10.1016/j.jclinepi.2025.111894","DOIUrl":"10.1016/j.jclinepi.2025.111894","url":null,"abstract":"<div><div>Plain language summaries (PLSs) of systematic reviews present complex health evidence in accessible language. Advances in artificial intelligence (AI), particularly large language models, may enhance the generation of PLSs. This protocol describes a randomized, parallel-group, two-armed, noninferiority trial comparing AI-assisted vs human-generated PLSs. Adults aged 18 years or older, proficient in English, will be recruited online via an audience recruitment platform. Participants are randomly assigned (1:1 ratio) to (1) the intervention group: three AI-assisted PLSs based on recent Cochrane reviews; or (2) the control group: three human-generated Cochrane PLSs. The primary outcome is comprehension (aligned with QUEST's Understanding dimension), assessed via a 10-item multiple-choice questionnaire for each summary, structured according to Cochrane PLS template sections. Secondary outcomes are readability, quality of information, safety considerations, and perceived trustworthiness. This study aims to provide insights into integrating AI technologies in health communication. Its findings will inform future practices in disseminating evidence-based health information to the public.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"185 ","pages":"Article 111894"},"PeriodicalIF":7.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144685629","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":"Peer review reports of randomized controlled trials in oncology can be short and superficial","authors":"Patricia Logullo ,&nbsp;Angela MacCarthy ,&nbsp;Shona Kirtley ,&nbsp;Garrett S. Bullock ,&nbsp;Paula Dhiman ,&nbsp;Jie Ma ,&nbsp;Gary S. Collins","doi":"10.1016/j.jclinepi.2025.111893","DOIUrl":"10.1016/j.jclinepi.2025.111893","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Objectives&lt;/h3&gt;&lt;div&gt;To evaluate the quality of open peer review reports published alongside articles of randomized controlled trials (RCTs) in oncology.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;We searched and sampled from completed parallel RCT articles published in 2021 in 62 BioMed Central journals operating open peer review and evaluated their first-round peer review report. We assessed and described the peer review report content, clarity, and completeness and explored whether reviewers commented on the manuscript's importance, robustness, interpretation, discussion of results, and RCT reporting. Two investigators evaluated the review reports independently, with conflict resolution involving a third author.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;We sampled 26 RCTs and evaluated their 59 first peer review reports. Median word count was 276 (range = 0–1047). Only 11 reports were constructive (19%), suggesting solutions for the problems noted. Of reviewers commenting on the manuscript's methods section (&lt;em&gt;n&lt;/em&gt; = 46/59, 78%), 74% (&lt;em&gt;n&lt;/em&gt; = 34/46) addressed the suitability of the methodology. Fewer commented on the adequacy of conclusions (&lt;em&gt;n&lt;/em&gt; = 15/59; 25%) or the applicability of results (&lt;em&gt;n&lt;/em&gt; = 5/59; 9%), or whether study limitations had been acknowledged by authors (&lt;em&gt;n&lt;/em&gt; = 11/59; 18%). Only four (7%) commented on open research practices, including deviations from protocols, completeness of reporting, and sharing of data and materials.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusion&lt;/h3&gt;&lt;div&gt;Peer review reports of published RCTs in oncology were short, superficial, and rarely constructive. Although there is indication that reviewers commented on study methodology, little attention was paid to study conclusions, deviation from study protocols, completeness of reporting, or data availability. Such review reports would be of limited value to authors for improving their trial study manuscripts, or to editors in deciding on manuscript publication.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Plain Language Summary&lt;/h3&gt;&lt;div&gt;Clinical trials are research studies that test whether a treatment or action works to help prevent or treat a disease. The results from these studies are important because they help doctors and policy makers decide what care is best for patients. Before the results from a clinical trial are published, other experts, sometimes including members of the public, carefully check the study to make sure it was conducted properly and that the results are trustworthy. This checking process is called “peer review”. Reviewers look at things like how the study was carried out, whether the results make sense, and if the conclusions are fair. In our project, we looked at how well this peer review process worked in a selection of medical journals that make their review reports public. We read the reviews for 26 published trials to see what the reviewers said. We found that most of the review reports were very short and did not provide much detail to help th","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"185 ","pages":"Article 111893"},"PeriodicalIF":7.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144555652","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 population-based recalibration method for updating survival neural networks models for cardiovascular risk prediction in United Kingdom and China","authors":"Xiaofei Liu ,&nbsp;Jun Zhang ,&nbsp;Larry Liu ,&nbsp;Xun Tang ,&nbsp;Pei Gao","doi":"10.1016/j.jclinepi.2025.111895","DOIUrl":"10.1016/j.jclinepi.2025.111895","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Objectives&lt;/h3&gt;&lt;div&gt;Machine learning algorithms, particularly survival neural networks (SNNs), promise to improve cardiovascular disease (CVD) risk prediction. However, the necessity and approach for recalibrating SNN models across diverse populations remain unclear. We aimed to propose a population-based recalibration method and validate it using two large cohort studies.