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Cancelli G, Rossi CS, Dell'Aquila M, Mantaj P, Hirofuji A, Soletti G, Harik L, Cangut B, Al Zaghari T, Leith J, Falco G, Ibrahim M, Dimagli A, Rahouma M, Gaudino MFL. Predictors of premature termination of cardiac surgery trials: insights from the Clinicaltrial.gov database. Eur J Cardiothorac Surg 2024; 66:ezae310. [PMID: 39133169 DOI: 10.1093/ejcts/ezae310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2024] [Revised: 08/05/2024] [Accepted: 08/10/2024] [Indexed: 08/13/2024] Open
Abstract
OBJECTIVES Clinical trials that are terminated prematurely may generate incomplete and potentially biased data and the reasons for premature trials termination are poorly understood. Our objective was to describe the incidence of premature trial termination and identify factors associated with it. METHODS We performed a systematic search on ClinicalTrials.gov to identify all cardiac surgery trials from 1991 to 2023. Trials that were terminated prematurely were identified. Factors independently associated with premature termination were identified using multivariable logistic regression analysis. RESULTS A total of 746 clinical trials were included; of them 577 were completed and 169 (22.6%) were terminated prematurely. Most of the trials originated from North America [294 (39.4%)], Europe [264 (35.4%)] or Asia [141 (18.9%)]. Fourteen of the trials terminated prematurely (8.3%) were phase 1, 75 (44.4%) phase 2, 49 (29.0%) phase 3 and 31 (18.3%) phase 4. Fifty (29.6%) trials were terminated because of slow recruitment, 20 (11.8%) because of sponsor decision and 12 (7.1%) because of lack of funding. Left ventricular assist device trials [odds ratio (OR) 3.65, 95% confidence interval (CI) (1.65-8.00) P = 0.001], valve surgery trials [OR 4.30, 95% CI (2.33-8.00) P < 0.001], aortic surgery trials [OR 2.86 95% CI (1.22-6.43) P = 0.012], phase 2 [OR 3.02, 95% CI (1.31-7.93) P = 0.015] and phase 4 trials [OR 3.62, 95% CI (1.43-10.23) P = 0.010] were at higher risk of premature termination while trials performed in Asia [OR 0.18, 95% CI (0.07-0.39) P ≤ 0.001] and Europe [OR 0.49, 95% CI (0.30-0.80) P = 0.004] were less likely to be terminated prematurely. CONCLUSIONS Slow recruitment is the most common reason for premature termination of cardiac surgery trials. Trials on left ventricular assist device, valve surgery, aortic surgery, phase 2 trials and phase 4 trials are more likely to be terminated, while trials conducted in Asia and Europe are less likely to be terminated prematurely.
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Affiliation(s)
- Gianmarco Cancelli
- Department of Cardiothoracic Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Camilla S Rossi
- Department of Cardiothoracic Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Michele Dell'Aquila
- Department of Cardiothoracic Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Polina Mantaj
- Department of Cardiothoracic Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Aina Hirofuji
- Department of Cardiothoracic Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Giovanni Soletti
- Department of Cardiothoracic Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Lamia Harik
- Department of Cardiothoracic Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Busra Cangut
- Department of Nuclear Medicine, Mount Sinai Hospital, New York, NY, USA
| | - Talal Al Zaghari
- Department of Cardiothoracic Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Jordan Leith
- Department of Cardiothoracic Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Giorgia Falco
- Department of Cardiothoracic Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Mudathir Ibrahim
- Department of General Surgery, Maimonides Medical Center, New York, NY, USA
| | - Arnaldo Dimagli
- Department of Cardiothoracic Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Mohamed Rahouma
- Department of Cardiothoracic Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Mario F L Gaudino
- Department of Cardiothoracic Surgery, Weill Cornell Medicine, New York, NY, USA
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Lippert T, Schmucker E, Shukla A, Reddy R, Neerumalla P, Blanco G, Velanovich V. Publication Bias in Upper Gastrointestinal Oncology Clinical Trials. J Gastrointest Cancer 2024; 55:950-955. [PMID: 38546788 DOI: 10.1007/s12029-024-01047-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/20/2024] [Indexed: 06/20/2024]
Abstract
PURPOSE Evidence-based medicine requires evaluation of the medical literature to guide clinical reasoning and treatment recommendations. The presence of publication bias towards exclusion of non-statistically significant clinical trials may be leading to an incomplete evaluation of the literature and cause potentially incomplete guidance for patients. We aimed to compare publication rates and impact of publications of positive and negative outcome clinical trials. METHODS We queried the US National Library of Medicine Clinical Trials database identifying clinical trials with reported results on the topics of pancreatic, liver, and gastric cancer. A "positive" trial was defined as having a statistically significant difference between the treatment arms, while a "negative" did not. Data collected included termination cause, intervention, funding type, publication rates, and journal characteristics. RESULTS In total, 535 clinical trials were examined, across all pathologies clinical trials with significant findings for the primary outcome were published at a higher rate (99%) compared to those with non-significant findings (77%) (p < 0.01). Significantly, more studies with significant findings reached at least 80% of their estimated enrollment goal versus non-significant studies, 72% and 53% respectively (p < 0.01). Three of four metrics for impact of publication showed no difference between significant and non-significant studies once they reached publication. CONCLUSION These findings suggest that clinical trials of three of the most common upper gastrointestinal malignancies have a publication bias towards studies with significant primary outcome findings. This study has implications to the way evidence-based medicine is practiced as the medical literature appears to be failing to capture important data for consideration of clinical decision making.
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Affiliation(s)
- Trenton Lippert
- University of South Florida Morsani College of Medicine, Tampa, FL, USA.
| | - Erin Schmucker
- Nova Southeastern University Kiran C. Patel College of Osteopathic Medicine, Clearwater, FL, USA
| | - Anchal Shukla
- University of South Florida Morsani College of Medicine, Tampa, FL, USA
| | - Ruha Reddy
- University of South Florida Morsani College of Medicine, Tampa, FL, USA
| | - Pooja Neerumalla
- University of South Florida Morsani College of Medicine, Tampa, FL, USA
| | - Gabriella Blanco
- University of South Florida Morsani College of Medicine, Tampa, FL, USA
| | - Vic Velanovich
- Department of Surgery, University of South Florida Morsani College of Medicine, Tampa, FL, USA
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Khan MS, Usman MS, Talha KM, Van Spall HGC, Greene SJ, Vaduganathan M, Khan SS, Mills NL, Ali ZA, Mentz RJ, Fonarow GC, Rao SV, Spertus JA, Roe MT, Anker SD, James SK, Butler J, McGuire DK. Leveraging electronic health records to streamline the conduct of cardiovascular clinical trials. Eur Heart J 2023; 44:1890-1909. [PMID: 37098746 DOI: 10.1093/eurheartj/ehad171] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Revised: 02/05/2023] [Accepted: 03/07/2023] [Indexed: 04/27/2023] Open
Abstract
Conventional randomized controlled trials (RCTs) can be expensive, time intensive, and complex to conduct. Trial recruitment, participation, and data collection can burden participants and research personnel. In the past two decades, there have been rapid technological advances and an exponential growth in digitized healthcare data. Embedding RCTs, including cardiovascular outcome trials, into electronic health record systems or registries may streamline screening, consent, randomization, follow-up visits, and outcome adjudication. Moreover, wearable sensors (i.e. health and fitness trackers) provide an opportunity to collect data on cardiovascular health and risk factors in unprecedented detail and scale, while growing internet connectivity supports the collection of patient-reported outcomes. There is a pressing need to develop robust mechanisms that facilitate data capture from diverse databases and guidance to standardize data definitions. Importantly, the data collection infrastructure should be reusable to support multiple cardiovascular RCTs over time. Systems, processes, and policies will need to have sufficient flexibility to allow interoperability between different sources of data acquisition. Clinical research guidelines, ethics oversight, and regulatory requirements also need to evolve. This review highlights recent progress towards the use of routinely generated data to conduct RCTs and discusses potential solutions for ongoing barriers. There is a particular focus on methods to utilize routinely generated data for trials while complying with regional data protection laws. The discussion is supported with examples of cardiovascular outcome trials that have successfully leveraged the electronic health record, web-enabled devices or administrative databases to conduct randomized trials.
