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Yorke-Edwards V, Diaz-Montana C, Murray ML, Sydes MR, Love SB. Monitoring metrics over time: Why clinical trialists need to systematically collect site performance metrics. RESEARCH METHODS IN MEDICINE & HEALTH SCIENCES 2023; 4:124-135. [PMID: 37795045 PMCID: PMC7615148 DOI: 10.1177/26320843221147855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/06/2023]
Abstract
Background Over the last decade, there has been an increasing interest in risk-based monitoring (RBM) in clinical trials, resulting in a number of guidelines from regulators and its inclusion in ICH GCP. However, there is a lack of detail on how to approach RBM from a practical perspective, and insufficient understanding of best practice. Purpose We present a method for clinical trials units to track their metrics within clinical trials using descriptive statistics and visualisations. Research Design We suggest descriptive statistics and visualisations within a SWAT methodology. Study Sample We illustrate this method using the metrics from TEMPER, a monitoring study carried out in three trials at the MRC Clinical Trials Unit at UCL. Data Collection The data collection for TEMPER is described in DOI: 10.1177/1740774518793379. Results We show the results and discuss a protocol for a Study-Within-A-Trial (SWAT 167) for those wishing to use the method. Conclusions The potential benefits metric tracking brings to clinical trials include enhanced assessment of sites for potential corrective action, improved evaluation and contextualisation of the influence of metrics and their thresholds, and the establishment of best practice in RBM. The standardisation of the collection of such monitoring data would benefit both individual trials and the clinical trials community.
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Affiliation(s)
- Victoria Yorke-Edwards
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, UK
| | - Carlos Diaz-Montana
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, UK
| | - Macey L Murray
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, UK
- Health Data Research UK, London, UK
- NHS DigiTrials, Data Services Directorate, NHS Digital, Leeds, UK
| | - Matthew R Sydes
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, UK
- Health Data Research UK, London, UK
- British Heart Foundation Data Science Centre, Health Data Research UK, London, UK
| | - Sharon B Love
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, University College London, London, UK
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Klatte K, Subramaniam S, Benkert P, Schulz A, Ehrlich K, Rösler A, Deschodt M, Fabbro T, Pauli-Magnus C, Briel M. Development of a risk-tailored approach and dashboard for efficient management and monitoring of investigator-initiated trials. BMC Med Res Methodol 2023; 23:84. [PMID: 37020207 PMCID: PMC10074803 DOI: 10.1186/s12874-023-01902-y] [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: 09/10/2022] [Accepted: 03/23/2023] [Indexed: 04/07/2023] Open
Abstract
BACKGROUND Most randomized controlled trials (RCTs) in the academic setting have limited resources for clinical trial management and monitoring. Inefficient conduct of trials was identified as an important source of waste even in well-designed studies. Thoroughly identifying trial-specific risks to enable focussing of monitoring and management efforts on these critical areas during trial conduct may allow for the timely initiation of corrective action and to improve the efficiency of trial conduct. We developed a risk-tailored approach with an initial risk assessment of an individual trial that informs the compilation of monitoring and management procedures in a trial dashboard. METHODS We performed a literature review to identify risk indicators and trial monitoring approaches followed by a contextual analysis involving local, national and international stakeholders. Based on this work we developed a risk-tailored management approach with integrated monitoring for RCTs and including a visualizing trial dashboard. We piloted the approach and refined it in an iterative process based on feedback from stakeholders and performed formal user testing with investigators and staff of two clinical trials. RESULTS The developed risk assessment comprises four domains (patient safety and rights, overall trial management, intervention management, trial data). An accompanying manual provides rationales and detailed instructions for the risk assessment. We programmed two trial dashboards tailored to one medical and one surgical RCT to manage identified trial risks based on daily exports of accumulating trial data. We made the code for a generic dashboard available on GitHub that can be adapted to individual trials. CONCLUSIONS The presented trial management approach with integrated monitoring enables user-friendly, continuous checking of critical elements of trial conduct to support trial teams in the academic setting. Further work is needed in order to show effectiveness of the dashboard in terms of safe trial conduct and successful completion of clinical trials.
