Clinical Trials最新文献

{"title":"UK paediatric clinical trial protocols: A review of guidance for participant management and care in the event of premature termination.","authors":"Helen Pluess-Hall, Paula Smith, Julie Menzies","doi":"10.1177/17407745241296864","DOIUrl":"10.1177/17407745241296864","url":null,"abstract":"<p><strong>Background/aims: </strong>Clinical trials provide an opportunity to identify new treatments and can offer patients access to treatments otherwise unavailable. However, approximately 10% of paediatric clinical trials discontinue before the trial has completed. If this premature termination is because the trial treatment(s) being investigated are identified to be ineffective or unsafe, it results in the abrupt discontinuation of the investigational medicinal product for participants. For some participants, there may not be other treatment options to pursue at the trial-end. Trials prematurely terminating can be a distressing experience for all involved and currently there is little published evidence about the guidance provided to healthcare professionals in the event of premature trial termination. The study protocol is the source of guidance for healthcare professionals delivering clinical research, detailing how to conduct all aspects of the trial. The aim was to quantify the proportion of clinical trial protocols that included premature trial termination and subsequently those that provided instructions related to participant management and care. In addition, to analyse the context in which premature termination was included and the detail of any instructions for participant management and care.</p><p><strong>Methods: </strong>The ClinicalTrials.gov database was searched by a single reviewer for UK interventional drug trials enrolling children with an available study protocol. Protocols were searched to assess if the risk of premature trial termination was identified, the context for premature termination being included, if information was provided to support the management and care of participants should this situation occur and the detail of those instructions. Data were summarised descriptively.</p><p><strong>Results: </strong>Of 245 clinical trial protocols, 235 (95.9%) identified the possibility of premature trial termination, the majority within the context of the sponsor asserting their right to terminate the trial (82.7%, 115/235) and providing reasons why the trial could be stopped (65.5%, 91/235). Forty-two percent (98/235) provided guidance for participant management and care, most commonly to contact/inform the participant (45.9%, 45/98). Directions varied in the quantity and level of detail.</p><p><strong>Conclusions: </strong>This review of UK clinical trial protocol highlights that information surrounding premature termination is lacking, with only 42% providing guidance on the care of trial participants. While this ensures regulatory compliance, it fails to consider the challenge for healthcare professionals in managing participants on-going care or the duty of care owed to participants. Further research is required to understand if additional documents are being used in practice, and if these meet the needs of healthcare professionals in supporting research participants and families during premature trial termination","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745241296864"},"PeriodicalIF":2.2,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142667166","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":"Pragmatic monitoring of emerging efficacy data in randomized controlled trials.","authors":"Shrikant I Bangdiwala, Salim Yusuf","doi":"10.1177/17407745241290729","DOIUrl":"https://doi.org/10.1177/17407745241290729","url":null,"abstract":"<p><p>Monitoring the conduct of phase III randomized controlled trials is driven by ethical reasons to protect the study integrity and the safety of trial participants. We propose a group sequential, pragmatic approach for monitoring the accumulating efficacy information in randomized controlled trials. The \"Population Health Research Institute boundary\" is simple to implement and sensible, as it considers the reduction in uncertainty with increasing information as the study progresses. It is also pragmatic, since it takes into consideration the typical monitoring behavior of monitoring committees of large multicenter trials and is relatively easily implemented. It not only controls the overall Lan-DeMets type I error probability (alpha) spent, but performs better than other group sequential boundaries for the total nominal study alpha. We illustrate the use of our monitoring approach in the early termination of two past completed trials.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745241290729"},"PeriodicalIF":2.2,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142616308","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":"Statistical properties of items and summary scores from the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE^®) in a diverse cancer sample.","authors":"Carolyn Mead-Harvey, Ethan Basch, Lauren J Rogak, Blake T Langlais, Gita Thanarajasingam, Brenda F Ginos, Minji K Lee, Claire Yee, Sandra A Mitchell, Lori M Minasian, Tito R Mendoza, Antonia V Bennett, Deborah Schrag, Amylou C Dueck, Gina L Mazza","doi":"10.1177/17407745241286065","DOIUrl":"10.1177/17407745241286065","url":null,"abstract":"<p><strong>Background/aims: </strong>The Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE^®) was developed to capture symptomatic adverse events from the patient perspective. We aim to describe statistical properties of PRO-CTCAE items and summary scores and to provide evidence for recommendations regarding PRO-CTCAE administration and reporting.