Journal of Clinical Epidemiology最新文献

Context: 'Real-world' evidence (RWE) and related terms are gaining popularity in scientific literature, usually in reference to evidence collected outside of traditional randomized controlled trials (RCT). However, the concept lacks a standardized definition and rests on a poor epistemological foundation. This commentary explores the 'illusion of the real', arguing that RWE-related terminology undermines scientific transparency by implying that routinely collected data captures an objective truth more effectively than controlled experiments.

Methods: A commentary with critical epistemological analysis of RWE.

Results: RWE underpins the epistemological illusion that the collection of observational or routine data is a passive, neutral, or intervention-free process. In fact, collecting data is, in itself, an active action by the researcher: an intervention that modifies, filters, and constructs the observed reality. This intervention introduces structural biases that remove any evidence of the supposed 'real truth'. Neither RCT nor observational studies can perhaps access the absolute truth, since the act of observing and control already alters the phenomenon. The pursuit of 'real' evidence creates an anarchic methodological space where the lack of control is mistaken for authenticity, ultimately producing contextual constructions rather than objective truths.

Conclusions: Although data collected outside traditional RCT are essential to decision-making, the 'real-world' label is a rhetorical construct that obscures study design and introduces an illusion of objective truth. Because all scientific inquiry is limited by the observer's methods, 'real-world' claims are essentially fallacious. To promote transparency, researchers should abandon RWE-related terminology in favor of precise study labelling and explicit disclosures of data source limitations.

Objective: Vaccination is a safe and effective method for preventing infectious diseases but for novel pathogens vaccine supplies may be limited. We modeled distribution of a limited vaccine supply to specific age groups to investigate the effectiveness at preventing infection and mortality of a novel influenza-like virus.

Methods: We used the Agent-based modeling platform Framework for Reconstructing Epidemic Dynamics (FRED). Limited supplies of vaccine were administered to target age groups. Increased vaccination rates in the 5-17 year old age group tested the ability of single-age group vaccination to interrupt viral transmission. Mortality was estimated using patterns associated with historic pandemic respiratory pathogens.

Results: In all cases limited vaccination had relatively little impact on overall infections. Distribution of vaccine to 5-17 years olds stopped transmission only at very high vaccine coverage, high vaccine effectiveness and relatively low viral transmissibility. The best strategy for decreasing mortality in all modeled scenarios was to target the age group with the highest mortality.

Conclusions: Results suggests that in the event of a highly transmissible disease, limited vaccine supplies will not interrupt transmission. Vaccine distribution protecting the most vulnerable from severe outcomes, even without limiting transmission, was the most effective strategy for preventing mortality.

Plain language summary: In the case of an emerging disease, vaccine supplies may be limited during the time of high transmission. In such a situation, vaccinating the age group with the highest transmission rate may not be the best strategy to limit mortality, since it will not stop transmission or produce herd immunity. Vaccination may be better used to target the age group with the highest mortality, which may be different for different diseases.

Objective: MDMA and psilocybin are being investigated as potential treatments for psychiatric disorders and have received increasing regulatory and media attention, due to the methodological complexities and societal context of psychedelic substances. Therefore, we assessed the consistency of protocol registration and adverse event (AE) reporting in clinical trials of MDMA and psilocybin.

Study design and setting: We conducted a cross-sectional analysis of all clinical trials on MDMA or psilocybin registered on ClinicalTrials.gov by March 12, 2025. For each trial, we assessed changes to primary outcome measures (POMs) and eligibility criteria over time, and evaluated whether these changes were disclosed in corresponding publications. For completed trials with both posted results and published articles, we compared AE reporting between the article and the corresponding ClinicalTrials.gov registration.

Results: Out of 336 trials, major changes were recorded to POMs for 17.6% trials and to eligibility criteria for 28.6% trials, most of which occurred after participant recruitment began. Among completed trials, 72.0% did not report results on ClinicalTrials.gov, and most posted results exceeded the FDAAA-recommended one-year reporting window. Only 3 of 29 trials with both posted results and publications showed full concordance in AE reporting, with most exhibiting both qualitative and quantitative discrepancies.

