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LABORATORY AND EXPERIMENTAL MEDICINE (99 journals)

Showing 1 - 99 of 99 Journals sorted alphabetically
AAPS PharmSciTech     Hybrid Journal   (Followers: 9)
Actualites Pharmaceutiques     Full-text available via subscription   (Followers: 7)
Adipocyte     Open Access   (Followers: 1)
African Journal of Laboratory Medicine     Open Access   (Followers: 2)
American Journal of Experimental and Clinical Research     Open Access   (Followers: 4)
American Journal of Medical and Biological Research     Open Access   (Followers: 10)
Animal Models and Experimental Medicine     Open Access  
Annals of Clinical Chemistry and Laboratory Medicine     Open Access   (Followers: 5)
Applied In Vitro Toxicology     Hybrid Journal   (Followers: 2)
Archives of Clinical and Experimental Medicine     Open Access  
Archives of Medical Research     Hybrid Journal   (Followers: 3)
Archives of Pathology & Laboratory Medicine     Full-text available via subscription   (Followers: 31)
Archives of Preventive Medicine     Open Access   (Followers: 3)
Biomedical Engineering     Hybrid Journal   (Followers: 3)
Bulletin of Experimental Biology and Medicine     Hybrid Journal  
Clinica Chimica Acta     Hybrid Journal   (Followers: 30)
Clinical & Experimental Metastasis     Hybrid Journal  
Clinical and Experimental Medical Journal     Full-text available via subscription   (Followers: 1)
Clinical and Experimental Medicine     Hybrid Journal   (Followers: 4)
Clinical Trials     Hybrid Journal   (Followers: 21)
Clinical Trials in Degenerative Diseases     Open Access  
Clinical Trials in Orthopedic Disorders     Open Access   (Followers: 1)
Current Medicine Research and Practice     Full-text available via subscription  
Current Research in Drug Discovery     Open Access   (Followers: 1)
Drug Design, Development and Therapy     Open Access   (Followers: 4)
Ecography     Hybrid Journal   (Followers: 28)
European Journal of Hospital Pharmacy : Science and Practice (EJHP)     Hybrid Journal   (Followers: 8)
European Journal of Medical Research     Open Access   (Followers: 1)
European Journal of Nanomedicine     Hybrid Journal   (Followers: 1)
Experimental & Molecular Medicine     Open Access   (Followers: 1)
Experimental Aging Research: An International Journal Devoted to the Scientific Study of the Aging Process     Hybrid Journal   (Followers: 3)
Experimental and Therapeutic Medicine     Full-text available via subscription   (Followers: 1)
Experimental Biology and Medicine     Hybrid Journal   (Followers: 3)
Expert Opinion on Drug Delivery     Hybrid Journal   (Followers: 20)
Frontiers in Laboratory Medicine     Open Access  
Frontiers in Medical Technology     Open Access   (Followers: 1)
IN VIVO     Full-text available via subscription   (Followers: 5)
International Archives of Biomedical and Clinical Research     Open Access  
International Journal of Experimental Pathology     Hybrid Journal   (Followers: 1)
International Journal of Health Research and Innovation     Open Access   (Followers: 1)
International Journal of Research in Medical Sciences     Open Access   (Followers: 5)
International Journal of Statistics in Medical Research     Hybrid Journal   (Followers: 5)
Journal of Cell Science & Therapy     Open Access   (Followers: 1)
Journal of Applied Biomaterials & Functional Materials     Hybrid Journal   (Followers: 1)
Journal of Biomedical and Clinical Research     Open Access  
Journal of Clinical Laboratory Analysis     Open Access   (Followers: 14)
Journal of Clinical Medicine and Research     Open Access  
Journal of Clinical Medicine Research     Open Access   (Followers: 4)
Journal of Clinical Trials     Open Access   (Followers: 6)
Journal of Current and Advance Medical Research     Open Access   (Followers: 1)
Journal of Current Medical Research and Practice     Open Access  
Journal of Current Research in Scientific Medicine     Open Access  
Journal of Current Researches on Health Sector     Open Access  
Journal of Drug Delivery and Therapeutics JDDT     Open Access   (Followers: 1)
Journal of Enzyme Inhibition and Medicinal Chemistry     Open Access   (Followers: 4)
Journal of Experimental & Clinical Medicine     Full-text available via subscription   (Followers: 1)
Journal of Experimental & Clinical Cancer Research     Open Access   (Followers: 2)
Journal of Experimental and Clinical Medicine     Open Access  
Journal of Experimental Medicine     Full-text available via subscription   (Followers: 45)
Journal of Experimental Pharmacology     Open Access   (Followers: 2)
Journal of Histotechnology     Hybrid Journal   (Followers: 2)
Journal of International Medical Research     Open Access   (Followers: 3)
Journal of Investigative Medicine High Impact Case Reports     Open Access  
Journal of Medicine and Biomedical Research     Open Access   (Followers: 1)
Journal of Muhammadiyah Medical Laboratory Technologist     Open Access  
Journal of Operating Department Practitioners     Full-text available via subscription   (Followers: 2)
Journal of the American Society of Cytopathology     Hybrid Journal   (Followers: 6)
Journal of Trace Elements in Medicine and Biology     Hybrid Journal   (Followers: 1)
Lab on a Chip     Full-text available via subscription   (Followers: 42)
Laboratory Investigation     Hybrid Journal   (Followers: 3)
Medical Devices & Sensors     Hybrid Journal  
Medical Image Analysis     Hybrid Journal   (Followers: 15)
Medical Instrumentation     Open Access  
Medical Laboratory Observer     Full-text available via subscription  
Medical Laboratory Technology Journal     Open Access  
Medicinal Chemistry Research     Hybrid Journal   (Followers: 12)
Medtech Insight     Full-text available via subscription   (Followers: 4)
Nanomedicine: Nanotechnology, Biology and Medicine     Hybrid Journal   (Followers: 7)
New Zealand Journal of Medical Laboratory Science     Full-text available via subscription   (Followers: 1)
Oriental Pharmacy and Experimental Medicine     Partially Free   (Followers: 3)
Pathology and Laboratory Medicine International     Open Access   (Followers: 7)
Physical Biology     Hybrid Journal   (Followers: 4)
Practical Laboratory Medicine     Open Access   (Followers: 2)
Proceedings of the Institution of Mechanical Engineers Part H: Journal of Engineering in Medicine     Hybrid Journal   (Followers: 3)
Prosthetics and Orthotics International     Hybrid Journal   (Followers: 9)
Pulse     Full-text available via subscription  
Qualitative Research in Medicine & Healthcare     Open Access  
Recent Advances in Biology and Medicine     Open Access  
Regulatory Toxicology and Pharmacology     Hybrid Journal   (Followers: 43)
Reproduction     Full-text available via subscription   (Followers: 7)
Revista Peruana de Medicina Experimental y Salud Pública     Open Access  
Revista Romana de Medicina de Laborator     Open Access  
RSC Medicinal Chemistry     Full-text available via subscription   (Followers: 6)
SA Pharmacist's Assistant     Open Access  
Savannah Journal of Medical Research and Practice     Full-text available via subscription  
SLAS Technology     Hybrid Journal   (Followers: 2)
Statistics in Medicine     Hybrid Journal   (Followers: 190)
Trends in Molecular Medicine     Full-text available via subscription   (Followers: 14)
Turkish Journal of Clinics and Laboratory     Open Access   (Followers: 1)
Similar Journals
Journal Cover
Clinical Trials
Journal Prestige (SJR): 2.399
Citation Impact (citeScore): 2
Number of Followers: 21  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1740-7745 - ISSN (Online) 1740-7753
Published by Sage Publications Homepage  [1093 journals]
  • A survey of the feasibility of developing osteoporosis clinical trials in
           Duchenne muscular dystrophy: Survey of the opinion of young people with
           Duchenne muscular dystrophy, families and clinicians
    • Authors: Sze Choong Wong, Shuko Joseph, Nadia Capaldi, Marina Di Marco, Jennifer Dunne, Michela Guglieri, Iain Horrocks, Volker Straub, S Faisal Ahmed
      Abstract: Clinical Trials, Ahead of Print.
      Background/aimsGiven the extent of osteoporosis in people with Duchenne muscular dystrophy treated with glucocorticoids and the limited evidence of bone-protective therapies, clinical trials are needed. We conducted surveys to obtain the opinion of young people with Duchenne muscular dystrophy, parents/guardians and neuromuscular clinicians on the feasibility of osteoporosis clinical trials in this population.MethodsOnline surveys were sent to three groups: (a) people with a confirmed diagnosis of Duchenne muscular dystrophy (≥14 years), (b) parents and guardians and (c) neuromuscular clinicians in the UK NorthStar Clinical Network. Surveys (a) and (b) were distributed via the UK Duchenne muscular dystrophy Registry.ResultsSurvey respondents included 52 people with Duchenne muscular dystrophy with a median age of 17 years (range: 14, 40) and 183 parents/guardians. Fourteen out of 23 (61%) NorthStar centres responded. Of the 52 people with Duchenne muscular dystrophy, 13 (25%) were very concerned about their bone health and 21 (40%) were slightly concerned. Of the 183 parents/guardians, 75 (41%) were very concerned about their son’s bone health and 90 (49%) were slightly concerned. Fractures and quality of life were the top two main outcome measures identified by people with Duchenne muscular dystrophy. Fractures and bone density were the top two main outcome measures identified by parents/guardians and neuromuscular clinicians. Thirty percent of people with Duchenne muscular dystrophy and 40% of parents/guardians would not take part if an osteoporosis trial involved a placebo that was administered parenterally. Only 2 of the 14 NorthStar centres (14%) would enrol people with Duchenne muscular dystrophy if a parenteral placebo was used in an osteoporosis trial in Duchenne muscular dystrophy.ConclusionThere is great awareness of bone health and the need for bone-protective trials among people with Duchenne muscular dystrophy and their carers. However, a proportion of people with Duchenne muscular dystrophy and parents are reluctant to participate in a placebo-controlled osteoporosis trial that included a parenteral therapy. A larger proportion of health care experts are unwilling to enrol their patients in such a trial. Our finding is relevant for the design of bone-protective studies in Duchenne muscular dystrophy.
      Citation: Clinical Trials
      PubDate: 2020-10-05T04:49:50Z
      DOI: 10.1177/1740774520958395
       
