JournalTOCs

Clinical Trials
Journal Prestige (SJR): 2.399

Citation Impact (citeScore): 2
Number of Followers: 18

Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1740-7745 - ISSN (Online) 1740-7753
Published by Sage Publications

[1175 journals]

Corrigendum
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Clinical Trials, Ahead of Print.
  
  Citation: Clinical Trials
  PubDate: 2022-11-15T06:07:43Z
  DOI: 10.1177/17407745221123714
The maraca plot: A novel visualization of hierarchical composite endpoints
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Martin Karpefors, Daniel Lindholm, Samvel B Gasparyan
  Abstract: Clinical Trials, Ahead of Print.
  Background:Hierarchical composite endpoints are complex endpoints combining outcomes of different types and different clinical importance into an ordinal outcome that prioritizes the clinically most important (e.g. most severe) event of a patient. Hierarchical composite endpoint can be analysed with the win odds, an adaptation of win ratio to include ties. One of the difficulties in interpreting hierarchical composite endpoint is the lack of proper tools for visualizing the treatment effect captured by hierarchical composite endpoint, given the complex nature of the endpoint which combines events of different types.Methods:Hierarchical composite endpoints usually combine time-to-event outcomes and continuous outcomes into a composite; hence, it is important to capture not only the shift from more severe categories to less severe categories in the active group in comparison to the control group (as in any ordinal endpoint), but also changes occurring within each category. We introduce the novel maraca plot which combines violin plots (with nested box plots) to visualize the density of the distribution of the continuous outcome and Kaplan–Meier plots for time-to-event outcomes into a comprehensive visualization.Conclusion:The novel maraca plot is suggested for visualization of hierarchical composite endpoints consisting of several time-to-event outcomes and a continuous outcome. It has a very simple structure and therefore easily communicates both the overall treatment effect and the effect on individual components.
  Citation: Clinical Trials
  PubDate: 2022-11-14T11:51:39Z
  DOI: 10.1177/17407745221134949
Randomized controlled trials of biomarker targets
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Margret Erlendsdottir, Forrest W Crawford
  Abstract: Clinical Trials, Ahead of Print.
  Introduction:Randomized controlled trials are used to estimate the causal effect of a treatment on a health outcome of interest in a patient population. Often the specified treatment in a randomized controlled trial is a medical intervention—such as a drug or procedure—experienced directly by the patient. Sometimes the “treatment” in a randomized controlled trial is a target—such as a goal biomarker measurement—that the patient’s physician attempts to reach using available medications or procedures. Large randomized controlled trials of biomarker targets are common in clinical research, and trials have been conducted to compare targets in the management of hypertension, diabetes, anemia, and acute respiratory distress syndrome. However, different randomized controlled trials intended to evaluate the same biomarker targets have produced conflicting recommendations, and meta-analyses that aggregate results of trials of biomarker targets have been inconclusive.Methods:We use causal reasoning to explain why randomized controlled trials of biomarker targets can arrive at conflicting or misleading conclusions. We describe four key threats to the validity of trials of targets: (1) intention-to-treat analysis can be misleading when a direct effect of target assignment on the outcome exists due to lack of blinding; (2) incomparability in results across trials of targets; (3) time-varying adaptive treatment strategies; and (4) Goodhart’s law, “when a measure becomes a target, it ceases to be a good measure.”Results:We illustrate these findings using evidence from 15 randomized controlled trials of blood pressure targets for management of hypertension. Randomized trials of blood pressure targets exhibit substantial variation in the trial patient populations and antihypertensives used to achieve the blood pressure targets assigned in the trials. The trials did not compare or account for time-varying treatment strategies used to reach the randomized targets. Possible “off-target” effects of antihypertensive medications needed to reach lower blood pressure targets may explain the absence of a clear benefit from intensive blood pressure control.Discussion:Researchers should critically assess meta-analyses of trials of targets for variation in the types, distributions, and off-target effects of therapies studied. Trial investigators should release detailed information about the biomarker targets compared in new randomized trials, as well as confounders, treatments delivered, and outcomes. New randomized controlled trials should experimentally compare treatment algorithms incorporating biomarkers, rather than targets alone. Causal inference methodology that adjusts for time-varying confounding should be used to compare time-varying treatment strategies in observational settings.
  Citation: Clinical Trials
  PubDate: 2022-11-14T11:43:19Z
  DOI: 10.1177/17407745221131820
Strategies to facilitate adolescent access to medicines: Improving
regulatory guidance
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Christina Bucci-Rechtweg, Angeliki Siapkara, Kristina An Haack Bonnet, Solange Corriol Rohou, Elin Haf Davies, Martine Dehlinger Kremer, Margaret Gamalo, Carmen Moreno, Robert M Nelson, Rhian Thomas Turner
  Abstract: Clinical Trials, Ahead of Print.
  Background:Historically, pediatric medicines are developed after adult trials are completed, even when identical drug targets and disease similarities exist across the populations. This has resulted in significant delays in the authorization of medicines for adolescent use, limiting access to beneficial drugs. This study sought to understand how adolescent inclusion in adult trials is positioned in regulatory guidance documents as they set critical expectations for trial design and regulatory decision-making.Methods:This study utilized a qualitative analysis approach. Guidance documents were identified via Food and Drug Administration and European Medicines Agency websites. Utilizing a blinded adjudication process, the documents were classified as permissive, exclusionary, or silent regarding recommendations about adolescent inclusion in adult clinical trials. A post hoc analysis of similarities and differences between the Food and Drug Administration and European Medicines Agency guidance documents was conducted to assess the possible role of regional pediatric research laws on age-inclusive trial methodologies as well as emergent themes by therapeutic area.Results:In total, 96 Food and Drug Administration (1977 to 2019) and 106 European Medicines Agency (1987 to 2019) guidance documents were identified for analysis. The guidance contained explicit or implicit recommendations supporting adolescent inclusion in adult trials in 32% of Food and Drug Administration and 15% of European Medicines Agency documents, while 14% and 21%, respectively, were found to be exclusionary. A large number of guidance documents were silent regarding the applicability of adolescent-inclusive trial designs (53% and 64%, Food and Drug Administration and European Medicines Agency, respectively). Analysis by therapeutic area revealed the most permissive of adolescent inclusion in Food and Drug Administration guidance for infectious diseases and conditions requiring blood products in European Medicines Agency guidance. A more holistic approach to age-inclusive trial design was identified in disease guidance published by the Food and Drug Administration Oncology Center of Excellence.Discussion:There are many influences on the development and/or revision of regulatory guidance documents. Substantial scientific knowledge and regulatory precedence for the inclusion of adolescents within adult trials are available to inform research approaches. Our study has identified important opportunities for the enhancement of guidance. For example, contextualization of developmental factors influencing adolescent disease progression provides insights into the role of adolescent inclusion. If addressed, guidance documents can facilitate broader acceptance of age-inclusive trial methodologies and accelerate adolescent access to medicines.
  Citation: Clinical Trials
  PubDate: 2022-11-05T09:38:24Z
  DOI: 10.1177/17407745221132302
Feasibility of recruiting in prisons during a randomized controlled trial
with people with serious mental illness
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Jonathan Phillips, Amy Blank Wilson, Melissa L. Villodas, Anna Parisi, Ehren Dohler, Ashley Givens
  Abstract: Clinical Trials, Ahead of Print.
