Clinical Trials最新文献

{"title":"Sample size estimation for the averted events ratio.","authors":"David T Dunn, Oliver T Stirrup, David V Glidden","doi":"10.1177/17407745251377435","DOIUrl":"https://doi.org/10.1177/17407745251377435","url":null,"abstract":"<p><strong>Background: </strong>The averted events ratio (AER) is a recently developed estimand for non-inferiority active-control prevention trials with a time-to-event outcome. In contrast to the traditional rate ratio or rate difference, the AER is based on the number of events <i>averted</i> by each of the two treatments rather than the observed events. The AER requires an assumption about either the background event rate (the counterfactual placebo incidence) or the counterfactual effectiveness of the control treatment. We develop and present sample size formulae for trials in which the AER is defined as the primary estimand, and draw comparisons with the conventional 95-95 method based on the rate ratio.</p><p><strong>Methods: </strong>We express sample size in terms of the expected number of events and required person-years follow-up in the control and experimental arms. Sample size formulae were based on Wald confidence intervals on a logarithmic scale, assuming the active and control treatments to be equally effective. Using the AER, sample size depends on whether the analysis will be based on the counterfactual placebo incidence or the counterfactual treatment effectiveness. For both approaches, and the 95-95 method, sample size is a function of the background event rate, the effectiveness of the control treatment, the preservation-of-effect size (non-inferiority margin), the confidence limit for inferring non-inferiority, and the desired statistical power to demonstrate non-inferiority.</p><p><strong>Results: </strong>The smallest sample size is obtained using the AER based on the counterfactual placebo incidence. The advantage is greater the higher the value of the control treatment effectiveness. For example, compared with the 95-95 method, it allows between a 2.6-fold and 4.0-fold reduction in sample size for 50% treatment effectiveness (depending of the non-inferiority margin), and between a 7.7-fold and 11.9-fold reduction for 80% treatment effectiveness. The AER based on the control treatment effectiveness is less efficient but still requires smaller sample sizes than the 95-95 method: between a 1.5-fold and 2.9-fold reduction for 50% treatment effectiveness, and between a 2.3-fold and 6.4-fold reduction for 80% treatment effectiveness. Sample size is highly sensitive to the non-inferiority margin: increasing the preservation-of-effect size from 50% to 60% implies a 1.84-fold increase in the sample size; from 60% to 70%, an increase of 2.15-fold; and from 70% to 80%, an increase of 2.55-fold.</p><p><strong>Conclusion: </strong>As well as having important advantages of interpretation, using the AER as the primary estimand in active-control non-inferiority trials permits smaller and more cost-effective studies. Ideally, the AER should be derived via the counterfactual placebo incidence when this is practicable.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745251377435"},"PeriodicalIF":2.2,"publicationDate":"2025-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145344025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Practical inference for a complier average causal effect in cluster randomised trials with a binary outcome.","authors":"Tansy Edwards, Jennifer Thompson, Charles Opondo, Elizabeth Allen","doi":"10.1177/17407745251378407","DOIUrl":"https://doi.org/10.1177/17407745251378407","url":null,"abstract":"<p><strong>Background: </strong>Individual non-compliance with an intervention in cluster randomised trials can occur and estimating an intervention effect according to intention-to-treat ignores non-compliance and underestimates efficacy. The effect of the intervention among compliers (the complier average causal effect) provides an unbiased estimate of efficacy but inference can be complex in cluster randomised trials.</p><p><strong>Methods: </strong>We evaluated the performance of a pragmatic bootstrapping approach accounting for clustering to obtain a 95% confidence interval (CI) for a CACE for cluster randomised trials with monotonicity and one-sided non-compliance. We investigated a variety of scenarios for correlated cluster-level prevalence of a binary outcome and non-compliance (5%, 10%, 20%, 30%, 40%). Cluster randomised trials were simulated with the minimum number of clusters to provide at least 80% and at least 90% power, to detect an ITT odds ratio (OR) of 0.5 with 100 individuals per cluster.</p><p><strong>Results: </strong>Under all non-compliance scenarios (5%-40%), there was negligible bias for the CACE. In the worst-case of bias, a true OR of 0.18 was estimated as 0.15 for the rarest outcome (5%) and highest non-compliance (40%). There was no under-coverage of bootstrap CIs. CIs were the correct width for an outcome prevalence of 20%-40% but too wide for a less common outcome. Loss of power for a CACE bootstrap analysis versus ITT regression analysis increased as the prevalence of the outcome decreased across all non-compliance scenarios, particularly for an outcome prevalence of less than 20%.