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Showing 1 - 200 of 1085 Journals sorted alphabetically
AADE in Practice     Hybrid Journal   (Followers: 6)
Abstracts in Anthropology     Full-text available via subscription   (Followers: 21)
Academic Pathology     Open Access   (Followers: 5)
Accounting History     Hybrid Journal   (Followers: 17, SJR: 0.527, CiteScore: 1)
Acta Radiologica     Hybrid Journal   (Followers: 2, SJR: 0.754, CiteScore: 2)
Acta Radiologica Open     Open Access   (Followers: 3)
Acta Sociologica     Hybrid Journal   (Followers: 37, SJR: 0.939, CiteScore: 2)
Action Research     Hybrid Journal   (Followers: 49, SJR: 0.308, CiteScore: 1)
Active Learning in Higher Education     Hybrid Journal   (Followers: 345, SJR: 1.397, CiteScore: 2)
Adaptive Behavior     Hybrid Journal   (Followers: 9, SJR: 0.288, CiteScore: 1)
Administration & Society     Hybrid Journal   (Followers: 14, SJR: 0.675, CiteScore: 1)
Adoption & Fostering     Hybrid Journal   (Followers: 23, SJR: 0.313, CiteScore: 0)
Adsorption Science & Technology     Open Access   (Followers: 7, SJR: 0.258, CiteScore: 1)
Adult Education Quarterly     Hybrid Journal   (Followers: 214, SJR: 0.566, CiteScore: 2)
Adult Learning     Hybrid Journal   (Followers: 41)
Advances in Dental Research     Hybrid Journal   (Followers: 7, SJR: 1.791, CiteScore: 4)
Advances in Developing Human Resources     Hybrid Journal   (Followers: 30, SJR: 0.614, CiteScore: 2)
Advances in Mechanical Engineering     Open Access   (Followers: 134, SJR: 0.272, CiteScore: 1)
Advances in Methods and Practices in Psychological Science     Full-text available via subscription   (Followers: 10)
Advances in Structural Engineering     Full-text available via subscription   (Followers: 45, SJR: 0.599, CiteScore: 1)
Advances in Tumor Virology     Open Access   (Followers: 3, SJR: 0.108, CiteScore: 0)
AERA Open     Open Access   (Followers: 10)
Affilia     Hybrid Journal   (Followers: 4, SJR: 0.496, CiteScore: 1)
Agrarian South : J. of Political Economy     Hybrid Journal   (Followers: 2)
Air, Soil & Water Research     Open Access   (Followers: 13, SJR: 0.214, CiteScore: 1)
Alexandria : The J. of National and Intl. Library and Information Issues     Full-text available via subscription   (Followers: 64)
AlterNative : An Intl. J. of Indigenous Peoples     Full-text available via subscription   (Followers: 13, SJR: 0.194, CiteScore: 0)
Alternative Law J.     Hybrid Journal   (Followers: 10, SJR: 0.176, CiteScore: 0)
Alternatives : Global, Local, Political     Hybrid Journal   (Followers: 12, SJR: 0.351, CiteScore: 1)
American Behavioral Scientist     Hybrid Journal   (Followers: 22, SJR: 0.982, CiteScore: 2)
American Economist     Hybrid Journal   (Followers: 7)
American Educational Research J.     Hybrid Journal   (Followers: 207, SJR: 2.913, CiteScore: 3)
American J. of Alzheimer's Disease and Other Dementias     Hybrid Journal   (Followers: 18, SJR: 0.67, CiteScore: 2)
American J. of Cosmetic Surgery     Hybrid Journal   (Followers: 6)
American J. of Evaluation     Hybrid Journal   (Followers: 16, SJR: 0.646, CiteScore: 2)
American J. of Health Promotion     Hybrid Journal   (Followers: 32, SJR: 0.807, CiteScore: 1)
American J. of Hospice and Palliative Medicine     Hybrid Journal   (Followers: 41, SJR: 0.65, CiteScore: 1)
American J. of Law & Medicine     Full-text available via subscription   (Followers: 11, SJR: 0.204, CiteScore: 1)
American J. of Lifestyle Medicine     Hybrid Journal   (Followers: 5, SJR: 0.431, CiteScore: 1)
American J. of Medical Quality     Hybrid Journal   (Followers: 11, SJR: 0.777, CiteScore: 1)
American J. of Men's Health     Open Access   (Followers: 8, SJR: 0.595, CiteScore: 2)
American J. of Rhinology and Allergy     Hybrid Journal   (Followers: 9, SJR: 0.972, CiteScore: 2)
American J. of Sports Medicine     Hybrid Journal   (Followers: 193, SJR: 3.949, CiteScore: 6)
American Politics Research     Hybrid Journal   (Followers: 33, SJR: 1.313, CiteScore: 1)
American Review of Public Administration     Hybrid Journal   (Followers: 19, SJR: 2.062, CiteScore: 2)
American Sociological Review     Hybrid Journal   (Followers: 307, SJR: 6.333, CiteScore: 6)
American String Teacher     Full-text available via subscription   (Followers: 2)
Analytical Chemistry Insights     Open Access   (Followers: 25, SJR: 0.224, CiteScore: 1)
Angiology     Hybrid Journal   (Followers: 3, SJR: 0.849, CiteScore: 2)
Animation     Hybrid Journal   (Followers: 13, SJR: 0.197, CiteScore: 0)
Annals of Clinical Biochemistry     Hybrid Journal   (Followers: 10, SJR: 0.634, CiteScore: 1)
Annals of Otology, Rhinology & Laryngology     Hybrid Journal   (Followers: 15, SJR: 0.807, CiteScore: 1)
Annals of Pharmacotherapy     Hybrid Journal   (Followers: 52, SJR: 1.096, CiteScore: 2)
Annals of the American Academy of Political and Social Science     Hybrid Journal   (Followers: 46, SJR: 1.225, CiteScore: 3)
Annals of the ICRP     Hybrid Journal   (Followers: 4, SJR: 0.548, CiteScore: 1)
Anthropocene Review     Hybrid Journal   (Followers: 9, SJR: 3.341, CiteScore: 7)
Anthropological Theory     Hybrid Journal   (Followers: 42, SJR: 0.739, CiteScore: 1)
Antitrust Bulletin     Hybrid Journal   (Followers: 11)
Antiviral Chemistry and Chemotherapy     Open Access   (Followers: 2, SJR: 0.635, CiteScore: 2)
Antyajaa : Indian J. of Women and Social Change     Hybrid Journal  
Applied Biosafety     Hybrid Journal   (SJR: 0.131, CiteScore: 0)
Applied Psychological Measurement     Hybrid Journal   (Followers: 23, SJR: 1.17, CiteScore: 1)
Applied Spectroscopy     Full-text available via subscription   (Followers: 26, SJR: 0.489, CiteScore: 2)
Armed Forces & Society     Hybrid Journal   (Followers: 19, SJR: 0.29, CiteScore: 1)
Arts and Humanities in Higher Education     Hybrid Journal   (Followers: 42, SJR: 0.305, CiteScore: 1)
Asia Pacific Media Educator     Hybrid Journal   (Followers: 1, SJR: 0.23, CiteScore: 0)
Asia-Pacific J. of Management Research and Innovation     Full-text available via subscription   (Followers: 3)
Asia-Pacific J. of Public Health     Hybrid Journal   (Followers: 9, SJR: 0.558, CiteScore: 1)
Asian and Pacific Migration J.     Full-text available via subscription   (Followers: 105, SJR: 0.324, CiteScore: 1)
Asian Cardiovascular and Thoracic Annals     Hybrid Journal   (Followers: 2, SJR: 0.305, CiteScore: 0)
Asian J. of Comparative Politics     Hybrid Journal   (Followers: 4)
Asian J. of Legal Education     Full-text available via subscription   (Followers: 4)
Asian J. of Management Cases     Hybrid Journal   (Followers: 6, SJR: 0.101, CiteScore: 0)
ASN Neuro     Open Access   (Followers: 2, SJR: 1.534, CiteScore: 3)
Assessment     Hybrid Journal   (Followers: 17, SJR: 1.519, CiteScore: 3)
Assessment for Effective Intervention     Hybrid Journal   (Followers: 15, SJR: 0.578, CiteScore: 1)
Australasian Psychiatry     Hybrid Journal   (Followers: 9, SJR: 0.433, CiteScore: 1)
Australian & New Zealand J. of Psychiatry     Hybrid Journal   (Followers: 20, SJR: 1.801, CiteScore: 2)
Australian and New Zealand J. of Criminology     Hybrid Journal   (Followers: 523, SJR: 0.612, CiteScore: 1)
Australian J. of Career Development     Hybrid Journal   (Followers: 4)
Australian J. of Education     Hybrid Journal   (Followers: 42, SJR: 0.403, CiteScore: 1)
Australian J. of Management     Hybrid Journal   (Followers: 13, SJR: 0.497, CiteScore: 1)
Autism     Hybrid Journal   (Followers: 325, SJR: 1.739, CiteScore: 4)
Autism & Developmental Language Impairments     Open Access   (Followers: 11)
Behavior Modification     Hybrid Journal   (Followers: 12, SJR: 0.877, CiteScore: 2)
Behavioral and Cognitive Neuroscience Reviews     Hybrid Journal   (Followers: 26)
Bible Translator     Hybrid Journal   (Followers: 12)
Biblical Theology Bulletin     Hybrid Journal   (Followers: 18, SJR: 0.184, CiteScore: 0)
Big Data & Society     Open Access   (Followers: 48)
Biochemistry Insights     Open Access   (Followers: 7)
Bioinformatics and Biology Insights     Open Access   (Followers: 12, SJR: 1.141, CiteScore: 2)
Biological Research for Nursing     Hybrid Journal   (Followers: 7, SJR: 0.685, CiteScore: 2)
Biomarker Insights     Open Access   (Followers: 1, SJR: 0.81, CiteScore: 2)
Biomarkers in Cancer     Open Access   (Followers: 10)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 12)
Biomedical Informatics Insights     Open Access   (Followers: 8)
Bioscope: South Asian Screen Studies     Hybrid Journal   (Followers: 3, SJR: 0.235, CiteScore: 0)
BMS: Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique     Hybrid Journal   (Followers: 4, SJR: 0.226, CiteScore: 0)
Body & Society     Hybrid Journal   (Followers: 25, SJR: 1.531, CiteScore: 3)
Bone and Tissue Regeneration Insights     Open Access   (Followers: 2)
Brain and Neuroscience Advances     Open Access  
Breast Cancer : Basic and Clinical Research     Open Access   (Followers: 9, SJR: 0.823, CiteScore: 2)
British J. of Music Therapy     Hybrid Journal   (Followers: 8)
British J. of Occupational Therapy     Hybrid Journal   (Followers: 195, SJR: 0.323, CiteScore: 1)
British J. of Pain     Hybrid Journal   (Followers: 25, SJR: 0.579, CiteScore: 2)
British J. of Politics and Intl. Relations     Hybrid Journal   (Followers: 32, SJR: 0.91, CiteScore: 2)
British J. of Visual Impairment     Hybrid Journal   (Followers: 13, SJR: 0.337, CiteScore: 1)
British J.ism Review     Hybrid Journal   (Followers: 17)