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Affiliation(s)
- Muhammad Shahzeb Khan
- Division of Cardiology, Duke University School of Medicine, 2301 Erwin Rd., Durham, NC 27705, USA
| | - Muhammad Shariq Usman
- Department of Medicine, University of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216, USA
| | - Khawaja M Talha
- Department of Medicine, University of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216, USA
| | - Harriette G C Van Spall
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton, ON, Canada
| | - Stephen J Greene
- Division of Cardiology, Duke University School of Medicine, 2301 Erwin Rd., Durham, NC 27705, USA
- Duke Clinical Research Institute, Durham, NC, USA
| | - Muthiah Vaduganathan
- Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sadiya S Khan
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Nicholas L Mills
- BHF Centre for Cardiovascular Science, University of Edinburgh, Chancellors Building, Royal Infirmary of Edinburgh, Edinburgh, Scotland, UK
- Usher Institute, University of Edinburgh, Edinburgh, Scotland, UK
| | - Ziad A Ali
- DeMatteis Cardiovascular Institute, St Francis Hospital and Heart Center, Roslyn, NY, USA
| | - Robert J Mentz
- Division of Cardiology, Duke University School of Medicine, 2301 Erwin Rd., Durham, NC 27705, USA
- Duke Clinical Research Institute, Durham, NC, USA
| | - Gregg C Fonarow
- Division of Cardiology, University of California Los Angeles, Los Angeles, CA, USA
| | - Sunil V Rao
- Division of Cardiology, New York University Langone Health System, New York, NY, USA
| | - John A Spertus
- Department of Cardiology, Saint Luke's Mid America Heart Institute, Kansas City, MO, USA
- Kansas City's Healthcare Institute for Innovations in Quality, University of Missouri, Kansas, MO, USA
| | - Matthew T Roe
- Division of Cardiology, Duke University School of Medicine, 2301 Erwin Rd., Durham, NC 27705, USA
- Duke Clinical Research Institute, Durham, NC, USA
| | - Stefan D Anker
- Department of Cardiology (CVK), Berlin Institute of Health Center for Regenerative Therapies (BCRT), and German Centre for Cardiovascular Research (DZHK) Partner Site Berlin, Charité Universitätsmedizin, Berlin, Germany
| | - Stefan K James
- Department of Medical Sciences, Scientific Director UCR, Uppsala University, Uppsala, Uppland, Sweden
| | - Javed Butler
- Department of Medicine, University of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216, USA
- Baylor Scott & White Research Institute, Dallas, TX, USA
| | - Darren K McGuire
- Division of Cardiology, Department of Internal Medicine, UT Southwestern Medical Center and Parkland Health and Hospital System, Dallas, TX, USA
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Zhang E, DuBois SG. Early Termination of Oncology Clinical Trials in the United States. Cancer Med 2023; 12:5517-5525. [PMID: 36305832 PMCID: PMC10028157 DOI: 10.1002/cam4.5385] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 10/07/2022] [Accepted: 10/16/2022] [Indexed: 11/08/2022] Open
Abstract
PURPOSE The aim of this study was to evaluate the rate of early trial discontinuation of oncology trials and reasons for early termination, to assess potential trends in rates of oncology trial termination, and to perform a comprehensive analysis of predictors of early termination. This study intends to inform efforts in improving efficiency of the oncology clinical trial enterprise. METHODS We conducted a cross-sectional study of interventional cancer clinical trials registered in ClinicalTrials.gov database from September 27, 2007 to June 30, 2015, with at least one site listed in the United States. We evaluated predictors of early trial termination using Fisher exact or χ2 tests and logistic regression. RESULTS Of 8687 trials, 22.74% (n = 1975) were terminated trials. Rates of early trial termination appeared stable over the study. Statistically significant univariate predictors of early termination for any reason include cancer category, phase, funding source, location, and age. In multivariable analysis, trials spanning multiple cancer categories and international trials were less likely to terminate early whereas phase 2 trials and trials funded by academia/foundation were more likely to terminate early. The most common reason for early termination was "Other, Multiple Reasons, or Unknown" (36.9%), followed by accrual issues (34.5%). In multivariate analysis among all terminated trials, supportive care trials, phase 2 trials, and non-industry funded trials had significantly higher odds of trial discontinuation specifically due to poor accrual. CONCLUSION In this national sample of cancer clinical trials, early trial discontinuation was common. Many factors influenced early trial termination with poor accrual being a common reason. Specific trial features are associated with differential likelihood of early trial termination for any reason and for early trial termination due to poor accrual.
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Affiliation(s)
- Ellen Zhang
- Harvard Medical School, Boston, Massachusetts, USA
| | - Steven G DuBois
- Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Harvard Medical School, Boston, Massachusetts, USA
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5
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Ritchie M, Gillen DL, Grill JD. Recruitment across two decades of NIH-funded Alzheimer's disease clinical trials. Alzheimers Res Ther 2023; 15:28. [PMID: 36732846 PMCID: PMC9893207 DOI: 10.1186/s13195-023-01177-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 01/23/2023] [Indexed: 02/04/2023]
Abstract
BACKGROUND Timely accrual of a representative sample is a key factor in whether Alzheimer's disease (AD) clinical trials successfully answer the scientific questions under study. Studies in other fields have observed that, over time, recruitment to trials has become increasingly reliant on larger numbers of sites, with declines in the average per-site recruitment rate. Here, we examined the trends in recruitment over a 20-year period of NIH-funded AD clinical trials conducted by the Alzheimer's Disease Cooperative Study (ADCS), a temporally consistent network of sites devoted to interventional research. METHODS We performed retrospective analyses of eleven ADCS randomized clinical trials. To examine the recruitment planning, we calculated the expected number of participants to be enrolled per site for each trial. To examine the actual trial recruitment rates, we quantified the number of participants enrolled per site per month. RESULTS No effects of time were observed on recruitment planning or overall recruitment rates across trials. No trial achieved an overall recruitment rate greater than one subject per site per month. We observed the fastest recruitment rates in trials with no competition and the slowest in trials that overlapped in time. The highest recruitment rates were consistently seen early within trials and declined over the course of studies. CONCLUSIONS Trial recruitment projections should plan for fewer than one participant randomized per site per month and consider the number of other AD trials being conducted concurrently.
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Affiliation(s)
- Marina Ritchie
- UC Irvine Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, 92697, USA.