</p><p><strong>Conclusions: </strong>Our bootstrapping approach provides an accessible and computationally simple method to evaluate efficacy in support of ITT analyses in cluster randomised trials.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745251378407"},"PeriodicalIF":2.2,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145298963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Meta-analytic evaluation of surrogate endpoints at multiple time points in randomized controlled trials with time-to-event endpoints.","authors":"Xiaoyu Tang, Ludovic Trinquart","doi":"10.1177/17407745251377734","DOIUrl":"https://doi.org/10.1177/17407745251377734","url":null,"abstract":"<p><strong>Background: </strong>Valid surrogate endpoints are of great interest for efficient evaluation of novel therapies. With surrogate and true time-to-event endpoints, meta-analytic approaches for surrogacy validation commonly rely on the hazard ratio, ignore that randomized trials possibly contribute to the meta-analysis for different follow-up durations, overlook the importance of the time lag between surrogate and true endpoints in determining surrogate utility, and assume that treatment effects and the strength of surrogacy remain constant over time. In this context, we introduce a novel two-stage meta-analytic model to evaluate trial-level surrogacy.</p><p><strong>Methods: </strong>Our model employs restricted mean survival time (RMST) differences to quantify treatment effects at the first stage. At the second stage, the model is based on the between-study covariance matrix of RMSTs and differences in RMST to assess surrogacy through coefficients of determination at multiple timepoints. This framework integrates estimates from each component RCT without extrapolation beyond the trial-specific time support, can explicitly model a time lag between endpoints, and remains valid under non-proportional hazards.</p><p><strong>Results: </strong>Simulation studies indicate that our model yields unbiased and precise estimates of the coefficient of determination. In an individual patient data meta-analysis in gastric cancer, estimates of coefficients of determination from our model reflect the temporal lag between endpoints and reveal dynamic changes in surrogacy strength over time compared to the Clayton survival copula model, a widely used reference method in surrogate endpoint validation for time-to-event outcomes.</p><p><strong>Conclusion: </strong>Our new meta-analytic model to evaluate trial-level surrogacy using the difference in RMST as the measure of treatment effect does not require the proportional hazard assumption, captures the strength of surrogacy at multiple time points, and can evaluate surrogacy with a time lag between surrogate and true endpoints. The proposed method enhances the rigor and practicality of surrogate endpoint validation in time-to-event settings.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745251377734"},"PeriodicalIF":2.2,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145298965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Patient notification about pragmatic clinical trials conducted with a waiver of consent: A qualitative study.","authors":"Stephanie R Morain, Abigail Brickler, Matthew W Semler, Jonathan D Casey","doi":"10.1177/17407745251377730","DOIUrl":"https://doi.org/10.1177/17407745251377730","url":null,"abstract":"<p><strong>Background: </strong>Some scholars have proposed that investigators and health systems should notify patients about their enrollment in pragmatic clinical trials conducted with a waiver of consent. However, others argue that decision-making about notification requires judgment, and reports suggest considerable heterogeneity about whether, when, and how individuals enrolled in pragmatic clinical trials with a waiver of consent are notified about that enrollment. Empirical data can inform this decision-making.</p><p><strong>Methods: </strong>We conducted semi-structured interviews with knowledgeable stakeholders involved in conducting and/or overseeing pragmatic clinical trials conducted with waivers of consent, including investigators, those charged with the oversight of human subjects research, and operational leadership. Interviews were conducted via video conference from September to December 2024 and were audio-recorded and professionally transcribed. Data were qualitatively analyzed using an integrated approach, including both a priori codes drawn from the interview guide and emergent, inductive codes.