  • Adverse event load, onset, and maximum grade: A novel method of reporting
           adverse events in cancer clinical trials
    • Authors: Guilherme S Lopes, Christophe Tournigand, Curtis L Olswold, Romain Cohen, Emmanuelle Kempf, Leonard Saltz, Richard M Goldberg, Herbert Hurwitz, Charles Fuchs, Aimery de Gramont, Qian Shi
      Abstract: Clinical Trials, Ahead of Print.
      BackgroundCurrent adverse event reporting practices do not document longitudinal characteristics of adverse effects, and alternative methods are not easily interpretable and have not been employed by clinical trials. Introducing time parameters in the evaluation of safety that are comprehensive yet easily interpretable could allow for a better understanding of treatment quality. In this study, we developed and applied a novel adverse event reporting method based on longitudinal adverse event changes to aid describing, summarizing, and presenting adverse event profile. We termed it the “Adverse Event Load, Onset, and Maximum Grade” method.MethodsWe developed two adverse event summary metrics to complement the traditional maximum grade report. Onset time indicates the time period in which the maximum grade for a specific adverse event occurred and was defined as “early” (i.e. maximum grade happened for the first time before 6 weeks) or “late” (i.e. after the 6th week). Adverse event load indicates the overall severity of a specific adverse event over the entire treatment. Higher adverse event load indicates a worse overall experience. These metrics can be calculated for adverse events with different maximum grades, in treatments with planned changes (e.g. dosage changes), using data sets with different number of adverse event data points between treatments (e.g. treatments with longer cycle lengths may have less adverse event data points) and on data sets with different adverse event data availability (e.g. cycle basis and patient-outcome reports). We tested the utility of this method using individual patient data from two major backbone therapies (“Irinotecan” and “Oxaliplatin”) from the N9741 trial available in the Fondation ARCAD database (fondationarcad.org). We investigated profiles of diarrhea, neutropenia/leukopenia, and nausea/vomiting.ResultsOur method provided additional information compared to traditional adverse event reports. For example, for nausea/vomiting, while patients in Irinotecan had a higher risk of experiencing maximum grade 3–4 (15.6% vs 7.6%, respectively; p 
      Citation: Clinical Trials
      PubDate: 2020-10-01T07:54:07Z
      DOI: 10.1177/1740774520959313
       
  • Summarising salient information on historical controls: A structured
           assessment of validity and comparability across studies
    • Authors: Anthony Hatswell, Nick Freemantle, Gianluca Baio, Emmanuel Lesaffre, Joost van Rosmalen
      Abstract: Clinical Trials, Ahead of Print.
      BackgroundWhile placebo-controlled randomised controlled trials remain the standard way to evaluate drugs for efficacy, historical data are used extensively across the development cycle. This ranges from supplementing contemporary data to increase the power of trials to cross-trial comparisons in estimating comparative efficacy. In many cases, these approaches are performed without in-depth review of the context of data, which may lead to bias and incorrect conclusions.MethodsWe discuss the original ‘Pocock’ criteria for the use of historical data and how the use of historical data has evolved over time. Based on these factors and personal experience, we created a series of questions that may be asked of historical data, prior to their use. Based on the answers to these questions, various statistical approaches are recommended. The strategy is illustrated with a case study in colorectal cancer.ResultsA number of areas need to be considered with historical data, which we split into three categories: outcome measurement, study/patient characteristics (including setting and inclusion/exclusion criteria), and disease process/intervention effects. Each of these areas may introduce issues if not appropriately handled, while some may preclude the use of historical data entirely. We present a tool (in the form of a table) for highlighting any such issues. Application of the tool to a colorectal cancer data set demonstrates under what conditions historical data could be used and what the limitations of such an analysis would be.ConclusionHistorical data can be a powerful tool to augment or compare with contemporary trial data, though caution is required. We present some of the issues that may be considered when involving historical data and what (if any) statistical approaches may account for differences between studies. We recommend that, where historical data are to be used in analyses, potential differences between studies are addressed explicitly.
      Citation: Clinical Trials
      PubDate: 2020-09-22T05:23:34Z
      DOI: 10.1177/1740774520944855
       
  • Empirical power comparison of statistical tests in contemporary phase III
           randomized controlled trials with time-to-event outcomes in oncology
    • Authors: Miki Horiguchi, Michael J Hassett, Hajime Uno
      Abstract: Clinical Trials, Ahead of Print.
      Background:More than 95% of recent cancer randomized controlled trials used the log-rank test to detect a treatment difference making it the predominant tool for comparing two survival functions. As with other tests, the log-rank test has both advantages and disadvantages. One advantage is that it offers the highest power against proportional hazards differences, which may be a major reason why alternative methods have rarely been employed in practice. The performance of statistical tests has traditionally been investigated both theoretically and numerically for several patterns of difference between two survival functions. However, to the best of our knowledge, there has been no attempt to compare the performance of various statistical tests using empirical data from past oncology randomized controlled trials. So, it is unknown whether the log-rank test offers a meaningful power advantage over alternative testing methods in contemporary cancer randomized controlled trials. Focusing on recently reported phase III cancer randomized controlled trials, we assessed whether the log-rank test gave meaningfully greater power when compared with five alternative testing methods: generalized Wilcoxon, test based on maximum of test statistics from multiple weighted log-rank tests, difference in t-year event rate, and difference in restricted mean survival time with fixed and adaptive [math].Methods:Using manuscripts from cancer randomized controlled trials recently published in high-tier clinical journals, we reconstructed patient-level data for overall survival (69 trials) and progression-free survival (54 trials). For each trial endpoint, we estimated the empirical power of each test. Empirical power was measured as the proportion of trials for which a test would have identified a significant result (p value 
      Citation: Clinical Trials
      PubDate: 2020-09-16T06:17:09Z
      DOI: 10.1177/1740774520940256
       
  • Use of electronic recruitment methods in a clinical trial of adults with
           gout
    • Authors: Hailey N Miller, Jeanne Charleston, Beiwen Wu, Kelly Gleason, Karen White, Cheryl R Dennison Himmelfarb, Daniel E Ford, Timothy B Plante, Allan C Gelber, Lawrence J Appel, Edgar R Miller, Stephen P Juraschek
      Abstract: Clinical Trials, Ahead of Print.
      Background/aims:Electronic-based recruitment methods are increasingly utilized in clinical trials to recruit and enroll research participants. The cost-effectiveness of electronic-based methods and impact on sample generalizability is unknown. We compared recruitment yields, cost-effectiveness, and demographic characteristics across several electronic and traditional recruitment methods.Methods:We analyzed data from the diet gout trial recruitment campaign. The diet gout trial was a randomized, controlled, cross-over trial that examined the effects of a dietary approaches to stop hypertension (DASH)–like diet on uric acid levels in adults with gout. We used four electronic medical record and four non-electronic medical record–based recruitment methods to identify and recruit potentially eligible participants. We calculated the response rate, screening visit completion rate, and randomization rate for each method. We also determined cost per response, the screening, and randomization for each method. Finally, we compared the demographic characteristics among individuals who completed the screening visit by recruitment method.Results:Of the 294 adults who responded to the recruitment campaign, 51% were identified from electronic medical record–based methods. Patient portal messaging, an electronic medical record–based method, resulted in the highest response rate (4%), screening visit completion rate (37%), and randomization rate (21%) among these eight methods. Electronic medical record–based methods ($60) were more cost-effective per response than non-electronic medical record–based methods ($107). Electronic-based methods, including patient portal messaging and Facebook, had the highest proportion of White individuals screened (52% and 60%). Direct mail to non-active patient portal increased enrollment of traditionally under-represented groups, including both women and African Americans.Conclusion:An electronic medical record–based recruitment strategy that utilized the electronic medical record for participant identification and postal mailing for participant outreach was cost-effective and increased participation of under-represented groups. This hybrid strategy represents a promising approach to improve the timely execution and broad generalizability of future clinical trials.
      Citation: Clinical Trials
      PubDate: 2020-09-16T06:14:52Z
      DOI: 10.1177/1740774520956969
       
  • Disparities in clinical trial participation and the influence of physician
           specialty
    • Authors: Jared Silberlust, Maritza M Suarez, Alberto J Caban-Martinez
      Abstract: Clinical Trials, Ahead of Print.