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Study Design and Setting&lt;/h3&gt;&lt;div&gt;A total of 347,206 individuals aged 40–74 years without prior CVD from UK Biobank (UKB) were for model training and internal validation and 177,756 individuals from a Chinese cohort study (CHinese Electronic health Records Research in Yinzhou [CHERRY]) were for external validation. Three types of SNN models (DeepSurv, age-specific DeepSurv, and DeepHit) were developed for the 10-year CVD risk prediction and compared to Cox models. These models were recalibrated using the proposed method to adjust for differences in disease incidence between populations based on population-level summarized data, and compared with a traditional method that used individual-level data.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;All SNN models demonstrated robust discrimination in both UKB and CHERRY validation sets (C-indices&gt;0.720), but underpredicted risk for CHERRY populations by 60%. The population-based recalibration method largely corrected the initial risk underestimation, yielding observed-to-expected (O:E) ratios of 1.080, 1.115, and 1.153 for recalibrated DeepSurv, age-specific DeepSurv, and DeepHit, achieving comparable calibration to individual-based recalibration method (O:E ratios: 1.040, 1.054 for DeepSurv and age-specific DeepSurv). The well-calibrated age-specific DeepSurv and Cox models identified high-risk groups with distinct characteristics, with 79% overlap for women and 63% for men.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusion&lt;/h3&gt;&lt;div&gt;The proposed method effectively adjusts predictions for survival neural network models using population-level summarized data without modifying the original network, making recalibration essential for applying machine learning models to different populations. The method highlights the clinical potential of SNN models for broader application across diverse regions.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Plain Language Summary&lt;/h3&gt;&lt;div&gt;Machine learning, particularly neural networks for survival analysis, shows great potential in disease risk prediction but typically requires adjustments, or \"recalibration\" for diverse populations. We proposed a recalibration method using population-level summarized data, rather than individual data, which is often hard to obtain. We derived several survival neural network models for 10-year cardiovascular disease risk prediction in the UK Biobank and validated them in the CHinese Electronic health Records Research in Yinzhou (CHERRY) cohort. Although the models ranked individual risk effectively, they underpredicted actual risk in the Chinese population. The proposed method successfully","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"185 ","pages":"Article 111895"},"PeriodicalIF":7.3,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144555651","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":"Individual participant data–informed risk of bias assessments for randomized controlled trials in systematic reviews and meta-analyses","authors":"James X. Sotiropoulos ,&nbsp;Kylie E. Hunter ,&nbsp;Jannik Aagerup ,&nbsp;Jonathan G. Williams ,&nbsp;Sol Libesman ,&nbsp;Mason Aberoumand ,&nbsp;Angie Barba ,&nbsp;Rui Wang ,&nbsp;Thomas D. Love ,&nbsp;Brittany J. Johnson ,&nbsp;Anna Lene Seidler","doi":"10.1016/j.jclinepi.2025.111875","DOIUrl":"10.1016/j.jclinepi.2025.111875","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Objectives&lt;/h3&gt;&lt;div&gt;In evidence synthesis, assessing risk of bias (ROB) of eligible studies is crucial to inform interpretation of findings. Standardized tools like Cochrane's ROB-1 or ROB-2 traditionally rely on published information to inform assessments, but this is often incomplete or unclear. Availability of raw individual participant data (IPD) enables more in-depth assessments; however, guidance on how to use IPD in ROB assessments is lacking. We aim to develop preliminary guidance on how to use IPD to inform ROB assessments of randomized controlled trials (RCTs) for three case studies.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Study Design and Setting&lt;/h3&gt;&lt;div&gt;In stage 1, we reviewed relevant literature, consulted our networks, and drew on previous experience to compile items on how IPD may inform ROB assessment for each domain. We discussed feasibility and potential usefulness of each item with an international, interdisciplinary expert advisory group and developed preliminary guidance, which was piloted in two IPD meta-analyses (MAs) (65 RCTs) using ROB-1. In stage 2, the guide was adapted for ROB-2 and applied to another IPD-MA (34 RCTs). All assessments were conducted in duplicate by two independent reviewers. In stage 3, we conducted an evaluation workshop to further refine each item, and capture important lessons. To assess the impact of IPD-informed assessments, we compared them to existing ROB-1 assessments performed with published information alone for 33 trials.