</p><p><strong>Results: </strong>Twenty-three of 28 experts invited to participate completed interviews. Respondents described rationales both for and against notification. Rationales for notification included both appeals to moral values (respect for persons, respect for autonomy, and transparency), as well as instrumental goals (promoting understanding of and/or support for research, avoiding downstream surprise, and supporting buy-in). Rationales against notification included preserving scientific validity, perceiving notification to lack value, and concerns that notification might be burdensome for patient-subjects or undermine trust and/or clinical or public health goals. Decision-making about notification was context-specific and reflected features related to the study design, the health system setting, the patient population, the clinical condition, and the intervention(s) being evaluated. While some factors were consistently described as weighing against notification, including scientific validity or decisions for which a patient would not be offered a choice outside the research context, other factors resulted in divergent decisions across different pragmatic clinical trials (or even across different sites for the same trial).</p><p><strong>Conclusions: </strong>While several rationales support notification about enrollment in pragmatic clinical trials conducted with waivers of consent, the relative value and practicability of notification is context-dependent. Some features, such as the need to preserve scientific validity, may appropriately weigh in favor of forgoing notification. However, evidence of divergent decision-making for similar trials suggests the need for a framework to guide future notification decisions. These data can be an important input to inform future framework development.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745251377730"},"PeriodicalIF":2.2,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145298955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Confirmatory evidence supporting single pivotal trial new drug approvals by the Food and Drug Administration, 2015 through 2023.","authors":"Carla Barile Godoy, Reshma Ramachandran, Pradyumna Sapre, Joseph S Ross","doi":"10.1177/17407745251376620","DOIUrl":"https://doi.org/10.1177/17407745251376620","url":null,"abstract":"<p><strong>Backgrounds/aims: </strong>To secure market authorization, the Food and Drug Administration requires that drug manufacturers demonstrate product safety and efficacy for an indicated use based on two adequate and well-controlled studies, known as pivotal clinical trials. A single pivotal trial may also be sufficient for product approval, however, if safety and efficacy is clearly and convincingly demonstrated, or if accompanied by confirmatory evidence. We examined all original drug and biologic indication approvals by the Food and Drug Administration between 2015 and 2023 to determine what proportion of those approved on the basis of a single pivotal trial were accompanied by confirmatory evidence, the type and strength of this evidence, and whether confirmatory evidence was cited more frequently after December 2019, when the Food and Drug Administration released draft guidance clarifying issues related to confirmatory evidence.</p><p><strong>Methods: </strong>Information was extracted from publicly available Food and Drug Administration documents, and we used descriptive statistics to characterize the sample and chi-square tests to compare the frequency with which confirmatory evidence was cited before and after December 2019.</p><p><strong>Results: </strong>Overall, the Food and Drug Administration approved 441 original drug and biologic indications between 2015 and 2023; 40 of which were excluded. Of the remaining, 181 (41%) were based on 2 or more pivotal trials, 35 (7.9%) on a single pivotal trial with at least one clinical primary efficacy endpoint without orphan designation, and 185 (42%) on a single pivotal trial. Among the final category of approvals, the Food and Drug Administration explicitly referenced confirmatory evidence for 36 (19.5%) single pivotal trial approvals and implicitly referenced confirmatory evidence for 4 (2.2%) others. These 40 approvals referenced 99 unique sources of confirmatory evidence, most commonly pharmacodynamic/mechanistic (n = 49) and other (n = 32). Reference to confirmatory evidence was greater after the Food and Drug Administration issued clarifying guidance in December 2019 (pre: 7% vs post: 34%; p < 0.0001).</p><p><strong>Conclusions: </strong>Given the rising number of the Food and Drug Administration approvals based on a single pivotal trial, greater clarity on confirmatory evidence standards and communication of its use could be considered.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745251376620"},"PeriodicalIF":2.2,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145291408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adjudication of cause of death in older adults: Learnings for death certification from the ASPirin in Reducing Events in the Elderly study.","authors":"Mark R Nelson, John J McNeil, Nigel Stocks, Sameer Panjwani, Raj C Shah","doi":"10.1177/17407745251368001","DOIUrl":"https://doi.org/10.1177/17407745251368001","url":null,"abstract":"<p><strong>Background: </strong>Death certificates are a legal requirement for a body to be buried or cremated. Many randomised clinical trials utilise disease-specific causes of death as key outcomes informed by these documents. Determination of cause of death is commonly assigned to an adjudication committee, a time- and resource-intensive process which becomes more difficult in trials of older individuals. We sought to assess whether a simple transcription from a death certificate would be adequate to meet trial requirements and whether the certification process itself can be improved to meet public health and research requirements.