      Citation: Clinical Trials
      PubDate: 2020-09-14T07:54:22Z
      DOI: 10.1177/1740774520956578
       
  • Detecting participant noncompliance across multiple time points by
           modeling a longitudinal biomarker
    • Authors: Ross L Peterson, Joseph S Koopmeiners, Tracy T Smith, Sharon E Murphy, Eric C Donny, David M Vock
      Abstract: Clinical Trials, Ahead of Print.
      Introduction:Participant noncompliance, in which participants do not follow their assigned treatment protocol, has long complicated the interpretation of randomized clinical trials. No gold standard has been identified for detecting noncompliance, but in some trials participants’ biomarkers can provide objective information that suggests exposure to non-study treatments. However, existing methods are limited to retrospectively detecting noncompliance at a single time point based on a single biomarker measurement. We propose a novel method that can leverage participants’ full biomarker history to detect noncompliance across multiple time points. Conditional on longitudinal biomarker data, our method can estimate the probability of compliance at (1) a single time point of the trial, (2) all time points, and (3) a future time point.Methods:Across time points, we model the biomarker as a mixture density with (latent) components corresponding to longitudinal patterns of compliance. To estimate the mixture density, we fit mixed effects models for both compliance and the biomarker. We use the mixture density to derive compliance probabilities that condition on the longitudinal biomarker data. We evaluate our compliance probabilities by simulation and apply them to a trial in which current smokers were asked to only smoke low nicotine study cigarettes (Center for the Evaluation of Nicotine in Cigarettes Project 1 Study 2). In the simulation, we investigated three different effects of compliance on the biomarker, as well as the effect of misspecification of the covariance structures. We compared probability estimators (1) and (2) to those that ignore the longitudinal correlation in the data according to area under the receiver operating characteristic curve. We evaluated estimator (3) by plotting its calibration lines. For Center for the Evaluation of Nicotine in Cigarettes Project 1 Study 2, we compared estimators (1) and (3) to a probability estimator of compliance at the last time point that ignores the longitudinal correlation.Results:In the simulation, for both compliance at the last time point and at all time points, conditioning on the longitudinal biomarker data uniformly raised area under the receiver operating characteristic curve across all three compliance effect scenarios. The gains in area under the receiver operating characteristic curve were smaller under misspecification. The calibration lines for the prediction of compliance closely followed 45°, though with additional variability under misspecification. For compliance at the last time point of Center for the Evaluation of Nicotine in Cigarettes Project 1 Study 2, conditioning on participants’ full biomarker history boosted area under the receiver operating characteristic curve by three percentage points. The prediction probabilities somewhat accurately approximated the non-longitudinal compliance probabilities.Discussion:Compared to existing methods that only use a single biomarker measurement, our method can account for the longitudinal correlation in the biomarker and compliance to more accurately identify noncompliant participants. Our method can also use participants’ biomarker history to predict compliance at a future time point.
      Citation: Clinical Trials
      PubDate: 2020-09-14T07:53:45Z
      DOI: 10.1177/1740774520956949
       
  • Behavioral and social science research to support development of
           educational materials for clinical trials of broadly neutralizing
           antibodies for HIV treatment and prevention
    • Authors: Pablo K Valente, Yumeng Wu, Yehuda Z Cohen, Marina Caskey, Kathrine Meyers
      Abstract: Clinical Trials, Ahead of Print.
      Background/AimsEarly integration of behavioral and social sciences research into clinical trials can improve trial conduct and facilitate future implementation of biomedical interventions. We sought to examine participants’ experiences in clinical trials with broadly neutralizing antibodies and describe the development of educational materials for use in future broadly neutralizing antibody research.MethodsWe conducted semi-structured interviews with trial participants in phase 1 trials evaluating safety and efficacy of broadly neutralizing antibodies for HIV prevention and treatment and key informants (i.e. trial staff involved in broadly neutralizing antibody research). Semi-structured interviews were transcribed and analyzed thematically. Based on findings from the interviews, we developed educational materials addressing concerns and misconceptions identified among trial participants with input from community and research stakeholders. Educational materials were used in subsequent clinical trials with broadly neutralizing antibodies. We evaluated trial staff’s experiences with newly developed educational materials in follow-up key informant interviews.ResultsAlthough most participants were concerned about long-term harms related to the investigational product upon enrollment, absence of severe side effects in the trial led to an underestimation of risks related to the study during trial participation. Participants showed a poor understanding of what broadly neutralizing antibodies are and the differences between broadly neutralizing antibodies and other HIV prevention and treatment products, such as antiretrovirals. Many trial participants overestimated the possible public health impact of the broadly neutralizing antibody trials in which they were enrolled, associating broadly neutralizing antibody research with the development of vaccine or cure for HIV in the near future. Based on these concerns and misconceptions among trial participants, we developed a frequently asked questions document and adapted an existing educational video about broadly neutralizing antibodies. In follow-up interviews, key informants reported that materials helped address trial participants’ concerns and questions related to the trial. Key informants reported using the educational materials not only during informed consent but also throughout trial participation, which contributed to making informed consent an “ongoing” process.ConclusionIntegration of behavioral research into clinical trials with broadly neutralizing antibodies is key to identify and address key concerns among trial participants. Behavioral and social sciences research promotes communication between trial participants and biomedical researchers, facilitates engagement of participants and trial staff, and strengthens trial conduct. Development of educational materials collaboratively by behavioral and clinical scientists, trial staff, and community stakeholders is feasible and may help to address trial participants’ concerns and misconceptions. Future research should evaluate the impact of educational materials in recruitment and retention of trial participants.
      Citation: Clinical Trials
      PubDate: 2020-08-25T04:20:32Z
      DOI: 10.1177/1740774520948042
       
  • Non-inferiority trials using a surrogate marker as the primary endpoint:
           An increasing phenotype in cardiovascular trials
    • Authors: Behnood Bikdeli, César Caraballo, John Welsh, Joseph S Ross, Sanjay Kaul, Gregg W Stone, Harlan M Krumholz
      Abstract: Clinical Trials, Ahead of Print.
      Background/aimsNon-inferiority trials are increasing in cardiovascular medicine, with approval of many drugs and devices on the basis of such studies. Surrogate markers as primary endpoints have been also more frequently used for efficient assessment of cardiovascular interventions. However, there is uncertainty about their concordance with clinical outcomes. Non-inferiority design using a surrogate marker as a primary endpoint may pose particular challenges in clinical interpretation. We sought to explore the publication trends, methodology, and reporting features of non-inferiority cardiovascular trials that used a primary surrogate marker as the primary endpoint.MethodsWe searched six high-impact journals (The New England Journal of Medicine, The Journal of the American Medical Association, The Lancet, The Journal of the American College of Cardiology, Circulation, and European Heart Journal) from 1 January 1990 to 31 December 2018 and identified non-inferiority cardiovascular trials that used a surrogate marker as the primary endpoint. We assessed the non-inferiority margin reported in the manuscript and other publicly available platforms (e.g. protocol, clinicaltrials.gov). We also determined whether the included non-inferiority trials with surrogate markers as primary endpoints were followed by clinical outcome trials.ResultsWe screened 15,553 publications and identified 247 cardiovascular trials that used a non-inferiority design. Of these, 37 had a surrogate marker as a primary endpoint (18 drug trials, 13 device trials, 6 others). All of these non-inferiority trials with surrogate outcomes were published after 2000, mostly in cardiology journals (13 in The Journal of the American College of Cardiology, 9 in European Heart Journal, 8 in Circulation, 6 in The Lancet, 1 in The New England Journal of Medicine), and their publication rate increased over time (p 
      Citation: Clinical Trials
      PubDate: 2020-08-25T04:20:02Z
      DOI: 10.1177/1740774520949157
       
  • Intent-to-treat analysis of cluster randomized trials when clusters report
           unidentifiable outcome proportions
    • Authors: Stacia M DeSantis, Ruosha Li, Yefei Zhang, Xueying Wang, Sally W Vernon, Barbara C Tilley, Gary Koch
      Abstract: Clinical Trials, Ahead of Print.
      BackgroundCluster randomized trials are designed to evaluate interventions at the cluster or group level. When clusters are randomized but some clusters report no or non-analyzable data, intent-to-treat analysis, the gold standard for the analysis of randomized controlled trials, can be compromised. This article presents a very flexible statistical methodology for cluster randomized trials whose outcome is a cluster-level proportion (e.g. proportion from a cluster reporting an event) in the setting where clusters report non-analyzable data (which in general could be due to nonadherence, dropout, missingness, etc.). The approach is motivated by a previously published stratified randomized controlled trial called, “The Randomized Recruitment Intervention Trial (RECRUIT),” designed to examine the effectiveness of a trust-based continuous quality improvement intervention on increasing minority recruitment into clinical trials (ClinicalTrials.gov Identifier: NCT01911208).MethodsThe novel approach exploits the use of generalized estimating equations for cluster-level reports, such that all clusters randomized at baseline are able to be analyzed, and intervention effects are presented as risk ratios. Simulation studies under different outcome missingness scenarios and a variety of intra-cluster correlations are conducted. A comparative analysis of the method with imputation and per protocol approaches for RECRUIT is presented.ResultsSimulation results show the novel approach produces unbiased and efficient estimates of the intervention effect that maintain the nominal type I error rate. Application to RECRUIT shows similar effect sizes when compared to the imputation and per protocol approach.ConclusionThe article demonstrates that an innovative bivariate generalized estimating equations framework allows one to implement an intent-to-treat analysis to obtain risk ratios or odds ratios, for a variety of cluster randomized designs.
      Citation: Clinical Trials
      PubDate: 2020-08-25T04:19:44Z
      DOI: 10.1177/1740774520936668
       