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;We identified 12 items across the ROB domains. IPD provided opportunities to enhance ROB assessments by enabling additional checks for selection bias (ie, testing randomization) and attrition bias (ie, more granular assessment of incomplete data at various time points). We also identified domains for which availability of IPD enabled reduction of ROB, for instance, by mitigating selective outcome reporting bias or by reincluding excluded participants in intention-to-treat analyses. Applying IPD-informed assessments led to changes in ROB judgment in 25 of 33 studies, most commonly, resolution of domains previously marked as “unclear”.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusion&lt;/h3&gt;&lt;div&gt;Our preliminary guidance for IPD-informed ROB assessments may be applied in IPD-MAs to increase the accuracy of ROB assessments and in some cases reduce ROB to create a more reliable evidence base informing policy and practice.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Plain Language Summary&lt;/h3&gt;&lt;div&gt;When making decisions about how to treat a patient in clinical practice, it is important to consider the results of all relevant studies. Usually, combined analyses of multiple clinical trials rely on published reports, in which researchers summarize their findings. However, looking at the original data from these studies, instead of just the published reports, can improve the quality of analyses. Access to these underlying data also allows for more thorough assessment of the studies' quality and any pot","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"185 ","pages":"Article 111875"},"PeriodicalIF":7.3,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144530972","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":"Clinical study report data did not substantially alter point estimates but improved precision in a nephrology systematic review","authors":"Julian Hirt ,&nbsp;Dawid Pieper ,&nbsp;Monika Becker ,&nbsp;Jessica Breuing ,&nbsp;Mark R. Marshall ,&nbsp;Käthe Goossen","doi":"10.1016/j.jclinepi.2025.111890","DOIUrl":"10.1016/j.jclinepi.2025.111890","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Objectives&lt;/h3&gt;&lt;div&gt;To investigate the effect of adding clinical study report (CSR) data to publication and author data on data completeness and meta-analytical results.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Study Design and Setting&lt;/h3&gt;&lt;div&gt;Case report of a systematic review with meta-analysis of randomized controlled trials on icodextrin compared to glucose solutions in peritoneal dialysis including 19 clinical trials. We considered the outcomes mortality, peritoneal dialysis technique failure, quality of life, net peritoneal ultrafiltration (at 3–6 months, and 1–2 years), serious adverse events (SAE), peritonitis, and uncontrolled fluid overload. The results for these outcomes were reanalyzed using (a) publication and author data only, then compared with (b) publication and author data with added CSR data. At outcome level, we compared the number of included trials, pooled point estimates (ie, regarding effect direction), and 95% confidence intervals (CIs; ie, regarding overlap and width) between the two groups of trials (a and b). We illustrated the results of our meta-analyses in forest plots and narratively summarized them.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;Except for two of the eight assessed outcomes (quality of life and net peritoneal ultrafiltration [1–2 years]), more complete data was available when adding CSRs to publication and author data. Point estimates were not statistically significantly different for publication and author data, compared to publication, author, and CSR data, for any outcome. For peritonitis, point estimates were on opposite sides of the line of no effect but remained statistically nonsignificant when adding CSR data. For SAE and net peritoneal ultrafiltration (3–6 months), the width of the 95% CI was narrower when adding CSR data and for net peritoneal ultrafiltration (3–6 months), in addition, the point estimate statistically significantly favored icodextrin when adding CSR data.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusion&lt;/h3&gt;&lt;div&gt;The fraction of publications reporting results varied substantially by outcome, with SAE most under-reported in publications. While the integration of CSR data did not substantially alter meta-analytical results, it enhanced data completeness and precision in effect estimates. Our findings underscore the importance of accessing CSR data to optimize evidence syntheses and inform clinical decision-making.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Plain Language Summary&lt;/h3&gt;&lt;div&gt;When researchers want to understand how well a treatment works, they often combine results from several clinical studies in a process called a meta-analysis. Usually, these analyses rely on data published in scientific journals. However, published articles don't always include all the important results. Additional information can sometimes be found in clinical study reports (CSRs), which are detailed documents submitted by pharmaceutical companies to regulatory agencies. In this study, we looked at how including CSR data might affect the results of a ","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"185 ","pages":"Article 111890"},"PeriodicalIF":7.3,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144530971","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":"Metformin to treat breast cancer: an application of the prevalent new-user design for observational studies with no active comparator","authors":"Charles Khouri ,&nbsp;Sophie Dell’Aniello ,&nbsp;Hui Yin ,&nbsp;Laurent Azoulay ,&nbsp;Samy Suissa","doi":"10.1016/j.jclinepi.2025.111880","DOIUrl":"10.1016/j.jclinepi.2025.111880","url":null,"abstract":"<div><h3>Objectives</h3><div>Numerous observational studies have reported significant reductions in cancer outcomes, including breast cancer in women, with metformin use. However, most studies were affected by immortal time bias. We assessed whether metformin use in women diagnosed with breast cancer is associated with lower breast cancer-related and all-cause mortality and illustrate the impact of immortal time bias on the results.