</p><p><strong>Methods: </strong>Random audit of 100 death certificates from ASpirin in Reducing Endpoints in the Elderly, a randomised controlled trial conducted in Australian general practice and US community research centres. Participants were Australians (aged 70+ years) and Americans (65+) living in the community and without life-limiting medical conditions at baseline, recruited between 1 March 2010 and 31 December 2014 for the ASpirin in Reducing Endpoints in the Elderly trial. Outcome of interest was misclassification of death rate.</p><p><strong>Results: </strong>There were 2757 deaths in the 19,114 study population. In a random sample of 100 of these deaths, misclassification of cause of death was identified through the trial adjudication process in 9% of death certificates.</p><p><strong>Conclusion: </strong>In trials without the resources of ASpirin in Reducing Endpoints in the Elderly, a coding method can be accepted. Based on our experience, we recommend changes to the structure and process of death certification to better serve both clinical research and public health needs, particularly in older, multimorbid populations.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745251368001"},"PeriodicalIF":2.2,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145224993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How is missing data handled in cluster randomized controlled trials? A review of trials published in the NIHR Journals Library 1997-2024.","authors":"Siqi Wu, Richard M Jacques, Stephen J Walters","doi":"10.1177/17407745251378117","DOIUrl":"https://doi.org/10.1177/17407745251378117","url":null,"abstract":"<p><strong>Background: </strong>Cluster randomized controlled trials are increasingly used to evaluate the effectiveness of interventions in clinical and public health research. However, missing data in cluster randomized controlled trials can lead to biased results and reduce statistical power if not handled appropriately. This study aimed to review, describe and summarize how missing primary outcome data are handled in reports of publicly funded cluster randomized controlled trials.</p><p><strong>Methods: </strong>This study reviewed the handling of missing data in cluster randomized controlled trials published in the UK National Institute for Health and Care Research Journals Library from 1 January 1997 to 31 December 2024. Data extraction focused on trial design, missing data mechanisms, handling methods in primary analyses and sensitivity analyses.</p><p><strong>Results: </strong>Among the 110 identified cluster randomized controlled trials, 45% (50/110) did not report or take any action on missing data in either primary analysis or sensitivity analysis. In total, 75% (82/110) of the identified cluster randomized controlled trials did not impute missing values in their primary analysis. Advanced methods like multiple imputation were applied in only 15% (16/110) of primary analyses and 28% (31/110) of sensitivity analyses. On the contrary, the review highlighted that missing data handling methods have evolved over time, with an increasing adoption of multiple imputation since 2017. Overall, the reporting of how missing data is handled in cluster randomized controlled trials has improved in recent years, but there are still a large proportion of cluster randomized controlled trials lack of transparency in reporting missing data, where essential information such as the assumed missing mechanism could not be extracted from the reports.</p><p><strong>Conclusion: </strong>Despite progress in adopting multiple imputation, inconsistent reporting and reliance on simplistic methods (e.g. complete case analysis) undermine cluster randomized controlled trial credibility. Recommendations include stricter adherence to CONSORT guidelines, routine sensitivity analyses for different missing mechanisms and enhanced training in advanced imputation techniques. This review provides updated insights into how missing data are handled in cluster randomized controlled trials and highlight the urgency for methodological transparency to ensure robust evidence generation in clustered trial designs.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745251378117"},"PeriodicalIF":2.2,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145225050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimating treatment effects in trials with outcome data truncated by death: A case study on aligning estimators with estimands.","authors":"Tra My Pham, Brennan C Kahan, Andre Lopes, Memuna Rashid, Peter J Hoskin, Ian R White","doi":"10.1177/17407745251360645","DOIUrl":"https://doi.org/10.1177/17407745251360645","url":null,"abstract":"<p><strong>Background/aims: </strong>Randomised clinical trials assessing treatment effects on health outcomes (e.g. quality of life) can be affected by data truncation by death, where some patients die before their outcome measure is assessed and their data become undefined after death. The ICH E9(R1) addendum on estimands discusses four strategies for handling such terminal intercurrent events: hypothetical, composite, while-alive, and principal stratum. While the addendum emphasises the importance of aligning statistical methods of analysis (i.e. estimators) with estimands, it does not provide specific guidance and consideration on the choice of estimators in practice. We aim to (1) demonstrate how some statistical methods commonly used in trials can be used to estimate different intercurrent event strategies for handling data truncation by death; and (2) describe how missing outcome data (e.g. due to missed assessments or loss to follow-up) can be handled for each estimator.