Building Acoustics     Hybrid Journal   (Followers: 4, SJR: 0.215, CiteScore: 1)
Building Services Engineering Research & Technology     Hybrid Journal   (Followers: 3, SJR: 0.583, CiteScore: 1)
Bulletin of Science, Technology & Society     Hybrid Journal   (Followers: 7)
Business & Society     Hybrid Journal   (Followers: 12)
Business and Professional Communication Quarterly     Hybrid Journal   (Followers: 8, SJR: 0.348, CiteScore: 1)
Business Information Review     Hybrid Journal   (Followers: 16, SJR: 0.279, CiteScore: 0)
Business Perspectives and Research     Hybrid Journal   (Followers: 3)
Cahiers Élisabéthains     Hybrid Journal   (Followers: 1, SJR: 0.111, CiteScore: 0)
Calcutta Statistical Association Bulletin     Full-text available via subscription   (Followers: 1)
California Management Review     Hybrid Journal   (Followers: 30, SJR: 2.209, CiteScore: 4)
Canadian J. of Kidney Health and Disease     Open Access   (Followers: 6, SJR: 1.007, CiteScore: 2)
Canadian J. of Nursing Research (CJNR)     Hybrid Journal   (Followers: 13)
Canadian J. of Occupational Therapy     Hybrid Journal   (Followers: 134, SJR: 0.626, CiteScore: 1)
Canadian J. of Psychiatry     Hybrid Journal   (Followers: 28, SJR: 1.769, CiteScore: 3)
Canadian J. of School Psychology     Hybrid Journal   (Followers: 11, SJR: 0.266, CiteScore: 1)
Canadian Pharmacists J. / Revue des Pharmaciens du Canada     Hybrid Journal   (Followers: 3, SJR: 0.536, CiteScore: 1)
Cancer Control     Open Access   (Followers: 1)
Cancer Growth and Metastasis     Open Access   (Followers: 1)
Cancer Informatics     Open Access   (Followers: 4, SJR: 0.64, CiteScore: 1)
Capital and Class     Hybrid Journal   (Followers: 7, SJR: 0.282, CiteScore: 1)
Cardiac Cath Lab Director     Full-text available via subscription  
Cardiovascular and Thoracic Open     Open Access  
Career Development and Transition for Exceptional Individuals     Hybrid Journal   (Followers: 8, SJR: 0.44, CiteScore: 1)
Cartilage     Hybrid Journal   (Followers: 5, SJR: 0.889, CiteScore: 3)
Cell and Tissue Transplantation and Therapy     Open Access   (Followers: 2)
Cell Transplantation     Open Access   (Followers: 4, SJR: 1.023, CiteScore: 3)
Cephalalgia     Hybrid Journal   (Followers: 7, SJR: 1.581, CiteScore: 3)
Child Language Teaching and Therapy     Hybrid Journal   (Followers: 31, SJR: 0.501, CiteScore: 1)
Child Maltreatment     Hybrid Journal   (Followers: 9, SJR: 1.22, CiteScore: 3)
Child Neurology Open     Open Access   (Followers: 6)
Childhood     Hybrid Journal   (Followers: 18, SJR: 0.894, CiteScore: 2)
Childhood Obesity and Nutrition     Open Access   (Followers: 11)
China Information     Hybrid Journal   (Followers: 7, SJR: 0.767, CiteScore: 2)
China Report     Hybrid Journal   (Followers: 10, SJR: 0.221, CiteScore: 0)
Chinese J. of Sociology     Full-text available via subscription   (Followers: 4)
Christianity & Literature     Full-text available via subscription   (Followers: 8)
Chronic Illness     Hybrid Journal   (Followers: 6, SJR: 0.672, CiteScore: 2)
Chronic Respiratory Disease     Hybrid Journal   (Followers: 9, SJR: 0.808, CiteScore: 2)
Chronic Stress     Open Access  
Citizenship, Social and Economics Education     Full-text available via subscription   (Followers: 6, SJR: 0.145, CiteScore: 0)
Cleft Palate-Craniofacial J.     Hybrid Journal   (Followers: 7, SJR: 0.757, CiteScore: 1)
Clin-Alert     Hybrid Journal   (Followers: 1)
Clinical and Applied Thrombosis/Hemostasis     Open Access   (Followers: 16, SJR: 0.49, CiteScore: 1)
Clinical and Translational Neuroscience     Open Access  
Clinical Case Studies     Hybrid Journal   (Followers: 3, SJR: 0.364, CiteScore: 1)
Clinical Child Psychology and Psychiatry     Hybrid Journal   (Followers: 45, SJR: 0.73, CiteScore: 2)
Clinical EEG and Neuroscience     Hybrid Journal   (Followers: 6, SJR: 0.552, CiteScore: 2)
Clinical Ethics     Hybrid Journal   (Followers: 10, SJR: 0.296, CiteScore: 1)
Clinical Medicine Insights : Arthritis and Musculoskeletal Disorders     Open Access   (Followers: 3, SJR: 0.537, CiteScore: 2)
Clinical Medicine Insights : Blood Disorders     Open Access   (SJR: 0.314, CiteScore: 2)
Clinical Medicine Insights : Cardiology     Open Access   (Followers: 6, SJR: 0.686, CiteScore: 2)
Clinical Medicine Insights : Case Reports     Open Access   (Followers: 1, SJR: 0.283, CiteScore: 1)
Clinical Medicine Insights : Circulatory, Respiratory and Pulmonary Medicine     Open Access   (Followers: 3, SJR: 0.425, CiteScore: 2)
Clinical Medicine Insights : Ear, Nose and Throat     Open Access   (Followers: 1)
Clinical Medicine Insights : Endocrinology and Diabetes     Open Access   (Followers: 32, SJR: 0.63, CiteScore: 2)
Clinical Medicine Insights : Oncology     Open Access   (Followers: 3, SJR: 1.129, CiteScore: 3)
Clinical Medicine Insights : Pediatrics     Open Access   (Followers: 3)
Clinical Medicine Insights : Psychiatry     Open Access   (Followers: 9)
Clinical Medicine Insights : Reproductive Health     Open Access   (Followers: 2, SJR: 0.776, CiteScore: 0)
Clinical Medicine Insights : Therapeutics     Open Access   (Followers: 1, SJR: 0.172, CiteScore: 0)
Clinical Medicine Insights : Trauma and Intensive Medicine     Open Access   (Followers: 4)
Clinical Medicine Insights : Urology     Open Access   (Followers: 2)
Clinical Medicine Insights : Women's Health     Open Access   (Followers: 4)
Clinical Nursing Research     Hybrid Journal   (Followers: 29, SJR: 0.471, CiteScore: 1)
Clinical Pathology     Open Access   (Followers: 3)
Clinical Pediatrics     Hybrid Journal   (Followers: 22, SJR: 0.487, CiteScore: 1)
Clinical Psychological Science     Hybrid Journal   (Followers: 11, SJR: 3.281, CiteScore: 5)
Clinical Rehabilitation     Hybrid Journal   (Followers: 70, SJR: 1.322, CiteScore: 3)
Clinical Risk     Hybrid Journal   (Followers: 5, SJR: 0.133, CiteScore: 0)
Clinical Trials     Hybrid Journal   (Followers: 22, SJR: 2.399, CiteScore: 2)
Clothing and Textiles Research J.     Hybrid Journal   (Followers: 24, SJR: 0.36, CiteScore: 1)
Common Law World Review     Full-text available via subscription   (Followers: 18)
Communication & Sport     Hybrid Journal   (Followers: 8, SJR: 0.385, CiteScore: 1)
Communication and the Public     Hybrid Journal   (Followers: 1)
Communication Disorders Quarterly     Hybrid Journal   (Followers: 15, SJR: 0.458, CiteScore: 1)
Communication Research     Hybrid Journal   (Followers: 20, SJR: 2.171, CiteScore: 3)
Community College Review     Hybrid Journal   (Followers: 9, SJR: 1.451, CiteScore: 1)
Comparative Political Studies     Hybrid Journal   (Followers: 226, SJR: 3.772, CiteScore: 3)
Compensation & Benefits Review     Hybrid Journal   (Followers: 8)
Competition & Change     Hybrid Journal   (Followers: 11, SJR: 0.843, CiteScore: 2)
Competition and Regulation in Network Industries     Full-text available via subscription   (Followers: 8, SJR: 0.143, CiteScore: 0)
Concurrent Engineering     Hybrid Journal   (Followers: 3, SJR: 0.642, CiteScore: 2)
Conflict Management and Peace Science     Hybrid Journal   (Followers: 35, SJR: 2.441, CiteScore: 1)
Contemporary Drug Problems     Full-text available via subscription   (Followers: 3, SJR: 0.609, CiteScore: 2)
Contemporary Education Dialogue     Hybrid Journal   (Followers: 5, SJR: 0.102, CiteScore: 0)
Contemporary Issues in Early Childhood     Full-text available via subscription   (Followers: 6, SJR: 0.766, CiteScore: 1)
Contemporary Review of the Middle East     Full-text available via subscription   (Followers: 12)
Contemporary Sociology : A J. of Reviews     Full-text available via subscription   (Followers: 34, SJR: 0.195, CiteScore: 0)
Contemporary Voice of Dalit     Full-text available via subscription   (Followers: 1)
Contexts     Hybrid Journal   (Followers: 6)
Contributions to Indian Sociology     Hybrid Journal   (Followers: 4, SJR: 0.376, CiteScore: 0)
Convergence The Intl. J. of Research into New Media Technologies     Hybrid Journal   (Followers: 50, SJR: 0.521, CiteScore: 1)

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Similar Journals
Journal Cover
Clinical Trials
Journal Prestige (SJR): 2.399
Citation Impact (citeScore): 2
Number of Followers: 22  
Hybrid Journal Hybrid journal   * Containing 1 Open Access Open Access article(s) in this issue *
ISSN (Print) 1740-7745 - ISSN (Online) 1740-7753
Published by Sage Publications Homepage  [1084 journals]
  • Editorial
    • Authors: Colin B Begg
      Pages: 446 - 446
      Abstract: Clinical Trials, Volume 16, Issue 5, Page 446-446, October 2019.

      Citation: Clinical Trials
      PubDate: 2019-09-12T07:09:28Z
      DOI: 10.1177/1740774519871520
  • Prevalence and significance of race and ethnicity subgroup analyses in
           Cochrane intervention reviews
    • Authors: Patrick Liu, Joseph S Ross, John PA Ioannidis, Sanket S Dhruva, Vasilis Vasiliou, Joshua D Wallach
      Abstract: Clinical Trials, Ahead of Print.

      Citation: Clinical Trials
      PubDate: 2019-11-11T07:19:23Z
      DOI: 10.1177/1740774519887148
  • Nonparticipation reasons in a randomized international trial of a new
           latent tuberculosis infection regimen
    • Authors: Kimberley N Chapman Hedges, Andrey S Borisov, Jussi J Saukkonen, Nigel A Scott, Emily J Hecker, Lorna Bozeman, Carol Dukes Hamilton, Amy Kerrigan, Patricia Bessler, Antonio Moreno-Martinez, Bert Arevalo, Stefan V Goldberg
      Abstract: Clinical Trials, Ahead of Print.
