Risk based monitoring (RBM) tools for clinical trials: A systematic review

Hurley, Caroline; Shiely, Frances; Power, J. R.; Clarke, Mike; Eustace, Joseph A.; Flanagan, Evelyn; Kearney, Patricia M.

doi:10.1016/j.cct.2016.09.003

Cited by 38 publications

(40 citation statements)

References 14 publications

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“…[…] The sponsor may choose on-site monitoring, a combination of on-site and centralized monitoring, or, where justified, centralized monitoring". To date, only a few tools for implementing risk-based monitoring of clinical trials have been described [16,30,31], most of them combining on-site and centralized monitoring. Among them, risk-assessment tools were used within the French OPTIMON (for OPTImization of MONitoring -NCT00780091) trial [32] and the ADAMON (for ADApted MONitoring) projects.…”

Section: Discussionmentioning

confidence: 99%

“…However, considering the exponential rise in clinical research costs (SDV has been estimated to account for approximately 25% of overall clinical trial costs [3]) and the undemonstrated impact of full SDV on data quality [4][5][6][7][8], the question of implementing a reduced or a targeted SDV and its cost/benefit ratio has emerged [9][10][11][12]. Since the beginning of the decade, regulatory agencies have suggested that sponsors should adapt the nature and extent of the monitoring to a risk-based approach [13][14][15] and nowadays, there is a growing consensus that a monitoring focused on the most critical data elements and processes necessary to achieve study objectives is more interesting than routine visits to all clinical sites and 100% data verification to ensure overall study quality [16,17]. However, the impact of this approach on data quality needs to be evaluated.…”

Section: Introductionmentioning

confidence: 99%

“…However, the impact of this approach on data quality needs to be evaluated. A wide range of alternative monitoring methods have been described in the literature [16,[18][19][20][21][22][23] but the publications mainly assessed the impact on data quality retrospectively, and none of them evaluated the impact of these alternative monitoring strategies on global workload and clinical trials costs. Moreover, the place of centralized data-management (DM), which consists in detecting missing data and protocol deviations and controlling data consistency on the electronic database after SDV, has not been questioned in these new settings.…”

Section: Introductionmentioning

confidence: 99%

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Impact of a targeted monitoring on data‐quality and data‐management workload of randomized controlled trials: A prospective comparative study

Fougerou‐Leurent

Laviolle

Tual

et al. 2019

Brit J Clinical Pharma

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AimsMonitoring risk‐based approaches in clinical trials are encouraged by regulatory guidance. However, the impact of a targeted source data verification (SDV) on data‐management (DM) workload and on final data quality needs to be addressed.MethodsMONITORING was a prospective study aiming at comparing full SDV (100% of data verified for all patients) and targeted SDV (only key data verified for all patients) followed by the same DM program (detecting missing data and checking consistency) on final data quality, global workload and staffing costs.ResultsIn all, 137 008 data including 18 124 key data were collected for 126 patients from 6 clinical trials. Compared to the final database obtained using the full SDV monitoring process, the final database obtained using the targeted SDV monitoring process had a residual error rate of 1.47% (95% confidence interval, 1.41–1.53%) on overall data and 0.78% (95% confidence interval, 0.65–0.91%) on key data. There were nearly 4 times more queries per study with targeted SDV than with full SDV (mean ± standard deviation: 132 ± 101 vs 34 ± 26; P = .03). For a handling time of 15 minutes per query, the global workload of the targeted SDV monitoring strategy remained below that of the full SDV monitoring strategy. From 25 minutes per query it was above, increasing progressively to represent a 50% increase for 45 minutes per query.ConclusionTargeted SDV monitoring is accompanied by increased workload for DM, which allows to obtain a small proportion of remaining errors on key data (<1%), but may substantially increase trial costs.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Impact of a targeted monitoring on data‐quality and data‐management workload of randomized controlled trials: A prospective comparative study

Fougerou‐Leurent

Laviolle

Tual

et al. 2019

Brit J Clinical Pharma

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“…Policies officially approved by a recognised government entity, whether peer-reviewed or not, were included in the study. e most commonly used quality assessment framework for grey literature is the Authority, Accuracy, Coverage, Objectivity, Date, Significance (AACODS) [29,92,93]. However, we found the AACODS framework inappropriate for the quality assessment of policy documents.…”

Section: Quality Assessmentmentioning

confidence: 90%

Governments’ Policy Response to Drought in Eswatini and Lesotho: A Systematic Review of the Characteristics, Comprehensiveness, and Quality of Existing Policies to Improve Community Resilience to Drought Hazards