</p><p><strong>Method: </strong>We use data from SCORAD, a non-inferiority randomised trial comparing single-fraction versus multifraction radiotherapy on ambulatory status at 8 weeks (primary outcome) among patients with spinal canal compression from metastatic cancer. Here, we estimate the effect of radiotherapy on quality of life (secondary outcome), quantified by the difference in mean global health status between the two groups at 8 weeks. We outline the strategies for handling death and describe a selection of commonly used estimators corresponding to each strategy. The handling of missing data is considered and demonstrated as part of the estimation process.</p><p><strong>Results: </strong>The hypothetical strategy, targeting a treatment effect assuming patients had not died, can be estimated using linear mixed models (a likelihood approach) or multiple imputation (a method commonly used for handling missing data). The composite and while-alive strategies relate to the 'outcome' attribute of the estimand; the former incorporates death into the definition of the primary outcome, the latter only uses outcome data before death. These can be estimated by re-defining the outcome, for example, assigning a value reflecting poor global health status post-death, or using the last global health status observed before death. The principal stratum strategy, targeting a treatment effect among patients who would not die under either treatment, can be estimated by an analysis of survivors under specific assumptions. Missing data can be handled with linear mixed models or multiple imputation.</p><p><strong>Conclusions: </strong>Regarding death as an intercurrent event in the process of defining the estimand for the trial will help clarify the choice of suitable estimators. When choosing the estimators, it is important to consider the assumptions required by the estimators as well as their plausibility given the setting of the trial.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745251360645"},"PeriodicalIF":2.2,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145224979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization of studies considered and required under Medicare's coverage with evidence development program.","authors":"Maryam Mooghali, Osman Moneer, Guneet Janda, Joseph S Ross, Sanket S Dhruva, Reshma Ramachandran","doi":"10.1177/17407745251313979","DOIUrl":"10.1177/17407745251313979","url":null,"abstract":"&lt;p&gt;&lt;p&gt;IntroductionIn 2005, the Centers for Medicare and Medicaid Services introduced the Coverage with Evidence Development program for items and services with limited evidence of benefit and harm for Medicare beneficiaries, aiming to generate evidence to determine whether they meet the statutory \"reasonable and necessary\" criteria for coverage. Coverage with Evidence Development requires participation in clinical studies approved by the Centers for Medicare and Medicaid Services (i.e. Coverage with Evidence Development-approved studies) as a condition of coverage. We examined the quality of evidence generated by Coverage with Evidence Development-approved studies compared with those that informed Centers for Medicare and Medicaid Services' initial Coverage with Evidence Development decisions (i.e. National Coverage Determination studies).MethodsUsing Centers for Medicare and Medicaid Services' webpage, we identified all items and services covered under Coverage with Evidence Development and their Coverage with Evidence Development-approved studies. Through searching PubMed and Google Scholar, we identified original research articles that reported results for primary endpoints of Coverage with Evidence Development-approved studies. We then reviewed the initial Coverage with Evidence Development decision memos and identified National Coverage Determination studies that were original research.We characterized and compared Coverage with Evidence Development-approved studies and National Coverage Determination studies.ResultsFrom 2005 to 2023, 26 items and services were covered under the Coverage with Evidence Development program, associated with 196 National Coverage Determination studies (170 (86.7%) clinical trials and 26 (13.3%) registries) and 116 unique Coverage with Evidence Development-approved studies (86 (74.1%) clinical trials, 23 (19.8%) registries, 4 (3.4%) claims-based studies, and 3 (2.6%) expanded access studies). Among clinical trial studies, National