      Background/aimsEfficient recruitment of eligible participants, optimizing time and sample size, is a crucial component in conducting a successful clinical trial. Inefficient participant recruitment can impede study progress, consume staff time and resources, and limit quality and generalizability or the power to assess outcomes. Recruitment for disease prevention trials poses additional challenges because patients are asymptomatic. We evaluated candidates for a disease prevention trial to determine reasons for nonparticipation and to identify factors that can be addressed to improve recruitment efficiency.MethodsDuring 2001–2009, the Tuberculosis Trials Consortium conducted Study 26 (PREVENT TB), a randomized clinical trial at 26 sites in four countries, among persons with latent tuberculosis infection at high risk for tuberculosis disease progression, comparing 3 months of directly observed once-weekly rifapentine plus isoniazid with 9 months of self-administered daily isoniazid. During March 2005–February 2008, non-identifying demographic information, risk factors for experiencing active tuberculosis disease, and reasons for not enrolling were collected from screened patients to facilitate interpretation of trial data, to meet Consolidated Standards of Reporting Trials standards, and to evaluate reasons for nonparticipation.ResultsOf the 7452 candidates screened in Brazil, Canada, Spain, and the United States, 3584 (48%) were not enrolled, because of ineligibility (41%), site decision (10%), or patient choice (49%). Among those who did not enroll by own choice, and for whom responses were recorded on whether they would accept treatment outside of the study (n = 1430), 68% reported that they planned to accept non-study latent tuberculosis infection treatment. Among 1305 patients with one or more reported reasons for nonparticipation, study staff recorded a total of 1886 individual reasons (reason count: median = 1/patient; range = 1–9) for why patients chose not to enroll, including grouped concerns about research (24% of 1886), work or school conflicts (20%), medication or health beliefs (16%), latent tuberculosis infection beliefs (11%), and patient lifestyle and family concerns (10%).ConclusionEducational efforts addressing clinical research concerns and beliefs about medication and health, as well as study protocols that accommodate patient-related concerns (e.g. work, school, and lifestyle) might increase willingness to enter clinical trials. Findings from this evaluation can support development of communication and education materials for clinical trial sites at the beginning of a trial to allow study staff to address potential participant concerns during study screening.
      Citation: Clinical Trials
      PubDate: 2019-11-06T09:57:44Z
      DOI: 10.1177/1740774519885380
  • A third trial oversight committee: Functions, benefits and issues
    • Authors: J Athene Lane, Carrol Gamble, William J Cragg, Doreen Tembo, Matthew R Sydes
      Abstract: Clinical Trials, Ahead of Print.
      Background/aims:Clinical trial oversight is central to the safety of participants and production of robust data. The United Kingdom Medical Research Council originally set out an oversight structure comprising three committees in 1998. The first committee, led by the trial team, is hands-on with trial conduct/operations (‘Trial Management Group’) and essential. The second committee (Data Monitoring Committee), usually completely independent of the trial, reviews accumulating trial evidence and is used by most later phase trials. The Independent Data Monitoring Committee makes recommendations to the third oversight committee. The third committee, (‘Trial Steering Committee’), facilitates in-depth interactions of independent and non-independent trial members and gives broader oversight (blinded to comparative analysis). We investigated the roles and functioning of the third oversight committee with multiple research methods. We reflect upon these findings to standardise the committee’s remit and operation and to potentially increase its usage.Methods:We utilised findings from our recent published suite of research on the third oversight committee to inform guideline revision. In brief, we conducted a survey of 38 United Kingdom–registered Clinical Trials Units, reviewed a cohort of 264 published trials, observed 8 third oversight committee meetings and interviewed 52 trialists. We convened an expert panel to discuss third oversight committees. Subsequently, we interviewed nine patient/lay third committee members and eight committee Chairs.Results:In the survey, most Clinical Trials Units required a third committee for all their trials (27/38, 71%) with independent members (ranging from 1 to 6). In the survey and interviews, the independence of the third committee was valued to make unbiased consideration of Independent Data Monitoring Committee recommendations and to advise on trial progress, protocol changes and recruitment issues in conjunction with the trial leadership. The third committee also advised funders and sponsors about trial continuation and represented patients and the public by including lay members. Of the cohort of 264 published trials, 144 reported a ‘steering’ committee (55%), but the independence of these members was not described so these may have been internal Trial Management Groups. Around two thirds of papers (60%) reported having an Independent Data Monitoring Committee and 26.9% neither a steering nor an Independent Data Monitoring Committee. However, before revising the third committee charter (Terms of Reference), greater standardisation is needed around defining member independence, composition, primacy of decision-making, interactions with other committees and the lifespan.Conclusion:A third oversight committee has benefits for trial oversight and conduct, and a revised charter will facilitate greater standardisation and wider adoption.
      Citation: Clinical Trials
      PubDate: 2019-10-31T06:05:55Z
      DOI: 10.1177/1740774519881619
  • Commentary on Engen et al: Risk-based, dynamic, process-oriented
           monitoring strategies and their burden
    • Authors: Marnie Bertolet, Maria Mori Brooks, Jeffrey L Carson
      Abstract: Clinical Trials, Ahead of Print.

      Citation: Clinical Trials
      PubDate: 2019-10-24T12:50:31Z
      DOI: 10.1177/1740774519881617
  • A randomized evaluation of on-site monitoring nested in a multinational
           randomized trial
    • Authors: Nicole Wyman Engen, Kathy Huppler Hullsiek, Waldo H Belloso, Elizabeth Finley, Fleur Hudson, Eileen Denning, Catherine Carey, Mary Pearson, Jonathan Kagan
      Abstract: Clinical Trials, Ahead of Print.
      Background:Evidence from prospectively designed studies to guide on-site monitoring practices for randomized trials is limited. A cluster randomized study, nested within the Strategic Timing of AntiRetroviral Treatment (START) trial, was conducted to evaluate on-site monitoring.Methods:Sites were randomized to either annual on-site monitoring or no on-site monitoring. All sites were centrally monitored, and local monitoring was carried out twice each year. Randomization was stratified by country and projected enrollment in START. The primary outcome was a participant-level composite outcome including components for eligibility errors, consent violations, use of antiretroviral treatment not recommended by protocol, late reporting of START primary and secondary clinical endpoints (defined as the event being reported more than 6 months from occurrence), and data alteration and fraud. Logistic regression fixed effect hierarchical models were used to compare on-site versus no on-site monitoring for the primary composite outcome and its components. Odds ratios and 95% confidence intervals comparing on-site monitoring versus no on-site monitoring are cited.Results:In total, 99 sites (2107 participants) were randomized to receive annual on-site monitoring and 97 sites (2264 participants) were randomized to be monitored only centrally and locally. The two monitoring groups were well balanced at entry. In the on-site monitoring group, 469 annual on-site monitoring visits were conducted, and 134 participants (6.4%) in 56 of 99 sites (57%) had a primary monitoring outcome. In the no on-site monitoring group, 85 participants (3.8%) in 34 of 97 sites (35%) had a primary monitoring outcome (odds ratio = 1.7; 95% confidence interval: 1.1–2.7; p = 0.03). Informed consent violations accounted for most outcomes in each group (56 vs 41 participants). The largest odds ratio was for eligibility violations (odds ratio = 12.2; 95% confidence interval: 1.8–85.2; p = 0.01). The number of participants with a late START primary endpoint was similar for each monitoring group (23 vs 16 participants). Late START grade 4 and unscheduled hospitalization events were found for 34 participants in the on-site monitoring group and 19 participants in the no on-site monitoring group (odds ratio = 2.0; 95% confidence interval: 1.1–3.7; p = 0.02). There were no cases of data alteration or fraud. Based on the travel budget for on-site monitoring and the hours spent conducting on-site monitoring, the estimated cost of on-site monitoring was over US$2 million.Conclusion:On-site monitoring led to the identification of more eligibility and consent violations and START clinical events being reported more than 6 months from occurrence as compared to no on-site monitoring. Considering the nature of the excess monitoring outcomes identified at sites receiving on-site monitoring, as well as the cost of on-site monitoring, the value to the START study was limited.
      Citation: Clinical Trials
      PubDate: 2019-10-24T12:50:11Z
      DOI: 10.1177/1740774519881616
  • Closed testing of each group versus the others combined in a multiple
           group analysis
    • Authors: John M Lachin, Ionut Bebu
      Abstract: Clinical Trials, Ahead of Print.
      Background:Many studies, such as a study of comparative effectiveness, entail a comparison of the beneficial and adverse effects of multiple K[math] 2 competing therapies. Often, the analysis consists of a comparison of the K groups using an omnibus (T2-like) test for any difference among the groups followed by pairwise comparisons with adjustments for multiple tests.Methods:We evaluate the properties of an analysis strategy in which each group is compared to the average of the others in hopes of establishing the overall superiority (or harm) of at least one of the therapies. Testing of one-versus-others can be accomplished for virtually any model using simple tests, and the type I error probability [math] can be controlled by conducting such tests under the closed testing principle. Testing using linear models, the family of generalized linear models, and Cox proportional hazards models is described with examples.Results:Since each tested hypothesis compares one treatment to the average of the others, the K-level null hypothesis in the tree of closed testing is equivalent to any of the (K−1)-level tests, thus reducing the number of tests required. This applies to linear, generalized linear, and Cox proportional hazards models. While the Bonferroni, Holm, and Hommel procedures preserve the desired level [math], all are conservative relative to closed one-versus-others testing and closed testing in general provides greater power.Conclusion:Testing each of the multiple treatments versus the average of the others is readily and efficiently conducted under the closed testing principle and may be especially useful in the assessment of studies of comparative effectiveness.
      Citation: Clinical Trials
      PubDate: 2019-10-24T12:49:08Z
      DOI: 10.1177/1740774519879932
  • Informal professionalization of healthy participants in phase I clinical
           trials in Russia

         This is an Open Access Article Open Access Article

    • Authors: Olga Zvonareva, Igor Pimenov, Natalia Kutishenko, Igor Mareev, Sergey Martsevich, Evgeny Kulikov
      Abstract: Clinical Trials, Ahead of Print.
      Background:Previous social science research has shown how some healthy phase I trial participants identify themselves as workers and rely on trials as a major source of income. The term “professionalization” has been used to denote this phenomenon.Purpose:We aim to examine a component of healthy trial participants’ professionalization that has not yet been systematically studied: how repeat phase I trial participants develop and claim expertise that distinguishes them from others and makes them uniquely positioned to perform high-quality clinical trial labor. We also aim to explain the significance of these research results for protection of healthy participants in phase I trials.Methods:This qualitative exploratory study was conducted in Russia, in two phase I trial units. It involved semi-structured interviews with 28 healthy trial participants with varying lengths of experience in trials, observations of work done in trial units, and interpretive conversations with investigative staff.Results:Interviewed healthy individuals who repeatedly participate in phase I trials describe developing knowledge and skills that involve appreciating the meaning of trial procedures, coming up with techniques to efficiently follow them, organizing themselves and others in the course of a trial, and sharing tacit ways of doing trial work well with other less experienced participants. Our results suggest that a prerequisite for such expertise-centered professionalization is the emergence of a positive identity linked to seeing value in trial participation work. A crucial component of professionalization thus understood is the development of a work ethic that entails caring about results and being reliable partners for investigators.Limitations:The attitudes and behaviors presented in this article are not suggested to be universally shared among healthy trial participants, but rather represent a particular instance of professionalization that coexists with other views and tactics.Conclusions:A way of better protecting healthy trial participants begins with recognizing their skills, knowledge, and the centrality of the contribution they are making to pharmaceutical research. Currently, the expertise of experienced trial participants is recognized on the work floor only; therefore, the professionalization we described is informal. Yet, the informal professionalization process is inherently risky as it does not involve any change in the formal conditions of trial participants’ work. Instituting formal measures for protecting healthy trial participants as skilled workers combined with recognition of their expertise is essential.
      Citation: Clinical Trials
      PubDate: 2019-10-24T12:48:50Z
      DOI: 10.1177/1740774519877851
  • Comparison of methods for control allocation in multiple arm studies using
           response adaptive randomization
    • Authors: Kert Viele, Kristine Broglio, Anna McGlothlin, Benjamin R. Saville
      Abstract: Clinical Trials, Ahead of Print.