  BackgroundSuccessful participant recruitment is vital to the feasibly of intervention research. In the behavioral and social sciences, intervention researchers face a myriad of recruitment barriers, many of which stem from working in real-world settings and among hard-to-access populations. Optimizing recruitment efforts requires being intentional about study planning and resource allocation, carefully documenting the outcomes of recruitment efforts, and developing and implementing procedures and strategies to overcome anticipated recruitment barriers.MethodsThe current article presents recruitment flowcharts to illustrate (a) the multistep recruitment process and (b) the points of potential participant attrition during recruitment from a two-phase group-based intervention study conducted among individuals with serious mental illness incarcerated in a state prison system in the U.S. In addition, qualitative methods are used to examine strategies employed during the study to support recruitment efforts.ResultsDespite challenges, this study was able to achieve recruitment goals. Analyses found the majority of potential participant attrition occurred prior to informed consent, highlighting the need for studies to track recruitment efforts in more detail than is currently recommended by commonly used guidelines. Strategies to optimize recruitment efforts included maximizing recruiter availability, developing a responsive communication approach, demonstrating respect for facility procedures and operations, and ensuring peak preparedness.ConclusionCareful documentation of recruitment efforts and the early deployment of recruitment strategies is vital to the feasibility of intervention studies conducted in real-world settings with hard-to-access populations. The publication of recruitment procedures and outcomes can help future researchers anticipate recruitment challenges and inform recruitment goals, timelines, and strategies.
  Citation: Clinical Trials
  PubDate: 2022-10-21T07:09:23Z
  DOI: 10.1177/17407745221130757
Electronic common technical document submission with analysis using R
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Yujie Zhao, Nan Xiao, Keaven Anderson, Yilong Zhang
  Abstract: Clinical Trials, Ahead of Print.
  Background:In clinical trial development, it is a critical step to submit applications, amendments, supplements, and reports on medicinal products to regulatory agencies. The electronic common technical document is the standard format to enable worldwide regulatory submission. There is a growing trend of using R for clinical trial analysis and reporting as part of regulatory submissions, where R functions, analysis scripts, analysis results, and all proprietary code dependencies are required to be included. One unmet and significant gap is the lack of tools, guidance, and publicly available examples to prepare submission R programs following the electronic common technical document specification.Methods:We introduce a simple and sufficient R package, pkglite, to convert analysis scripts and associated proprietary dependency R packages into a compact, text-based file, which makes the submission document self-contained, easy to restore, transfer, review, and submit following the electronic common technical document specification and regulatory guidelines (e.g. the study data technical conformance guide from the US Food and Drug Administration). The pkglite R package is published on Comprehensive R Archive Network and developed on GitHub.Results:As a tool, pkglite can pack and unpack multiple R packages with their dependencies to facilitate the reproduction and make it an off-the-shelf tool for both sponsors and reviewers. As a grammar, pkglite provides an explicit trace of the packing scope using the concept of file specifications. As a standard, pkglite offers an open file format to represent and exchange R packages as a text file. We use a mock-up example to demonstrate the workflow of using pkglite to prepare submission programs following the electronic common technical document specification.Conclusion:pkglite and the proposed workflow enable the sponsor to submit well-organized R scripts following the electronic common technical document specification. The workflow has been used in the first publicly available R-based submission to the US Food and Drug Administration by the R Consortium R submission working group (https://www.r-consortium.org/blog/2022/03/16/update-successful-r-based-test-package-submitted-to-fda).
  Citation: Clinical Trials
  PubDate: 2022-09-28T12:13:41Z
  DOI: 10.1177/17407745221123244
A hybrid approach to comparing parallel-group and stepped-wedge
cluster-randomized trials with a continuous primary outcome when there is
uncertainty in the intra-cluster correlation
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Samuel K Sarkodie, James MS Wason, Michael J Grayling
  Abstract: Clinical Trials, Ahead of Print.
  Background/Aims:To evaluate how uncertainty in the intra-cluster correlation impacts whether a parallel-group or stepped-wedge cluster-randomized trial design is more efficient in terms of the required sample size, in the case of cross-sectional stepped-wedge cluster-randomized trials and continuous outcome data.Methods:We motivate our work by reviewing how the intra-cluster correlation and standard deviation were justified in 54 health technology assessment reports on cluster-randomized trials. To enable uncertainty at the design stage to be incorporated into the design specification, we then describe how sample size calculation can be performed for cluster- randomized trials in the ‘hybrid’ framework, which places priors on design parameters and controls the expected power in place of the conventional frequentist power. Comparison of the parallel-group and stepped-wedge cluster-randomized trial designs is conducted by placing Beta and truncated Normal priors on the intra-cluster correlation, and a Gamma prior on the standard deviation.Results:Many Health Technology Assessment reports did not adhere to the Consolidated Standards of Reporting Trials guideline of indicating the uncertainty around the assumed intra-cluster correlation, while others did not justify the assumed intra-cluster correlation or standard deviation. Even for a prior intra-cluster correlation distribution with a small mode, moderate prior densities on high intra-cluster correlation values can lead to a stepped-wedge cluster-randomized trial being more efficient because of the degree to which a stepped-wedge cluster-randomized trial is more efficient for high intra-cluster correlations. With careful specification of the priors, the designs in the hybrid framework can become more robust to, for example, an unexpectedly large value of the outcome variance.Conclusion:When there is difficulty obtaining a reliable value for the intra-cluster correlation to assume at the design stage, the proposed methodology offers an appealing approach to sample size calculation. Often, uncertainty in the intra-cluster correlation will mean a stepped-wedge cluster-randomized trial is more efficient than a parallel-group cluster-randomized trial design.
  Citation: Clinical Trials
  PubDate: 2022-09-10T05:44:02Z
  DOI: 10.1177/17407745221123507
The evolution of Data and Safety Monitoring Boards
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Curtis L Meinert
  Abstract: Clinical Trials, Ahead of Print.
  
  Citation: Clinical Trials
  PubDate: 2022-09-10T05:38:05Z
  DOI: 10.1177/17407745221119171
Importance of patient engagement in the conduct of pragmatic multicenter
randomized controlled trials: The ADAPTABLE experience
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Guillaume Marquis-Gravel, Madelaine Faulkner, Greg Merritt, Peter Farrehi, Nadine Zemon, Holly R Robertson, W Schuyler Jones, Jennifer Kraschnewski
  Abstract: Clinical Trials, Ahead of Print.