  • Recruitment, retention, and adherence in a clinical trial: The Pediatric
           Heart Network’s Marfan Trial experience
    • Authors: Michelle S Hamstra, Victoria L Pemberton, Nicholas Dagincourt, Danielle Hollenbeck-Pringle, Felicia L Trachtenberg, James F Cnota, Andrew M Atz, Elizabeth Cappella, Sylvia De Nobele, Josephine Grima, Martha King, Rosalind Korsin, Linda M Lambert, Meghan K MacNeal, Larry W Markham, Gretchen MacCarrick, Donna M Sylvester, Patricia Walter, Mingfen Xu, Ronald V Lacro
      Abstract: Clinical Trials, Ahead of Print.
      Background/Aims:The Pediatric Heart Network Marfan Trial was a randomized trial comparing atenolol versus losartan on aortic root dilation in 608 children and young adults with Marfan syndrome. Barriers to enrollment included a limited pool of eligible participants, restrictive entry criteria, and a diverse age range that required pediatric and adult expertise. Retention was complicated by a 3-year commitment to a complex study and medication regimen. The Network partnered with the Marfan Foundation, bridging the community with the research. The aims of this study are to report protocol and medication adherence and associated predictive factors, and to describe recruitment and retention strategies.Methods:Recruitment, retention, and adherence to protocol activities related to the primary outcome were measured. Retention was measured by percentage of enrolled participants with 3-year outcome data. Protocol adherence was calculated by completion rates of study visits, ambulatory electrocardiography (Holter monitoring), and quarterly calls. Medication adherence was assessed by the number of tablets or the amount of liquid in bottles returned. Centers were ranked according to adherence (high, medium, and low tertiles). Recruitment, retention, and adherence questionnaires were completed by sites. Descriptive statistics summarized recruitment, retention, and adherence, as well as questionnaire results. Regression modeling assessed predictors of adherence.Results:Completion rates for visits, Holter monitors, and quarterly calls were 99%, 94%, and 96%, respectively. Primary outcome data at 3 years were obtained for 88% of participants. The mean percentage of medication taken was estimated at 89%. Site and age were associated with all measures of adherence. Young adult and African American participants had lower levels of adherence. Higher adherence sites employed more strategies; had more staffing resources, less key staff turnover, and more collaboration with referring providers; utilized the Foundation’s resources; and used a greater number of strategies to recruit, retain, and promote protocol and medication adherence.Conclusion:Overall adherence was excellent for this trial conducted within a National Institutes of Health–funded clinical trial network. Strategies specifically targeted to young adults and African Americans may have been beneficial. Many strategies employed by higher adherence sites are ones that any site could easily use, such as greeting families at non-study hospital visits, asking for family feedback, providing calendars for tracking schedules, and recommending apps for medication reminders. Additional key learnings include adherence differences by age, race, and site, the value of collaborative learning, and the importance of partnerships with patient advocacy groups. These lessons could shape recruitment, retention, and adherence to improve the quality of future complex trials involving rare conditions.
      Citation: Clinical Trials
      PubDate: 2020-08-21T12:00:12Z
      DOI: 10.1177/1740774520945988
       
  • User-centered design principles in the development of clinical research
           tools
    • Authors: Anita Walden, Lynsi Garvin, Michelle Smerek, Constance Johnson
      Abstract: Clinical Trials, Ahead of Print.
      Background:Increasing and sustaining the engagement of participants in clinical research studies is a goal for clinical investigators, especially for studies that require long-term or frequent involvement of participants. Technology can be used to reduce barriers to participation by providing multiple options for clinical data entry and form submission. However, electronic systems used in clinical research studies should be user-friendly while also ensuring data quality. Directly involving study participants in evaluating the effectiveness and usability of electronic tools may promote wider adoption, maintain involvement, and increase user satisfaction of the technology. While developers of healthcare applications have incorporated user-centered designs, these methods remain uncommon in the design of clinical study tools such as patient-reported outcome surveys or electronic data capture digital health tools.Methods:Our study evaluated whether the clinical research setting may benefit from implementing user-centered design principles. Study participants were recruited to test the web-based form for the Measurement to Understand the Reclassification of Disease of Cabarrus/Kannapolis (MURDOCK) Study Community Translational Population Health Registry and Biorepository that would enable them to complete their study forms electronically. The study enrollment form collects disease history, conditions, smoking status, medications, and other information. The system was initially evaluated by the data management team through traditional user-acceptance testing methods. During the tool evaluation phase, a decision was made to incorporate a small-scale usability study to directly test the system.Results:Results showed that a majority of participants found the system easy to use. Of the eight required tasks, 75% were completed successfully. Of the 72 heuristics violated, language was the most frequent violation.Conclusion:Our study showed that user-centered usability methods can identify important issues and capture information that can enhance the participant’s experience and may improve the quality of study tools.
      Citation: Clinical Trials
      PubDate: 2020-08-20T10:22:51Z
      DOI: 10.1177/1740774520946314
       
  • Exploring mechanisms of action in clinical trials of complex surgical
           interventions using mediation analysis
    • Authors: Linda Sharples, Olympia Papachristofi, Saleema Rex, Sabine Landau
      Abstract: Clinical Trials, Ahead of Print.
      Background:Surgical interventions allow for tailoring of treatment to individual patients and implementation may vary with surgeon and healthcare provider. In addition, in clinical trials assessing two competing surgical interventions, the treatments may be accompanied by co-interventions.Aims:This study explores the use of causal mediation analysis to (1) delineate the treatment effect that results directly from the surgical intervention under study and the indirect effect acting through a co-intervention and (2) to evaluate the benefit of the surgical intervention if either everybody in the trial population received the co-intervention or nobody received it.Methods:Within a counterfactual framework, relevant direct and indirect effects of a surgical intervention are estimated and adjusted for confounding via parametric regression models, for the situation where both mediator and outcome are binary, with baseline stratification factors included as fixed effects and surgeons as random intercepts. The causal difference in probability of a successful outcome (estimand of interest) is calculated using Monte Carlo simulation with bootstrapping for confidence intervals. Packages for estimation within standard statistical software are reviewed briefly. A step by step application of methods is illustrated using the Amaze randomised trial of ablation as an adjunct to cardiac surgery in patients with irregular heart rhythm, with a co-intervention (removal of the left atrial appendage) administered to a subset of participants at the surgeon’s discretion. The primary outcome was return to normal heart rhythm at one year post surgery.Results:In Amaze, 17% (95% confidence interval: 6%, 28%) more patients in the active arm had a successful outcome, but there was a large difference between active and control arms in the proportion of patients who received the co-intervention (55% and 30%, respectively). Causal mediation analysis suggested that around 1% of the treatment effect was attributable to the co-intervention (16% natural direct effect). The controlled direct effect ranged from 18% (6%, 30%) if the co-intervention were mandated, to 14% (2%, 25%) if it were prohibited. Including age as a moderator of the mediation effects showed that the natural direct effect of ablation appeared to decrease with age.Conclusions:Causal mediation analysis is a useful quantitative tool to explore mediating effects of co-interventions in surgical trials. In Amaze, investigators could be reassured that the effect of the active treatment, not explainable by differential use of the co-intervention, was significant across analyses.
      Citation: Clinical Trials
      PubDate: 2020-08-20T10:22:51Z
      DOI: 10.1177/1740774520947644
       
  • When and how to include vulnerable subjects in clinical trials
    • Authors: David Wendler
      Abstract: Clinical Trials, Ahead of Print.
      There has been a good deal of discussion in the literature regarding which subjects are vulnerable in the context of clinical trials. There has been significantly less discussion regarding when and how to include vulnerable subjects in clinical trials. This lack of guidance is a particular problem for trials covered by the US regulations, which mandate strict requirements on the inclusion of three groups: pregnant women/fetuses, prisoners, and children. For the past 30 years, funders, investigators, and institutional review boards have frequently responded to these regulations by excluding pregnant women/fetuses, prisoners, and children from clinical trials. More recent work has emphasized the extent to which a default of exclusion can undermine the value of clinical trials, especially pragmatic trials. A default of exclusion also has the potential to undermine the interests of vulnerable groups, in both the short and the long term. These concerns raise the need for guidance on how to satisfy existing US regulations, while minimizing their negative impact on the value of clinical trials and the interests of vulnerable groups. The present manuscript thus describes a six-step decision procedure that institutional review boards can use to determine when and how to include vulnerable subjects in clinical trials, including pragmatic trials, that are covered by US regulations.
      Citation: Clinical Trials
      PubDate: 2020-08-18T05:05:28Z
      DOI: 10.1177/1740774520945601
       
  • The DURATIONS randomised trial design: Estimation targets, analysis
           methods and operating characteristics
    • Authors: Matteo Quartagno, James R Carpenter, A Sarah Walker, Michelle Clements, Mahesh KB Parmar
      Abstract: Clinical Trials, Ahead of Print.
      Background:Designing trials to reduce treatment duration is important in several therapeutic areas, including tuberculosis and bacterial infections. We recently proposed a new randomised trial design to overcome some of the limitations of standard two-arm non-inferiority trials. This DURATIONS design involves randomising patients to a number of duration arms and modelling the so-called ‘duration-response curve’. This article investigates the operating characteristics (type-1 and type-2 errors) of different statistical methods of drawing inference from the estimated curve.Methods:Our first estimation target is the shortest duration non-inferior to the control (maximum) duration within a specific risk difference margin. We compare different methods of estimating this quantity, including using model confidence bands, the delta method and bootstrap. We then explore the generalisability of results to estimation targets which focus on absolute event rates, risk ratio and gradient of the curve.Results:We show through simulations that, in most scenarios and for most of the estimation targets, using the bootstrap to estimate variability around the target duration leads to good results for DURATIONS design-appropriate quantities analogous to power and type-1 error. Using model confidence bands is not recommended, while the delta method leads to inflated type-1 error in some scenarios, particularly when the optimal duration is very close to one of the randomised durations.Conclusions:Using the bootstrap to estimate the optimal duration in a DURATIONS design has good operating characteristics in a wide range of scenarios and can be used with confidence by researchers wishing to design a DURATIONS trial to reduce treatment duration. Uncertainty around several different targets can be estimated with this bootstrap approach.
      Citation: Clinical Trials
      PubDate: 2020-08-17T06:19:48Z
      DOI: 10.1177/1740774520944377
       