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, 92697, USA.
| | - Daniel L Gillen
- UC Irvine Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, 92697, USA
- Department of Statistics, University of California, Irvine, Irvine, CA, 92697, USA
| | - Joshua D Grill
- UC Irvine Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, 92697, USA
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, 92697, USA
- Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, 92697, USA
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Snyder KL, Merz JF. A census of clinical trials conducted under the U.S. exception from informed consent rule. Acad Emerg Med 2023; 30:133-138. [PMID: 36575604 DOI: 10.1111/acem.14645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 12/06/2022] [Accepted: 12/19/2022] [Indexed: 12/29/2022]
Abstract
BACKGROUND The exception from informed consent (EFIC) rule was adopted in 1996, permitting waiver of informed consent for certain emergency research, including trials funded by the U.S. government. The rule requires prospective consent from patients or their legally authorized representative(s) (LAR) if practicable. For those enrolled without consent, the patient or their LAR must be given an opportunity to opt out from continued participation at the earliest opportunity. We sought to census the trials conducted under the EFIC rule to facilitate research to better understand how the rule is being used. METHODS We conducted a multipronged search to identify all trials conducted under the EFIC rule, drawing on reviews, database searches, examination of the FDA's docket, posting an inquiry on the institutional review board forum, and email requests to lead authors of all published EFIC trials and related review articles. We describe the trials, when they were started and completed, and whether they were terminated early. RESULTS We identified a total of 110 trials as of the end of April 2022: 78 complete, 13 recruiting, seven registered on clinicaltrials.gov but not yet recruiting, five trials that were abandoned before enrolling any subjects, and seven trials in early planning. Nine of the 78 completed trials were pilot or feasibility trials. Of 69 completed full trials, 30 (43.5%) were terminated early. The most common reason for early termination was futility (15 trials, 25.0%) followed by poor recruitment (10 trials, 14.5%). The rate of conduct of trials has been remarkably constant since 2001, with roughly 18 trials started in each 5-year period. CONCLUSIONS We have compiled a census of trials conducted under the U.S. FDA's EFIC rule, the availability of which we hope will stimulate further in-depth data collection and analysis of this set of trials.
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Affiliation(s)
- Krista L Snyder
- Abramson Cancer Center of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jon F Merz
- Department of Medical Ethics & Health Policy, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Morrell W, Gelinas L, Zarin D, Bierer BE. Ensuring the Scientific Value and Feasibility of Clinical Trials: A Qualitative Interview Study. AJOB Empir Bioeth 2023; 14:99-110. [PMID: 36599052 DOI: 10.1080/23294515.2022.2160510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
BACKGROUND Ethical and scientific principles require that clinical trials address an important question and have the resources needed to complete the study. However, there are no clear standards for review that would ensure that these principles are upheld. METHODS We conducted semi-structured interviews with a convenience sample of nineteen experts in clinical trial design, conduct, and/or oversight to elucidate current practice and identify areas of need with respect to ensuring the scientific value and feasibility of clinical trials prior to initiation and while ongoing. We used a priori and grounded theory to analyze the data and constant comparative method to induce higher order themes. RESULTS Interviewees perceived determination of scientific value as the responsibility of the investigator and, secondarily, other parties who review or oversee research. Interviewees reported that ongoing trials are rarely reevaluated due to emerging evidence from external sources, evaluation is complex, and there would be value in the development of standards for monitoring and evaluating evidence systematically. Investigators, IRBs, and/or data monitoring committees (DMCs) could undertake these responsibilities. Feasibility assessments are performed but are typically inadequate; potential solutions are unclear. CONCLUSIONS There are three domains where current approaches are suboptimal and in which further guidance is needed. First, who has the responsibility for conducting scientific review, whether it be the investigator, IRB, and/or DMC is often unclear. Second, the standards for scientific review (e.g., appropriate search terms, data sources, and analytic plan) should be defined. Third, guidance is needed on the evaluation of ongoing studies in light of potentially new and evolving evidence, with particular reference to evidence from outside the trial itself.
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Affiliation(s)
- Walker Morrell
- Multi-Regional Clinical Trials Center, Brigham & Women's Hospital and Harvard, Cambridge, MA, USA
| | - Luke Gelinas
- Multi-Regional Clinical Trials Center, Brigham & Women's Hospital and Harvard, Cambridge, MA, USA.,Advarra IRB, Columbia, MD, USA
| | - Deborah Zarin
- Multi-Regional Clinical Trials Center, Brigham & Women's Hospital and Harvard, Cambridge, MA, USA
| | - Barbara E Bierer
- Multi-Regional Clinical Trials Center, Brigham & Women's Hospital and Harvard, Cambridge, MA, USA.,Harvard Medical School, Boston, MA, USA.,Brigham & Women's Hospital, Boston, MA, USA
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Strong B, Oostema JA, Nikroo N, Hussain M, Reeves MJ. Early Termination of Acute Stroke Randomized Controlled Trials Published Between 2013 and 2020: A Systematic Review. Circ Cardiovasc Qual Outcomes 2021; 14:e007995. [PMID: 34932376 DOI: 10.1161/circoutcomes.121.007995] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Termination of a clinical trial before the maximum planned sample size is accrued can occur for multiple valid reasons but has implications for the interpretation of results. We undertook a systematic review of contemporary acute stroke trials to document the prevalence of and reasons for early termination. METHODS We searched MEDLINE for randomized controlled trials of acute stroke therapies published between 2013 and 2020 in 9 major clinical journals. Manuscripts describing the primary results of phase 2 and phase 3 trials of acute stroke care were included. Data on study characteristics and adherence to CONSORT reporting guidelines were abstracted and summarized using descriptive statistics. Where feasible, we compared treatment effect sizes between trials terminated early and those not terminated early. RESULTS Of 96 randomized controlled trials, 39 (41%) were terminated early, 84 (88%) had a data and safety monitoring board, and 57 (59%) reported a prespecified statistical stopping rule. Among the 39 trials terminated early, 10 were discontinued for benefit, 10 due to logistical issues, 8 for futility, 6 because of newly available evidence, 1 for harm, and 4 for other or a combination of reasons. The median percentage of the maximum planned sample size accrued among trials terminated early was 63% (range, 8%-89%). Only 55% of trials (53 of 96) reported whether interim efficacy analyses were conducted, as recommended by the CONSORT guidelines. When 10 endovascular therapy trials were compared according to early termination status, the effect sizes of trials terminated early for benefit were only modestly larger than those not terminated early. CONCLUSIONS The high prevalence of early termination in combination with the wide variety of reasons underscores the necessity of meticulous trial planning and adherence to methodological and reporting guidelines for early termination. Registration: URL: https://www.crd.york.ac.uk/prospero/; Unique identifier: CRD42019128727.
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Affiliation(s)
- Brent Strong
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (B.S., N.N., M.H., M.J.R.)
| | - J Adam Oostema
- Department of Emergency Medicine, Michigan State University, Grand Rapids (J.A.O.)
| | - Nadia Nikroo
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (B.S., N.N., M.H., M.J.R.)
| | - Murtaza Hussain
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (B.S., N.N., M.H., M.J.R.)
| | - Mathew J Reeves
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (B.S., N.N., M.H., M.J.R.)