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Affiliation(s)
- Katharina Klatte
- Department of Clinical Research, University Hospital Basel and University of Basel, Spitalstrasse 12, Basel, CH- 4031, Switzerland.
| | - Suvitha Subramaniam
- Department of Clinical Research, University Hospital Basel and University of Basel, Spitalstrasse 12, Basel, CH- 4031, Switzerland
| | - Pascal Benkert
- Department of Clinical Research, University Hospital Basel and University of Basel, Spitalstrasse 12, Basel, CH- 4031, Switzerland
| | - Alexandra Schulz
- Department of Clinical Research, University Hospital Basel and University of Basel, Spitalstrasse 12, Basel, CH- 4031, Switzerland
| | - Klaus Ehrlich
- Department of Clinical Research, University Hospital Basel and University of Basel, Spitalstrasse 12, Basel, CH- 4031, Switzerland
| | - Astrid Rösler
- Department of Clinical Research, University Hospital Basel and University of Basel, Spitalstrasse 12, Basel, CH- 4031, Switzerland
| | - Mieke Deschodt
- Department of Public Health & Primary Care, KU Leuven, Leuven, Belgium
- Competence Centre of Nursing, University Hospitals Leuven, Leuven, Belgium
| | - Thomas Fabbro
- Department of Clinical Research, University Hospital Basel and University of Basel, Spitalstrasse 12, Basel, CH- 4031, Switzerland
| | - Christiane Pauli-Magnus
- Department of Clinical Research, University Hospital Basel and University of Basel, Spitalstrasse 12, Basel, CH- 4031, Switzerland
| | - Matthias Briel
- Department of Clinical Research, University Hospital Basel and University of Basel, Spitalstrasse 12, Basel, CH- 4031, Switzerland
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
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Takaoka A, Zytaruk N, Davis M, Matte A, Johnstone J, Lauzier F, Marshall J, Adhikari N, Clarke FJ, Rochwerg B, Lamontagne F, Hand L, Watpool I, Porteous RK, Masse MH, D'Aragon F, Niven D, Heels-Ansdell D, Duan E, Dionne J, English S, St-Arnaud C, Millen T, Cook DJ. Monitoring and auditing protocol adherence, data integrity and ethical conduct of a randomized clinical trial: A case study. J Crit Care 2022; 71:154094. [PMID: 35724443 DOI: 10.1016/j.jcrc.2022.154094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 06/01/2022] [Indexed: 11/29/2022]
Abstract
PURPOSE To categorize, quantify and interpret findings documented in feedback letters of monitoring or auditing visits for an investigator-initiated, peer-review funded multicenter randomized trial testing probiotics for critically ill patients. MATERIALS & METHODS In 37 Canadian centers, monitoring and auditing visits were performed by 3 trained individuals; findings were reported in feedback letters. At trial termination, we performed duplicate content analysis on letters, categorizing observations first into unique findings, followed by 10 pre-determined trial quality management domains. We further classified each observation into a) missing operational records, b) errors in process, and potential threats to c) data integrity, d) patient privacy or e) safety. RESULTS Across 37 monitoring or auditing visits, 75 unique findings were categorized into 10 domains. Most frequently, observations were in domains of training documentation (180/566 [32%]) and the informed consent process (133/566 [23%]). Most observations were missing operational records (438/566 [77%]) rather than errors in process (128/566 [23%]). Of 75 findings, 13 (62/566 observations [11%]) posed a potential threat to data integrity, 1 (1/566 observation [0.18%]) to patient privacy, and 9 (49/566 observations [8.7%]) to patient safety. CONCLUSIONS Monitoring and auditing findings predominantly concerned missing documentation with minimal threats to data integrity, patient privacy or safety. TRIAL REGISTRATION PROSPECT (Probiotics: Prevention of Severe Pneumonia and Endotracheal Colonization Trial): NCT02462590.
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Affiliation(s)
- Alyson Takaoka
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada.
| | - Nicole Zytaruk
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada.
| | - Megan Davis
- School of Medicine, Royal College of Surgeons in Ireland, Dublin, Ireland.
| | - Andrea Matte
- Department of Respiratory Therapy, Humber River Hospital, North York, Ontario, Canada
| | - Jennie Johnstone
- Departments of Laboratory Medicine and Pathobiology & Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
| | - François Lauzier
- Department of Critical Care, Université Laval, Laval, Quebec, Canada.
| | - John Marshall
- Interdepartmental Division of Critical Care, University of Toronto, Toronto, Ontario, Canada.
| | - Neill Adhikari
- Interdepartmental Division of Critical Care, University of Toronto, Toronto, Ontario, Canada.
| | - France J Clarke
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada.
| | - Bram Rochwerg
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada; Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
| | - François Lamontagne
- Department of Critical Care, Université de Sherbrooke, Sherbrooke, Quebec, Canada.
| | - Lori Hand
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada.
| | - Irene Watpool
- Department of Critical Care, Ottawa Health Research Institute, Ottawa, Ontario, Canada.
| | - Rebecca K Porteous
- Department of Critical Care, Ottawa Health Research Institute, Ottawa, Ontario, Canada.
| | - Marie-Hélène Masse
- Department of Critical Care, Université de Sherbrooke, Sherbrooke, Quebec, Canada.
| | - Frédérick D'Aragon
- Department of Critical Care, Université de Sherbrooke, Sherbrooke, Quebec, Canada.
| | - Daniel Niven
- Department of Critical Care, University of Calgary, Calgary, Alberta, Canada.
| | - Diane Heels-Ansdell
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada.
| | - Erick Duan
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada; Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
| | - Joanna Dionne
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada; Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
| | - Shane English
- Department of Critical Care, Ottawa Health Research Institute, Ottawa, Ontario, Canada.
| | - Charles St-Arnaud
- Department of Critical Care, Université de Sherbrooke, Sherbrooke, Quebec, Canada.
| | - Tina Millen
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
| | - Deborah J Cook
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada; Department of Medicine, McMaster University, Hamilton, Ontario, Canada.