  Background/AimsActively engaging patient partners in the conduct of trials is crucial to ensure the studies answer genuine, patient-centered, unmet clinical needs, and to facilitate participant recruitment and retention. The aim of this article is to demonstrate the feasibility of patient engagement within a large pragmatic multicenter randomized controlled trial, specifically for the purposes of dissemination of study information/updates and to favorize recruitment and retention.MethodsIn the patient-centric, pragmatic ADAPTABLE randomized trial, transparent and timely dissemination of information on the study updates to the trial participants was undertaken to create meaningful engagement and to facilitate retention. A national panel of patient partners, the Adaptors, were directly involved in this information dissemination strategy, and study participants were engaged both nationally and locally to design recruitment methods iteratively during the conduct of the trial. All Adaptors had a lived experience with cardiovascular disease.ResultsAdaptors attended bi-weekly meetings facilitated by the director of the study’s patient-powered research network. They drafted and/or edited newsletters and ad hoc educational information written in a lay-friendly manner for study participants, which were regularly distributed to the ADAPTABLE community, in addition to online forums where participants could share their experience of their involvement in ADAPTABLE. To spur recruitment, a patient-driven initiative was to draft letters sharing their story, which were distributed by the local study teams. Patient partners thought that using patients’ voice to provide their perspectives on why they believed this project was important would be more engaging for prospective participants than traditional approaches.ConclusionsADAPTABLE’s experience has demonstrated the feasibility of engaging patients as partners in the conduct of a large-scale, multi-center, pragmatic randomized controlled trial. Future trials should embrace and iteratively improve this model by engaging patient partners as early as study protocol development and funding applications, and quantify its impact on the effectiveness and value of the trial.
  Citation: Clinical Trials
  PubDate: 2022-08-24T05:41:36Z
  DOI: 10.1177/17407745221118559
Analysis of adaptive platform trials using a network approach
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Ian C Marschner, I Manjula Schou
  First page: 479
  Abstract: Clinical Trials, Ahead of Print.
  BackgroundAdaptive platform trials allow randomized controlled comparisons of multiple treatments using a common infrastructure and the flexibility to adapt key design features during the study. Nonetheless, they have been criticized due to the potential for time trends in the underlying risk level of the population. Such time trends lead to confounding between design features and risk level, which may introduce bias favoring one or more treatments. This is particularly true when experimental treatments are not all randomized during the same time period as the control, leading to the potential for bias from non-concurrent controls.MethodsTwo analysis methods addressing this bias are stratification and adjustment. Stratification uses only comparisons between treatment cohorts randomized during identical time periods and does not use non-concurrent randomizations. Adjustment uses a modeled analysis including time period adjustment, allowing all data to be used, even from periods without concurrent randomization. We show that these competing approaches may be embedded in a common framework using network meta-analysis principles. We interpret the stages between adaptations in a platform trial as separate fixed design trials. This allows platform trials to be viewed as networks of direct randomized comparisons and indirect non-randomized comparisons. Network meta-analysis methodology can be re-purposed to aggregate the total information from a platform trial and to transparently decompose this total information into direct randomized evidence and indirect non-randomized evidence. This allows sensitivity to indirect information to be assessed and the two analysis methods to be clearly compared.ResultsSimulations of platform trials were analyzed using a network approach implemented in the netmeta package in R. The results demonstrated bias of unadjusted methods in the presence of time trends in risk level. Adjustment and stratification were both unbiased when direct evidence and indirect evidence were consistent. Network tests of inconsistency may be used to diagnose inconsistency when it exists. In an illustrative network analysis of one of the treatment comparisons from the STAMPEDE platform trial in metastatic prostate cancer, indirect comparisons using non-concurrent controls were inconsistent with the information from direct randomized comparisons. This supports the primary analysis approach of STAMPEDE, which used only direct randomized comparisons.ConclusionNetwork meta-analysis provides a natural methodology for analyzing the network of direct and indirect treatment comparisons from a platform trial. Such analyses provide transparent separation of direct and indirect evidence, allowing assessment of the impact of non-concurrent controls. We recommend time-stratified analysis of concurrently controlled comparisons for primary analyses, with time-adjusted analyses incorporating non-concurrent controls reserved for secondary analyses. However, regardless of which methodology is used, a network analysis provides a useful supplement to the primary analysis.
  Citation: Clinical Trials
  PubDate: 2022-08-22T11:48:58Z
  DOI: 10.1177/17407745221112001
The Bayesian Time Machine: Accounting for temporal drift in multi-arm
platform trials
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Benjamin R Saville, Donald A Berry, Nicholas S Berry, Kert Viele, Scott M Berry
  First page: 490
  Abstract: Clinical Trials, Ahead of Print.
  BackgroundMulti-arm platform trials investigate multiple agents simultaneously, typically with staggered entry and exit of experimental treatment arms versus a shared control arm. In such settings, there is considerable debate whether to limit analyses for a treatment arm to concurrent randomized control subjects or to allow comparisons to both concurrent and non-concurrent (pooled) control subjects. The potential bias from temporal drift over time is at the core of this debate.MethodsWe propose time-adjusted analyses, including a “Bayesian Time Machine,” to model potential temporal drift in the entire study population, such that primary analyses can incorporate all randomized control subjects from the platform trial. We conduct a simulation study to assess performance relative to utilizing concurrent or pooled controls.ResultsIn multi-arm platform trials with staggered entry, analyses adjusting for temporal drift (either Bayesian or frequentist) have superior estimation of treatment effects and favorable testing properties compared to analyses using either concurrent or pooled controls. The Bayesian Time Machine generally provides estimates with greater precision and smaller mean square error than alternative approaches, at the risk of small bias and small Type I error inflation.ConclusionsThe Bayesian Time Machine provides a compromise between bias and precision by smoothing estimates across time and leveraging all available data for the estimation of treatment effects. Prior distributions controlling the behavior of dynamic smoothing across time must be pre-specified and carefully calibrated to the unique context of each trial, appropriately accounting for the population, disease, and endpoints.
  Citation: Clinical Trials
  PubDate: 2022-08-22T11:48:28Z
  DOI: 10.1177/17407745221112013
Commentary: Two approaches to analyze platform trials incorporating
non-concurrent controls with a common assumption
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Marta Bofill Roig, Franz König, Elias Meyer, Martin Posch
  First page: 502
  Abstract: Clinical Trials, Ahead of Print.
  
  Citation: Clinical Trials
  PubDate: 2022-08-22T11:48:00Z
  DOI: 10.1177/17407745221112016
Facilitating clinical research through automation: Combining optical
character recognition with natural language processing
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Julie Hom, Janet Nikowitz, Rebecca Ottesen, Joyce C Niland
  First page: 504
  Abstract: Clinical Trials, Ahead of Print.
  Background/AimsPerformance status is crucial for most clinical research, as an eligibility criterion, a comorbidity covariate, or a trial endpoint. Yet information on performance status often is embedded as free text within a patient’s electronic medical record, rather than coded directly, thereby making this concept extremely difficult to extract for research. Furthermore, performance status information frequently resides in outside reports, which are scanned into the electronic medical record along with thousands of clinic notes. The image format of scanned documents also is a major obstacle to the search and retrieval of information, as natural language processing cannot be applied to unstructured text within an image. We, therefore, utilized optical character recognition software to convert images to a searchable format, allowing the application of natural language processing to identify pertinent performance status data elements within scanned electronic medical records.MethodsOur study cohort consisted of 189 subjects diagnosed with diffuse large B-cell lymphoma for whom performance status was a required data element for analysis of prognostic factors related to recurrence and survival. Manual abstraction of performance status was previously conducted by a clinical Subject Matter Expert, serving as the gold standard. Leveraging our data warehouse, we extracted relevant scanned electronic medical record documents and applied optical character recognition to these images using the ABBYY FineReader software. The Linguamatics i2e natural language processing software was then used to run queries for performance status against the corpus of electronic medical record documents. We evaluated our optical character recognition/natural language processing pipeline for accuracy and reduction in data extraction effort.ResultsWe found that there was high accuracy and reduced time for extraction of performance status data by applying our optical character recognition/natural language processing pipeline. The transformed scanned documents from a random sample of patients yielded excellent precision, recall, and F score, with
  Citation: Clinical Trials
  PubDate: 2022-05-24T10:29:01Z
  DOI: 10.1177/17407745221093621
A permutation procedure to detect heterogeneous treatments effects in
randomized clinical trials while controlling the type I error rate
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Jack M Wolf, Joseph S Koopmeiners, David M Vock
  First page: 512
  Abstract: Clinical Trials, Ahead of Print.