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Barnett AG, Glasziou P. Target and actual sample sizes for studies from two trial registries from 1999 to 2020: an observational study. BMJ Open 2021. [PMCID: PMC8719224 DOI: 10.1136/bmjopen-2021-053377] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
Objectives To investigate differences between target and actual sample sizes, and what study characteristics were associated with sample sizes. Design Observational study. Setting The large trial registries of clinicaltrials.gov (starting in 1999) and ANZCTR (starting in 2005) through to 2021. Participants Over 280 000 interventional studies excluding studies that were withheld, terminated for safety reasons or were expanded access. Main outcome measures The actual and target sample sizes, and the within-study ratio of the actual to target sample size. Results Most studies were small: the median actual sample sizes in the two databases were 60 and 52. There was a decrease over time in the target sample size of 9%–10% per 5 years, and a larger decrease of 18%–21% per 5 years for the actual sample size. The actual-to-target sample size ratio was 4.1% lower per 5 years, meaning more studies (on average) failed to hit their target sample size. Conclusion Registered studies are more often under-recruited than over-recruited and worryingly both target and actual sample sizes appear to have decreased over time, as has the within-study gap between the target and actual sample size. Declining sample sizes and ongoing concerns about underpowered studies mean more research is needed into barriers and facilitators for improving recruitment and accessing data.
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Affiliation(s)
- Adrian Gerard Barnett
- Australian Centre for Health Services Innovation and Centre for Healthcare Transformation, School of Public Health & Social Work, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Paul Glasziou
- CREBP, Bond University, Robina, Queensland, Australia
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Krutsinger DC, Yadav KN, Harhay MO, Bartels K, Courtright KR. A systematic review and meta-analysis of enrollment into ARDS and sepsis trials published between 2009 and 2019 in major journals. Crit Care 2021; 25:392. [PMID: 34781998 PMCID: PMC8591428 DOI: 10.1186/s13054-021-03804-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 10/26/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Enrollment problems are common among randomized controlled trials conducted in the ICU. However, little is known about actual trial enrollment rates and influential factors. We set out to determine the overall enrollment rate in recent randomized controlled trials (RCTs) of patients with acute respiratory distress syndrome (ARDS), acute lung injury (ALI), or sepsis, and which factors influenced enrollment rate. METHODS We conducted a systematic review by searching Pubmed using predefined terms for ARDS/ALI and sepsis to identify individually RCTs published among the seven highest impact general medicine and seven highest impact critical care journals between 2009 and 2019. Cluster randomized trials were excluded. Data were extracted by two independent reviewers using an electronic database management system. We conducted a random-effects meta-analysis of the eligible trials for the primary outcome of enrollment rate by time and site. RESULTS Out of 457 articles identified, 94 trials met inclusion criteria. Trials most commonly evaluated pharmaceutical interventions (53%), were non-industry funded (78%), and required prospective informed consent (81%). The overall mean enrollment rate was 0.83 (95% confidence interval: 0.57-1.21) participants per month per site. Enrollment in ARDS/ALI and sepsis trials were 0.48 (95% CI 0.32-0.70) and 0.98 (95% CI 0.62-1.56) respectively. The enrollment rate was significantly higher for single-center trials (4.86; 95% CI 2.49-9.51) than multicenter trials (0.52; 95% CI 0.41-0.66). Of the 36 trials that enrolled < 95% of the target sample size, 8 (22%) reported slow enrollment as the reason. CONCLUSIONS In this systematic review and meta-analysis, recent ARDS/ALI and sepsis clinical trials had an overall enrollment rate of less than 1 participant per site per month. Novel approaches to improve critical care trial enrollment efficiency are needed to facilitate the translation of best evidence into practice.
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Affiliation(s)
- Dustin C. Krutsinger
- Division of Pulmonary, Critical Care, and Sleep Medicine, University of Nebraska Medical Center, 985910 NE Medical Center, Omaha, NE 68198 USA
| | - Kuldeep N. Yadav
- Palliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, 300 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104 USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Michael O. Harhay
- Palliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, 300 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104 USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
- Pulmonary, Allergy, and Critical Care Division, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Karsten Bartels
- Department of Anesthesiology, University of Nebraska Medical Center, 985910 NE Medical Center, Omaha, NE 68198 USA
| | - Katherine R. Courtright
- Palliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, 300 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104 USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
- Pulmonary, Allergy, and Critical Care Division, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
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11
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Huo BN, Ai ML, Jia YT, Liu Y, Wang Y, Yin NG, Song L. General characteristics and reasons for the discontinuation of drug clinical trials in mainland China. BMC Med Res Methodol 2021; 21:246. [PMID: 34773983 PMCID: PMC8590359 DOI: 10.1186/s12874-021-01443-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 10/22/2021] [Indexed: 11/18/2022] Open
Abstract
Background Although discontinuation is common in clinical trials, no study has been conducted to analyse the current situation and reasons for the suspension or discontinuation of drug clinical trials in China. This study aims to analyse the general characteristics and reasons for the discontinuation of registered clinical trials in mainland China and to identify the associated factors. Methods We conducted a cross-sectional observational study of discontinued trials registered in the Drug Trial Registration and Information Publication Platform before March 31, 2020. All trials with a status of terminated or stopped recorded in the platform were classified as discontinued trials and included in the analysis. The basic characteristics of the discontinued trials were recorded, reasons for trial discontinuation were recorded and divided into 4 categories as drug development strategy, trial planning, trial conduct and studied drug. Pearson’s chi-square test and fisher’s exact test were used to compare the differences in reasons for discontinuation between neoplasm trials and non-neoplasm trials, and to examine the associations of trial characteristics with different reasons related to trials discontinuation. Results Three hundred twelve discontinued trials were included in this study. The studied drugs were mainly chemical drugs [229 (73.4%)], and indications of the studied drugs were mainly neoplasms [77 (24.7%)]. Geographical location of the discontinued trials were mostly in northern [114 (36.5%)] and eastern [96 (30.8%)] China. Study type of the included trials was mainly bioequivalence studies [97 (31.1%)]. The most common reason for trial discontinuation was commercial or strategic decision [84 (26.9%)], followed by futility/lack of efficacy [70 (22.4%)]. The number of trial centers, sample size and whether participants had been enrolled were significantly associated with trial discontinuation (P < 0.05). Multiple center trials showed a higher rate of trial discontinuation due to trial conduct related reasons than single center trials (P < 0.05), trials with sample size > 500 showed a higher rate of trial discontinuation due to studied drug related reasons (P < 0.05), and trials enrolled participants showed a lower rate of trial discontinuation due to commercial or strategic decision and a higher rate of trial discontinuation due to studied drug related reasons than trials without enrolled participants (P < 0.05). Besides, neoplasm trials showed a higher rate of trial discontinuation due to poor recruitment and safety comparing with non-neoplasm trials (P < 0.05). Conclusions Trial discontinuation in China mainly occurred because of commercial or strategic decision and futility/lack of efficacy of the studied drug. Clinical trials with multiple centers and a large sample size may more likely be discontinued due to trial conduct related reasons such as good clinical practice. Discontinuation due to drug safety and lack of efficacy in multiple center trials with a large sample size deserves more attention to avoid resources wastes. Full communication with regulatory authorities such as Center for Drug Evaluation and research institutes to develop a feasible protocol is important for sponsors to avoid trial discontinuation due to protocol issues.