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Klatte K, Pauli-Magnus C, Love SB, Sydes MR, Benkert P, Bruni N, Ewald H, Arnaiz Jimenez P, Bonde MM, Briel M. Monitoring strategies for clinical intervention studies. Cochrane Database Syst Rev 2021; 12:MR000051. [PMID: 34878168 PMCID: PMC8653423 DOI: 10.1002/14651858.mr000051.pub2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
BACKGROUND Trial monitoring is an important component of good clinical practice to ensure the safety and rights of study participants, confidentiality of personal information, and quality of data. However, the effectiveness of various existing monitoring approaches is unclear. Information to guide the choice of monitoring methods in clinical intervention studies may help trialists, support units, and monitors to effectively adjust their approaches to current knowledge and evidence. OBJECTIVES To evaluate the advantages and disadvantages of different monitoring strategies (including risk-based strategies and others) for clinical intervention studies examined in prospective comparative studies of monitoring interventions. SEARCH METHODS We systematically searched CENTRAL, PubMed, and Embase via Ovid for relevant published literature up to March 2021. We searched the online 'Studies within A Trial' (SWAT) repository, grey literature, and trial registries for ongoing or unpublished studies. SELECTION CRITERIA We included randomized or non-randomized prospective, empirical evaluation studies of different monitoring strategies in one or more clinical intervention studies. We applied no restrictions for language or date of publication. DATA COLLECTION AND ANALYSIS We extracted data on the evaluated monitoring methods, countries involved, study population, study setting, randomization method, and numbers and proportions in each intervention group. Our primary outcome was critical and major monitoring findings in prospective intervention studies. Monitoring findings were classified according to different error domains (e.g. major eligibility violations) and the primary outcome measure was a composite of these domains. Secondary outcomes were individual error domains, participant recruitment and follow-up, and resource use. If we identified more than one study for a comparison and outcome definitions were similar across identified studies, we quantitatively summarized effects in a meta-analysis using a random-effects model. Otherwise, we qualitatively summarized the results of eligible studies stratified by different comparisons of monitoring strategies. We used the GRADE approach to assess the certainty of the evidence for different groups of comparisons. MAIN RESULTS We identified eight eligible studies, which we grouped into five comparisons. 1. Risk-based versus extensive on-site monitoring: based on two large studies, we found moderate certainty of evidence for the combined primary outcome of major or critical findings that risk-based monitoring is not inferior to extensive on-site monitoring. Although the risk ratio was close to 'no difference' (1.03 with a 95% confidence interval [CI] of 0.81 to 1.33, below 1.0 in favor of the risk-based strategy), the high imprecision in one study and the small number of eligible studies resulted in a wide CI of the summary estimate. Low certainty of evidence suggested that monitoring strategies with extensive on-site monitoring were associated with considerably higher resource use and costs (up to a factor of 3.4). Data on recruitment or retention of trial participants were not available. 2. Central monitoring with triggered on-site visits versus regular on-site visits: combining the results of two eligible studies yielded low certainty of evidence with a risk ratio of 1.83 (95% CI 0.51 to 6.55) in favor of triggered monitoring intervention. Data on recruitment, retention, and resource use were not available. 3. Central statistical monitoring and local monitoring performed by site staff with annual on-site visits versus central statistical monitoring and local monitoring only: based on one study, there was moderate certainty of evidence that a small number of major and critical findings were missed with the central monitoring approach without on-site visits: 3.8% of participants in the group without on-site visits and 6.4% in the group with on-site visits had a major or critical monitoring finding (odds ratio 1.7, 95% CI 1.1 to 2.7; P = 0.03). The absolute number of monitoring findings was very low, probably because defined major and critical findings were very study specific and central monitoring was present in both intervention groups. Very low certainty of evidence did not suggest a relevant effect on participant retention, and very low certainty evidence indicated an extra cost for on-site visits of USD 2,035,392. There were no data on recruitment. 4. Traditional 100% source data verification (SDV) versus targeted or remote SDV: the two studies assessing targeted and remote SDV reported findings only related to source documents. Compared to the final database obtained using the full SDV monitoring process, only a small proportion of remaining errors on overall data were identified using the targeted SDV process in the MONITORING study (absolute difference 1.47%, 95% CI 1.41% to 1.53%). Targeted SDV was effective in the verification of source documents, but increased the workload on data management. The other included study was a pilot study, which compared traditional on-site SDV versus remote SDV and found little difference in monitoring findings and the ability to locate data values despite marked differences in remote access in two clinical trial networks. There were no data on recruitment or retention. 5. Systematic on-site initiation visit versus on-site initiation visit upon request: very low certainty of evidence suggested no difference in retention and recruitment between the two approaches. There were no data on critical and major findings or on resource use. AUTHORS' CONCLUSIONS The evidence base is limited in terms of quantity and quality. Ideally, for each of the five identified comparisons, more prospective, comparative monitoring studies nested in clinical trials and measuring effects on all outcomes specified in this review are necessary to draw more reliable conclusions. However, the results suggesting risk-based, targeted, and mainly central monitoring as an efficient strategy are promising. The development of reliable triggers for on-site visits is ongoing; different triggers might be used in different settings. More evidence on risk indicators that identify sites with problems or the prognostic value of triggers is needed to further optimize central monitoring strategies. In particular, approaches with an initial assessment of trial-specific risks that need to be closely monitored centrally during trial conduct with triggered on-site visits should be evaluated in future research.