  Background/AimsSecondary analyses of randomized clinical trials often seek to identify subgroups with differential treatment effects. These discoveries can help guide individual treatment decisions based on patient characteristics and identify populations for which additional treatments are needed. Traditional analyses require researchers to pre-specify potential subgroups to reduce the risk of reporting spurious results. There is a need for methods that can detect such subgroups without a priori specification while allowing researchers to control the probability of falsely detecting heterogeneous subgroups when treatment effects are uniform across the study population.MethodsWe propose a permutation procedure for tuning parameter selection that allows for type I error control when testing for heterogeneous treatment effects framed within the Virtual Twins procedure for subgroup identification. We verify that the type I error rate can be controlled at the nominal rate and investigate the power for detecting heterogeneous effects when present through extensive simulation studies. We apply our method to a secondary analysis of data from a randomized trial of very low nicotine content cigarettes.ResultsIn the absence of type I error control, the observed type I error rate for Virtual Twins was between 99% and 100%. In contrast, models tuned via the proposed permutation were able to control the type I error rate and detect heterogeneous effects when present. An application of our approach to a recently completed trial of very low nicotine content cigarettes identified several variables with potentially heterogeneous treatment effects.ConclusionsThe proposed permutation procedure allows researchers to engage in secondary analyses of clinical trials for treatment effect heterogeneity while maintaining the type I error rate without pre-specifying subgroups.
  Citation: Clinical Trials
  PubDate: 2022-05-09T08:43:10Z
  DOI: 10.1177/17407745221095855
Rethinking intercurrent events in defining estimands for tuberculosis
trials
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Tra My Pham, Conor D Tweed, James R Carpenter, Brennan C Kahan, Andrew J Nunn, Angela M Crook, Hanif Esmail, Ruth Goodall, Patrick PJ Phillips, Ian R White
  First page: 522
  Abstract: Clinical Trials, Ahead of Print.
  Background/aimsTuberculosis remains one of the leading causes of death from an infectious disease globally. Both choices of outcome definitions and approaches to handling events happening post-randomisation can change the treatment effect being estimated, but these are often inconsistently described, thus inhibiting clear interpretation and comparison across trials.MethodsStarting from the ICH E9(R1) addendum’s definition of an estimand, we use our experience of conducting large Phase III tuberculosis treatment trials and our understanding of the estimand framework to identify the key decisions regarding how different event types are handled in the primary outcome definition, and the important points that should be considered in making such decisions. A key issue is the handling of intercurrent (i.e. post-randomisation) events (ICEs) which affect interpretation of or preclude measurement of the intended final outcome. We consider common ICEs including treatment changes and treatment extension, poor adherence to randomised treatment, re-infection with a new strain of tuberculosis which is different from the original infection, and death. We use two completed tuberculosis trials (REMoxTB and STREAM Stage 1) as illustrative examples. These trials tested non-inferiority of new tuberculosis treatment regimens versus a control regimen. The primary outcome was a binary composite endpoint, ‘favourable’ or ‘unfavourable’, which was constructed from several components.ResultsWe propose the following improvements in handling the above-mentioned ICEs and loss to follow-up (a post-randomisation event that is not in itself an ICE). First, changes to allocated regimens should not necessarily be viewed as an unfavourable outcome; from the patient perspective, the potential harms associated with a change in the regimen should instead be directly quantified. Second, handling poor adherence to randomised treatment using a per-protocol analysis does not necessarily target a clear estimand; instead, it would be desirable to develop ways to estimate the treatment effects more relevant to programmatic settings. Third, re-infection with a new strain of tuberculosis could be handled with different strategies, depending on whether the outcome of interest is the ability to attain culture negativity from infection with any strain of tuberculosis, or specifically the presenting strain of tuberculosis. Fourth, where possible, death could be separated into tuberculosis-related and non-tuberculosis-related and handled using appropriate strategies. Finally, although some losses to follow-up would result in early treatment discontinuation, patients lost to follow-up before the end of the trial should not always be classified as having an unfavourable outcome. Instead, loss to follow-up should be separated from not completing the treatment, which is an ICE and may be considered as an unfavourable outcome.ConclusionThe estimand framework clarifies many issues in tuberculosis trials but also challenges trialists to justify and improve their outcome definitions. Future trialists should consider all the above points in defining their outcomes.
  Citation: Clinical Trials
  PubDate: 2022-07-19T10:52:52Z
  DOI: 10.1177/17407745221103853
Quantification of hematoma and perihematomal edema volumes in
intracerebral hemorrhage study: Design considerations in an artificial
intelligence validation (QUANTUM) study
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Natasha Ironside, James Patrie, Sherman Ng, Dale Ding, Tanvir Rizvi, Jeyan S Kumar, Panagiotis Mastorakos, Mohamed Z Hussein, Kareem El Naamani, Rawad Abbas, M Harrison Snyder, Yan Zhuang, Kathryn N Kearns, Kevin T Doan, Leah M Shabo, Saurabh Marfatiah, David Roh, Angela Lignelli-Dipple, Jan Claassen, Bradford B Worrall, Karen C Johnston, Pascal Jabbour, Min S Park, E Sander Connolly, Sugoto Mukherjee, Andrew M Southerland, Ching-Jen Chen
  First page: 534
  Abstract: Clinical Trials, Ahead of Print.
  Background:Hematoma and perihematomal edema volumes are important radiographic markers in spontaneous intracerebral hemorrhage. Accurate, reliable, and efficient quantification of these volumes will be paramount to their utility as measures of treatment effect in future clinical studies. Both manual and semi-automated quantification methods of hematoma and perihematomal edema volumetry are time-consuming and susceptible to inter-rater variability. Efforts are now underway to develop a fully automated algorithm that can replace them. A (QUANTUM) study to establish inter-quantification method measurement equivalency, which deviates from the traditional use of measures of agreement and a comparison hypothesis testing paradigm to indirectly infer quantification method measurement equivalence, is described in this article. The Quantification of Hematoma and Perihematomal Edema Volumes in Intracerebral Hemorrhage study aims to determine whether a fully automated quantification method and a semi-automated quantification method for quantification of hematoma and perihematomal edema volumes are equivalent to the hematoma and perihematomal edema volumes of the manual quantification method.Methods/Design:Hematoma and perihematomal edema volumes of supratentorial intracerebral hemorrhage on 252 computed tomography scans will be prospectively quantified in random order by six raters using the fully automated, semi-automated, and manual quantification methods. Primary outcome measures for hematoma and perihematomal edema volumes will be quantified via computed tomography scan on admission (
  Citation: Clinical Trials
  PubDate: 2022-07-02T08:01:29Z
  DOI: 10.1177/17407745221105886
When is it impractical to ask informed consent' A systematic review
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Sara JM Laurijssen, Rieke van der Graaf, Wouter B van Dijk, Ewoud Schuit, Rolf HH Groenwold, Diederick E Grobbee, Martine C de Vries
  First page: 545
  Abstract: Clinical Trials, Ahead of Print.