Kamara

Sahle

Agho

et al. 2020

Discrete Dynamics in Nature and Society

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The southern African kingdoms of Eswatini and Lesotho experience recurrent drought-induced disasters. Policies have been enacted, but no attempt has been made to synthesise the effects on disaster resilience. This review analyses the characteristics, quality, and comprehensiveness of drought-resilience policies in Eswatini and Lesotho. We have systematically reviewed public policies that shape responses to disaster resilience published between 1 January 1980 and 30 June 2019. A combination of keywords was used to search electronic bibliographic databases, multidisciplinary databases, key organisational websites, and the first 20 pages of Google for policies that addressed disaster and/or drought resilience. Identified documents were downloaded into an EndNote database and screened for eligibility using predetermined criteria. The logic of events framework was used for quality assessment, and a metaethnographic approach was applied for data synthesis. Three broad categories of characteristics, thematic outcomes and quality, and comprehensiveness of policy documents emerged and are presented. Policy responses contributing to disaster resilience were found in n = 32 out of 13,700 documents. Three (n = 3/32) policies were statutory, and the rest were nonstatutory. Eleven (n = 11/32) were assessed to be of high quality. Policy responses relating to drought resilience focused on reducing vulnerability to recurrent disasters; promoting drought and climate change adaptation; improving agriculture and food security; safeguarding cultural heritage; and preventing gender inequality and gender-based violence as well as improving disaster governance. However, the construct of drought resilience was not strongly articulated as a major policy goal across policy documents. There is an urgent need to promote better understanding of drought resilience in order to motivate policymakers to steer away from reactive interventions and position resilience as a major national policy goal in both countries to expedite inclusive growth and safeguard development gains and the health and wellbeing of the majority of their populations who are rural-based populations.

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“…https://doi.org/10.1101/2020.04.01.20049627 doi: medRxiv preprint Dynamic methods risk-based monitoring scoping review -v1.0 29-Feb-2020.docx 6/47 including 'triggered monitoring' 14 or, as in ICH GCP guidance, 'targeted monitoring', 16 and may employ data-driven approaches from methods known collectively as 'central statistical monitoring', 17 or more subjective assessments. 14,18,19 A recent systematic review has established the breadth of tools available to assess overall trial risk (and to use this assessment to define the monitoring strategy) in the setup stage, 20 but so far there has been no such exercise for methods to assess ongoing site-level risk once a trial has started. We conducted a scoping review 21 to identify and characterise available methods.…”

Section: Summary Of Supplementary Information Introductionmentioning

confidence: 99%

Dynamic methods for ongoing assessment of site-level risk in risk-based monitoring of clinical trials: a scoping review

Cragg

Hurley

Yorke-Edwards

et al. 2020

Preprint

Self Cite

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Background/Aims It is increasingly recognised that reliance on frequent site visits for monitoring clinical trials is inefficient. Regulators and trialists have in recent years encouraged more risk-based monitoring. Risk assessment should take place before a trial begins in order to define the overarching monitoring strategy. It can also be done on an ongoing basis, in order to target sites for monitoring activity. Various methods have been proposed for such prioritisation, often using terms like 'central statistical monitoring', 'triggered monitoring' or, as in ICH Good Clinical Practice guidance, 'targeted on-site monitoring'. We conducted a scoping review to identify such methods, to establish if any published methods were supported by adequate evidence to allow wider implementation, and to point the way to future developments in this field of research. Methods We used 7 publication databases, 2 sets of methodological conference abstracts and an internet search engine to look for methods for using centrally held trial data to assess site conduct during a trial. We included only reports in English, and excluded reports published before 1996 and reports not directly relevant to our research question. We used reference and citation searches to find additional relevant reports. We extracted data using a pre-defined template. We contacted authors to request additional information about included reports and to check whether reports might be eligible. Results We included 30 reports in our final dataset, of which 21 were peer-reviewed publications. 20 reports described central statistical monitoring methods (of which 7 focussed on detection of fraud or misconduct) and 9 described triggered monitoring methods. 21 reports included some assessment of their methods' effectiveness. Most commonly this involved exploring the methods' characteristics using real trial data with no known integrity issues. Of the 21 with some effectiveness assessment, most presented limited or no information about whether or not concerns identified through central monitoring constituted meaningful problems. Some reports commented on cost savings from reduced on-site monitoring, but none gave detailed costings for the development and maintenance of central monitoring methods themselves. Conclusions Our review identified various proposed methods, some of which could be combined within the same trial. The apparent emphasis on fraud detection may not be proportionate in all trial settings. Although some methods have self-justifying benefits for data cleaning activity, many have limitations that may currently prevent their routine use for targeting trial monitoring activity. The implementation costs, or uncertainty about these, may also be a barrier. We make recommendations for how the evidence-base supporting these methods could be improved. Keywords: trial monitoring, risk-based monitoring, triggered monitoring, central statistical monitoring, Good Clinical Practice, research misconduct, data fabrication

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Risk based monitoring (RBM) tools for clinical trials: A systematic review

Cited by 38 publications

References 14 publications

Impact of a targeted monitoring on data‐quality and data‐management workload of randomized controlled trials: A prospective comparative study

Impact of a targeted monitoring on data‐quality and data‐management workload of randomized controlled trials: A prospective comparative study

Governments’ Policy Response to Drought in Eswatini and Lesotho: A Systematic Review of the Characteristics, Comprehensiveness, and Quality of Existing Policies to Improve Community Resilience to Drought Hazards

Dynamic methods for ongoing assessment of site-level risk in risk-based monitoring of clinical trials: a scoping review

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