Central data monitoring in the multicentre randomised SafeBoosC-III trial – a pragmatic approach
Abstract Background Data monitoring of clinical trials is a tool aimed at reducing the risks of random errors (e.g. clerical errors) and systematic errors, which include misinterpretation, misunderstandings, and fabrication. Traditional ‘good clinical practice data monitoring’ with on-site monitors...
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| Format: | Article |
| Language: | English |
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BMC
2021-07-01
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| Series: | BMC Medical Research Methodology |
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| Online Access: | https://doi.org/10.1186/s12874-021-01344-4 |
| _version_ | 1818903502073626624 |
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| author | Markus Harboe Olsen Mathias Lühr Hansen Sanam Safi Janus Christian Jakobsen Gorm Greisen Christian Gluud The SafeBoosC-III Trial Group |
| author_facet | Markus Harboe Olsen Mathias Lühr Hansen Sanam Safi Janus Christian Jakobsen Gorm Greisen Christian Gluud The SafeBoosC-III Trial Group |
| author_sort | Markus Harboe Olsen |
| collection | DOAJ |
| description | Abstract Background Data monitoring of clinical trials is a tool aimed at reducing the risks of random errors (e.g. clerical errors) and systematic errors, which include misinterpretation, misunderstandings, and fabrication. Traditional ‘good clinical practice data monitoring’ with on-site monitors increases trial costs and is time consuming for the local investigators. This paper aims to outline our approach of time-effective central data monitoring for the SafeBoosC-III multicentre randomised clinical trial and present the results from the first three central data monitoring meetings. Methods The present approach to central data monitoring was implemented for the SafeBoosC-III trial, a large, pragmatic, multicentre, randomised clinical trial evaluating the benefits and harms of treatment based on cerebral oxygenation monitoring in preterm infants during the first days of life versus monitoring and treatment as usual. We aimed to optimise completeness and quality and to minimise deviations, thereby limiting random and systematic errors. We designed an automated report which was blinded to group allocation, to ease the work of data monitoring. The central data monitoring group first reviewed the data using summary plots only, and thereafter included the results of the multivariate Mahalanobis distance of each centre from the common mean. The decisions of the group were manually added to the reports for dissemination, information, correcting errors, preventing furture errors and documentation. Results The first three central monitoring meetings identified 156 entries of interest, decided upon contacting the local investigators for 146 of these, which resulted in correction of 53 entries. Multiple systematic errors and protocol violations were identified, one of these included 103/818 randomised participants. Accordingly, the electronic participant record form (ePRF) was improved to reduce ambiguity. Discussion We present a methodology for central data monitoring to optimise quality control and quality development. The initial results included identification of random errors in data entries leading to correction of the ePRF, systematic protocol violations, and potential protocol adherence issues. Central data monitoring may optimise concurrent data completeness and may help timely detection of data deviations due to misunderstandings or fabricated data. |
| first_indexed | 2024-12-19T20:52:33Z |
| format | Article |
| id | doaj.art-da3d05b8b2ab4e808c3fea013aa25e9f |
| institution | Directory Open Access Journal |
| issn | 1471-2288 |
| language | English |
| last_indexed | 2024-12-19T20:52:33Z |
| publishDate | 2021-07-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Research Methodology |
| spelling | doaj.art-da3d05b8b2ab4e808c3fea013aa25e9f2022-12-21T20:06:03ZengBMCBMC Medical Research Methodology1471-22882021-07-0121111010.1186/s12874-021-01344-4Central data monitoring in the multicentre randomised SafeBoosC-III trial – a pragmatic approachMarkus Harboe Olsen0Mathias Lühr Hansen1Sanam Safi2Janus Christian Jakobsen3Gorm Greisen4Christian Gluud5The SafeBoosC-III Trial GroupCopenhagen Trial Unit, Centre for Clinical Intervention Research, The Capital Region, Copenhagen University Hospital - RigshospitaletDepartment of Neonatology, Juliane Marie Centre, Copenhagen University Hospital - RigshospitaletCopenhagen Trial Unit, Centre for Clinical Intervention Research, The Capital Region, Copenhagen University Hospital - RigshospitaletCopenhagen Trial Unit, Centre for Clinical Intervention Research, The Capital Region, Copenhagen University Hospital - RigshospitaletDepartment of Neonatology, Juliane Marie Centre, Copenhagen University Hospital - RigshospitaletCopenhagen Trial Unit, Centre for Clinical Intervention Research, The Capital Region, Copenhagen University Hospital - RigshospitaletAbstract Background Data monitoring of clinical trials is a tool aimed at reducing the risks of random errors (e.g. clerical errors) and systematic errors, which include misinterpretation, misunderstandings, and fabrication. Traditional ‘good clinical practice data monitoring’ with on-site monitors increases trial costs and is time consuming for the local investigators. This paper aims to outline our approach of time-effective central data monitoring for the SafeBoosC-III multicentre randomised clinical trial and present the results from the first three central data monitoring meetings. Methods The present approach to central data monitoring was implemented for the SafeBoosC-III trial, a large, pragmatic, multicentre, randomised clinical trial evaluating the benefits and harms of treatment based on cerebral oxygenation monitoring in preterm infants during the first days of life versus monitoring and treatment as usual. We aimed to optimise completeness and quality and to minimise deviations, thereby limiting random and systematic errors. We designed an automated report which was blinded to group allocation, to ease the work of data monitoring. The central data monitoring group first reviewed the data using summary plots only, and thereafter included the results of the multivariate Mahalanobis distance of each centre from the common mean. The decisions of the group were manually added to the reports for dissemination, information, correcting errors, preventing furture errors and documentation. Results The first three central monitoring meetings identified 156 entries of interest, decided upon contacting the local investigators for 146 of these, which resulted in correction of 53 entries. Multiple systematic errors and protocol violations were identified, one of these included 103/818 randomised participants. Accordingly, the electronic participant record form (ePRF) was improved to reduce ambiguity. Discussion We present a methodology for central data monitoring to optimise quality control and quality development. The initial results included identification of random errors in data entries leading to correction of the ePRF, systematic protocol violations, and potential protocol adherence issues. Central data monitoring may optimise concurrent data completeness and may help timely detection of data deviations due to misunderstandings or fabricated data.https://doi.org/10.1186/s12874-021-01344-4Central monitoringData qualityData deviationsMissing dataClinical trialsMahalanobis distance |
| spellingShingle | Markus Harboe Olsen Mathias Lühr Hansen Sanam Safi Janus Christian Jakobsen Gorm Greisen Christian Gluud The SafeBoosC-III Trial Group Central data monitoring in the multicentre randomised SafeBoosC-III trial – a pragmatic approach BMC Medical Research Methodology Central monitoring Data quality Data deviations Missing data Clinical trials Mahalanobis distance |
| title | Central data monitoring in the multicentre randomised SafeBoosC-III trial – a pragmatic approach |
| title_full | Central data monitoring in the multicentre randomised SafeBoosC-III trial – a pragmatic approach |
| title_fullStr | Central data monitoring in the multicentre randomised SafeBoosC-III trial – a pragmatic approach |
| title_full_unstemmed | Central data monitoring in the multicentre randomised SafeBoosC-III trial – a pragmatic approach |
| title_short | Central data monitoring in the multicentre randomised SafeBoosC-III trial – a pragmatic approach |
| title_sort | central data monitoring in the multicentre randomised safeboosc iii trial a pragmatic approach |
| topic | Central monitoring Data quality Data deviations Missing data Clinical trials Mahalanobis distance |
| url | https://doi.org/10.1186/s12874-021-01344-4 |
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