</p><p><strong>Methods: </strong>Using data from the PRO-CTCAE validation study (NCT02158637), prevalence, means, and standard deviations of PRO-CTCAE items, composite scores, and mean and maximum scores across attributes (frequency, severity, and/or interference) of symptomatic adverse events were calculated. For each adverse event, correlations and agreement between attributes, correlations between attributes and composite scores, and correlations between composite, mean, and maximum scores were estimated.</p><p><strong>Results: </strong>PRO-CTCAE items were completed by 899 patients with various cancer types. Most patients reported experiencing one or more adverse events, with the most prevalent being fatigue (87.7%), sad/unhappy feelings (66.0%), anxiety (63.6%), pain (63.2%), insomnia (61.8%), and dry mouth (60.0%). Attributes were moderately to strongly correlated within an adverse event (<i>r</i> = 0.53 to 0.77, all <i>p</i> < 0.001) but not fully concordant (κ_weighted = 0.26 to 0.60, all <i>p</i> < 0.001), with interference demonstrating lowest mean scores and prevalence among attributes of the same adverse event. Attributes were moderately to strongly correlated with composite scores (<i>r</i> = 0.67 to 0.97, all <i>p</i> < 0.001). Composite scores were moderately to strongly correlated with mean and maximum scores for the same adverse event (<i>r</i> = 0.69 to 0.94, all <i>p</i> < 0.001). Correlations between composite scores of different adverse events varied widely (<i>r</i> = 0.04 to 0.68) but were moderate to strong for conceptually related adverse events.</p><p><strong>Conclusions: </strong>Results provide evidence for PRO-CTCAE administration and reporting recommendations that the full complement of attributes be administered for each adverse event, and that attributes as well as summary scores be reported.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745241286065"},"PeriodicalIF":2.2,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142496568","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":"The state of individual participant data sharing for the highest-revenue medicines.","authors":"Natansh D Modi, Lee X Li, Jessica M Logan, Michael D Wiese, Ahmad Y Abuhelwa, Ross A McKinnon, Andrew Rowland, Michael J Sorich, Ashley M Hopkins","doi":"10.1177/17407745241286147","DOIUrl":"https://doi.org/10.1177/17407745241286147","url":null,"abstract":"<p><strong>Background: </strong>Amid growing emphasis from pharmaceutical companies, advocacy groups, and regulatory bodies for sharing of individual participant data, recent audits reveal limited sharing, particularly for high-revenue medicines. Therefore, this study aimed to assess the individual participant data-sharing eligibility of clinical trials supporting the Food and Drug Administration approval of the top 30 highest-revenue medicines for 2021.</p><p><strong>Methods: </strong>A cross-sectional analysis was conducted on 316 clinical trials supporting approval of the top 30 revenue-generating medicines of 2021. The study assessed whether these trials were eligible for individual participant data sharing, defined as being publicly listed on a data-sharing platform or confirmed by the trial sponsors as in scope for independent researcher individual participant data investigations. Information was gathered from various sources including ClinicalTrials.gov, the European Union Clinical Trials Register, and PubMed. Key factors such as the trial phase, completion dates, and the nature of the data-sharing process were also examined.</p><p><strong>Results: </strong>Of the 316 trials, 201 (64%) were confirmed eligible for sharing, meaning they were either publicly listed on a data-sharing platform or confirmed by the trial sponsors as in scope for independent researcher individual participant data investigations. A total of 102 (32%) were confirmed ineligible, and for 13 (4%), the sponsor indicated that a full research proposal would be required to determine eligibility. The analysis also revealed a higher rate of individual participant data sharing among companies that utilized independent platforms, such as Vivli, for managing their individual participant data-sharing process. Trials not marked as completed had significantly lower eligibility for individual participant data sharing.</p><p><strong>Conclusion: </strong>This study highlights that a substantial portion of trials for top revenue-generating medicines are eligible for individual participant data sharing. However, challenges persist, particularly for trials that are marked as ongoing and for trials where the sharing processes are managed internally by pharmaceutical companies. Data-sharing rates could be improved by adopting open-access individual participant data-sharing models or using independent platforms. Standardizing policies to facilitate immediate individual participant data availability for approved medicines is necessary.