      Background/Aims:Response adaptive randomization has many polarizing properties in two-arm settings comparing control to a single treatment. The generalization of these features to the multiple arm setting has been less explored, and existing comparisons in the literature reach disparate conclusions. We investigate several generalizations of two-arm response adaptive randomization methods relating to control allocation in multiple arm trials, exploring how critiques of response adaptive randomization generalize to the multiple arm setting.Methods:We perform a simulation study to investigate multiple control allocation schemes within response adaptive randomization, comparing the designs on metrics such as power, arm selection, mean square error, and the treatment of patients within the trial.Results:The results indicate that the generalization of two-arm response adaptive randomization concerns is variable and depends on the form of control allocation employed. The concerns are amplified when control allocation may be reduced over the course of the trial but are mitigated in the methods considered when control allocation is maintained or increased during the trial. In our chosen example, we find minimal advantage to increasing, as opposed to maintaining, control allocation; however, this result reflects an extremely limited exploration of methods for increasing control allocation.Conclusion:Selection of control allocation in multiple arm response adaptive randomization has a large effect on the performance of the design. Some disparate comparisons of response adaptive randomization to alternative paradigms may be partially explained by these results. In future comparisons, control allocation for multiple arm response adaptive randomization should be chosen to keep in mind the appropriate match between control allocation in response adaptive randomization and the metric or metrics of interest.
      Citation: Clinical Trials
      PubDate: 2019-10-19T12:19:54Z
      DOI: 10.1177/1740774519877836
  • Commentary on Zvonareva et al.: Exploring the many meanings of
           “professional” in research participation
    • Authors: Jill A Fisher
      Abstract: Clinical Trials, Ahead of Print.

      Citation: Clinical Trials
      PubDate: 2019-10-05T10:06:51Z
      DOI: 10.1177/1740774519877850
  • Comparison between protocols and publications for prognostic and
           predictive cancer biomarker studies
    • Authors: Adelaide Doussau, Esther Vinarov, Brianna Barsanti-Innes, Jonathan Kimmelman
      Abstract: Clinical Trials, Ahead of Print.
      Background:Method prespecification in study protocols is important for controlling bias in reports. The primary goal of this study was to assess potential for discordance between study protocols and publications reporting predictive or prognostic cancer biomarker research. Secondary objectives included comparing characteristics of publications with accessible protocols compared to those without.Methods:Publications reporting predictive or prognostic cancer biomarker research were identified from 15 major journals, 2012–2015. Protocols were sought online or through repeated queries of corresponding authors. The following four items were extracted: (1) biomarkers, (2) biospecimen/assays, (3) sample size, (4) endpoints. We defined “explicit discordance” as the presence of major inconsistencies on these items.Results:Of 149 eligible publications, we obtained 19 eligible protocols online (13%). Out of a random sample of 103 publications where protocols were not available online, 12 protocols (12%) were furnished by corresponding authors; 8 (8% of authors) explicitly stated the absence of a protocol. Among 24 retrospective cohort studies, no protocol could be accessed. We found explicit discordance between publications and protocols for 18 studies (58%), in particular choice of biomarkers (36%), biospecimen/assays (6%), or endpoints (29%).Conclusion:Protocols are generally not accessible or not used for cancer biomarker studies. Publications were often explicitly discordant with protocols, particularly regarding biomarkers and endpoints. Our findings point to common unaddressed risk of bias in publications of major journals reporting the relationship between cancer biomarkers and clinical endpoints.
      Citation: Clinical Trials
      PubDate: 2019-10-05T10:04:52Z
      DOI: 10.1177/1740774519876912
  • Rejoinder
    • Authors: Lingyun Ji, Lisa M McShane, Mark Krailo, Richard Sposto
      Abstract: Clinical Trials, Ahead of Print.

      Citation: Clinical Trials
      PubDate: 2019-10-04T06:35:42Z
      DOI: 10.1177/1740774519875971
  • Bias in retrospective analyses of biomarker effect using data from an
           outcome-adaptive randomized trial
    • Authors: Lingyun Ji, Lisa M McShane, Mark Krailo, Richard Sposto
      Abstract: Clinical Trials, Ahead of Print.
      Background/AimsBiomarker-stratified outcome-adaptive randomization trials, in which randomization probabilities depend on both biomarker value and outcomes of previously treated patients, are receiving increased attention in oncology research. Data from these trials can also form the basis of investigation of additional biomarkers that may not have been incorporated into the original trial design. In this article, we investigate the validity of a standard analytical method that utilizes data from a biomarker-stratified outcome-adaptive randomization trial to assess the effect of a newly identified biomarker on patient outcomes.MethodsIn the context of an ancillary biomarker study for a two-arm phase II trial with a response endpoint, we conduct analytic and simulation studies to investigate bias in estimated biomarker effects under outcome-adaptive randomization. Conditions under which bias arises and magnitude of the bias are examined in several settings. We then propose unbiased estimators of biomarker effects with appropriate variance estimators.ResultsWe demonstrate that use of biomarker-stratified outcome-adaptive randomization perturbs the patient population and treatment assignments. Consequently, application of standard analysis methods to data from an outcome-adaptive randomization trial either to estimate prognostic effect of a new biomarker in uniformly treated patients or to estimate effect of treatment in relation to the new biomarker can lead to substantially biased estimates. The proposed adjusted estimators are asymptotically unbiased, and the proposed variance estimators correctly reflect the sample variability in the estimators.ConclusionThis article demonstrates existence of bias when standard, naïve statistical methods are utilized to assess biomarker effects using data from a biomarker-stratified outcome-adaptive randomization trial, and hence that results from naïve analyses must be interpreted with great caution. These findings highlight that, in an era where data and specimens are increasingly being shared for biomarker studies, care must be taken to document and understand implications of the study design under which specimens or data have been obtained.
      Citation: Clinical Trials
      PubDate: 2019-10-04T06:34:42Z
      DOI: 10.1177/1740774519875969
  • Recruitment of trial participants through electronic medical record
           patient portal messaging: A pilot study
    • Authors: Timothy B Plante, Kelly T Gleason, Hailey N Miller, Jeanne Charleston, Kristen McArthur, Cheryl Dennison Himmelfarb, Mariana Lazo, Daniel E Ford, Edgar R Miller, Lawrence J Appel, Stephen P Juraschek
      Abstract: Clinical Trials, Ahead of Print.
      Background/aim:Cost-efficient methods are essential for successful participant recruitment in clinical trials. Patient portal messages are an emerging means of recruiting potentially eligible patients into trials. We assessed the response rate and complaint rate from direct-to-patient, targeted recruitment through patient portals of an electronic medical record for a clinical trial, and compared response rates by differences in message content.Methods:The Study to Understand Fall Reduction and Vitamin D in You (STURDY) trial is a National Institutes of Health–sponsored, community-based study of vitamin D supplementation for fall prevention in older adults conducted at Johns Hopkins. Potential participants were identified using the Epic electronic medical record at the Johns Hopkins Health System based on age (≥70 years), ZIP code (30-mile radius of study site), and prior activation of a patient portal account. We prepared a shorter message and a longer message. Both had basic information about study participation, but the longer message also contained information about the significance of the study and a personal invitation from the STURDY principal investigator. The Hopkins Institutional Review Board did not require prior consent from the patient or their providers. We calculated the response rate and tracked the number of complaints and requests for removal from future messages. We also determined response rate according to message content.Results:Of the 5.5 million individuals receiving care at the Johns Hopkins Health System, a sample of 6896 met our inclusion criteria and were sent one patient portal recruitment message between 6 April 2017 and 3 August 2017. Assessment of enrollment by this method ended on 1 December 2017. There were 116 patients who expressed interest in the study (response rate: 1.7%). Twelve (0.2%) recipients were randomized. There were two complaints (0.03%) and one request to unsubscribe from future recruitment messages (0.01%). Response rate was higher with the longer message than the shorter message (2.1% vs 1.2%; p = 0.005).Conclusion:Patient portal messages inviting seniors to participate in a randomized controlled trial resulted in a response rate similar to commercial email marketing and resulted in very few complaints or opt-out requests. Furthermore, a longer message with more content enhanced response rate. Recruitment through patient portals might be an effective strategy to enroll trial participants.
      Citation: Clinical Trials
      PubDate: 2019-10-04T06:33:02Z
      DOI: 10.1177/1740774519873657
  • A high-volume, low-cost approach to participant screening and enrolment:
           Experiences from the T4DM diabetes prevention trial
    • Authors: Karen Bracken, Anthony Keech, Wendy Hague, Carolyn Allan, Ann Conway, Mark Daniel, Val Gebski, Mathis Grossmann, David J Handelsman, Warrick J Inder, Alicia Jenkins, Robert McLachlan, Kristy P Robledo, Bronwyn Stuckey, Bu B Yeap, Gary Wittert
      Abstract: Clinical Trials, Ahead of Print.
      Background/aims:Participant recruitment to diabetes prevention randomised controlled trials is challenging and expensive. The T4DM study, a multicentre, Australia-based, Phase IIIb randomised controlled trial of testosterone to prevent Type 2 diabetes in men aged 50–74 years, faced the challenge of screening a large number of prospective participants at a small number of sites, with few staff, and a limited budget for screening activities. This article evaluates a high-volume, low-cost, semi-automated approach to screen and enrol T4DM study participants.Methods:We developed a sequential multi-step screening process: (1) web-based pre-screening, (2) laboratory screening through a network of third-party pathology centres, and (3) final on-site screening, using online data collection, computer-driven eligibility checking, and automated, email-based communication with prospective participants. Phone- and mail-based data collection and communication options were available to participants at their request. The screening process was administered by the central coordinating centre through a central data management system.Results:Screening activities required staffing of approximately 1.6 full-time equivalents over 4 years. Of 19,022 participants pre-screened, 13,108 attended a third-party pathology collection centre for laboratory screening, 1217 received final, on-site screening, and 1007 were randomised. In total, 95% of the participants opted for online pre-screening over phone-based pre-screening. Screening costs, including both direct and staffing costs, totalled AUD1,420,909 (AUD75 per subject screened and AUD1411 per randomised participant).Conclusion:A multi-step, semi-automated screening process with web-based pre-screening facilitated low-cost, high-volume participant enrolment to this large, multicentre randomised controlled trial. Centralisation and automation of screening activities resulted in substantial savings compared to previous, similar studies. Our screening approach could be adapted to other randomised controlled trial settings to minimise the cost of screening large numbers of participants.
      Citation: Clinical Trials
      PubDate: 2019-10-04T06:31:41Z
      DOI: 10.1177/1740774519872999
  • Commentary on Ji et al: Sub-optimal illustration of response adaptive
    • Authors: Benjamin R Saville, William Meurer
      Abstract: Clinical Trials, Ahead of Print.

      Citation: Clinical Trials
      PubDate: 2019-10-03T01:12:28Z
      DOI: 10.1177/1740774519875968
  • Cluster randomised trials with different numbers of measurements at
           baseline and endline: Sample size and optimal allocation
    • Authors: Andrew J Copas, Richard Hooper
      Abstract: Clinical Trials, Ahead of Print.
      Background/Aims:Published methods for sample size calculation for cluster randomised trials with baseline data are inflexible and primarily assume an equal amount of data collected at baseline and endline, that is, before and after the intervention has been implemented in some clusters. We extend these methods to any amount of baseline and endline data. We explain how to explore sample size for a trial if some baseline data from the trial clusters have already been collected as part of a separate study. Where such data aren’t available, we show how to choose the proportion of data collection devoted to the baseline within the trial, when a particular cluster size or range of cluster sizes is proposed.Methods:We provide a design effect given the cluster size and correlation parameters, assuming different participants are assessed at baseline and endline in the same clusters. We show how to produce plots to identify the impact of varying the amount of baseline data accounting for the inevitable uncertainty in the cluster autocorrelation. We illustrate the methodology using an example trial.Results:Baseline data provide more power, or allow a greater reduction in trial size, with greater values of the cluster size, intracluster correlation and cluster autocorrelation.Conclusion:Investigators should think carefully before collecting baseline data in a cluster randomised trial if this is at the expense of endline data. In some scenarios, this will increase the sample size required to achieve given power and precision.