  BackgroundInformed consent is one of the cornerstones of biomedical research with human subjects. Research ethics committees may allow for a modification or a waiver of consent when the research has social value, involves minimal risk, and if consent is impractical to obtain. While the conditions of social value and minimal risk have received ample attention in research ethics literature, the impractical condition remains unclear. There seem to be different interpretations of the meaning of impractical within academic literature. To address this lack of clarity, we performed a systematic review on the interpretation of impractical.MethodsFirst, we examined international research ethics guidelines on their usage and interpretation of impractical. Next, we used international ethical guidelines to identify synonyms of the term “impractical.” Accordingly, PubMed, Embase, and Web of Science were searched for articles that included “informed consent” and “impractical” or one of its synonyms.ResultsWe found that there were only a few international ethics guidelines that described what could be considered impractical. Out of 2329 identified academic articles, 42 were included. Impractical was used to describe four different conditions: (1) obtaining informed consent becomes too demanding for researchers, (2) obtaining informed consent leads to invalid study outcomes, (3) obtaining informed consent harms the participant, and (4) obtaining informed consent is meaningless for the participant.ConclusionThere are conditions that render conventional informed consent truly impractical, such as untraceable participants or harm for participants. At the same time, researchers have a moral responsibility to design an infrastructure in which consent can be obtained, even if they face hardship in obtaining consent. In addition, researchers should seek to minimize harm inflicted upon participants when harm may occur as a result of the consent procedure. Invalidity of research due to consent issues should not be regarded as impractical but as a condition that limits the social value of research. Further research is essential for when a waiver of informed consent based on impractical is also reasonable.
  Citation: Clinical Trials
  PubDate: 2022-07-01T08:58:52Z
  DOI: 10.1177/17407745221103567
Landscape of coronavirus disease 2019 clinical trials: New frontiers and
challenges
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Susan Halabi, Jinyi Zhou, Yijie He, Linda R Bressler, Adrian F Hernandez, Nicholas A Turner, Hwanhee Hong
  First page: 561
  Abstract: Clinical Trials, Ahead of Print.
  Background/AimThe number of coronavirus disease 2019 deaths and cases continues to increase globally. Novel therapies are urgently needed to treat patients with coronavirus disease 2019. We sought to provide a critical review of trials designed during the coronavirus disease 2019 pandemic. Our primary goal was to provide a critical review of the landscape of clinical trials designed to address the coronavirus disease 2019 pandemic. Specifically, we were interested in assessing the design of phase II/III and phase III interventional trials.MethodsWe utilized the ClinicalTrials.gov database to include trials registered between 1 December 2019 and 11 April 2021 to survey the current landscape of clinical trials for coronavirus disease 2019. Variables extracted included: National Clinical Trial number, title, location, sponsor, study type, start date, completion date, gender group, age group, primary outcome, secondary outcome, overall status, and associated references.ResultsAbout 57% of studies were interventional, 14.5% were phase III trials, and the majority of the therapeutic trials included hospitalized patients. There were 52 primary composite outcomes and 285 unique interventions spanning 10 drug classes. The outcomes, disease severity, and comparators varied substantially across trials, and the trials were often too small to be definitive.ConclusionThese findings are relevant as we strongly advocate for global coordination of efforts through the use of common platforms that enable harmonizing of endpoints, collection of common key variables and clear definition of disease severity to have clinically meaningful results from clinical trials.
  Citation: Clinical Trials
  PubDate: 2022-07-02T07:59:09Z
  DOI: 10.1177/17407745221105106
Risk-proportionate approach to paediatric clinical trials: The legal
requirements, challenges, and the way forward under the European Union
Clinical Trials Regulation
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Mandy Wan, Elisa Alessandrini, Paul Brogan, Despina Eleftheriou, Adilia Warris, Roger Brüggemann, Mark Turner
  First page: 573
  Abstract: Clinical Trials, Ahead of Print.
  BackgroundIt is now widely accepted that there is a need for safety and efficacy data on medicines used in children. In the European Union, legislation has provided the necessary framework obligating and incentivizing pharmaceutical companies to carry out appropriate paediatric research to support the development of new medicines. This change in research culture, that medicines used in children should be appropriately researched in children, has also led to the recognition of the importance of investigator-initiated clinical trials in furthering medical knowledge on the off-label use of authorized medicines for which paediatric data are often limited. However, medicines regulatory authorities of European Union countries have largely adopted a uniform approach to the regulation of both industry-sponsored and investigator-initiated trials and, in doing so, have added disproportionate burden to the conduct of paediatric clinical trials investigating authorized medicines.Case studiesTwo European multinational paediatric clinical trials funded by the conect4children consortium are presented to provide a comparative insight into past challenges and to illustrate how the new framework provided by the European Clinical Trials Regulation (No. 536/2014) addresses these barriers in practice.ConclusionThe European Clinical Trials Regulation gives a strong impetus to a risk-proportionate approach and offers a path for more efficient delivery of investigator-initiated paediatric clinical trials.
  Citation: Clinical Trials
  PubDate: 2022-05-05T09:18:16Z
  DOI: 10.1177/17407745221093812
Payments for research participation: Don’t tax the Guinea pig
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Leah Z Rand, Aaron S Kesselheim
  First page: 579
  Abstract: Clinical Trials, Ahead of Print.
  Under current US statute, payments to research participants are taxable income. This means that even though institutional review boards and researchers agree to specific payment amounts to account for the burden of research, participants are paid less than anticipated, and participants’ net payment will vary depending on their home state. Unlike other entities in the research enterprise, who receive incentivizing tax exemptions and credits, research participation is tax dis-incentivized. In addition, incentives and rewards for other socially valuable activities are not taxed. Given these differences and the restrictions on research payments, it is unfair to tax participants on their payments and the statue should be revised.
  Citation: Clinical Trials
  PubDate: 2022-07-02T08:04:09Z
  DOI: 10.1177/17407745221105896
On what basis did Health Canada approve OxyContin in 1996': A
retrospective analysis of regulatory data
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Jessie Pappin, Itai Bavli, Matthew Herder
  First page: 584
  Abstract: Clinical Trials, Ahead of Print.
  The marketing and sale of oxycodone (OxyContin) by Purdue Pharma has commanded a great deal of legal and policy attention due to the drug’s central role in the ongoing overdose crisis. However, little is known about the basis for OxyContin’s approval by regulators, such as Health Canada in 1996. Taking advantage of a recently created online database containing information pertaining to the safety and effectiveness of drugs, we conducted a retrospective analysis of Purdue Pharma’s submission to Health Canada, including both published and unpublished clinical trials. None of the trials sponsored by Purdue Pharma sought to meaningfully assess the risks of misuse or addiction associated with OxyContin. The trials were short in duration (maximum length was 24 days) and only assessed safety and efficacy of a 12-h dosing interval. Also, the two trial reports that explicitly mentioned (but did not formally evaluate) the risk of misuse were not published, making it unclear how Health Canada concluded that there was no risk of misuse. In our view, these findings underscore the need for transparency of not only of clinical trial data, but also the regulator’s interpretation of such data, which is currently lacking in Canada. Furthermore, they call into question why Health Canada’s role in precipitating the overdose crisis has not received greater scrutiny, including in the context of recent litigation surrounding OxyContin.