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Affiliation(s)
- Katharina Klatte
- Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Christiane Pauli-Magnus
- Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Sharon B Love
- MRC Clinical Trials Unit at UCL, University College London , London, UK
| | - Matthew R Sydes
- MRC Clinical Trials Unit at UCL, University College London, London, UK
| | - Pascal Benkert
- Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Nicole Bruni
- Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Hannah Ewald
- University Medical Library, University of Basel, Basel, Switzerland
| | - Patricia Arnaiz Jimenez
- Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Marie Mi Bonde
- Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Matthias Briel
- Department of Clinical Research, University Hospital Basel and University of Basel, Basel, Switzerland
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Houston L, Cortie CH, Probst Y, Meyer BJ. Improving data monitoring in Australian clinical trials and research: Free resources and templates. Clin Trials 2021; 18:639-641. [PMID: 34231396 DOI: 10.1177/17407745211026726] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Lauren Houston
- School of Medicine, University of Wollongong, Wollongong, NSW, Australia.,Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW, Australia
| | - Colin H Cortie
- School of Medicine, University of Wollongong, Wollongong, NSW, Australia.,Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW, Australia
| | - Yasmine Probst
- School of Medicine, University of Wollongong, Wollongong, NSW, Australia.,Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW, Australia
| | - Barbara J Meyer
- School of Medicine, University of Wollongong, Wollongong, NSW, Australia.,Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW, Australia
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Houston L, Martin A, Yu P, Probst Y. Time-consuming and expensive data quality monitoring procedures persist in clinical trials: A national survey. Contemp Clin Trials 2021; 103:106290. [PMID: 33503495 DOI: 10.1016/j.cct.2021.106290] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 01/19/2021] [Accepted: 01/20/2021] [Indexed: 12/21/2022]
Abstract
INTRODUCTION The Good Clinical Practice guideline identifies that data monitoring is an essential research activity. However, limited evidence exists on how to perform monitoring including the amount or frequency that is needed to ensure data quality. This study aims to explore the monitoring procedures that are implemented to ensure data quality in Australian clinical research studies. MATERIAL AND METHODS Clinical studies listed on the Australian and New Zealand Clinical Trials Registry were invited to participate in a national cross-sectional, mixed-mode, multi-contact (postal letter and e-mail) web-based survey. Information was gathered about the types of data quality monitoring procedures being implemented. RESULTS Of the 3689 clinical studies contacted, 589 (16.0%) responded, of which 441 (77.4%) completed the survey. Over half (55%) of the studies applied source data verification (SDV) compared to risk-based targeted and triggered monitoring (10-11%). Conducting 100% on-site monitoring was most common for those who implemented the traditional approach. Respondents who did not conduct 100% monitoring, included 1-25% of data points for SDV, centralized or on-site monitoring. The incidence of adverse events and protocol deviations were the most likely factors to trigger a site visit for risk-based triggered (63% and 44%) and centralized monitoring (48% and 44%), respectively. CONCLUSION Instead of using more optimal risk-based approaches, small single-site clinical studies are conducting traditional monitoring procedures which are time consuming and expensive. Formal guidelines need to be improved and provided to all researchers for 'new' risk-based monitoring approaches.
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Affiliation(s)
- Lauren Houston
- School of Medicine, University of Wollongong, Australia; Illawarra Health and Medical Research Institute, Australia.
| | | | - Ping Yu
- Illawarra Health and Medical Research Institute, Australia; School of Computing and Information Technology, University of Wollongong, Australia
| | - Yasmine Probst
- School of Medicine, University of Wollongong, Australia; Illawarra Health and Medical Research Institute, Australia
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