  • Addressing the quality of submissions to ClinicalTrials.gov for
           registration and results posting: The use of a checklist
    • Authors: Oswald Tetteh, Prince Nuamah, Anthony Keyes
      Abstract: Clinical Trials, Ahead of Print.
      Background:US Federal regulations since the late 1990s have required registration of some clinical trials and submission of results for some of these trials on a public registry, ClinicalTrials.gov. The quality of the submissions made to ClinicalTrials.gov determines the duration of the Quality Control review, whether the submission will pass the review (success), and how many review cycles it will take for a study to be posted. Success rate for all results submitted to ClinicalTrials.gov is less than 25%. To increase the success of investigators’ submissions and meet the requirements of registration and submission of results in a timely fashion, the Johns Hopkins ClinicalTrials.gov Program implemented a policy to review all studies for quality before submission. To standardize our review for quality, minimize inter-reviewer variability, and have a tool for training new staff, we developed a checklist.Methods:The Program staff learned from major comments received from ClinicalTrials.gov and also reviewed the Protocol Registration and Results System review criteria for registration and results to fully understand how to prepare studies to pass Quality Control review. These were summarized into bulleted points and incorporated into a checklist used by Program staff to review studies before submission.Results:In the period before the introduction of the checklist, 107 studies were submitted for registration with a 45% (48/107) success rate, a mean (SD) of 18.9 (26.72) days in review, and 1.74 (0.78) submission cycles. Results for 44 records were submitted with 11% (5/44) success rate, 115.80 (129.33) days in review, and 2.23 (0.68) submission cycles. In the period after the checklist, 104 studies were submitted for registration with 80% (83/104) success rate, 2.12 (3.85) days in review, and 1.22 (0.46) submission cycles. Results for 22 records were submitted with 41% (9/22) success rate, 39.27 (19.84) days in review, and 1.64 (0.58) submission cycles. Of the 44 results submitted prior to the checklist, 30 were Applicable or Probable Applicable Clinical Trials, with 10% (3/30) being posted within 30 days as required of the National Institutes of Health. For the 22 results submitted after the checklist, 17 were Applicable or Probable Applicable Clinical Trials, with 47% (8/17) being posted within 30 days of submission. These pre- and post-checklist differences were statistically significant improvements.Conclusion:The checklist has substantially improved our success rate and contributed to a reduction in the review days and number of review cycles. If Academic Medical Centers and industry will adopt or create a similar checklist to review their studies before submission, the quality of the submissions can be improved and the duration of review can be minimized.
      Citation: Clinical Trials
      PubDate: 2020-08-05T11:13:45Z
      DOI: 10.1177/1740774520942746
       
  • Retrospective collection of 90-day modified Rankin Scale is accurate
    • Authors: Mengxi Wang, Suja S Rajan, Asha P Jacob, Noopur Singh, Stephanie A Parker, Ritvij Bowry, James C Grotta, Jose-Miguel Yamal
      Abstract: Clinical Trials, Ahead of Print.
      Background:The 90-day modified Rankin Scale is a widely used outcome after stroke but is sometimes hard to ascertain due to loss to follow-up. Missing outcomes can result in biased and/or inefficient estimates in clinical trials. The aim of this study is to assess the validity of acquiring the 90-day modified Rankin Scale at a later point of time when the patient has been lost at 90 days to impute the missing value.Methods:Participants who had prospectively completed a 90-day modified Rankin Scale questionnaire on their own in the Benefits of Stroke Treatment Using a Mobile Stroke Unit study were randomly interviewed to recall the 90-day modified Rankin Scale at 6, 9, or 12 months after hospital discharge over the phone. Concordance between the two scores was assessed using kappa and weighted kappa statistics. Logistic regression was used to identify factors associated with inconsistent reporting of the 90-day modified Rankin Scale.Results:Substantial agreement was observed between in-the-moment and retrospective 90-day modified Rankin Scale recalled at 6, 9, or 12 months (weighted kappa = 0.93, 95% confidence interval: 0.89–0.98; weighted kappa = 0.93, 95% confidence interval: 0.85–1.00 and weighted kappa = 0.89, 95% confidence interval: 0.82–0.95, respectively).Conclusion:Retrospective recall of 90-day modified Rankin Scale at a later time point is a valid means to impute missing data in stroke clinical trials.
      Citation: Clinical Trials
      PubDate: 2020-08-05T11:12:06Z
      DOI: 10.1177/1740774520942466
       
  • Barriers to uptake of the hip fracture core outcome set: An international
           survey of 80 hip fracture trialists
    • Authors: Jessica Fletcher, Katie Jane Sheehan, Toby O Smith
      Abstract: Clinical Trials, Ahead of Print.
      Background:Core outcome sets are an agreed recommendation to inform the selection of outcome measures in clinical trials. There has been low uptake of the 2014 hip fracture core outcome set. The reasons for this remain unclear. The aim of this study was to understand the reasons for the non-adoption and approaches to increase adoption of the hip fracture core outcome set.Methods:Randomised controlled trials from PubMed (2017–2019) and ClinicalTrials.gov (2015–2019) were identified. Corresponding authors for each identified trial (n = 302) were surveyed using five questions on awareness of the hip fracture core outcome set, reasons for non-adoption and approaches to increase adoption. Data were analysed descriptively using frequencies, mean values and standard deviations.Results:Fifty-four percent of the respondents (n = 43) were aware of the concept of core outcome set. Only 15% (n = 12) based the outcome measure selection on the 2014 hip fracture core outcome set. Key reasons for non-adoption included the following: authors being unaware and perceived inappropriateness to their trial design. Eighty-six percent (n = 69) of respondents agreed to the need for increased awareness of core outcome sets through research training, academic and clinical journal requirements, and funding or publication stipulations. Eighty-eight percent (n = 70) of respondents indicated the current core outcome set required revision to focus on trials investigating people with cognitive impairment, caregivers, rehabilitation, surgical interventions and anaesthetic trial designs.Conclusion:Barriers to the adoption of the hip fracture core outcome set centre on education, awareness of the core outcome sets and applicability to the breath of hip fracture trial designs. Further consideration should be made to address these, to improve the harmonisation of outcome measures across hip fracture trials.
      Citation: Clinical Trials
      PubDate: 2020-07-17T06:46:51Z
      DOI: 10.1177/1740774520941444
       
  • Methodologies for pragmatic and efficient assessment of benefits and
           harms: Application to the SOCRATES trial
    • Authors: Scott R Evans, Mikael Knutsson, Pierre Amarenco, Gregory W Albers, Philip M Bath, Hans Denison, Per Ladenvall, Jenny Jonasson, J Donald Easton, Kazuo Minematsu, Carlos A Molina, Yongjun Wang, KS Lawrence Wong, S Claiborne Johnston
      Abstract: Clinical Trials, Ahead of Print.
      Background/Aims:Standard approaches to trial design and analyses can be inefficient and non-pragmatic. Failure to consider a range of outcomes impedes evidence-based interpretation and reduces power. Traditional approaches synthesizing information obtained from separate analysis of each outcome fail to incorporate associations between outcomes and recognize the cumulative nature of outcomes in individual patients, suffer from competing risk complexities during interpretation, and since efficacy and safety analyses are often conducted on different populations, generalizability is unclear. Pragmatic and efficient approaches to trial design and analyses are needed.Methods:Approaches providing a pragmatic assessment of benefits and harms of interventions, summarizing outcomes experienced by patients, and providing sample size efficiencies are described. Ordinal outcomes recognize finer gradations of patient responses. Desirability of outcome ranking is an ordinal outcome combining benefits and harms within patients. Analysis of desirability of outcome ranking can be based on rank-based methodologies including the desirability of outcome ranking probability, the win ratio, and the proportion in favor of treatment. Partial credit analyses, involving grading the levels of the desirability of outcome ranking outcome similar to an academic test, provides an alternative approach. The methodologies are demonstrated using the acute stroke or transient ischemic attack treated with aspirin or ticagrelor and patient outcomes study (SOCRATES; NCT01994720), a randomized clinical trial.Results:Two 5-level ordinal outcomes were developed for SOCRATES. The first was based on a modified Rankin scale. The odds ratio is 0.86 (95% confidence interval = 0.75, 0.99; p = 0.04) indicating that the odds of worse stroke categorization for a trial participant assigned to ticagrelor is 0.86 times that of a trial participant assigned to aspirin. The 5-level desirability of outcome ranking outcome incorporated and prioritized survival; the number of strokes, myocardial infarction, and major bleeding events; and whether a stroke event was disabling. The desirability of outcome ranking probability and win ratio are 0.504 (95% confidence interval = 0.499, 0.508; p = 0.10) and 1.11 (95% confidence interval = 0.98, 1.26; p = 0.10), respectively, implying that the probability of a more desirable result with ticagrelor is 50.4% and that a more desirable result occurs 1.11 times more frequently on ticagrelor versus aspirin.Conclusion:Ordinal outcomes can improve efficiency through required pre-specification, careful construction, and analyses. Greater pragmatism can be obtained by composing outcomes within patients. Desirability of outcome ranking provides a global assessment of the benefits and harms that more closely reflect the experience of patients. The desirability of outcome ranking probability, the proportion in favor of treatment, the win ratio, and partial credit can more optimally inform patient treatment, enhance the understanding of the totality of intervention effects on patients, and potentially provide efficiencies over standard analyses. The methods provide the infrastructure for incorporating patient values and estimating personalized effects.
      Citation: Clinical Trials
      PubDate: 2020-07-15T11:53:57Z
      DOI: 10.1177/1740774520941441
       
  • Recruiting breast cancer patients for mHealth research: Obstacles to
           clinic-based recruitment for a mobile phone app intervention study
    • Authors: Alisha Gupta, Gabrielle Ocker, Philip I Chow
      Abstract: Clinical Trials, Ahead of Print.
      BackgroundNearly half of newly diagnosed breast cancer patients will report clinically significant symptoms of depression and/or anxiety within the first year of diagnosis. Research on the trajectory of distress in cancer patients suggests that targeting patients early in the diagnostic pathway could be particularly impactful. Given the recent rise of smartphone adoption, apps are a convenient and accessible platform from which to deliver mental health support; however, little research has examined their potential impact among newly diagnosed cancer patients. One reason is likely due to the obstacles associated with in-clinic recruitment of newly diagnosed cancer patients for mHealth pilot studies.MethodsThis article draws from our experiences of a recently completed pilot study to test a suite of mental health apps in newly diagnosed breast cancer patients. Recruitment strategies included in-clinic pamphlets, flyers, and direct communication with clinicians. Surgical oncologists and research staff members approached eligible patients after a medical appointment. Research team members met with patients to provide informed consent and review the study schedule.ResultsFour domains of in-clinic recruitment challenges emerged: (a) coordination with clinic staff, (b) perceived burden among breast cancer patients, (c) limitations regarding the adoption and use of technology, and (d) availability of resources. Potential solutions are provided for each challenge.ConclusionRecruitment of newly diagnosed cancer patients is a major challenge to conducting mobile intervention studies for researchers on a pilot-study budget. To realize the impact of mobile interventions for the most vulnerable cancer patient populations, health researchers must address barriers to in-clinic recruitment to provide vital preliminary data in proposals of large-scale research projects.
      Citation: Clinical Trials
      PubDate: 2020-07-14T08:41:04Z
      DOI: 10.1177/1740774520939247
       
  • Formulary restrictions may impact enrollment in pragmatic trials and limit
           generalizability of findings to vulnerable populations
    • Authors: Jodi B Segal
      Abstract: Clinical Trials, Ahead of Print.