  Citation: Clinical Trials
  PubDate: 2022-08-04T11:09:41Z
  DOI: 10.1177/17407745221108436
Harmonisation of large-scale, heterogeneous individual participant adverse
event data from randomised trials of statin therapy
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Cholesterol Treatment Trialists’ Collaboration
  First page: 593
  Abstract: Clinical Trials, Ahead of Print.
  Background:Meta-analyses of individual-level data from randomised trials are often required to detect clinically worthwhile effects. The Cholesterol Treatment Trialists’ Collaboration, which includes data from numerous large long-term statin trials, is conducting a review of the effects of statin therapy on all adverse events collected in those trials. This article describes the approaches used and challenges faced to systematically capture and categorise the data.Methods:Protocols, statistical analysis plans, case report forms, clinical study reports and datasets were obtained, reviewed and checked. Relevant baseline and follow-up data from each trial was then reorganised into standardised formats based upon the Clinical Data Interchange Standards Consortium Study Data Tabulation Model. Adverse event data were organised and coded (automatically or, where necessary, manually) according to a common medical dictionary based upon the Medical Dictionary for Regulatory Activities.Results:Data from 23 double-blind statin trials and 5 open-label statin trials were provided, either through direct data transfer or through online access platforms. Together, these trials provided 845 datasets containing over 38 million records relating to 30,495 study variables and 181,973 randomised participants. Of the 46 Clinical Data Interchange Standards Consortium Study Data Tabulation Model domains that could potentially have been used to organise the data, the 13 most relevant to the project were identified and utilised, including 6 domains related to post-randomisation adverse events. Nearly 1.2 million adverse events were extracted and mapped to over 45,000 unique adverse event terms. Of these adverse events, 99% were coded to a Medical Dictionary for Regulatory Activities ‘lower level term’, with the remainder coded to a ‘higher level term’ or, very rarely, only a ‘higher level group term’.Conclusion:In this meta-analysis of adverse event data from the large randomised trials of statins, approaches based on common standards for data organisation and classification have provided a resource capable of allowing reliable and rapid evaluation of any previously unknown benefits or hazards of statin therapy.
  Citation: Clinical Trials
  PubDate: 2022-07-09T10:56:21Z
  DOI: 10.1177/17407745221105509
Evaluating group-sequential non-inferiority clinical trials following
interim stopping: The HIV Prevention Trials Network 083 trial
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Brett S Hanscom, Deborah J Donnell, Thomas R Fleming, James P Hughes, Marybeth McCauley, Beatriz Grinsztejn, Raphael J Landovitz, Scott S Emerson
  First page: 605
  Abstract: Clinical Trials, Ahead of Print.
  Background/Aims:The HIV Prevention Trials Network 083 trial was a group-sequential non-inferiority trial designed to compare HIV incidence under a novel experimental regimen for HIV prevention, long-acting injectable cabotegravir, with an active-control regimen of daily oral tenofovir disoproxil fumarate/emtricitabine (brand name Truvada). In March of 2020, just as the trial had completed enrollment, the COVID-19 pandemic threatened to prevent trial participants from attending study visits and obtaining study medication, motivating the study team to update the interim monitoring plan. The Data and Safety Monitoring Board subsequently stopped the trial at the first interim review due to strong early evidence of efficacy.Methods:Here we describe some unique aspects of the trial’s design, monitoring, analysis, and interpretation. We illustrate the importance of computing point estimates, confidence intervals, and p values based on the sampling distribution induced by sequential monitoring.Results:Accurate analysis, decision-making and interpretation of trial results rely on pre-specification of a stopping boundary, including the scale on which the stopping rule will be implemented, the specific test statistics to be calculated, and how the boundary will be adjusted if the available information fraction at interim review is different from planned. After appropriate adjustment for the sampling distribution and overrun, the HIV Prevention Trials Network 083 trial provided strong evidence that the experimental regimen was superior to the active control.Conclusions:For the HIV Prevention Trials Network 083 trial, the difference between corrected inferential statistics and naive results was quite small—as will often be the case—nevertheless, it is appropriate to report and publish the most accurate and unbiased statistical results.
  Citation: Clinical Trials
  PubDate: 2022-09-02T12:14:07Z
  DOI: 10.1177/17407745221118371
A Bayesian adaptive design for clinical trials of rare efficacy outcomes
with multiple definitions
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Shirin Golchi, James J Willard, Eleanor Pullenayegum, Diego G Bassani, Lisa G Pell, Kristian Thorlund, Daniel E Roth
  First page: 613
  Abstract: Clinical Trials, Ahead of Print.
  Introduction:Bayesian adaptive designs for clinical trials have gained popularity in the recent years due to the flexibility and efficiency that they offer. We consider the scenario where the outcome of interest comprises events with relatively low risk of occurrence and different case definitions resulting in varying control group risk assumptions. This is a scenario that occurs frequently for infectious diseases in global health research.Methods:We propose a Bayesian adaptive design that incorporates different case definitions of the outcome of interest that vary in stringency. A set of stopping rules are proposed where superiority and futility may be concluded with respect to different outcome definitions and therefore maintain a realistic probability of stopping in trials with low event rates. Through a simulation study, a variety of stopping rules and design configurations are compared.Results:The simulation results are provided in an interactive web application that allows the user to explore and compare the design operating characteristics for a variety of assumptions and design parameters with respect to different outcome definitions. The results for select simulation scenarios are provided in the article.Discussion:Bayesian adaptive designs offer the potential for maximizing the information learned from the data collected through clinical trials. The proposed design enables monitoring and utilizing multiple composite outcomes based on rare events to optimize the trial design operating characteristics.
  Citation: Clinical Trials
  PubDate: 2022-09-10T10:00:39Z
  DOI: 10.1177/17407745221118366
The design and conduct of a pragmatic cluster randomized trial of an
advance care planning program for nursing home residents with dementia
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Susan E Hickman, Susan L Mitchell, Laura C Hanson, Wanzhu Tu, Timothy E Stump, Kathleen T Unroe
  First page: 623
  Abstract: Clinical Trials, Ahead of Print.