      Citation: Clinical Trials
      PubDate: 2019-10-03T01:12:08Z
      DOI: 10.1177/1740774519873888
  • Benefit, burden, and impact for a cohort of post-approval cancer
           combination trials
    • Authors: Benjamin Gregory Carlisle, Adélaïde Doussau, Jonathan Kimmelman
      Abstract: Clinical Trials, Ahead of Print.
      Background:After approval, drug developers often pursue trials aimed at extending the uses of a new drug by combining it with other drugs. Little is known about the risk and benefits associated with such research.Methods:To establish a historic benchmark of risk and benefit, we searched Medline and Embase for clinical trials testing anti-cancer drugs in combination within 5 years of approval by the Food and Drug Administration of 12 anti-cancer “index” drugs first licensed 2005–2007 inclusive. Risk was assessed based on grade 3 or above drug-related adverse events; benefit was assessed based on efficacy outcomes and advancement of combinations into clinical practice guidelines or approval by the Food and Drug Administration.Results:We captured 323 published post-approval trials exploring combinations, including 266 unique combination–indication pairings and enrolling 29,835 patients. The pooled risk ratios for treatment-related grade 3–4 severe adverse events and deaths attributed to the study drugs for trials randomized between a combination arm and a comparator were 1.54 (1.33–1.79) and 1.51 (1.16–1.97), respectively. The pooled hazard ratios for overall survival and progression-free survival were 0.99 (0.92–1.05) and 0.85 (0.79–0.93), respectively. None of the combination–indication pairings launched after initial drug approval received approval by the Food and Drug Administration, and 13 pairings (4.9%) were recommended by the National Comprehensive Cancer Network within 5 years of the first trial within that pairing. The proportion of patients in our sample who participated in trials leading to an approval by the Food and Drug Administration or a National Comprehensive Cancer Network guideline recommendation was 12.7% with 5 years of follow-up, and 22.3% among pairings for which there were 8 years of follow-up.Conclusion:Patients were just as likely to benefit in the treatment arm as the control arm in terms of overall survival, but they were more likely to experience a treatment-related severe adverse event in post-approval trials of combination therapy.
      Citation: Clinical Trials
      PubDate: 2019-10-03T01:11:05Z
      DOI: 10.1177/1740774519873883
  • Evaluation of irrational dose assignment definitions using the continual
           reassessment method
    • Authors: Nolan A. Wages, Evan Bagley
      Abstract: Clinical Trials, Ahead of Print.
      Background:This article studies the notion of irrational dose assignment in Phase I clinical trials. This property was recently defined by Zhou and colleagues as a dose assignment that fails to de-escalate the dose when two out of three, three out of six, or four out of six patients have experienced a dose-limiting toxicity event at the current dose level. The authors claimed that a drawback of the well-known continual reassessment method is that it can result in irrational dose assignments. The aim of this article is to examine this definition of irrationality more closely within the conduct of the continual reassessment method.Methods:Over a broad range of assumed dose-limiting toxicity probability scenarios for six study dose levels and a variety of target dose-limiting toxicity rates, we simulated 2000 trials of n = 36 patients. For each scenario, we counted the number of irrational dose assignments that were made by the continual reassessment method, according to the definitions of Zhou and colleagues. For each of the irrational decisions made, we classified the dose assignment as an underdose assignment, a target dose assignment, or an overdose assignment based on the true dose-limiting toxicity probability at that dose.Results:Across eight dose-toxicity scenarios, there were a total of 181,581 dose assignments made in the simulation study. Of these assignments, 8165 (4.5%) decisions were made when two out of three, three out of six, or four out of six patients had experienced a dose-limiting toxicity at the current dose. Of these 8165 decisions, 1505 (18.4%) recommended staying at the current dose level and would therefore be classified as irrational by Zhou and colleagues. Among the irrational decisions, 41.2% were misclassified, meaning they were made either at the true target dose (17.9%) or at a true underdose (23.3%). The remaining 58.8% were made at a true overdose and therefore truly irrational. Overall, irrational dose assignments comprised
      Citation: Clinical Trials
      PubDate: 2019-09-24T06:10:46Z
      DOI: 10.1177/1740774519873316
  • Sequential or combined designs for Phase I/II clinical trials' A
           simulation study
    • Authors: Caroline Rossoni, Aurélie Bardet, Birgit Geoerger, Xavier Paoletti
      Abstract: Clinical Trials, Ahead of Print.
      Background:Phase I and Phase II clinical trials aim at identifying a dose that is safe and active. Both phases are increasingly combined. For Phase I/II trials, two main types of designs are debated: a dose-escalation stage to select the maximum tolerated dose, followed by an expansion cohort to investigate its activity (dose-escalation followed by an expansion cohort), or a joint modelling to identify the best trade-off between toxicity and activity (efficacy–toxicity). We explore this question in the context of a paediatric Phase I/II platform trial.Methods:In series of simulations, we assessed the operating characteristics of dose-escalation followed by an expansion cohort (DE-EC) designs without and with reassessment of the maximum tolerated dose during the expansion cohort (DE-ECext) and of the efficacy–toxicity (EffTox) design. We investigated the probability to identify an active and tolerable agent, that is, the percentage of correct decision, for various dose-toxicity activity scenarios.Results:For a large therapeutic index, the percentage of correct decision reached 96.0% for efficacy–toxicity versus 76.1% for dose-escalation followed by an expansion cohort versus 79.6% for DE-ECext. Conversely, when all doses were deemed not active, the percentage of correct decision was 47% versus 55.9% versus 69.2%, respectively, for efficacy–toxicity, dose-escalation followed by an expansion cohort and DE-ECext. Finally, in the case of a narrow therapeutic index, the percentage of correct decision was 48.0% versus 64.3% versus 67.2%, respectively, efficacy–toxicity, dose-escalation followed by an expansion cohort and DE-ECext.Conclusion:As narrow indexes are common in oncology, according to the present results, the sequential dose-escalation followed by an expansion cohort is recommended. The importance to re-estimate the maximum tolerated dose during the expansion cohort is confirmed. However, despite their theoretical advantages, Phase I/II designs are challenged by the variations in populations between the Phase I and the Phase II parts and by the lagtime in the evaluation of toxicity and activity.
      Citation: Clinical Trials
      PubDate: 2019-09-20T01:26:47Z
      DOI: 10.1177/1740774519872702
  • Availability of study protocols for randomized trials published in
           high-impact medical journals: A cross-sectional analysis
    • Authors: O’Mareen Spence, Kyungwan Hong, Richie Onwuchekwa Uba, Peter Doshi
      Abstract: Clinical Trials, Ahead of Print.
      Background:To improve reporting transparency and research integrity, some journals have begun publishing study protocols and statistical analysis plans alongside trial publications. We sought to assess the overall availability and characteristics of protocols and statistical analysis plans of randomized clinical trials published in the top five (by impact factor) general medicine journals.Methods:All randomized clinical trials published in Annals of Internal Medicine, BMJ, JAMA, Lancet, and NEJM in 2016 were identified. For each randomized clinical trial, we searched for protocols and statistical analysis plans on journal websites (including supplementary material) and in the article, for example, a referenced publication or link to trial or institutional website. Characteristics of randomized clinical trials were extracted from the publication and clinical trial registry. A detailed assessment of protocols and statistical analysis plans was conducted in a 20% random sample of randomized clinical trials.Results:Protocols were available for 299 (82%) trials, ranging from 50% in BMJ to>95% in NEJM and JAMA. Statistical analysis plans were available for 182 (50%) trials and varied from
      Citation: Clinical Trials
      PubDate: 2019-08-27T06:37:31Z
      DOI: 10.1177/1740774519868310
  • Recommendations for improving clinical trial design to facilitate the
           study of youth-onset type 2 diabetes
    • Authors: Muhammad Yazid Jalaludin, Margarita Barrientos-Pérez, Mona Hafez, Jane Lynch, Naim Shehadeh, Serap Turan, Daniel Weghuber
      Abstract: Clinical Trials, Ahead of Print.
      BackgroundThe prevalence of type 2 diabetes is increasing in youths and differs from adult-onset type 2 diabetes in its characteristics and progression. Currently, only two drugs are approved for youth-onset type 2 diabetes and many patients are not meeting glycemic targets. Clearly, there is an urgent need to complete clinical trials in youths with type 2 diabetes to increase the therapeutic choice for these patients. However, factors such as limited patient numbers, unwillingness of patients to participate in trials, failure to meet strict inclusion and exclusion criteria, and poor clinic attendance have limited the size and number of trials in this complicated patient demographic.RecommendationsThis is a narrative opinion piece on the design of clinical trials in youth-onset type 2 diabetes prepared by researchers who undertake this type of study in different countries. The review addresses possible ways to enhance trial designs in youth-onset type 2 diabetes to meet regulatory requirements, while minimizing the barriers to patients’ participation. The definition of adolescence, recruitment of sufficient patient numbers, increasing flexibility in selection criteria, improving convenience of trial visits, requirements of a control group, possible endpoints, and trial compliance are all considered. The authors recommend allowing extrapolation from adult data, using multiple interventional arms within future trials, broadening inclusion criteria, and focusing on endpoints beyond glucose control, among others, in order to improve the successful completion of more trials in this population.ConclusionsImprovements in trial design will enable better recruitment and retention and thereby more evidence for treatment outcomes for youth-onset type 2 diabetes.
      Citation: Clinical Trials
      PubDate: 2019-08-27T06:37:11Z
      DOI: 10.1177/1740774519870190
  • Design and monitoring of survival trials based on restricted mean survival
    • Authors: Xiaodong Luo, Bo Huang, Hui Quan
      Abstract: Clinical Trials, Ahead of Print.
      Background/Aims:Restricted mean survival time has become a popular treatment effect measurement because of its nice interpretability. However, study design based on restricted mean survival times often requires extensive simulation studies as the variance structure is hard to obtain analytically. This article aims to provide a flexible approach to conduct study design and monitoring based on the restricted mean survival times without resorting to simulation.Methods:We assume that both the event time and censoring time distributions are piecewise exponential, and the accrual distribution is piecewise uniform, with which the restricted mean survival times and their variance–covariance structure can be conveniently computed.Results:Since we allow arbitrary number of pieces in the piecewise exponential and uniform distributions, the resulting model can handle a wide range of scenarios. The usefulness of the approach is demonstrated via an example.Conclusion:The proposed approach is flexible and useful in the design and monitoring of survival trials based on restricted mean survival times.
      Citation: Clinical Trials
      PubDate: 2019-08-27T06:36:51Z
      DOI: 10.1177/1740774519871447
  • Bayesian clinical trials at The University of Texas MD Anderson Cancer
           Center: An update
    • Authors: Rebecca S Slack Tidwell, S Andrew Peng, Minxing Chen, Diane D Liu, Ying Yuan, J Jack Lee
      Abstract: Clinical Trials, Ahead of Print.