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745241286147"},"PeriodicalIF":2.2,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459903","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":"Using non-inferiority test of proportions in design of randomized non-inferiority trials with time-to-event endpoint with a focus on low-event-rate setting.","authors":"Lingyun Ji, Todd A Alonzo","doi":"10.1177/17407745241284786","DOIUrl":"10.1177/17407745241284786","url":null,"abstract":"<p><strong>Background/aims: </strong>For cancers with low incidence, low event rates, and a time-to-event endpoint, a randomized non-inferiority trial designed based on the logrank test can require a large sample size with significantly prolonged enrollment duration, making such a non-inferiority trial not feasible. This article evaluates a design based on a non-inferiority test of proportions, compares its required sample size to the non-inferiority logrank test, assesses whether there are scenarios for which a non-inferiority test of proportions can be more efficient, and provides guidelines in usage of a non-inferiority test of proportions.</p><p><strong>Methods: </strong>This article describes the sample size calculation for a randomized non-inferiority trial based on a non-inferiority logrank test or a non-inferiority test of proportions. The sample size required by the two design methods are compared for a wide range of scenarios, varying the underlying Weibull survival functions, the non-inferiority margin, and loss to follow-up rate.</p><p><strong>Results: </strong>Our results showed that there are scenarios for which the non-inferiority test of proportions can have significantly reduced sample size. Specifically, the non-inferiority test of proportions can be considered for cancers with more than 80% long-term survival rate. We provide guidance in choice of this design approach based on parameters of the Weibull survival functions, the non-inferiority margin, and loss to follow-up rate.</p><p><strong>Conclusion: </strong>For cancers with low incidence and low event rates, a non-inferiority trial based on the logrank test is not feasible due to its large required sample size and prolonged enrollment duration. The use of a non-inferiority test of proportions can make a randomized non-inferiority Phase III trial feasible.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"17407745241284786"},"PeriodicalIF":2.2,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459904","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":"15th Annual University of Pennsylvania conference on statistical issues in clinical trial/advances in time-to-event analyses in clinical trials (afternoon panel discussion).","authors":"Ionut Bebu, Rebecca A Betensky, Michael P Fay","doi":"10.1177/17407745241271939","DOIUrl":"10.1177/17407745241271939","url":null,"abstract":"","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"612-622"},"PeriodicalIF":2.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142388715","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":"Analysis of composite time-to-event endpoints in cardiovascular outcome trials.","authors":"Rachel Marceau West, Gregory Golm, Devan V Mehrotra","doi":"10.1177/17407745241267999","DOIUrl":"10.1177/17407745241267999","url":null,"abstract":"<p><p>Composite time-to-event endpoints are commonly used in cardiovascular outcome trials. For example, the IMPROVE-IT trial comparing ezetimibe+simvastatin to placebo+simvastatin in 18,144 patients with acute coronary syndrome used a primary composite endpoint with five component outcomes: (1) cardiovascular death, (2) non-fatal stroke, (3) non-fatal myocardial infarction, (4) coronary revascularization ≥30 days after randomization, and (5) unstable angina requiring hospitalization. In such settings, the traditional analysis compares treatments using the observed time to the occurrence of the first (i.e. earliest) component outcome for each patient. This approach ignores information for subsequent outcome(s), possibly leading to reduced power to demonstrate the benefit of the test versus the control treatment. We use real data examples and simulations to contrast the traditional approach with several alternative approaches that use data for all the intra-patient component outcomes, not just the first.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"576-583"},"PeriodicalIF":2.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141906134","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":"Is inadequate risk stratification diluting hazard ratio estimates in randomized clinical trials?","authors":"Devan V Mehrotra, Rachel Marceau West","doi":"10.1177/17407745231222448","DOIUrl":"10.1177/17407745231222448","url":null,"abstract":"<p><p>In randomized clinical trials, analyses of time-to-event data without risk stratification, or with stratification based on pre-selected factors revealed at the end of the trial to be at most weakly associated with risk, are quite common. We caution that such analyses are likely delivering hazard ratio estimates that unwittingly dilute the evidence of benefit for the test relative to the control treatment. To make our case, first, we use a hypothetical scenario to contrast risk-unstratified and risk-stratified hazard ratios. Thereafter, we draw attention to the previously published 5-step stratified testing and amalgamation routine (5-STAR) approach in which a pre-specified treatment-blinded algorithm is applied to survival times