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Affiliation(s)
- Ben-Nian Huo
- Department of Pharmacy Children' s Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing Clinical pharmacy Key Specialty Construction Project, Chongqing, China
| | - Mao-Lin Ai
- Department of Pharmacy Children' s Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing Clinical pharmacy Key Specialty Construction Project, Chongqing, China
| | - Yun-Tao Jia
- Department of Pharmacy Children' s Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing Clinical pharmacy Key Specialty Construction Project, Chongqing, China
| | - Yao Liu
- Department of Pharmacy, Daping Hospital, Army Medical University, Chongqing, China
| | - Yang Wang
- Department of Pharmacy Children' s Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing Clinical pharmacy Key Specialty Construction Project, Chongqing, China
| | - Nan-Ge Yin
- Department of Pharmacy Children' s Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing Clinical pharmacy Key Specialty Construction Project, Chongqing, China
| | - Lin Song
- Department of Pharmacy Children' s Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing Clinical pharmacy Key Specialty Construction Project, Chongqing, China.
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12
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Azzolina D, Lorenzoni G, Bressan S, Da Dalt L, Baldi I, Gregori D. Handling Poor Accrual in Pediatric Trials: A Simulation Study Using a Bayesian Approach. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:2095. [PMID: 33669985 PMCID: PMC7924849 DOI: 10.3390/ijerph18042095] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 02/11/2021] [Accepted: 02/13/2021] [Indexed: 02/05/2023]
Abstract
In the conduction of trials, a common situation is related to potential difficulties in recruiting the planned sample size as provided by the study design. A Bayesian analysis of such trials might provide a framework to combine prior evidence with current evidence, and it is an accepted approach by regulatory agencies. However, especially for small trials, the Bayesian inference may be severely conditioned by the prior choices. The Renal Scarring Urinary Infection (RESCUE) trial, a pediatric trial that was a candidate for early termination due to underrecruitment, served as a motivating example to investigate the effects of the prior choices on small trial inference. The trial outcomes were simulated by assuming 50 scenarios combining different sample sizes and true absolute risk reduction (ARR). The simulated data were analyzed via the Bayesian approach using 0%, 50%, and 100% discounting factors on the beta power prior. An informative inference (0% discounting) on small samples could generate data-insensitive results. Instead, the 50% discounting factor ensured that the probability of confirming the trial outcome was higher than 80%, but only for an ARR higher than 0.17. A suitable option to maintain data relevant to the trial inference is to define a discounting factor based on the prior parameters. Nevertheless, a sensitivity analysis of the prior choices is highly recommended.
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Affiliation(s)
- Danila Azzolina
- Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, 35128 Padova, Italy; (D.A.); (G.L.); (I.B.)
- Department of Translational Medicine, University of Eastern Piedmont, 28100 Novara, Italy
| | - Giulia Lorenzoni
- Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, 35128 Padova, Italy; (D.A.); (G.L.); (I.B.)
| | - Silvia Bressan
- Department of Women’s and Children’s Health, University of Padova, 35128 Padova, Italy; (S.B.); (L.D.D.)
| | - Liviana Da Dalt
- Department of Women’s and Children’s Health, University of Padova, 35128 Padova, Italy; (S.B.); (L.D.D.)
| | - Ileana Baldi
- Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, 35128 Padova, Italy; (D.A.); (G.L.); (I.B.)
| | - Dario Gregori
- Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac Thoracic Vascular Sciences and Public Health, University of Padova, 35128 Padova, Italy; (D.A.); (G.L.); (I.B.)
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13
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Obstacles to the reuse of study metadata in ClinicalTrials.gov. Sci Data 2020; 7:443. [PMID: 33339830 PMCID: PMC7749162 DOI: 10.1038/s41597-020-00780-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Accepted: 11/24/2020] [Indexed: 02/08/2023] Open
Abstract
Metadata that are structured using principled schemas and that use terms from ontologies are essential to making biomedical data findable and reusable for downstream analyses. The largest source of metadata that describes the experimental protocol, funding, and scientific leadership of clinical studies is ClinicalTrials.gov. We evaluated whether values in 302,091 trial records adhere to expected data types and use terms from biomedical ontologies, whether records contain fields required by government regulations, and whether structured elements could replace free-text elements. Contact information, outcome measures, and study design are frequently missing or underspecified. Important fields for search, such as condition and intervention, are not restricted to ontologies, and almost half of the conditions are not denoted by MeSH terms, as recommended. Eligibility criteria are stored as semi-structured free text. Enforcing the presence of all required elements, requiring values for certain fields to be drawn from ontologies, and creating a structured eligibility criteria element would improve the reusability of data from ClinicalTrials.gov in systematic reviews, metanalyses, and matching of eligible patients to trials.
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14
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Dutta S, Kaur R, Haque M, Bhardwaj P, Saxena D, Rahman NAA, Lugova H, Jahan D, Islam S, Chowdhury TS, Charan J. <p>Terminated Interventional Trials in the Clinical Trial Registry of India Database: An Analysis to Evaluate the Reasons for Termination</p>. OPEN ACCESS JOURNAL OF CLINICAL TRIALS 2020. [DOI: 10.2147/oajct.s285177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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15
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Daudelin DH, Peterson LE, Selker HP. Pilot test of an accrual Common Metric for the NIH Clinical and Translational Science Awards (CTSA) Consortium: Metric feasibility and data quality. J Clin Transl Sci 2020; 5:e44. [PMID: 33948266 PMCID: PMC8057372 DOI: 10.1017/cts.2020.537] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 08/27/2020] [Accepted: 08/31/2020] [Indexed: 11/07/2022] Open
Abstract
Failure to accrue participants into clinical trials incurs economic costs, wastes resources, jeopardizes answering research questions meaningfully, and delays translating research discoveries into improved health. This paper reports the results of a pilot test of the Median Accrual Ratio (MAR) metric developed as a part of the Common Metrics Initiative of the NIH's National Center for Advancing Translational Science (NCATS) Clinical and Translational Science Award (CTSA) Consortium. Using the metric is intended to enhance the ability of the CTSA Consortium and its "hubs" to increase subject accrual into trials within expected timeframes. The pilot test was undertaken at Tufts Clinical and Translational Science Institute (CTSI) with eight CTSA Consortium hubs. We describe the pilot test methods, and results regarding feasibility of collecting metric data and the quality of data that was collected. Participating hubs welcomed the opportunity to assess accrual efforts, but experienced challenges in collecting accrual metric data due to insufficient infrastructure and inconsistent implementation of electronic data systems and lack of uniform data definitions. Also, the metric could not be constructed for all trial designs, particularly those using competitive enrollment strategies. We offer recommendations to address the identified challenges to facilitate progress to broad accrual metric data collection and use.