  Background/AimsA significant number of people with Alzheimer’s disease or related dementia diagnoses will be cared for in nursing homes near the end of life. Advance care planning (ACP), the process of eliciting and documenting patient-centered preferences for care, is considered essential to providing high quality care for this population. Nursing homes are currently required by regulations to offer ACP to residents and families, but no training requirements exist for nursing home staff, and approaches to fulfilling this regulatory and ethical responsibility vary. As a result, residents may receive care inconsistent with their goals, such as unwanted hospitalizations. Pragmatic trials offer a way to develop and test ACP in real-world settings to increase the likelihood of adoption of sustainable best practices.MethodsThe “Aligning Patient Preferences—a Role Offering Alzheimer’s patients, Caregivers, and Healthcare Providers Education and Support (APPROACHES)” project is designed to pragmatically test and evaluate a staff-led program in 137 nursing homes (68 = intervention, 69 = control) owned by two nursing home corporations. Existing nursing home staff receive standardized training and implement the ACP Specialist program under the supervision of a corporate lead. The primary trial outcome is the annual rate of hospital transfers (admissions and emergency department visits). Consistent with the spirit of a pragmatic trial, study outcomes rely on data already collected for quality improvement, clinical, or billing purposes. Configurational analysis will also be performed to identify conditions associated with implementation.ResultsPartnerships with large corporate companies enable the APPROACHES trial to rely on corporate infrastructure to roll out the intervention, with support for a corporate implementation lead who is charged with the initial introduction and ongoing support for nursing home-based ACP Specialists. These internal champions connect the project with other company priorities and use strategies familiar to nursing home leaders for the initiation of other programs. Standardized data collection across nursing homes also supports the conduct of pragmatic trials in this setting.DiscussionMany interventions to improve care in nursing homes have failed to demonstrate an impact or, if successful, maintain an impact over time. Pragmatic trials, designed to test interventions in real-world contexts that are evaluated through existing data sources collected routinely as part of clinical care, are well suited for the nursing home environment. A robust program that increases access to ACP for nursing home residents has the potential to increase goal-concordant care and is expected to reduce hospital transfers. If successful, the ACP Specialist Program will be primed for rapid translation into nursing home practice to reduce unwanted, burdensome hospitalizations and improve the quality of care for residents with dementia.
  Citation: Clinical Trials
  PubDate: 2022-07-11T06:46:17Z
  DOI: 10.1177/17407745221108992
An adaptive clinical trial design to identify the target dose of
tenecteplase for treatment of acute pulmonary embolism
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Sharon D Yeatts, Lydia D Foster, William G Barsan, Nicholas S Berry, Clifton W Callaway, Roger J Lewis, Benjamin R Saville, Robert Silbergleit, Jeffrey A Kline
  First page: 636
  Abstract: Clinical Trials, Ahead of Print.
  Background/AimsFibrinolytic therapy with tenecteplase has been proposed for patients with pulmonary embolism but the optimal dose is unknown. Higher-than-necessary dosing is likely to cause excess bleeding. We designed an adaptive clinical trial to identify the minimum and assumed safest dose of tenecteplase that maintains efficacy.MethodsWe propose a Bayesian adaptive, placebo-controlled, group-sequential dose-finding trial using response-adaptive randomization to preferentially allocate subjects to the most promising doses, dual analyses strategies (continuous and dichotomized) using a gatekeeping approach to maximize clinical impact, and interim stopping rules to efficiently address competing trial objectives. The operating characteristics of the proposed design were evaluated using Monte Carlo simulation across multiple hypothetical efficacy scenarios.ResultsSimulation demonstrated response-adaptive randomization can preferentially allocate subjects to doses which appear to be performing well based on interim data. Interim decision-making, including the interim evaluation of both analysis strategies with gatekeeping, allows the trial to continue enrollment when success with the dichotomized analysis strategy appears sufficiently likely and to stop enrollment and declare superiority based on the continuous analysis strategy when there is little chance of ultimately declaring superiority with the dichotomized analysis.ConclusionThe proposed design allows evaluation of a greater number of dose levels than would be possible with a non-adaptive design and avoids the need to choose either the continuous or the dichotomized analysis strategy for the primary endpoint.
  Citation: Clinical Trials
  PubDate: 2022-07-02T08:06:09Z
  DOI: 10.1177/17407745221105897
A platform trial design for preventive vaccines against Marburg virus and
other emerging infectious disease threats
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Ira M Longini, Yang Yang, Thomas R Fleming, César Muñoz-Fontela, Rui Wang, Susan S Ellenberg, George Qian, M Elizabeth Halloran, Martha Nason, Victor De Gruttola, Sabue Mulangu, Yunda Huang, Christl A Donnelly, Ana-Maria Henao Restrepo
  First page: 647
  Abstract: Clinical Trials, Ahead of Print.
  Background:The threat of a possible Marburg virus disease outbreak in Central and Western Africa is growing. While no Marburg virus vaccines are currently available for use, several candidates are in the pipeline. Building on knowledge and experiences in the designs of vaccine efficacy trials against other pathogens, including SARS-CoV-2, we develop designs of randomized Phase 3 vaccine efficacy trials for Marburg virus vaccines.Methods:A core protocol approach will be used, allowing multiple vaccine candidates to be tested against controls. The primary objective of the trial will be to evaluate the effect of each vaccine on the rate of virologically confirmed Marburg virus disease, although Marburg infection assessed via seroconversion could be the primary objective in some cases. The overall trial design will be a mixture of individually and cluster-randomized designs, with individual randomization done whenever possible. Clusters will consist of either contacts and contacts of contacts of index cases, that is, ring vaccination, or other transmission units.Results:The primary efficacy endpoint will be analysed as a time-to-event outcome. A vaccine will be considered successful if its estimated efficacy is greater than 50% and has sufficient precision to rule out that true efficacy is less than 30%. This will require approximately 150 total endpoints, that is, cases of confirmed Marburg virus disease, per vaccine/comparator combination. Interim analyses will be conducted after 50 and after 100 events. Statistical analysis of the trial will be blended across the different types of designs. Under the assumption of a 6-month attack rate of 1% of the participants in the placebo arm for both the individually and cluster-randomized populations, the most likely sample size is about 20,000 participants per arm.Conclusion:This event-driven design takes into the account the potentially sporadic spread of Marburg virus. The proposed trial design may be applicable for other pathogens against which effective vaccines are not yet available.
  Citation: Clinical Trials
  PubDate: 2022-07-22T11:47:46Z
  DOI: 10.1177/17407745221110880
Fitness of real-world data for clinical trial data collection: Results and
lessons from a HARMONY Outcomes ancillary study
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Bradley G Hammill, Jeffrey D Leimberger, Zachary Lampron, Sudha R Raman, Emily C O’Brien, Keele E Wurst, Sally Mountcastle, Marianne Cunnington, Salim Janmohamed, Lesley H Curtis
  First page: 655
  Abstract: Clinical Trials, Ahead of Print.
  BackgroundDespite the extensive use of real-world data for retrospective, observational clinical research, our understanding of how real-world data might increase the efficiency of data collection in patient-level randomized clinical trials is largely unknown. The structure of real-world data is inherently heterogeneous, with each source electronic health record and claims database different from the next. Their fitness-for-use as data sources for multisite trials in the United States has not been established.MethodsFor a subset of participants in the HARMONY Outcomes Trial, we obtained electronic health record data from recruiting sites or Medicare claims data from the Centers for Medicare & Medicaid Services. For baseline characteristics and follow-up events, we assessed the level of agreement between these real-world data and data documented in the trial database.ResultsReal-world data-derived demographic information tended to agree with trial-reported demographic information, although real-world data were less accurate in identifying medical history. The ability of real-world data to identify baseline medication usage differed by real-world data source, with claims data demonstrating substantially better performance than electronic health record data. The limited number of lab results in the collected electronic health record data matched closely with values in the trial database. There were not enough follow-up events in the ancillary study population to draw meaningful conclusions about the performance of real-world data for identification of events. Based on the conduct of this ancillary study, the challenges and opportunities of using real-world data within clinical trials are discussed.ConclusionBased on a subset of participants from the HARMONY Outcomes Trial, our results suggest that electronic health record or claims data, as currently available, are unlikely to be a complete substitute for trial data collection of medical history or baseline lab results, but that Medicare claims were able to identify most medications. The limited size of the study population prevents us from drawing strong conclusions based on these results, and other studies are clearly needed to confirm or refute these findings.