</div></div><div><h3>Study Design and Setting</h3><div>The Clinical Practice Research Datalink was used to identify a base cohort of all women with a new diagnosis of breast cancer and with type 2 diabetes, at least 18 years of age, between 1998 and 2020. We employed the prevalent new-user design to match metformin initiators 1:1 with nonusers on a prior diabetes diagnosis and time-conditional propensity scores. We also used the naïve approach that introduces immortal time when classifying metformin users. Hazard ratios (HRs) and 95% CIs of all-cause and breast cancer-related death were estimated.</div></div><div><h3>Results</h3><div>The base cohort included 13,314 women newly diagnosed with breast cancer and with type 2 diabetes, before (<em>n</em> = 4761) and after (<em>n</em> = 8553) their breast cancer diagnosis, of which 5047 initiated metformin during follow-up. The prevalent new-user design included 4923 metformin initiators and 4923 matched nonusers. The HRs of breast cancer-related and all-cause mortality were 1.12 (95% CI: 0.98–1.28) and 0.96 (95% CI: 0.89–1.05), respectively. The naïve approach, among women with diabetes at cohort entry, which included 1354 metformin users and 3407 metformin nonusers, resulted in adjusted HRs of 0.45 (95% CI: 0.40–0.50) and 0.58 (95% CI: 0.54–0.62) for breast cancer and all-cause mortality.</div></div><div><h3>Conclusion</h3><div>In this study, the use of metformin was not associated with a reduced risk of breast cancer-related and all-cause mortality. Using the flawed approach not accounting for immortal time bias, we confirmed the implausible beneficial effects of metformin on breast cancer and all-cause mortality reported in previous studies.</div></div><div><h3>Plain Language Summary</h3><div>Observational studies have reported that the antidiabetic drug metformin can increase the survival of women with breast cancer. However, these studies were shown to have a flaw in their analysis, called “immoral time bias”, known to exaggerate the benefit of a drug. We used a cohort of over 13,000 women with breast cancer to investigate the effectiveness of metformin on reducing mortality in women with breast cancer, using both the flawed and a correct time-matched approach. Using the flawed approach, we confirmed the implausible beneficial effects of metformin on breast cancer-related and on all-cause mortality reported in previous studies. Using the correct time-matched approach, we found that the use of metformin was not associated with these beneficial effects, confirming the im","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"185 ","pages":"Article 111880"},"PeriodicalIF":7.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144512767","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":"Adverse events are considered but not always explicitly selected as core outcomes in research: an updated systematic review","authors":"Sarah L. Gorst,&nbsp;Jonathan P. Lucas,&nbsp;Susanna Dodd,&nbsp;Samuel W. Lucas,&nbsp;Faye D. Baldwin,&nbsp;Paula R. Williamson","doi":"10.1016/j.jclinepi.2025.111889","DOIUrl":"10.1016/j.jclinepi.2025.111889","url":null,"abstract":"<div><h3>Objectives</h3><div>The annual systematic review update of published core outcome sets (COSs) by the Core Outcome Measures in Effectiveness Trials Initiative allows assessment of adherence to development standards. The objectives of this study were to assess the quality of COS development and the approach to the inclusion of adverse event outcomes.</div></div><div><h3>Study Design and Setting</h3><div>Studies reporting the development of a COS, published or indexed in 2022 and 2023, were identified using systematic review methods previously applied. Adherence to internationally agreed consensus-based standards for COS development was assessed. An existing outcome taxonomy was used to classify the core outcomes from all studies. The approach to consideration and inclusion of adverse event outcomes was examined.</div></div><div><h3>Results</h3><div>Fifty-eight COS development studies were included in the 2022 update and a further 40 studies in the 2023 update. Scope specification standards were fully met in all studies. Stakeholder inclusion standards were fully met in 38 (66%) and 34 (85%) of the 2022 and 2023 studies, respectively; the proportion meeting all four standards for the consensus process was lower, 13 (22%) and 13 (33%), respectively. The consideration of adverse events in the COS development process varied. Around half (54, 49%) of 2022–2023 COS included either the adverse events domain or specifically named adverse events as core outcomes.</div></div><div><h3>Conclusion</h3><div>Continued improvement in adherence to recognized standards, including patient participation, is evident; however, further improvement is needed in relation to the consensus process standards. COS developers should be explicit about and explain the rationale for their approach to consideration of adverse events.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"185 ","pages":"Article 111889"},"PeriodicalIF":7.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144512766","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}