      Background/aimsIn our 2009 article, we showed that Bayesian methods had established a foothold in developing therapies in our institutional oncology trials. In this article, we will document what has happened since that time. In addition, we will describe barriers to implementing Bayesian clinical trials, as well as our experience overcoming them.MethodsWe reviewed MD Anderson Cancer Center clinical trials submitted to the institutional protocol office for scientific and ethical review between January 2009 and December 2013, the same length time period as the previous article. We tabulated Bayesian methods implemented for design or analyses for each trial and then compared these to our previous findings.ResultsOverall, we identified 1020 trials and found that 283 (28%) had Bayesian components so we designated them as Bayesian trials. Among MD Anderson–only and multicenter trials, 56% and 14%, respectively, were Bayesian, higher rates than our previous study. Bayesian trials were more common in phase I/II trials (34%) than in phase III/IV (6%) trials. Among Bayesian trials, the most commonly used features were for toxicity monitoring (65%), efficacy monitoring (36%), and dose finding (22%). The majority (86%) of Bayesian trials used non-informative priors. A total of 75 (27%) trials applied Bayesian methods for trial design and primary endpoint analysis. Among this latter group, the most commonly used methods were the Bayesian logistic regression model (N = 22), the continual reassessment method (N = 20), and adaptive randomization (N = 16). Median institutional review board approval time from protocol submission was the same 1.4 months for Bayesian and non-Bayesian trials. Since the previous publication, the Biomarker-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) trial was the first large-scale decision trial combining multiple treatments in a single trial. Since then, two regimens in breast cancer therapy have been identified and published from the cooperative Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis (I-SPY 2), enhancing cooperation among investigators and drug developers across the nation, as well as advancing information needed for personalized medicine. Many software programs and Shiny applications for Bayesian trial design and calculations are available from our website which has had more than 21,000 downloads worldwide since 2004.ConclusionBayesian trials have the increased flexibility in trial design needed for personalized medicine, resulting in more cooperation among researchers working to fight against cancer. Some disadvantages of Bayesian trials remain, but new methods and software are available to improve their function and incorporation into cancer clinical research.
      Citation: Clinical Trials
      PubDate: 2019-08-27T06:35:51Z
      DOI: 10.1177/1740774519871471
  • Accrual Prediction Program: A web-based clinical trials tool for
           monitoring and predicting accrual for early-phase cancer studies
    • Authors: Junhao Liu, Jo A Wick, Dinesh Pal Mudaranthakam, Yu Jiang, Matthew S Mayo, Byron J Gajewski
      Abstract: Clinical Trials, Ahead of Print.
      BackgroundMonitoring subject recruitment is key to the success of a clinical trial. Accordingly, researchers have developed accrual-monitoring tools to support the design and conduct of trials. At an institutional level, delays in identifying studies with high risk of accrual failure can lead to inefficient and costly trials with little chances of meeting study objectives. Comprehensive accrual monitoring is necessary to the success of the research enterprise.MethodsThis article describes the design and implementation of the University of Kansas Cancer Center Accrual Prediction Program, a web-based platform was developed to support comprehensive accrual monitoring and prediction for all active clinical trials. The Accrual Prediction Program provides information on accrual, including the predicted completion date, predicted number of accrued subjects during the pre-specified accrual period, and the probability of achieving accrual targets. It relies on a Bayesian accrual prediction model to combine protocol information with real-time trial enrollment data and disseminates results via web application.ResultsFirst released in 2016, the Accrual Prediction Program summarizes enrollment information for active studies categorized by various trial attributes. The web application supports real-time evidence-based decision making for strategic resource allocation and study management of over 120 ongoing clinical trials at the University of Kansas Cancer Center.ConclusionThe Accrual Prediction Program makes accessing comprehensive accrual information manageable at an institutional level. Cancer centers or even entire institutions can reproduce the Accrual Prediction Program to achieve real-time comprehensive monitoring and prediction of subject accrual to aid investigators and administrators in the design, conduct, and management of clinical trials.
      Citation: Clinical Trials
      PubDate: 2019-08-27T06:35:32Z
      DOI: 10.1177/1740774519871474
  • Noninferiority trials with nonadherence to the assigned randomized
    • Authors: Edward L Korn, Robert J Gray, Boris Freidlin
      Abstract: Clinical Trials, Ahead of Print.
      Background:Nonadherence to treatment assignment in a noninferiority randomized trial is especially problematic because it attenuates observed differences between the treatment arms, possibly leading one to conclude erroneously that a truly inferior experimental therapy is noninferior to a standard therapy (inflated type 1 error probability). The Lachin–Foulkes adjustment is an increase in the sample size to account for random nonadherence for the design of a superiority trial with a time-to-event outcome; it has not been explored in the noninferiority trial setting nor with nonrandom nonadherence. Noninferiority trials where patients have knowledge of a personal prognostic risk score may lead to nonrandom nonadherence, as patients with a relatively high risk may be more likely to not adhere to the random assignment to the (reduced) experimental therapy, and patients with a relatively low risk score may be more likely to not adhere to the random assignment to the (more aggressive) standard therapy.Methods:We investigated via simulations the properties of the Lachin–Foulkes adjustment in the noninferiority setting. We considered nonrandom in addition to random nonadherence to the treatment assignment. For nonrandom nonadherence, we used the scenario where a risk score, potentially associated with the between-arm treatment difference, influences patients’ nonadherence. A sensitivity analysis is proposed for addressing the nonrandom nonadherence for this scenario. The noninferiority TAILORx adjuvant breast cancer trial, where eligibility was based on a genomic risk score, is used as an example throughout.Results:The Lachin–Foulkes adjustment to the sample size improves the operating characteristics of noninferiority trials with random nonadherence. However, to maintain type 1 error probability, it is critical to adjust the noninferiorty margin as well as the sample size. With nonrandom nonadherence that is associated with a prognostic risk score, the type 1 error probability of the Lachin–Foulkes adjustment can be inflated (e.g. doubled) when the nonadherence is larger in the experimental arm than the standard arm. The proposed sensitivity analysis lessens the inflation in this situation.Conclusion:The Lachin–Foulkes adjustment to the sample size and noninferiority margin is a useful simple technique for attenuating the effects of random nonadherence in the noninferiority setting. With nonrandom nonadherence associated with a risk score known to the patients, the type 1 error probability can be inflated in certain situations. A proposed sensitivity analysis for these situations can attenuate the inflation.
      Citation: Clinical Trials
      PubDate: 2019-08-14T08:21:23Z
      DOI: 10.1177/1740774519868479
  • A win ratio approach to the re-analysis of Multiple Risk Factor
           Intervention Trial
    • Authors: Ales Kotalik, Anne Eaton, Qinshu Lian, Carlos Serrano, John Connett, James D Neaton
      Abstract: Clinical Trials, Ahead of Print.
      Background:Composite outcomes, which combine multiple types of clinical events into a single outcome, are common in clinical trials. The usual analysis considers the time to first occurrence of any event in the composite. The major criticisms of such an approach are (1) this implicitly treats the outcomes as if they were of equal importance, but they often vary in terms of clinical relevance and severity, (2) study participants often experience more than one type of event, and (3) often less severe events occur before more severe ones, but the usual analysis disregards any information beyond that first event.Methods:A novel approach, referred to as the win ratio, which addresses the aforementioned criticisms of composite outcomes, is illustrated with a re-analysis of data on fatal and non-fatal cardiovascular disease time-to-event outcomes reported for the Multiple Risk Factor Intervention Trial. In this trial, 12,866 participants were randomized to a special intervention group (n = 6428) or a usual care (n = 6438) group. Non-fatal outcomes were ranked by risk of cardiovascular disease death up to 20 years after trial. In one approach, participants in the special intervention and usual care groups were first matched on coronary heart disease risk at baseline and time of enrollment. Each matched pair was categorized as a winner or loser depending on which one experienced a cardiovascular disease death first. If neither died of cardiovascular disease causes, they were evaluated on the most severe non-fatal outcome. This process continued for all the non-fatal outcomes. A second win ratio statistic, obtained from Cox partial likelihood, was also estimated. This statistic provides a valid estimate of the win ratio using multiple events if the marginal and conditional survivor functions of each outcome satisfy proportional hazards. Loss ratio statistics (inverse of win ratios) are compared to hazard ratios from the usual first event analysis. A larger 11-event composite was also considered.Results:For the 7-event cardiovascular disease composite, the previously reported first event analysis based on 581 events in the special intervention group and 652 events in the usual care group yielded a hazard ratio (95% confidence interval) of 0.89 (0.79–0.99), compared to 0.86 (0.77–0.97) and 0.91 (0.81–1.02) for the severity ranked estimates. Results for the 11-event composite also confirmed the findings of the first event analysis.Conclusion:The win ratio analysis was able to leverage information collected past the first experienced event and rank events by severity. The results were similar to and confirmed previously reported traditional first event analysis. The win ratio statistic is a useful adjunct to the traditional first event analysis for trials with composite outcomes.
      Citation: Clinical Trials
      PubDate: 2019-08-07T02:17:39Z
      DOI: 10.1177/1740774519868233
  • Public views regarding the responsibility of patients, clinicians, and
           institutions to participate in research in the United States
    • Authors: Kevin P Weinfurt, Li Lin, Jeremy Sugarman
      Abstract: Clinical Trials, Ahead of Print.
      BackgroundThe need for more and better evidence to inform clinical decision making among all stakeholders has fueled calls for creating learning healthcare systems. The successful realization of a learning healthcare system seems to assume that various parties have a responsibility to participate in learning activities, including research. The objective of this study was to determine whether members of the general public perceive an ethical responsibility to participate in pragmatic clinical research that would be inherent to a learning health system.MethodsA total of 2994 English-speaking adults completed a nationally representative online survey.ResultsAbout two-thirds of respondents were relatively neutral regarding a responsibility for themselves and others to participate in research; the remainder felt that they and others did not have a responsibility to participate in research.ConclusionsEfforts to justify and develop a robust learning health system in an ethically acceptable fashion need to take these findings into account.
      Citation: Clinical Trials
      PubDate: 2019-07-01T08:58:57Z
      DOI: 10.1177/1740774519858917
  • Risk to bystanders in clinical trials: A symposium
    • Authors: Nir Eyal
      First page: 447
      Abstract: Clinical Trials, Ahead of Print.
      This symposium takes a critical look at the ethics of impact on “bystanders” to clinical research. By that we mean study non-participants who nevertheless are at risk of being affected by the study in some way. This introduction suggests some questions to consider while reading through the symposium contributions, and gives a précis of each.
      Citation: Clinical Trials
      PubDate: 2019-08-01T02:34:52Z
      DOI: 10.1177/1740774519862758
  • Regulating impact on bystanders in clinical trials: An unsettled frontier
    • Authors: Nir Eyal, Jonathan Kimmelman, Lisa G Holtzman, Marc Lipsitch
      First page: 450
      Abstract: Clinical Trials, Ahead of Print.
      This article informally reviews key research ethics guidelines and regulations, academic scholarship, and research studies and finds wide variety in how they consider risk to bystanders in medical research (namely, non-participants whom studies nevertheless place at risk). Some of these key sources give no or very little consideration to bystanders, while others offer them the utmost protection (greater than they offer study participants). This unsettled frontier would benefit from a deeper investigation of the ethics of protecting research bystanders.
      Citation: Clinical Trials
      PubDate: 2019-08-01T02:35:21Z
      DOI: 10.1177/1740774519862783
  • Sex partners as bystanders in HIV prevention trials: Two test cases for
           research ethics
    • Authors: Till Bärnighausen
      First page: 455
      Abstract: Clinical Trials, Ahead of Print.