Coverage Determination studies and Coverage with Evidence Development-approved studies did not differ with respect to multi-arm design (59.4% vs 68.6%; &lt;i&gt;p&lt;/i&gt; = 0.15). However, among multi-arm clinical trial studies, National Coverage Determination studies were less likely than Coverage with Evidence Development-approved studies to be randomized (52.5% vs 93.2%; &lt;i&gt;p&lt;/i&gt; &lt; 0.001). Overall, National Coverage Determination studies less frequently had ≥ 1 primary endpoint focused on a clinical outcome measure (65.8% vs 87.9%; &lt;i&gt;p&lt;/i&gt; = 0.006) and less frequently exclusively enrolled Medicare beneficiaries (3.1% vs 25.9%; &lt;i&gt;p&lt;/i&gt; &lt; 0.001). In addition, National Coverage Determination studies had smaller population sizes than Coverage with Evidence Development-approved studies (median 100 (interquartile range, 45-414) vs 302 (interquartile range, 93-1000) patients; &lt;i&gt;p&lt;/i&gt; = 0.002). Among Coverage with Evidence Development-approved studies, 59 (50.9%) had not yet publicly reported resul","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"619-625"},"PeriodicalIF":2.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143374119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Standardising management of consent withdrawal and other clinical trial participation changes: The UKCRC Registered Clinical Trials Unit Network's PeRSEVERE project.","authors":"William J Cragg, Laura Clifton-Hadley, Jeremy Dearling, Susan J Dutton, Katie Gillies, Pollyanna Hardy, Daniel Hind, Søren Holm, Kerenza Hood, Anna Kearney, Rebecca Lewis, Sarah Markham, Lauren Moreau, Tra My Pham, Amanda Roberts, Sharon Ruddock, Mirjana Sirovica, Ratna Sohanpal, Puvan Tharmanathan, Rejina Verghis","doi":"10.1177/17407745251344524","DOIUrl":"10.1177/17407745251344524","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background/aims: &lt;/strong&gt;Existing regulatory and ethical guidance does not address real-life complexities in how clinical trial participants' level of participation may change. If these complexities are inappropriately managed, there may be negative consequences for trial participants and the integrity of trials they participate in. These concerns have been highlighted over many years, but there remains no single, comprehensive guidance for managing participation changes in ways that address real-life complexities while maximally promoting participant interests and trial integrity. Motivated by the lack of agreed standards, and observed variability in practice, representatives from academic clinical trials units and linked organisations in the United Kingdom initiated the PeRSEVERE project (PRincipleS for handling end-of-participation EVEnts in clinical trials REsearch) to agree on guiding principles and explore how these principles should be implemented.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We developed the PeRSEVERE principles through discussion and debate within a large, multidisciplinary collaboration, including research professionals and public contributors. We took an inclusive approach to drafting the principles, incorporating new ideas if they were within project scope. Our draft principles were scrutinised through an international consultation survey which focussed on the principles' clarity, feasibility, novelty and acceptability. Survey responses were analysed descriptively (for category questions) and using a combination of deductive and inductive analysis (for open questions). We used predefined rules to guide feedback handling. After finalising the principles, we developed accompanying implementation guidance from several sources.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In total, 280 people from 9 countries took part in the consultation survey. Feedback showed strong support for the principles with 96% of respondents agreeing with the principles' key messages. Based on our predefined rules, it was not necessary to amend our draft principles, but comments were nonetheless used to enhance the final project outputs. Our 17 finalised principles comprise 7 fundamental, 'overarching' principles, 6 about trial design and setup, 2 covering data collection and monitoring, and 2 on trial analysis and reporting.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;We devised a comprehensive set of guiding principles, with detailed practical recommendations, to aid the management of clinical trial participation changes, building on existing ethical and regulatory texts. Our outputs reflect the contributions of a substantial number of individuals, including public contributors and research professionals with various specialisms. This lends weight to our recommendations, which have implications for everyone who designs, funds, conducts, oversees or participates in trials. We suggest our principles could lead to improved standards in clinical trials and better exper","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"578-596"},"PeriodicalIF":2.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12476473/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144559362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}