      Citation: Clinical Trials
      PubDate: 2020-07-11T06:00:30Z
      DOI: 10.1177/1740774520941257
       
  • Effectiveness of social media (Facebook), targeted mailing, and in-person
           solicitation for the recruitment of young adult in a diabetes
           self-management clinical trial
    • Authors: Sarah-Jeanne Salvy, Kristine Carandang, Cheryl LP Vigen, Alyssa Concha-Chavez, Paola A Sequeira, Jeanine Blanchard, Jesus Diaz, Jennifer Raymond, Elizabeth A Pyatak
      Abstract: Clinical Trials, Ahead of Print.
      Background/AimsResearch is needed to identify promising recruitment strategies to reach and engage diverse young adults in diabetes clinical research. The aim of this study was to examine the relative strengths and weaknesses of three recruitment strategies used in a diabetes self-management clinical trial: social media advertising (Facebook), targeted mailing, and in-person solicitation of clinic patients.MethodsStrategies were compared in terms of (1) cost-effectiveness (i.e. cost of recruitment/number of enrolled participants), (2) ability to yield participants who would not otherwise be reached by alternative strategies, and (3) likelihood of participants recruited through each strategy to adhere to study procedures. We further explored the appeal (overall and among age and gender subgroups) of social media advertisement features.ResultsIn-person recruitment of clinic patients was overall the most cost-effective strategy. However, differences in demographic, clinical, and psychosocial characteristics of participants recruited via different strategies suggest that the combination of these approaches yielded a more diverse sample than would any one strategy alone. Once successfully enrolled, there was no difference in study completion and intervention adherence between individuals recruited by the three recruitment strategies.ConclusionsUltimately, the utility of a recruitment strategy is defined by its ability to effectively attract people representative of the target population who are willing to enroll in and complete the study. Leveraging a variety of recruitment strategies appears to produce a more representative sample of young adults, including those who are less engaged in diabetes care.
      Citation: Clinical Trials
      PubDate: 2020-07-06T09:48:13Z
      DOI: 10.1177/1740774520933362
       
  • Editorial: Clinical trial design in the era of COVID-19
    • Authors: Colin B Begg, Mithat Gonen, Daniel F Heitjan
      First page: 465
      Abstract: Clinical Trials, Ahead of Print.

      Citation: Clinical Trials
      PubDate: 2020-07-11T06:00:09Z
      DOI: 10.1177/1740774520940230
       
  • Clinical trials in the time of a pandemic
    • Authors: Susan S Ellenberg
      First page: 467
      Abstract: Clinical Trials, Ahead of Print.
      The first rumblings about a new coronavirus spreading in China were heard in January 2020. By the end of that month, the World Health Organization, recognizing the severity of the disease and the potential for global spread, had declared a public health emergency. By February 2020, cases had been identified in multiple countries, clinical trials of treatments with some biological plausibility had begun in China, and the initial steps of vaccine development were underway. In mid-March, by which time countries around the world were experiencing rapidly increasing numbers of cases and deaths, the World Health Organization categorized the outbreak as a pandemic. This new coronavirus was designated SARS-COV-2 in recognition of its similarity to the coronavirus responsible for the severe acute respiratory syndrome outbreak in 2002–2003. The race is on to develop treatments that can mitigate the severe consequences of infection and vaccines that can prevent infection and/or diminish the severity of disease in those who do get infected. Many challenges face these development efforts. Some are similar to those faced in the past; others are new. The urgency of finding ways to treat, and ultimately prevent, the consequences of this new and potentially deadly infection has led to unprecedented focus on clinical trials.
      Citation: Clinical Trials
      PubDate: 2020-07-11T05:59:29Z
      DOI: 10.1177/1740774520939871
       
  • Endpoints for randomized controlled clinical trials for COVID-19
           treatments
    • Authors: Lori E Dodd, Dean Follmann, Jing Wang, Franz Koenig, Lisa L Korn, Christian Schoergenhofer, Michael Proschan, Sally Hunsberger, Tyler Bonnett, Mat Makowski, Drifa Belhadi, Yeming Wang, Bin Cao, France Mentre, Thomas Jaki
      First page: 472
      Abstract: Clinical Trials, Ahead of Print.
      Background:Endpoint choice for randomized controlled trials of treatments for novel coronavirus-induced disease (COVID-19) is complex. Trials must start rapidly to identify treatments that can be used as part of the outbreak response, in the midst of considerable uncertainty and limited information. COVID-19 presentation is heterogeneous, ranging from mild disease that improves within days to critical disease that can last weeks to over a month and can end in death. While improvement in mortality would provide unquestionable evidence about the clinical significance of a treatment, sample sizes for a study evaluating mortality are large and may be impractical, particularly given a multitude of putative therapies to evaluate. Furthermore, patient states in between “cure” and “death” represent meaningful distinctions. Clinical severity scores have been proposed as an alternative. However, the appropriate summary measure for severity scores has been the subject of debate, particularly given the variable time course of COVID-19. Outcomes measured at fixed time points, such as a comparison of severity scores between treatment and control at day 14, may risk missing the time of clinical benefit. An endpoint such as time to improvement (or recovery) avoids the timing problem. However, some have argued that power losses will result from reducing the ordinal scale to a binary state of “recovered” versus “not recovered.”Methods:We evaluate statistical power for possible trial endpoints for COVID-19 treatment trials using simulation models and data from two recent COVID-19 treatment trials.Results:Power for fixed time-point methods depends heavily on the time selected for evaluation. Time-to-event approaches have reasonable statistical power, even when compared with a fixed time-point method evaluated at the optimal time.Discussion:Time-to-event analysis methods have advantages in the COVID-19 setting, unless the optimal time for evaluating treatment effect is known in advance. Even when the optimal time is known, a time-to-event approach may increase power for interim analyses.
      Citation: Clinical Trials
      PubDate: 2020-07-17T06:43:30Z
      DOI: 10.1177/1740774520939938
       
  • Highly efficient clinical trial designs for reliable screening of
           under-performing treatments: Application to the COVID-19 Pandemic
    • Authors: Steven Piantadosi
      First page: 483
      Abstract: Clinical Trials, Ahead of Print.
      Background:The COVID-19 pandemic presents challenges for clinical trials including urgency, disrupted infrastructure, numerous therapeutic candidates, and the need for highly efficient trial and development designs. This paper presents design components and rationale for constructing highly efficient trials to screen potential COVID-19 treatments.Methods:Key trial design elements useful in this circumstance include futility hypotheses, treatment pooling, reciprocal controls, ranking and selection, and platform administration. Assuming most of the many candidates for COVID-19 treatment are likely to be ineffective, these components can be combined to facilitate very efficient comparisons of treatments.Results:Simulations indicate such designs can reliably discard underperforming treatments using sample size to treatment ratios under 30.Conclusions:Methods to create very efficient clinical trial comparisons of treatments for COVID-19 are available. Such designs might be helpful in the pandemic and should be considered for similar needs in the future.
      Citation: Clinical Trials
      PubDate: 2020-07-15T11:52:06Z
      DOI: 10.1177/1740774520940227
       
  • Anti-Thrombotic Therapy to Ameliorate Complications of COVID-19 (ATTACC):
           Study design and methodology for an international, adaptive Bayesian
           randomized controlled trial
    • Authors: Brett L Houston, Patrick R Lawler, Ewan C Goligher, Michael E Farkouh, Charlotte Bradbury, Marc Carrier, Vlad Dzavik, Dean A Fergusson, Robert A Fowler, Jean-Phillippe Galanaud, Peter L Gross, Emily G McDonald, Mansoor Husain, Susan R Kahn, Anand Kumar, John Marshall, Srinivas Murthy, Arthur S Slutsky, Alexis F Turgeon, Scott M Berry, Robert S Rosenson, Jorge Escobedo, Jose C Nicolau, Lindsay Bond, Bridget-Anne Kirwan, Sophie de Brouwer, Ryan Zarychanski
      First page: 491
      Abstract: Clinical Trials, Ahead of Print.
      Background:Mortality from COVID-19 is high among hospitalized patients and effective therapeutics are lacking. Hypercoagulability, thrombosis and hyperinflammation occur in COVID-19 and may contribute to severe complications. Therapeutic anticoagulation may improve clinical outcomes through anti-thrombotic, anti-inflammatory and anti-viral mechanisms. Our primary objective is to evaluate whether therapeutic-dose anticoagulation with low-molecular-weight heparin or unfractionated heparin prevents mechanical ventilation and/or death in patients hospitalized with COVID-19 compared to usual care.Methods:An international, open-label, adaptive randomized controlled trial. Using a Bayesian framework, the trial will declare results as soon as pre-specified posterior probabilities for superiority, futility, or harm are reached. The trial uses response-adaptive randomization to maximize the probability that patients will receive the more beneficial treatment approach, as treatment effect information accumulates within the trial. By leveraging a common data safety monitoring board and pooling data with a second similar international Bayesian adaptive trial (REMAP-COVID anticoagulation domain), treatment efficacy and safety will be evaluated as efficiently as possible. The primary outcome is an ordinal endpoint with three possible outcomes based on the worst status of each patient through day 30: no requirement for invasive mechanical ventilation, invasive mechanical ventilation or death.Conclusion:Using an adaptive trial design, the Anti-Thrombotic Therapy To Ameliorate Complications of COVID-19 trial will establish whether therapeutic anticoagulation can reduce mortality and/or avoid the need for mechanical ventilation in patients hospitalized with COVID-19. Leveraging existing networks to recruit sites will increase enrollment and mitigate enrollment risk in sites with declining COVID-19 cases.
      Citation: Clinical Trials
      PubDate: 2020-08-20T10:22:47Z
      DOI: 10.1177/1740774520943846
       
  • COVID-19 impact on multi-site recruitment and enrollment
    • Authors: Emma Strujo, Mechelle Sanders, Kevin Fiscella, Marie Thomas, Brent Johnson, Alex Deets, Claudia Sanchez Lucas, Tameir Holder, Nina Johal, Amneris Luque, Andrea Cassells, Stephen Williams, Jonathan N Tobin
      First page: 501
      Abstract: Clinical Trials, Ahead of Print.