      Research involving human subjects can impose risk on some ‘bystanders’– people who are not themselves research subjects but whom the study may affect. We examine the consequences of research for a particular category of bystanders – research subjects’ sex partners – in trials testing interventions to reduce (1) HIV transmission (HIV treatment-as-prevention trials) and (2) HIV acquisition (HIV pre-exposure prophylaxis trials). Both types of trials provide useful test cases for assessing whether bystanders to research deserve special consideration in ethics reviews, and potentially some of the benefits and protections that research subjects receive. In HIV treatment-as-prevention trials, there are two groups of people who are alike in many important respects but treated very differently by research ethics: research subjects who contribute data on the primary endpoint of the trial (because some of them have sex with the people receiving the treatment conditions of the trials) – and bystanders who are not enrolled in the trials but who could have contributed primary endpoint data in the same way as the first group. In pre-exposure trials, the sex partners of people participating in pre-exposure prophylaxis trials are bystanders, even though they are necessary for the success of the trial. Research subjects’ autonomy is fiercely protected by trial enrolment processes. Bystanders, by contrast, often have no choice but to be affected by the study, because of their relationship to a research subject. In HIV prevention trials, standing by can come with important risks, including the same ones on which the success of the research hinges. It is thus important to consider the ethical obligations to protect bystanders, and the related procedural responsibilities.
      Citation: Clinical Trials
      PubDate: 2019-08-01T02:35:11Z
      DOI: 10.1177/1740774519865878
  • Ethical complexities of responding to bystander risk in HIV prevention
    • Authors: Nir Eyal, Daniel Wikler
      First page: 458
      Abstract: Clinical Trials, Ahead of Print.
      Till Bärnighausen points out the medical risks that two categories of contemporary HIV prevention trials, for “treatment-as-prevention” and for “pre-exposure prophylaxis,” pose to people who are not study participants. Bärnighausen’s compelling case forces reconsideration of the absence of bystanders in the law governing ethical review of health research. It raises the intriguing question: to what legal protection are bystanders morally entitled' The remedy might seem to be to accord bystanders the rights and protections currently accorded to human study participants. We counsel against that remedy on three grounds, inviting colleagues to suggest alternatives.
      Citation: Clinical Trials
      PubDate: 2019-08-01T02:34:22Z
      DOI: 10.1177/1740774519862765
  • Organ donor intervention trials and the ethical challenge of bystander
           organ recipients
    • Authors: Jonathan Kimmelman
      First page: 461
      Abstract: Clinical Trials, Ahead of Print.
      Donor intervention trials test treatments aimed at preserving organs in transplantation. Many such trials apply treatments to deceased organ donors before transplantation. Drawing on a recent National Academy of Medicine report, this review describes how such studies implicate the welfare of at least four different types of individuals who would not be considered human subjects under current regulations. I close by describing why protections of some sort ought to be extended to each of these four types of research bystanders.
      Citation: Clinical Trials
      PubDate: 2019-08-01T02:34:31Z
      DOI: 10.1177/1740774519862777
  • Organ donor intervention trials and risk to bystanders: An ethical
    • Authors: Ivan Glenn Cohen
      First page: 463
      Abstract: Clinical Trials, Ahead of Print.
      There are two distinct problems about bystander effects raised by organ donor intervention research. The first is the problem of “bystander organs”—sometimes called “non-target organs”—which Kimmelman discusses in his case presentation. How do we treat the recipients of organs that are not the subject of the intervention research but nonetheless might be directly affected by the research' The second problem is not about altering the organ but the pattern of distribution of organs. Each of these cases shows bystander effects that matter for real people. This article examines how research ethics should approach each of these cases.
      Citation: Clinical Trials
      PubDate: 2019-08-01T02:34:51Z
      DOI: 10.1177/1740774519865259
  • Objective monitoring of mosquito bednet usage and the ethical challenge of
           respecting study bystanders’ privacy
    • Authors: Paul Krezanoski, Jessica Haberer
      First page: 466
      Abstract: Clinical Trials, Ahead of Print.
      Insecticide-treated bednets are among the most prevalent and cost-effective tools for preventing malaria throughout the world. Consistent bednet use is crucial for effectiveness, but assessing adherence is challenging due to limitations in current measurement tools. Recent technologies have introduced methods for remote electronic bednet use monitoring. While valuable for researchers, these monitoring tools create potential ethical concerns for study bystanders because the monitors are typically unable to discriminate between individuals who are or are not study participants. Considerations related to study bystanders, including privacy, ancillary care obligations, and community perceptions, are discussed.
      Citation: Clinical Trials
      PubDate: 2019-08-01T02:35:07Z
      DOI: 10.1177/1740774519865525
  • Objective monitoring of mosquito bednet usage and the ethical challenge of
           privacy revelations about study bystanders: Ethical analysis
    • Authors: Amy L Fairchild
      First page: 469
      Abstract: Clinical Trials, Ahead of Print.
      Clinical trials and public health surveillance of bednet use for malaria prevention involve the ongoing collection of sensitive data from private settings. This article discusses risks to bystanders, who have not consented to participating in surveillance or research, but whose behavior may nevertheless be recorded. In the case of clinical trials, community consultation and consent processes are one well-accepted way to address potential risk to bystanders. I argue that the intrusive monitoring required by some bednet trials may render this type of consent insufficient. In these cases, either bystanders should be enrolled as participants and give consent or less intrusive monitoring methods should be used. Validated monitoring methods should also have relevance for practice beyond use in a clinical trial. Considering the global impact of malaria, applying these methods to public health surveillance would be a practical use. Existing justifications for surveillance without consent, which sometimes result in coercive public health measures, could apply to the case of bednets. Particularly in cases where there is the potential for harm to others, individuals who were not the original subjects of disease reporting are often caught in the surveillance net. Although an argument can be made that malaria meets this bar, considerations of feasibility, sustainability, and trust make intrusive surveillance unsustainable in the case of a daily, lifelong behavior such as bednet use.
      Citation: Clinical Trials
      PubDate: 2019-08-01T02:35:05Z
      DOI: 10.1177/1740774519865869
  • The ethical relevance of two types of adverse health effects on research
    • Authors: Gerard Vong
      First page: 473
      Abstract: Clinical Trials, Ahead of Print.
      Using cases from this symposium, I illustrate a distinction between clinical trials that harm research non-participants’ health and clinical trials that reduce a distinct health benefit to research non-participants. This distinction is ethically relevant for the design and justification of clinical trials. The relative stringency of the ethical duty to avoid harm makes it more important, all other things being equal, to avoid harms rather than avoid reduction of benefits. This is especially ethically important as it is often difficult to identify research non-participants who will suffer health harms due to research, let alone obtain their informed consent. In these difficult cases, all other things being equal, we have ethical reason to prefer clinical trials that only reduce non-participants’ health benefits to those that only involve harms to non-participants’ health. When such trials are not feasible and we are unable to get consent for the significant harms to research non-participants, these (and other) countervailing considerations must be outweighed by substantial social benefits in order for the trial to be ethically justified. Ethical research design must not just be concerned with the magnitude of adverse health effects on research non-participants but also the types of those effects.
      Citation: Clinical Trials
      PubDate: 2019-08-01T02:35:31Z
      DOI: 10.1177/1740774519867323
  • Facebook advertising for recruitment of midlife women with bothersome
           vaginal symptoms: A pilot study
    • Authors: Katherine A Guthrie, Bette Caan, Susan Diem, Kristine E Ensrud, Sharon R Greaves, Joseph C Larson, Katherine M Newton, Susan D Reed, Andrea Z LaCroix
      First page: 476
      Abstract: Clinical Trials, Ahead of Print.

      Citation: Clinical Trials
      PubDate: 2019-05-06T08:18:39Z
      DOI: 10.1177/1740774519846862
  • Recruitment and retention: A randomized controlled trial of video-enhanced
           versus standard consent processes within the E-OPTIMAL study
    • Authors: Linda Brubaker, J Eric Jelovsek, Emily S Lukacz, Sunil Balgobin, Alicia Ballard, Alison C Weidner, Marie G Gantz, Ryan Whitworth, Donna Mazloomdoost
      First page: 481
      Abstract: Clinical Trials, Ahead of Print.
      Background/aims:In this study, we compared two research consent techniques: a standardized video plus usual consent and usual consent alone.Methods:Individuals who completed 24-month outcomes (completers) in the Operations and Pelvic Muscle Training in the Management of Apical Support Loss study were invited to participate in an extended, longitudinal follow-up study (extended Operations and Pelvic Muscle Training in the Management of Apical Support Loss). Potential participants who were (1) able to provide consent and (2) not in long-term care facilities were randomized 1:1 to a standardized video detailing the importance of long-term follow-up studies of pelvic floor disorders followed by the usual institutional consent process versus the usual consent process alone. Randomization, stratified by site, used randomly permuted blocks. The primary outcome was the proportion of participants who enrolled in the extended study and completed data collection events 5 years after surgery. Secondary outcomes included the proportion enrolled in the extended study, completion of follow-up at each study year, completion of data collection points, completion of in-person visits, and completion of quality of life calls. Motivation and barriers to enrollment (study-level and personal-level) and satisfaction with the study consent process were measured by questionnaire prior to recruitment into extended Operations and Pelvic Muscle Training in the Management of Apical Support Loss. Groups were compared using an intention-to-treat principle, using unadjusted Student’s t-test (continuous) and chi-square or Fisher’s exact (categorical) test. A sample size of 340 (170/group) was estimated to detect a 15% difference in enrollment and study completion between groups with p 
      Citation: Clinical Trials
      PubDate: 2019-07-26T09:15:50Z
      DOI: 10.1177/1740774519865541
  • Research methodology and practical issues relating to the conduct of a
           medical device registry
    • Authors: Theodosios Bisdas, Patrick Bohan, Mario Lescan, Clark J Zeebregts, Jörg Tessarek, Joost van Herwaarden, Jos C van den Berg, Carlo Setacci, Vincent Riambau
      First page: 490
      Abstract: Clinical Trials, Ahead of Print.
      BackgroundThe postmarket research goal is to assess “generalizability” or “external validity” to see if the early results of clinical trials with investigational devices are reproducible in everyday practice in the real world and the longer term. Registries have an important but ambivalent role in achieving this goal.MethodsAlthough registries are common, in practice they follow the regulatory processes that appear designed primarily for pharmaceutical clinical trials and confirmatory studies. We review the literature to assess different definitions and the role of registries in the hierarchy of scientific evidence. We analyze common characteristics affecting registry design, implementation, and governance as well as safety reporting and off-label use while describing the experience of setting up an international, prospective registry for an endovascular device used to treat abdominal aortic aneurysms.ResultsKey areas in which to distinguish registries from trials are as follows: eligibility, setting (patients and institutions), device configurations and iterations, the use of design and quality “spaces,” a focus on systematic quality checks (rather than source data monitoring), open-ended follow-up, flexibility in the definition of end points and sample sizes, data sharing, and publishing commitments.ConclusionBoth clinical trials and registries are essential and complementary research methods and the strengths and weaknesses of each need to be recognized. The specific characteristics of registry research deserve to be acknowledged and safeguarded in the regulations governing clinical investigations with medical devices.
      Citation: Clinical Trials
      PubDate: 2019-06-11T12:40:33Z
      DOI: 10.1177/1740774519855395
  • Impact of retrospective data verification to prepare the ICON6 trial for
           use in a marketing authorization application
    • Authors: Andrew Embleton-Thirsk, Elizabeth Deane, Stephen Townsend, Laura Farrelly, Babasola Popoola, Judith Parker, Gordon Rustin, Matthew Sydes, Mahesh Parmar, Jonathan Ledermann, Richard Kaplan
      First page: 502
      Abstract: Clinical Trials, Ahead of Print.