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Affiliation(s)
- Denise H. Daudelin
- Tufts Clinical and Translational Science Institute, Tufts University, Boston, MA, USA
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA
| | - Laura E. Peterson
- Tufts Clinical and Translational Science Institute, Tufts University, Boston, MA, USA
| | - Harry P. Selker
- Tufts Clinical and Translational Science Institute, Tufts University, Boston, MA, USA
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA
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16
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de Melo-Martín I, Holtzman M, Hacker KS. "I Want to Do It, But I Want to Make Sure That I Do It Right." Views of Patients with Parkinson's Disease Regarding Early Stem Cell Clinical Trial Participation. AJOB Empir Bioeth 2020; 11:160-171. [PMID: 32516056 PMCID: PMC8212889 DOI: 10.1080/23294515.2020.1775721] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Background: First-in-human clinical trials with stem cells for Parkinson's disease (PD) are on the horizon. Their epistemic success depends on ensuring the participation of a sufficient number and appropriately diverse group of patients with PD. Their ethical soundness requires that the research community ensures that subjects' decisions about whether to participate or not are consistent with participants' values, motivations, and goals. We sought to identify PD patients' knowledge, concerns, and expectations regarding early-phase stem cell research in PD. Methods: We conducted five semi-structured focus groups with patients with PD. Group discussions were recorded, transcribed, and coded to identify participants' knowledge, concerns, and expectations regarding participation in early stem cell clinical research in PD. Results: Four themes were generated from our data analysis: (1) participants' skepticism about the potential benefits of these trials; (2) their desire to obtain information about various aspects related to this research; (3) a recognition that accessing available knowledge was often difficult; and (4) the relevance of trusting relationships with various stakeholders. Conclusions: Participants expressed skepticism about the immediate impact of stem cell research. Nonetheless, such skepticism often reflected an appropriate consideration of the risks and potential benefits of participating in high-risk clinical trials. Despite their skepticism, participants were eager to learn more about stem cell research and clinical trials processes. They identified consistently trusted avenues of knowledge on these topics, but they often found it difficult to access relevant information or to determine its value.
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Affiliation(s)
- Inmaculada de Melo-Martín
- Weill Cornell Medical College, Division of Medical Ethics, 407 E.61st St., RR-212, New York, NY 10065
| | - Michael Holtzman
- The New School for Social Research, Psychology Department, 80 Fifth Avenue, 6 Floor, New York, NY 10011
| | - Katrina S. Hacker
- The New School for Social Research, Psychology Department, 80 Fifth Avenue, 6 Floor, New York, NY 10011
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17
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Blümle A, Haag T, Balmford J, Rücker G, Schumacher M, Binder N. A multi-state model analysis of the time from ethical approval to publication of clinical research studies. PLoS One 2020; 15:e0230797. [PMID: 32218603 PMCID: PMC7100954 DOI: 10.1371/journal.pone.0230797] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 03/09/2020] [Indexed: 11/22/2022] Open
Abstract
Background Results of medical research should be made publicly available in a timely manner to enable patients and health professionals to make informed decisions about health issues. We aimed to apply a multi-state model to analyze the overall time needed to publish study results, and to examine predictors of the timing of transitions within the research process from study initiation through completion/discontinuation to eventual publication. Methods Using a newly developed multi-state model approach, we analysed the effect of different study-related factors on each of the transitions from study approval to eventual publication, using a data set of clinical studies approved by a German research ethics committee between 2000 and 2002. Results Of 917 approved studies, 806 were included in our analyses. About half of the clinical studies which began were subsequently published as full articles, and the median time from study approval to publication was 10 years. Differences across model states were apparent; several factors were predictive of the transition from study approval to completion, while funding source and collaboration were predictive of the transition from completion to publication. Conclusions The proposed multi-state model approach permits a more comprehensive analysis of time to publication than a simple examination of the transition from approval to publication, and thus the findings represent an advance on previous studies of this aspect of the research process.
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Affiliation(s)
- Anette Blümle
- Institute for Evidence in Medicine (for Cochrane Germany Foundation), Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
- * E-mail:
| | - Tobias Haag
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - James Balmford
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
- Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Gerta Rücker
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Martin Schumacher
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Nadine Binder
- Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
- Institute of Digitalization in Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
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18
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Krutsinger DC, Yadav KN, Cooney E, Brooks S, Halpern SD, Courtright KR. A pilot randomized trial of five financial incentive strategies to increase study enrollment and retention rates. Contemp Clin Trials Commun 2019; 15:100390. [PMID: 31431933 PMCID: PMC6580090 DOI: 10.1016/j.conctc.2019.100390] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Revised: 05/21/2019] [Accepted: 06/01/2019] [Indexed: 11/21/2022] Open
Abstract
Background Enrollment and retention difficulties remain major barriers to conducting clinical trials. Financial incentives may promote clinical trial enrollment, however delivery methods to maximize enrollment, maximize retention, and minimize cost remains uncertain. Methods We conducted a single-blind, web-based randomized controlled trial of five financial incentive strategies on enrollment and retention rates in a longitudinal study of advance directives among community-dwelling older adults. Participants were eligible to receive a fixed total financial incentive, but the disbursement amounts at each study timepoint (baseline, 2-weeks, 4-weeks, and 6-weeks) differed between study arms. At each timepoint, participants completed a different advance directive. We conducted an intention-to-treat analysis for the primary and secondary outcomes of enrollment and retention. Results 1803 adults were randomized to one of five incentive strategies: constant n = 361; increasing n = 357; U-shaped n = 361; surprise n = 360; self-select n = 364. Overall, 989 (54.9%) participants elected to enroll in the advance directive study. There were no differences in enrollment rates between the control (constant 53.5%) and any of the four intervention study arms (increasing 54.3%, p = 0.81; U-shaped 57.3%, p = 0.30; surprise 56.9%, p = 0.35; and self-select 52.2%, p = 0.73). There were no differences in retention rates between the control (constant 2.1%) and any of the four intervention study arms (increasing 5.2%, p = 0.09; U-shaped 3.9%, p = 0.23; surprise 2.4%, p = 0.54; self-select 2.1%, p = 0.63). Conclusions Financial incentive programs for trial enrollment informed by behavioral economic insights were no more effective than a constant-payment approach in this web-based pilot study.