Conclusion: Inconsistencies in protocol and adverse event reporting undermine the credibility and safety evaluation of MDMA and psilocybin trials. Greater transparency and stricter adherence to reporting standards are advised to ensure reliable evidence, protect participants, and maintain stakeholder and public trust.

Prediction models are widely used across all fields of medicine as tools to support patient counseling and guide treatment decisions. A key step before any prediction model can be implemented in clinical practice is internal validation, for which principles are well described in the literature. However, the application of these principles is challenging when complex models are used or when missing values are present in the predictor variables. Approaches for internal validation and handling of missing data often result in a multitude of datasets, such as multiple bootstrapped samples across multiple imputations. Analyzing such cross-multiplied datasets in a streamlined manner is not straightforward. This paper provides practical guidance and a structured R workflow to support clinical researchers in combining internal validation and imputation methods when building reliable prediction models.

Background: Many drug development and care decisions rest on phase Ib or II trial evidence, which may overestimate efficacy due to regression to the mean or bias.

Objective: To assess concordance between efficacy and safety estimates from phase Ib/II (P1b/2) and subsequent phase III (P3) solid tumour therapy trials.

Study design: We identified P3 solid tumour trials completed 2014-2020, then matched each to supporting phase P1b/2 trial(s) testing the same drug-indication pairing. Correlation was assessed for objective response rate (ORR), median overall survival (mOS), and serious adverse events (SAEs). We also assessed whether P3 effect sizes fell within 95% confidence intervals of P1b/2 results, and whether trial design features influenced regression.

Results: In 87 P1b/2-P3 identified pairings, correlations were positive and significant for ORR (β = 0.78, adj. Rˆ2 = 0.549, p < 0.001), mOS (β = 0.67, adj. Rˆ2 = 0.523, p < 0.001) and SAE rates (β = 0.54, adj. Rˆ2 = 0.285, p < 0.001). Regression was greater when P3 had low risk of bias (RoB) for ORR (β = 0.660, adj. Rˆ2 = 0.445) than when RoB was high (β = 1.00, Rˆ2 = 0.704). P3 estimates were at least twice as likely to fall below P1b/2 estimates than above (ORR: 21% vs. 10%; mOS: 25% vs. 6%; SAE: 22% vs. 4%).

Conclusion: Efficacy and toxicity estimates from P1b/2 trials of solid tumour drugs often regress in P3. The variability between early and confirmatory trials underscores the need for caution when interpreting early-phase estimates for clinical decisions.

Background and objectives: The "ISSHOOs (Identifying Social factors that Stratify Health Opportunities and Outcomes) in pain research" project endeavored to address the paucity and inconsistency of equity-relevant, sociodemographic data collection and reporting in human adult pain research. The resulting "ISSHOOs Recommendations" provide a data collection tool that has practical utility and is globally and cross-culturally relevant, adaptable, and freely accessible.

Methods: This explanation and elaboration manuscript is a companion to the ISSHOOs Recommendations. It aims to elaborate on the published recommendations and provide practical guidance to broaden understanding and facilitate use.

Results: We provide item-specific information relevant to each of the eight items in Set A (the minimum dataset), including relevant background, rationale, and guidance for item tailoring to suit specific populations and contexts. We discuss the selection of a sub-set of relevant items from Set B (the extended, optional dataset) and suggest how the ISSHOOs data have the potential to complement efforts to address equity concerns in analyses, interpretation, and reporting.

Conclusion: It is timely and important to improve and standardize the reporting of equity-relevant, sociodemographic data in pain research. The ISSHOOs recommendations, supported by this manuscript, have the potential to promote equity-relevant awareness and understanding and advance progress toward reducing health inequities for people with pain.