      Citation: Clinical Trials
      PubDate: 2020-08-20T10:22:46Z
      DOI: 10.1177/1740774520946270
       
  • A concern about survival time as an endpoint in coronavirus disease 2019
           clinical trials
    • Authors: Kay See Tan
      First page: 505
      Abstract: Clinical Trials, Ahead of Print.

      Citation: Clinical Trials
      PubDate: 2020-08-20T10:22:23Z
      DOI: 10.1177/1740774520946026
       
  • Comparison of survival distributions in clinical trials: A practical
           guidance
    • Authors: Xiaotian Chen, Xin Wang, Kun Chen, Yeya Zheng, Richard J Chappell, Jyotirmoy Dey
      First page: 507
      Abstract: Clinical Trials, Ahead of Print.
      BackgroundIn randomized clinical trials with censored time-to-event outcomes, the logrank test is known to have substantial statistical power under the proportional hazards assumption and is widely adopted as a tool to compare two survival distributions. However, the proportional hazards assumption is impossible to validate in practice until the data are unblinded. However, the statistical analysis plan of a randomized clinical trial and in particular its primary analysis method must be pre-specified before any unblinded information may be reviewed.PurposeThe purpose of this article is to guide applied biostatisticians in the prespecification of a desired primary analysis method when a treatment effect with nonproportional hazards is anticipated. While articles proposing alternate statistical tests are aplenty, to the best of our knowledge, there is no article available that attempts to simplify the choice and prespecification of a primary statistical test under specific expected patterns on nonproportional hazards. We provide such guidance by reviewing various tests proposed as more powerful alternatives to the standard logrank test under nonproportional hazards and simultaneously comparing their performance under a wide variety of nonproportional hazards scenarios to elucidate their advantages and disadvantages.MethodIn order to select the most preferable test for detecting specific differences between survival distributions of interest while controlling false positive rates, we review and assess the performance of weighted and adaptively weighted logrank tests, weighted and adaptively weighted Kaplan–Meier tests and versatile tests under various patterns of nonproportional hazards treatment effects through simulation.ConclusionWe validate some of the claimed properties of the proposed extensions and identify tests that may be more preferable under specific expected pattern of nonproportional hazards when such knowledge is available. We show that versatile tests, while achieving robustness to departures from proportional hazards, may lose interpretation of directionality (superiority or inferiority) and can only be seen to test departures from equality. Detailed summary and discussion of the performance of each test in terms of type I error rate and power are provided to formulate specific guidance about their applicability and use.
      Citation: Clinical Trials
      PubDate: 2020-06-27T08:32:07Z
      DOI: 10.1177/1740774520928614
       
  • A comparison of phase I dose-finding designs in clinical trials with
           monotonicity assumption violation
    • Authors: Rachid Abbas, Caroline Rossoni, Thomas Jaki, Xavier Paoletti, Pavel Mozgunov
      First page: 522
      Abstract: Clinical Trials, Ahead of Print.
      Background/AimsIn oncology, new combined treatments make it difficult to order dose levels according to monotonically increasing toxicity. New flexible dose-finding designs that take into account uncertainty in dose levels ordering were compared with classical designs through simulations in the setting of the monotonicity assumption violation. We give recommendations for the choice of dose-finding design.MethodsMotivated by a clinical trial for patients with high-risk neuroblastoma, we considered designs that require a monotonicity assumption, the Bayesian Continual Reassessment Method, the modified Toxicity Probability Interval, the Bayesian Optimal Interval design, and designs that relax monotonicity assumption, the Bayesian Partial Ordering Continual Reassessment Method and the No Monotonicity Assumption design. We considered 15 scenarios including monotonic and non-monotonic dose–toxicity relationships among six dose levels.ResultsThe No Monotonicity Assumption and Partial Ordering Continual Reassessment Method designs were robust to the violation of the monotonicity assumption. Under non-monotonic scenarios, the No Monotonicity Assumption design selected the correct dose level more often than alternative methods on average. Under the majority of monotonic scenarios, the Partial Ordering Continual Reassessment Method selected the correct dose level more often than the No Monotonicity Assumption design. Other designs were impacted by the violation of the monotonicity assumption with a proportion of correct selections below 20% in most scenarios. Under monotonic scenarios, the highest proportions of correct selections were achieved using the Continual Reassessment Method and the Bayesian Optimal Interval design (between 52.8% and 73.1%). The costs of relaxing the monotonicity assumption by the No Monotonicity Assumption design and Partial Ordering Continual Reassessment Method were decreases in the proportions of correct selections under monotonic scenarios ranging from 5.3% to 20.7% and from 1.4% to 16.1%, respectively, compared with the best performing design and were higher proportions of patients allocated to toxic dose levels during the trial.ConclusionsInnovative oncology treatments may no longer follow monotonic dose levels ordering which makes standard phase I methods fail. In such a setting, appropriate designs, as the No Monotonicity Assumption or Partial Ordering Continual Reassessment Method designs, should be used to safely determine recommended for phase II dose.
      Citation: Clinical Trials
      PubDate: 2020-07-07T08:34:54Z
      DOI: 10.1177/1740774520932130
       
  • Strengthening the interpretability of clinical trial results by assessing
           the effect of informative censoring on the primary estimand in PRECISION
    • Authors: Weihang Bao, Michael Gaffney, Milton L Pressler, Rana Fayyad, Wayne Wisemandle, Bruce Beckerman, Katherine E Wolski, Steven E Nissen
      First page: 535
      Abstract: Clinical Trials, Ahead of Print.
      Background:The ICH E9(R1) addendum states that the strategy to account for intercurrent events should be included when defining an estimand, the treatment effect to be estimated based on the study objective. The estimator used to assess the treatment effect needs to be aligned with the estimand that accounted for intercurrent events. Regardless of the strategy, missing data resulting from patient premature withdrawal could undermine the robustness of the study results. Informative censoring due to dropouts in an events-based study is one such example. Sensitivity analyses using imputation methods are useful to examine the uncertainty due to informative censoring and address the robustness and strength of the study results.Methods:We assessed the effect of premature patient withdrawal in the PRECISION study, a randomized non-inferiority clinical trial of patients with chronic arthritic pain that compared the cardiovascular safety of three nonsteroidal anti-inflammatory drugs–based treatment policies or paradigms. The protocol-defined use of concomitant or rescue medications was permitted since changes in pain medications due to insufficient analgesia were expected in patients in this long-term study. Anticipating that premature study discontinuations could potentially lead to informative censoring, a supplementary analysis was pre-specified in which censored outcomes due to the premature study discontinuation were imputed based on adverse events that were clinically associated with the primary endpoint (cardiovascular outcome based on the Antiplatelet Trialists Collaboration composite endpoint). Furthermore, tipping point analyses were conducted to test the robustness of the primary analysis results by assuming data censored not at random. The level of increase at which the primary study conclusion would change was estimated.Results:For the analysis of time to first primary endpoint event through 30 months, 4065 out of the 24,081 enrolled patients were lost to follow-up, withdrew consent, or were no longer willing to participate in the study. These withdrawals occurred gradually and resulted in a cumulative total of 5893 censored patient-years of observation (10.2%). The rate of discontinuation and the baseline characteristics of the discontinued patients were similar across the three treatment groups. The non-inferiority conclusion from the primary analysis was confirmed in the supplementary analysis incorporating relevant adverse events. Furthermore, tipping point analyses demonstrated that in order to lose non-inferiority in the primary analysis, the risk of primary endpoint events during the censored observation time would have to increase by more than 2.7-fold in the celecoxib group while remaining constant in the other nonsteroidal anti-inflammatory drugs groups, demonstrating that the scenarios where the study results are invalid appear not plausible.Conclusions:Supplementary and sensitivity analyses presented to address informative censoring in PRECISION helped to further interpret and strengthen the study results.
      Citation: Clinical Trials
      PubDate: 2020-07-09T12:57:02Z
      DOI: 10.1177/1740774520934747
       