  Citation: Clinical Trials
  PubDate: 2022-07-25T06:04:24Z
  DOI: 10.1177/17407745221114298
Measures of fidelity of delivery and engagement in self-management
interventions: A systematic review of measures
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Tasmin A Rookes, Anette Schrag, Kate Walters, Megan Armstrong
  First page: 665
  Abstract: Clinical Trials, Ahead of Print.
  Background/Aims:Self-management interventions are increasingly being developed and researched to improve long-term condition outcomes. To understand and interpret findings, it is essential that fidelity of intervention delivery and participant engagement are measured and reported. Before developing fidelity checklists to assess treatment fidelity of interventions, current recommendations suggest that a synthesis of fidelity measures reported in the literature is completed. Therefore, here we aim to identify what the current measures of fidelity of intervention delivery and engagement for self-management interventions for long-term conditions are and whether there is treatment fidelity.Methods:Four databases (MEDLINE, PubMed, CINAHL Plus and ScienceDirect) and the journal implementation science were systematically searched to identify published reports from inception to December 2020 for experimental studies measuring fidelity of intervention delivery and/or participant engagement in self-management interventions for long-term conditions. Data on fidelity of delivery and engagement measures and the findings were extracted and synthesised.Results:Thirty-nine articles were identified as eligible, with 25 studies measuring fidelity of delivery, 19 reporting engagement and 5 measuring both. For fidelity of delivery, measures included structured checklists, participant completed measures and researcher observations/notes. These were completed by researchers, participants and intervention leaders. Often there was little information around the development of these measures, particularly when the measure had been developed by the researchers, rather than building on others work. Eighteen of 25 studies reported there was fidelity of intervention delivery. For engagement, measures included data analytics, participant completed measures and researcher observations. Ten out of 19 studies reported participants were engaged with the intervention.Conclusion:In complex self-management interventions, it is essential to assess whether treatment fidelity of each core component of interventions is delivered, as outlined in the protocol, to understand which components are having an effect. Treatment fidelity checklists comparing what was planned to be delivered, with what was delivered should be developed with pre-defined cut-offs for when fidelity has been achieved. Similarly, when measuring engagement, while data analytics continue to rise with the increase in digital interventions, clear cut-offs for participant use and content engaged with to be considered an engagement participant need to be pre-determined.
  Citation: Clinical Trials
  PubDate: 2022-08-26T09:01:44Z
  DOI: 10.1177/17407745221118555
Recruitment characteristics of randomised trials in critical care: A
systematic review
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Mahesh Ramanan, Aashish Kumar, Laurent Billot, John Myburgh, Balasubramanian Venkatesh
  First page: 673
  Abstract: Clinical Trials, Ahead of Print.
  Background/Aims:To summarise the temporal trends of recruitment and methodological characteristics of critical care randomised controlled trials with the primary outcome of mortality.Methods:PubMed was searched for articles meeting inclusion and exclusion criteria. Randomised controlled trials, with primary outcome of mortality, of adult and paediatric critical care patients treated in an intensive care unit, were included. Neonatal intensive care unit trials, non-English publications and conference proceedings or abstracts without full-length publications were excluded. Duplicate literature search, article selection and quality assessment were performed by two reviewers with disputes resolved through discussion. Data were extracted into a custom-designed Research Electronic Data Capture database.Results:The search identified 67,199 records of which 230 were included. The annual number of critical care randomised controlled trials published increased gradually over a 30-year period from 0 in 1990 to 19 in 2014 with stabilisation at 8–11 between 2015 and 2020. Twenty-seven percent of randomised controlled trials were low risk in all categories using the Cochrane Risk of Bias tool. Methodological characteristics such as registration on clinical trials registries and data safety monitoring committee presence significantly (p
  Citation: Clinical Trials
  PubDate: 2022-09-07T06:16:21Z
  DOI: 10.1177/17407745221123248
Ethics challenges in sharing data from pragmatic clinical trials
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Stephanie R Morain, Juli Bollinger, Kevin Weinfurt, Jeremy Sugarman
  First page: 681
  Abstract: Clinical Trials, Ahead of Print.
  Numerous arguments have been advanced for broadly sharing de-identified, participant-level clinical trials data, and trial sponsors and journals are increasingly requiring it. However, data sharing in pragmatic clinical trials presents ethical challenges related to the use of waivers or alterations of informed consent for some pragmatic clinical trials and corresponding limitations of informed consent to guide sharing decisions; the potential for data sharing in pragmatic clinical trials to present risks not only for individual patient-subjects, but also for health systems and the clinicians within them; sharing of data from electronic health records instead of data newly collected for research purposes; and researchers’ limited capacity to control sensitive data within an electronic health record and potential implications of such limits for meeting obligations inherent to Certificates of Confidentiality. These challenges raise questions about the extent to which traditional research ethics governance structures are capable of guiding decisions about pragmatic clinical trial data sharing. This article identifies and examines these ethical challenges for pragmatic clinical trial data sharing. We suggest several areas for future empirical scholarship, including the need to identify patient and public attitudes regarding pragmatic clinical trial data sharing as well as to assess the demand for pragmatic clinical trial data and the correspondingly likely benefit of such sharing. Further conceptual work is also needed to explore how requirements to respect patient-subjects about whom data are shared in the context of pragmatic clinical trials should be understood, particularly in the absence of informed consent for initial research activities, and the appropriate balance between promoting the generation of socially valuable knowledge and respecting autonomy.
  Citation: Clinical Trials
  PubDate: 2022-09-08T06:10:41Z
  DOI: 10.1177/17407745221110881
Mobilizing the clinical trial ecosystem to drive adoption of master
protocols
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Abby Bronson, Marianne K Chase, Kimberly Fisher, Daniel Millar, Jane Perlmutter, Nicholas Richardson
  First page: 690
  Abstract: Clinical Trials, Ahead of Print.
  Master protocol studies typically use an overarching protocol to answer several questions by guiding a variety of sub-studies. These sub-studies can incorporate multiple diseases, therapies, or both. Although this innovative approach offers many benefits, including the ability to deliver clinical research that is more patient-centric and efficient, several common barriers curtail widespread adoption. The Clinical Trials Transformation Initiative (CTTI) convened industry representatives, regulatory agencies, patient groups, and academic institutions to identify emerging best practices and develop resources designed to help sponsors and other stakeholders overcome these challenges. We first identify some broad changes needed in the clinical trials ecosystem to facilitate mainstream adoption of master protocol studies, and we subsequently summarize CTTI’s resources designed to support this effort.
  Citation: Clinical Trials
  PubDate: 2022-09-10T05:23:33Z
  DOI: 10.1177/17407745221110199
On the proposed use of a finite-population correction factor in clinical
trials
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Andrew V Frane
  First page: 697
  Abstract: Clinical Trials, Ahead of Print.
  
  Citation: Clinical Trials
  PubDate: 2022-10-05T10:43:53Z
  DOI: 10.1177/17407745221110185
Response
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Authors: Audrey Mauguen
  First page: 699
  Abstract: Clinical Trials, Ahead of Print.
  
  Citation: Clinical Trials
  PubDate: 2022-10-05T10:44:13Z
  DOI: 10.1177/17407745221125051