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Affiliation(s)
- Dustin C Krutsinger
- Palliative and Advanced Illness Research Center, USA.,Fostering Improvement in End-of-Life Decision Science Program, USA.,Center of Health Incentives and Behavioral Economics, USA.,Leonard Davis Institute of Health Economics, USA.,Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kuldeep N Yadav
- Palliative and Advanced Illness Research Center, USA.,Fostering Improvement in End-of-Life Decision Science Program, USA.,Center of Health Incentives and Behavioral Economics, USA
| | - Elizabeth Cooney
- Palliative and Advanced Illness Research Center, USA.,Fostering Improvement in End-of-Life Decision Science Program, USA.,Center of Health Incentives and Behavioral Economics, USA.,Leonard Davis Institute of Health Economics, USA
| | - Steven Brooks
- Palliative and Advanced Illness Research Center, USA
| | - Scott D Halpern
- Palliative and Advanced Illness Research Center, USA.,Fostering Improvement in End-of-Life Decision Science Program, USA.,Center of Health Incentives and Behavioral Economics, USA.,Leonard Davis Institute of Health Economics, USA.,Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Katherine R Courtright
- Palliative and Advanced Illness Research Center, USA.,Fostering Improvement in End-of-Life Decision Science Program, USA.,Center of Health Incentives and Behavioral Economics, USA.,Leonard Davis Institute of Health Economics, USA.,Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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19
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Guinn D, Wilhelm EE, Lieberman G, Khozin S. Assessing function of electronic health records for real-world data generation. BMJ Evid Based Med 2019; 24:95-98. [PMID: 30478146 DOI: 10.1136/bmjebm-2018-111111] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/08/2018] [Indexed: 01/08/2023]
Affiliation(s)
- Daphne Guinn
- Program for Regulatory Science and Medicine, Georgetown University, Washington, District of Columbia, USA
- Department of Pharmacology and Physiology, Georgetown University, Washington, District of Columbia, USA
| | - Erin E Wilhelm
- Department of Pharmacology and Physiology, Georgetown University, Washington, District of Columbia, USA
| | | | - Sean Khozin
- US Food and Drug Administration, Silver Spring, Maryland, USA
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20
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O'Neill ZR, Deptuck HM, Quong L, Maclean G, Villaluna K, King-Azote P, Sharma M, Butcher K, Hart RG, Field TS. Who says "no" to participating in stroke clinical trials and why: an observational study from the Vancouver Stroke Program. Trials 2019; 20:313. [PMID: 31151483 PMCID: PMC6545028 DOI: 10.1186/s13063-019-3434-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Accepted: 05/13/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Successful stroke trials require adequate recruitment. In this observational study, we assessed reasons for refusal to provide informed consent in eligible patients approached for clinical trial participation at the Vancouver Stroke Program. METHODS We assessed screening logs from four trials that were actively recruiting at our center: three randomized trials, two of which investigated different antithrombotic strategies for secondary prevention (NAVIGATE-ESUS, NCT02313909 12/2014; DATAS-II, NCT02295826 11/2014) and one that investigated surgery plus medical management versus medical management alone for primary prevention (CREST-2, NCT02089217 03/2014). The fourth study was observational and non-randomized; all participants received an external monitoring device (PROPHECY, NCT03712865 10/2018). Screening logs from June 2015 to April 2017 were reviewed retrospectively. Subsequently, we used a prospective structured case report form for screening (May 2017-March 2018). We assessed and compared refusal rates between trials, demographics of those refusing consent, and their reasons for doing so. We used descriptive statistics, chi-square and Fisher's exact tests as appropriate for non-parametric data, and t-tests for parametric data. We examined likelihood of refusal by sex using multivariable logistic regression models including age and trial intervention as co-variables. RESULTS A total of 235 patients (43% women) were approached for consent. More patients refused the surgical (59%) and antithrombotic trials (53%) compared with the non-randomized external monitoring device study (13%) (p < 0.001). Surgical trial refusals were primarily due to a desire for certainty in receiving a particular intervention (39%), with the majority of those patients wanting surgery. Refusals for the antithrombotic trials were mainly due to concerns with the potential side effects of the study drug (41%); refusals in the device trial were mainly due to disinterest (46%). Women refused participation more often than men (48% vs 33%). Women remained less likely to consent than men, even after adjustment for age and trial intervention (OR 0.46, 95% CI 0.26-0.82, p = 0.009). CONCLUSIONS Concern surrounding drug safety, randomization, and disinterest were the chief deterrents to enrolment; there were also differences in rates of consent by gender. A better understanding of why patients refuse participation in stroke trials may help to develop future patient-directed communication strategies to improve enrolment. Further research is required to better understand the reasons underlying gender disparities in consent rates.
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Affiliation(s)
- Zoe R O'Neill
- Vancouver Stroke Program - Research Office, 8295-2775 Laurel Street, Vancouver,, BC, V5Z 1M9, Canada
| | - Halina M Deptuck
- Vancouver Stroke Program - Research Office, 8295-2775 Laurel Street, Vancouver,, BC, V5Z 1M9, Canada
| | - Lauren Quong
- Vancouver Stroke Program - Research Office, 8295-2775 Laurel Street, Vancouver,, BC, V5Z 1M9, Canada.,Faculty of Medicine, Memorial University, 300 Prince Philip Drive, St. John's, NL, A1B 3V6, Canada
| | - Genoveva Maclean
- Vancouver Stroke Program - Research Office, 8295-2775 Laurel Street, Vancouver,, BC, V5Z 1M9, Canada
| | - Karina Villaluna
- Vancouver Stroke Program - Research Office, 8295-2775 Laurel Street, Vancouver,, BC, V5Z 1M9, Canada
| | - Princess King-Azote
- Vancouver Stroke Program - Research Office, 8295-2775 Laurel Street, Vancouver,, BC, V5Z 1M9, Canada
| | - Mukul Sharma
- Population Health Research Institute, Hamilton Health Sciences, 237 Barton Street East, Hamilton, ON, L8L 2X2, Canada.,Faculty of Medicine, McMaster University, 237 Barton St. E., Hamilton, ON, L8L 2X2, Canada
| | - Ken Butcher
- University of New South Wales, Prince of Wales Clinical School, Level 1, South Wing, Edmund Blacket Building Prince of Wales Hospital, Ranwick, NSW, 2031, Australia
| | - Robert G Hart
- Population Health Research Institute, Hamilton Health Sciences, 237 Barton Street East, Hamilton, ON, L8L 2X2, Canada
| | - Thalia S Field
- Vancouver Stroke Program - Research Office, 8295-2775 Laurel Street, Vancouver,, BC, V5Z 1M9, Canada. .,Faculty of Medicine, University of British Columbia, S169-2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada.
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21
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Follett L, Geletta S, Laugerman M. Quantifying risk associated with clinical trial termination: A text mining approach. Inf Process Manag 2019. [DOI: 10.1016/j.ipm.2018.11.009] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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22
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Guinn D, Wilhelm EE, Shoulson I. Reasons for Premature Conclusion of Late Phase Clinical Trials: An Analysis of ClinicalTrials.gov Registered Phase III Trials. Ther Innov Regul Sci 2019. [DOI: 10.1177/2168479019830648] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Daphne Guinn
- Program for Regulatory Science & Medicine, Georgetown University, Washington, DC, USA
- Department of Pharmacology and Physiology, Georgetown University, Washington, DC, USA
| | - Erin E. Wilhelm
- Department of Pharmacology and Physiology, Georgetown University, Washington, DC, USA
| | - Ira Shoulson
- Program for Regulatory Science & Medicine, Georgetown University, Washington, DC, USA
- Department of Pharmacology and Physiology, Georgetown University, Washington, DC, USA
- Department of Neurology, Georgetown University, Washington, DC, USA
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Samman Tahhan A, Vaduganathan M, Greene SJ, Okafor M, Kumar S, Butler J. Evolving Landscape of Clinical Trials in Heart Failure: Patient Populations, Endpoint Selection, and Regions of Enrollment. Curr Heart Fail Rep 2019; 15:10-16. [PMID: 29350324 DOI: 10.1007/s11897-018-0374-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
PURPOSE OF REVIEW Clinical trial design and execution are evolving as increasingly important considerations with respect to the success of heart failure trials. The current review highlights temporal trends in characteristics of heart failure clinical trials. RECENT FINDINGS Recent trials in heart failure have required longer recruitment phases, displayed inefficient enrollment rates, increased use of composite and nonfatal endpoints, undergone rapid globalization, and gradually increased focus on heart failure with preserved ejection fraction. Understanding patterns and trends in clinical trial design and execution may inform future planning and conduct of trials of heart failure therapeutics.
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Affiliation(s)
- Ayman Samman Tahhan
- Emory Clinical Cardiovascular Research Institute, Emory University School of Medicine, Atlanta, GA, USA
| | - Muthiah Vaduganathan
- Brigham and Women's Hospital Heart & Vascular Center and Harvard Medical School, Boston, MA, USA
| | - Stephen J Greene
- Duke Clinical Research Institute and Division of Cardiology, Duke University Medical Center, Durham, NC, USA
| | - Maureen Okafor
- Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Sonali Kumar
- Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Javed Butler
- Division of Cardiology, Health Sciences Center, Stony Brook University, T-16, Room 080, SUNY, Stony Brook, NY, 11794, USA.