  • Double-blinding of an acupuncture randomized controlled trial optimized
           with clinical translational science award resources
    • Authors: Alana D Steffen, Larisa A Burke, Heather A Pauls, Marie L Suarez, Yingwei Yao, William H Kobak, Miho Takayama, Hiroyoshi Yajima, Ted J Kaptchuk, Nobuari Takakura, Diana J Wilkie, Judith M Schlaeger
      First page: 545
      Abstract: Clinical Trials, Ahead of Print.
      BackgroundClinical trial articles often lack detailed descriptions of the methods used to randomize participants, conceal allocation, and blind subjects and investigators to group assignment. We describe our systematic approach to implement and measure blinding success in a double-blind phase 2 randomized controlled trial testing the efficacy of acupuncture for the treatment of vulvodynia.MethodsRandomization stratified by vulvodynia subtype is managed by Research Electronic Data Capture software’s randomization module adapted to achieve complete masking of group allocation. Subject and acupuncturist blinding assessments are conducted multiple times to identify possible correlates of unblinding.ResultsAt present, 48 subjects have been randomized and completed the protocol resulting in 87 subject and 206 acupuncturist blinding assessments.DiscussionOur approach to blinding and blinding assessment has the potential to improve our understanding of unblinding over time in the presence of possible clinical improvement.
      Citation: Clinical Trials
      PubDate: 2020-07-11T05:57:12Z
      DOI: 10.1177/1740774520934910
       
  • Protocol adherence rates in superiority and noninferiority randomized
           clinical trials published in high impact medical journals
    • Authors: Nicolas A Bamat, Osayame A Ekhaguere, Lingqiao Zhang, Dustin D Flannery, Sara C Handley, Heidi M Herrick, Susan S Ellenberg
      First page: 552
      Abstract: Clinical Trials, Ahead of Print.
      Background/aims:Noninferiority clinical trials are susceptible to false confirmation of noninferiority when the intention-to-treat principle is applied in the setting of incomplete trial protocol adherence. The risk increases as protocol adherence rates decrease. The objective of this study was to compare protocol adherence and hypothesis confirmation between superiority and noninferiority randomized clinical trials published in three high impact medical journals. We hypothesized that noninferiority trials have lower protocol adherence and greater hypothesis confirmation.Methods:We conducted an observational study using published clinical trial data. We searched PubMed for active control, two-arm parallel group randomized clinical trials published in JAMA: The Journal of the American Medical Association, The New England Journal of Medicine, and The Lancet between 2007 and 2017. The primary exposure was trial type, superiority versus noninferiority, as determined by the hypothesis testing framework of the primary trial outcome. The primary outcome was trial protocol adherence rate, defined as the number of randomized subjects receiving the allocated intervention as described by the trial protocol and followed to primary outcome ascertainment (numerator), over the total number of subjects randomized (denominator). Hypothesis confirmation was defined as affirmation of noninferiority or the alternative hypothesis for noninferiority and superiority trials, respectively.Results:Among 120 superiority and 120 noninferiority trials, median and interquartile protocol adherence rates were 91.5 [81.4–96.7] and 89.8 [83.6–95.2], respectively; P = 0.47. Hypothesis confirmation was observed in 107/120 (89.2%) of noninferiority and 64/120 (53.3%) of superiority trials, risk difference (95% confidence interval): 35.8 (25.3–46.3), P < 0.001.Conclusion:Protocol adherence rates are similar between superiority and noninferiority trials published in three high impact medical journals. Despite this, we observed greater hypothesis confirmation among noninferiority trials. We speculate that publication bias, lenient noninferiority margins and other sources of bias may contribute to this finding. Further study is needed to identify the reasons for this observed difference.
      Citation: Clinical Trials
      PubDate: 2020-07-15T11:53:37Z
      DOI: 10.1177/1740774520941428
       
  • Commentary on Bamat et al.
    • Authors: Everardo D Saad, Marc Buyse
      First page: 560
      Abstract: Clinical Trials, Ahead of Print.

      Citation: Clinical Trials
      PubDate: 2020-07-15T11:54:24Z
      DOI: 10.1177/1740774520941442
       
  • Non-adjustment for multiple testing in multi-arm trials of distinct
           treatments: Rationale and justification
    • Authors: Richard A Parker, Christopher J Weir
      First page: 562
      Abstract: Clinical Trials, Ahead of Print.
      There is currently a lack of consensus and uncertainty about whether one should adjust for multiple testing in multi-arm trials of distinct treatments. A detailed rationale is presented to justify non-adjustment in this situation. We argue that non-adjustment should be the default starting position in simple multi-arm trials of distinct treatments.
      Citation: Clinical Trials
      PubDate: 2020-07-15T11:52:44Z
      DOI: 10.1177/1740774520941419
       
  • Commentary on Parker and Weir
    • Authors: Frank Bretz, Franz Koenig
      First page: 567
      Abstract: Clinical Trials, Ahead of Print.

      Citation: Clinical Trials
      PubDate: 2020-07-15T11:53:04Z
      DOI: 10.1177/1740774520941420
       
  • Adjusting for adherence in randomized trials when adherence is measured as
           a continuous variable: An application to the Lipid Research Clinics
           Coronary Primary Prevention Trial
    • Authors: Kerollos Nashat Wanis, Arin L Madenci, Miguel A Hernán, Eleanor J Murray
      First page: 570
      Abstract: Clinical Trials, Ahead of Print.
      Background:Clinicians and patients may be more interested in per-protocol effect estimates than intention-to-treat effect estimates from randomized trials. However, per-protocol effect estimates may be biased due to insufficient adjustment for prognostic factors that predict adherence. Adjustment for this bias is possible when appropriate methods, such as inverse probability weighting, are used. But, when adherence is measured as a continuous variable, constructing these weights can be challenging.Methods:In the placebo arm of the Lipid Research Clinics Coronary Primary Prevention Trial, we estimated the 7-year cumulative incidence of coronary heart disease under 100% adherence and 0% adherence to placebo. We used dose-response discrete-hazards models with inverse probability weighting to adjust for pre- and post-randomization covariates. We considered several continuous distributions for constructing the inverse probability weights.Results:The risk difference estimate for 100% adherence compared with 0% adherence ranged from −7.7 to −6.1 percentage points without adjustment for baseline and post-baseline covariates, and ranged from −1.8 to 2.2 percentage points with adjustment using inverse probability weights, depending on the dose-response model and inverse probability weight distribution used.Conclusions:Methods which appropriately adjust for time-varying post-randomization variables can explain away much of the bias in the “effect” of adherence to placebo. When considering continuous adherence, investigators should consider several models as estimates may be sensitive to the model chosen.
      Citation: Clinical Trials
      PubDate: 2020-05-16T06:21:52Z
      DOI: 10.1177/1740774520920893
       
  • Cost-benefit of outcome adjudication in nine randomised stroke trials
    • Authors: Peter J Godolphin, Philip M Bath, Ale Algra, Eivind Berge, John Chalmers, Misha Eliasziw, Graeme J Hankey, Naohisa Hosomi, Annamarei Ranta, Christian Weimar, Lisa J Woodhouse, Alan A Montgomery
      First page: 576
      Abstract: Clinical Trials, Ahead of Print.
      BackgroundCentral adjudication of outcomes is common for randomised trials and should control for differential misclassification. However, few studies have estimated the cost of the adjudication process.MethodsWe estimated the cost of adjudicating the primary outcome in nine randomised stroke trials (25,436 participants). The costs included adjudicators’ time, direct payments to adjudicators, and co-ordinating centre costs (e.g. uploading cranial scans and general set-up costs). The number of events corrected after adjudication was our measure of benefit. We calculated cost per corrected event for each trial and in total.ResultsThe primary outcome in all nine trials was either stroke or a composite that included stroke. In total, the adjudication process associated with this primary outcome cost in excess of £100,000 for a third of the trials (3/9). Mean cost per event corrected by adjudication was £2295.10 (SD: £1482.42).ConclusionsCentral adjudication is a time-consuming and potentially costly process. These costs need to be considered when designing a trial and should be evaluated alongside the potential benefits adjudication brings to determine whether they outweigh this expense.
      Citation: Clinical Trials
      PubDate: 2020-07-11T05:57:29Z
      DOI: 10.1177/1740774520939231
       
  • Mindfulness, Education, and Exercise for age-related cognitive decline:
           Study protocol, pilot study results, and description of the baseline
           sample
    • Authors: Julie Loebach Wetherell, Hayley S Ripperger, Michelle Voegtle, Beau M Ances, David Balota, Emily S Bower, Colin Depp, Lisa Eyler, Erin R Foster, Denise Head, Tamara Hershey, Steven Hickman, Noralinda Kamantigue, Samuel Klein, J Philip Miller, Michael D Yingling, Jeanne Nichols, Ginger E Nicol, Bruce W Patterson, Thomas L Rodebaugh, Joshua S Shimony, Abraham Snyder, Mary Stephens, Susan Tate, Mary L Uhrich, David Wing, Gregory F Wu, Eric J Lenze
      First page: 581
      Abstract: Clinical Trials, Ahead of Print.
      Background/AimsAge-related cognitive decline is a pervasive problem in our aging population. To date, no pharmacological treatments to halt or reverse cognitive decline are available. Behavioral interventions, such as physical exercise and Mindfulness-Based Stress Reduction, may reduce or reverse cognitive decline, but rigorously designed randomized controlled trials are needed to test the efficacy of such interventions.MethodsHere, we describe the design of the Mindfulness, Education, and Exercise study, an 18-month randomized controlled trial that will assess the effect of two interventions—mindfulness training plus moderate-to-vigorous intensity exercise or moderate-to-vigorous intensity exercise alone—compared with a health education control group on cognitive function in older adults. An extensive battery of biobehavioral assessments will be used to understand the mechanisms of cognitive remediation, by using structural and resting state functional magnetic resonance imaging, insulin sensitivity, inflammation, and metabolic and behavioral assessments.ResultsWe provide the results from a preliminary study (n = 29) of non-randomized pilot participants who received both the exercise and Mindfulness-Based Stress Reduction interventions. We also provide details on the recruitment and baseline characteristics of the randomized controlled trial sample (n = 585).ConclusionWhen complete, the Mindfulness, Education, and Exercise study will inform the research community on the efficacy of these widely available interventions improve cognitive functioning in older adults.
      Citation: Clinical Trials
      PubDate: 2020-06-27T08:32:08Z
      DOI: 10.1177/1740774520931864
       
 
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