from the trial to partition patients into well-separated risk strata using baseline covariates determined to be jointly strongly prognostic for event risk. After treatment unblinding, a treatment comparison is done within each risk stratum and stratum-level results are averaged for overall inference. For illustration, we use 5-STAR to reanalyze data for the primary and key secondary time-to-event endpoints from three published cardiovascular outcomes trials. The results show that the 5-STAR estimate is typically smaller (i.e. more in favor of the test treatment) than the originally reported (traditional) estimate. This is not surprising because 5-STAR mitigates the presumed dilution bias in the traditional hazard ratio estimate caused by no or inadequate risk stratification, as evidenced by two detailed examples. Pre-selection of stratification factors at the trial design stage to achieve adequate risk stratification for the analysis will often be challenging. In such settings, an objective risk stratification approach such as 5-STAR, which is partly aligned with guidance from the US Food and Drug Administration on covariate-adjustment in clinical trials, is worthy of consideration.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"571-575"},"PeriodicalIF":2.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139671450","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":"Using multistate models with clinical trial data for a deeper understanding of complex disease processes.","authors":"Terry M Therneau, Fang-Shu Ou","doi":"10.1177/17407745241267862","DOIUrl":"10.1177/17407745241267862","url":null,"abstract":"<p><p>A clinical trial represents a large commitment from all individuals involved and a huge financial obligation given its high cost; therefore, it is wise to make the most of all collected data by learning as much as possible. A multistate model is a generalized framework to describe longitudinal events; multistate hazards models can treat multiple intermediate/final clinical endpoints as outcomes and estimate the impact of covariates simultaneously. Proportional hazards models are fitted (one per transition), which can be used to calculate the absolute risks, that is, the probability of being in a state at a given time, the expected number of visits to a state, and the expected amount of time spent in a state. Three publicly available clinical trial datasets, colon, myeloid, and rhDNase, in the survival package in R were used to showcase the utility of multistate hazards models. In the colon dataset, a very well-known and well-used dataset, we found that the levamisole+fluorouracil treatment extended time in the recurrence-free state more than it extended overall survival, which resulted in less time in the recurrence state, an example of the classic \"compression of morbidity.\" In the myeloid dataset, we found that complete response (CR) is durable, patients who received treatment B have longer sojourn time in CR than patients who received treatment A, while the mutation status does not impact the transition rate to CR but is highly influential on the sojourn time in CR. We also found that more patients in treatment A received transplants without CR, and more patients in treatment B received transplants after CR. In addition, the mutation status is highly influential on the CR to transplant transition rate. The observations that we made on these three datasets would not be possible without multistate models. We want to encourage readers to spend more time to look deeper into clinical trial data. It has a lot more to offer than a simple yes/no answer if only we, the statisticians, are willing to look for it.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"531-540"},"PeriodicalIF":2.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141878507","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":"Statistical approaches for component-wise censored composite endpoints.","authors":"Anne Eaton","doi":"10.1177/17407745241265628","DOIUrl":"10.1177/17407745241265628","url":null,"abstract":"<p><p>Composite endpoints defined as the time to the earliest of two or more events are often used as primary endpoints in clinical trials. Component-wise censoring arises when different components of the composite endpoint are censored differently. We focus on a composite of death and a non-fatal event where death time is right censored and the non-fatal event time is interval censored because the event can only be detected during study visits. Such data are most often analysed using methods for right censored data, treating the time the non-fatal event was first detected as the time it occurred. This can lead to bias, particularly when the time between assessments is long. We describe several approaches for estimating the event-free survival curve and the effect of treatment on event-free survival via the hazard ratio that are specifically designed to handle component-wise censoring. We apply the methods to a randomized study of breastfeeding versus formula feeding for infants of mothers infected with human immunodeficiency virus.</p>","PeriodicalId":10685,"journal":{"name":"Clinical Trials","volume":" ","pages":"595-603"},"PeriodicalIF":2.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11533687/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141901175","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}