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Krutsinger DC, McMahon J, Stephens-Shields AJ, Bayes B, Brooks S, Hitsman BL, Lubitz SF, Reyes C, Schnoll RA, Ryan Greysen S, Mercede A, Patel MS, Reale C, Barg F, Karlawish J, Polsky D, Volpp KG, Halpern SD. Randomized evaluation of trial acceptability by INcentive (RETAIN): Study protocol for two embedded randomized controlled trials. Contemp Clin Trials 2019; 76:1-8. [PMID: 30414865 PMCID: PMC6354250 DOI: 10.1016/j.cct.2018.11.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Revised: 11/02/2018] [Accepted: 11/06/2018] [Indexed: 10/27/2022]
Abstract
INTRODUCTION The most common and conceptually sound ethical concerns with financial incentives for research participation are that they may (1) represent undue inducements by blunting peoples' perceptions of research risks, thereby preventing fully informed consent; or (2) represent unjust inducements by encouraging enrollment preferentially among the poor. Neither of these concerns has been shown to manifest in studies testing the effects of incentives on decisions to participate in hypothetical randomized clinical trials (RCTs), but neither has been assessed in real RCTs. METHODS AND ANALYSES We are conducting randomized trials of real incentives embedded within two parent RCTs. In each of two trials conducted in parallel, we are randomizing 576 participants to one of three incentive groups. Following preliminary determination of patients' eligibility in the parent RCT, we assess patients' research attitudes, demographic characteristics, perceived research risks, time spent reviewing consent documents, ability to distinguish research from patient care, and comprehension of key trial features. These quantitative assessments will be supplemented by semi-structured interviews for a selected group of participants that more deeply explore patients' motivations for trial participation. The trials are each designed to have adequate power to rule out undue and unjust inducement. We are also exploring potential benefits of incentives, including possible increased attention to research risks and cost-effectiveness.
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Affiliation(s)
- Dustin C Krutsinger
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Palliative and Advanced Illness Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Center for Health Incentives and Behavioral Economics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.
| | - Jacqueline McMahon
- Palliative and Advanced Illness Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Alisa J Stephens-Shields
- Palliative and Advanced Illness Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Brian Bayes
- Palliative and Advanced Illness Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Steven Brooks
- Palliative and Advanced Illness Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Brian L Hitsman
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Su Fen Lubitz
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Celine Reyes
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Robert A Schnoll
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - S Ryan Greysen
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ashley Mercede
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Mitesh S Patel
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Center for Health Incentives and Behavioral Economics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA; Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Catherine Reale
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Fran Barg
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA; Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; Department of Anthropology, University of Pennsylvania School of Arts and Sciences, Philadelphia, PA, United States
| | - Jason Karlawish
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn Memory Center at the Penn Neuroscience Center, Philadelphia, PA, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel Polsky
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Center for Health Incentives and Behavioral Economics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA; Department of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
| | - Kevin G Volpp
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Center for Health Incentives and Behavioral Economics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA; Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA; Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Scott D Halpern
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Palliative and Advanced Illness Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Center for Health Incentives and Behavioral Economics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA; Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Lorenzoni G, Comoretto RI, Ruffolo M, Azzolina D, Baldi I. Pediatric Trials Run in India: An Analysis of Clinical Trials.gov 2006-2015. Indian J Pediatr 2019; 86:10-14. [PMID: 30648225 DOI: 10.1007/s12098-018-2825-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 11/16/2018] [Indexed: 01/19/2023]
Abstract
OBJECTIVE To present a snapshot of 10 y of pediatric research, with a focus on trials with at least one enrolling site in India. METHODS The study included all interventional trials registered at ClinicalTrials.gov from January 2006 through December 2015, enrolling patients aged 0 to 18 y. The database for Aggregate Analysis of ClinicalTrials.gov (AACT) was the data source used. RESULTS Nine thousand, six hundred forty-eight pediatric clinical studies were identified. Of these, 193 had at least one enrolling site in India. The primary purpose for most of these trials was treatment (n = 92) and prevention (n = 65) coupled with an efficacy and/or safety endpoint (n = 158). Infant and toddlers were eligible for enrollment in the majority of trials (97%) while neonates only in 22% of trials. The rate of early termination or withdrawal was 5%. The most commonly studied conditions were bacterial infections, viruses, digestive and mental diseases. Overall, communicable diseases (n = 75) and major non-communicable diseases (n = 72) were equally investigated. CONCLUSIONS The most commonly studied therapeutic areas in trials enrolling from India and registered in ClinicalTrials.gov were appropriate for India public health needs and patients were not enrolled into studies inappropriately from this perspective.
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Affiliation(s)
- Giulia Lorenzoni
- Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padua, Padua, Italy
| | - Rosanna Irene Comoretto
- Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padua, Padua, Italy
| | - Mariangela Ruffolo
- Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padua, Padua, Italy
| | - Danila Azzolina
- Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padua, Padua, Italy
| | - Ileana Baldi
- Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padua, Padua, Italy.
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Baldi I, Gregori D, Desideri A, Berchialla P. Accrual monitoring in cardiovascular trials. Open Heart 2017; 4:e000720. [PMID: 29344371 PMCID: PMC5761309 DOI: 10.1136/openhrt-2017-000720] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2017] [Revised: 11/08/2017] [Accepted: 11/18/2017] [Indexed: 11/24/2022] Open
Abstract
Objective To provide brief guidance on how to design accrual monitoring activities in a clinical trial protocol. Setting Two completed clinical trials that did not achieve the planned sample size, the Cost of Strategies After Myocardial Infarction (COSTAMI) trial and the Biventricular Pacing After Cardiac Surgery (BiPACS) trial. Design A Bayesian monitoring tool, the constant accrual model, is applied retrospectively to accrual data from each case study to illustrate how the tool could be used to identify problems with accrual early in the trial period and to frame the conditions in which the approach can be used in practice. Results After 312 days and 155 patients enrolled in the COSTAMI trial, accrual could be classified as ‘off target’ on the basis of statistical criteria outlined in the protocol. As for the BiPACS trial, after 2 years, it was already evident that the accrual was ‘considerably off target’. Conclusions Prompt awareness of a high risk of accrual failure could trigger different interventions to overcome protocol-related, patient-related or investigator-related barriers to recruitment or ultimately contribute to an early stopping decision due to recruitment futility. Accrual prediction models should be included as standard tools for routine monitoring activities in cardiovascular research. Among them, methods relying on the Bayesian approach are particularly attractive, as they can naturally update past evidence when actual accrual data becomes available.
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Affiliation(s)
- Ileana Baldi
- Department of Cardiac, Thoracic and Vascular Sciences, Unit of Biostatistics, Epidemiology and Public Health, University of Padova, Padova, Italy
| | - Dario Gregori
- Department of Cardiac, Thoracic and Vascular Sciences, Unit of Biostatistics, Epidemiology and Public Health, University of Padova, Padova, Italy
| | - Alessandro Desideri
- Cardiovascular Research Foundation, San Giacomo Hospital, Castelfranco Veneto, Italy
| | - Paola Berchialla
- Department of Clinical and Biological Sciences, University of Torino, Torino, Italy
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