      Background:The ICON6 trial (ISRCTN68510403) is a phase III academic-led, international, randomized, three-arm, double-blind, placebo-controlled trial of the addition of cediranib to chemotherapy in recurrent ovarian cancer. It investigated the use of placebo during chemotherapy and maintenance (arm A), cediranib alongside chemotherapy followed by placebo maintenance (arm B) and cediranib throughout both periods (arm C). Results of the primary comparison showed a meaningful gain in progression-free survival (time to progression or death from any cause) when comparing arm A (placebo) with arm C (cediranib). As a consequence of the positive results, AstraZeneca was engaged with the Medical Research Council trials unit to discuss regulatory submission using ICON6 as the single pivotal trial.Methods:A relatively limited level of on-site monitoring, single data entry and investigator’s local evaluation of progression were used on trial. In order to submit a license application, it was decided that (a) extensive retrospective source data verification of medical records against case report forms should be performed, (b) further quality control checks for accuracy of data entry should be performed and (c) blinded independent central review of images used to define progression should be undertaken. To assess the value of these extra activities, we summarize the impact on both efficacy and safety outcomes.Results:Data point changes were minimal; those key to the primary results had a 0.47% error rate (36/7686), and supporting data points had a 0.18% error rate (109/59,261). The impact of the source data verification and quality control processes were analyzed jointly. The conclusion drawn for the primary outcome measure of progression-free survival between arm A and arm C was unchanged. The log-rank test p-value changed only at the sixth decimal place, the hazard ratio does not change from 0.57 with the exception of a marginal change in its upper bound (0.74–0.73) and the median progression-free survival benefit from arm C remained at 2.4 months. Separately, the blinded independent central review of progression scans was performed as a sensitivity analysis. Estimates and p values varied slightly but overall demonstrated a difference in arms, which is consistent with the initial result. Some increases in toxicity were observed, though these were generally minor, with the exception of hypertension. However, none of these increases were systematically biased toward one arm.Conclusion:The conduct of this pragmatic, academic-sponsored trial was sufficient given the robustness of the results, shown by the results remaining largely unchanged following retrospective verification despite not being designed for use in a marketing authorization. The burden of such comprehensive retrospective effort required to ensure the results of ICON6 were acceptable to regulators is difficult to justify.
      Citation: Clinical Trials
      PubDate: 2019-07-26T09:15:48Z
      DOI: 10.1177/1740774519862528
  • Detection of atypical data in multicenter clinical trials using
           unsupervised statistical monitoring
    • Authors: Laura Trotta, Yuusuke Kabeya, Marc Buyse, Erik Doffagne, David Venet, Lieven Desmet, Tomasz Burzykowski, Akira Tsuburaya, Kazuhiro Yoshida, Yumi Miyashita, Satoshi Morita, Junichi Sakamoto, Paurush Praveen, Koji Oba
      First page: 512
      Abstract: Clinical Trials, Ahead of Print.
      Background/AimsA risk-based approach to clinical research may include a central statistical assessment of data quality. We investigated the operating characteristics of unsupervised statistical monitoring aimed at detecting atypical data in multicenter experiments. The approach is premised on the assumption that, save for random fluctuations and natural variations, data coming from all centers should be comparable and statistically consistent. Unsupervised statistical monitoring consists of performing as many statistical tests as possible on all trial data, in order to detect centers whose data are inconsistent with data from other centers.MethodsWe conducted simulations using data from a large multicenter trial conducted in Japan for patients with advanced gastric cancer. The actual trial data were contaminated in computer simulations for varying percentages of centers, percentages of patients modified within each center and numbers and types of modified variables. The unsupervised statistical monitoring software was run by a blinded team on the contaminated data sets, with the purpose of detecting the centers with contaminated data. The operating characteristics (sensitivity, specificity and Youden’s J-index) were calculated for three detection methods: one using the p-values of individual statistical tests after adjustment for multiplicity, one using a summary of all p-values for a given center, called the Data Inconsistency Score, and one using both of these methods.ResultsThe operating characteristics of the three methods were satisfactory in situations of data contamination likely to occur in practice, specifically when a single or a few centers were contaminated. As expected, the sensitivity increased for increasing proportions of patients and increasing numbers of variables contaminated. The three methods showed a specificity better than 93% in all scenarios of contamination. The method based on the Data Inconsistency Score and individual p-values adjusted for multiplicity generally had slightly higher sensitivity at the expense of a slightly lower specificity.ConclusionsThe use of brute force (a computer-intensive approach that generates large numbers of statistical tests) is an effective way to check data quality in multicenter clinical trials. It can provide a cost-effective complement to other data-management and monitoring techniques.
      Citation: Clinical Trials
      PubDate: 2019-07-23T08:30:11Z
      DOI: 10.1177/1740774519862564
  • Creation of an institutional semi-independent data monitoring committee
    • Authors: Lisa R Tannock, Marietta Barton-Baxter, William W Stoops
      First page: 523
      Abstract: Clinical Trials, Ahead of Print.
      BackgroundA major goal of the National Institutes of Health’s Clinical and Translational Science Award program is to facilitate clinical research and enhance the transition of basic to clinical research. As such, a number of Clinical and Translational Science Award centers have developed services to facilitate the conduct of clinical research, including support with fulfilling regulatory requirements.MethodsThe University of Kentucky sought to establish an institutional semi-independent monitoring committee to provide oversight for clinical research studies per National Institutes of Health requirements and recommendations. Our semi-independent monitoring committee was initiated in 2010.ResultsSince the inception of our semi-independent monitoring committee we have restructured its operations and protocols to improve efficiency. This article discusses our experiences with semi-independent monitoring committee creation and growth.ConclusionThis article summarizes our experience in creating and maturing an institutional data monitoring committee.
      Citation: Clinical Trials
      PubDate: 2019-07-01T09:20:39Z
      DOI: 10.1177/1740774519859876
  • Design and analysis of a clinical trial using previous trials as
           historical control
    • Authors: David Alan Schoenfeld, Dianne M Finkelstein, Eric Macklin, Neta Zach, David L Ennist, Albert A Taylor, Nazem Atassi
      First page: 531
      Abstract: Clinical Trials, Ahead of Print.
      Background/AimsFor single arm trials, a treatment is evaluated by comparing an outcome estimate to historically reported outcome estimates. Such a historically controlled trial is often analyzed as if the estimates from previous trials were known without variation and there is no trial-to-trial variation in their estimands. We develop a test of treatment efficacy and sample size calculation for historically controlled trials that considers these sources of variation.MethodsWe fit a Bayesian hierarchical model, providing a sample from the posterior predictive distribution of the outcome estimand of a new trial, which, along with the standard error of the estimate, can be used to calculate the probability that the estimate exceeds a threshold. We then calculate criteria for statistical significance as a function of the standard error of the new trial and calculate sample size as a function of difference to be detected. We apply these methods to clinical trials for amyotrophic lateral sclerosis using data from the placebo groups of 16 trials.ResultsWe find that when attempting to detect the small to moderate effect sizes usually assumed in amyotrophic lateral sclerosis clinical trials, historically controlled trials would require a greater total number of patients than concurrently controlled trials, and only when an effect size is extraordinarily large is a historically controlled trial a reasonable alternative. We also show that utilizing patient level data for the prognostic covariates can reduce the sample size required for a historically controlled trial.ConclusionThis article quantifies when historically controlled trials would not provide any sample size advantage, despite dispensing with a control group.
      Citation: Clinical Trials
      PubDate: 2019-07-01T08:56:38Z
      DOI: 10.1177/1740774519858914
  • Open science: The open clinical trials data journey
    • Authors: Frank Rockhold, Christina Bromley, Erin K. Wagner, Marc Buyse
      First page: 539
      Abstract: Clinical Trials, Ahead of Print.
      Open data sharing and access has the potential to promote transparency and reproducibility in research, contribute to education and training, and prompt innovative secondary research. Yet, there are many reasons why researchers don’t share their data. These include, among others, time and resource constraints, patient data privacy issues, lack of access to appropriate funding, insufficient recognition of the data originators’ contribution, and the concern that commercial or academic competitors may benefit from analyses based on shared data. Nevertheless, there is a positive interest within and across the research and patient communities to create shared data resources. In this perspective, we will try to highlight the spectrum of “openness” and “data access” that exists at present and highlight the strengths and weakness of current data access platforms, present current examples of data sharing platforms, and propose guidelines to revise current data sharing practices going forward.
      Citation: Clinical Trials
      PubDate: 2019-07-26T09:15:50Z
      DOI: 10.1177/1740774519865512
  • Transparency and objectivity in governance of clinical trials data
           sharing: Current practices and approaches
    • Authors: Mahsa Shabani, Mojisola Obasa
      First page: 547
      Abstract: Clinical Trials, Ahead of Print.
      Sharing metadata, individual participant data and summary data, as a complement to results dissemination and trial registration requirements, is perceived to be advantageous by enabling faster and more accurate meta-analyses and reducing the need for additional trials. To date, various models of data access have been utilized in order to manage clinical trials data sharing and access in line with the rights and interests of sponsors, researchers and patients involved in clinical trials. In order to ensure responsible data sharing, the data access review process should be developed in a way that ensures fairness, transparency and objectivity. In this article, we critically review some examples of current governance models in clinical trials data sharing and suggest approaches to ensure the objectivity of the data access review process.
      Citation: Clinical Trials
      PubDate: 2019-07-26T09:15:54Z
      DOI: 10.1177/1740774519865517
  • Access to clinical trial data—Commentary
    • Authors: PJ Devereaux
      First page: 552
      Abstract: Clinical Trials, Ahead of Print.

      Citation: Clinical Trials
      PubDate: 2019-07-26T09:15:54Z
      DOI: 10.1177/1740774519865528
  • A novel, hybrid, single- and multi-site clinical trial design for CLN3
           disease, an ultra-rare lysosomal storage disorder
    • Authors: Heather R Adams, Sara Defendorf, Amy Vierhile, Jonathan W Mink, Frederick J Marshall, Erika F Augustine
      First page: 555
      Abstract: Clinical Trials, Ahead of Print.
      BackgroundTravel burden often substantially limits the ability of individuals to participate in clinical trials. Wide geographic dispersion of individuals with rare diseases poses an additional key challenge in the conduct of clinical trials for rare diseases. Novel technologies and methods can improve access to research by connecting participants in their homes and local communities to a distant research site. For clinical trials, however, understanding of factors important for transition from traditional multi-center trial models to local participation models is limited. We sought to test a novel, hybrid, single- and multi-site clinical trial design in the context of a trial for Juvenile Neuronal Ceroid Lipofuscinosis (CLN3 disease), a very rare pediatric neurodegenerative disorder.MethodsWe created a “hub and spoke” model for implementing a 22-week crossover clinical trial of mycophenolate compared with placebo, with two 8-week study arms. A single central site, the “hub,” conducted screening, consent, drug dispensing, and tolerability and efficacy assessments. Each participant identified a clinician to serve as a collaborating “spoke” site to perform local safety monitoring. Study participants traveled to the hub at the beginning and end of each study arm, and to their individual spoke site in the intervening weeks.ResultsA total of 18 spoke sites were established for 19 enrolled study participants. One potential participant was unable to identify a collaborating local site and was thus unable to participate. Study start-up required a median 6.7 months (interquartile range = 4.6–9.2 months). Only 33.3% (n = 6 of 18) of spoke site investigators had prior clinical trial experience, thus close collaboration with respect to study startup, training, and oversight was an important requirement. All but one participant completed all study visits; no study visits were missed due to travel requirements.ConclusionsThis study represents a step toward local trial participation for patients with rare diseases. Even in the context of close oversight, local participation models may be best suited for studies of compounds with well-understood side-effect profiles, for those with straightforward modes of administration, or for studies requiring extended follow-up periods.
      Citation: Clinical Trials
      PubDate: 2019-06-11T12:40:36Z
      DOI: 10.1177/1740774519855715
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