TY - JOUR
T1 - Central data monitoring in the multicentre randomised SafeBoosC-III trial – a pragmatic approach
AU - The SafeBoosC-III Trial Group
AU - Olsen, Markus Harboe
AU - Hansen, Mathias Lühr
AU - Safi, Sanam
AU - Jakobsen, Janus Christian
AU - Greisen, Gorm
AU - Gluud, Christian
AU - Pellicer, Adelina
AU - Bargiel, Agata
AU - Hopper, Andrew
AU - Truttmann, Anita
AU - Klamer, Anja
AU - Heuchan, Anne Marie
AU - Memisoglu, Asli
AU - Krolak-Olejnik, Barbara
AU - Rzepecka, Beata
AU - Loureiro, Bergona
AU - Lecart, Chantal
AU - Hagmann, Cornelia
AU - Ergenekon, Ebru
AU - Hatzidaki, Eleftheria
AU - Mastretta, Emmanuele
AU - Dempsey, Eugene
AU - Papathoma, Evangelina
AU - Lou, Fang
AU - Dimitriou, Gabriel
AU - Pichler, Gerhard
AU - Vento, Giovanni
AU - Hahn, Gitte Holst
AU - Naulaers, Gunnar
AU - Cheng, Guoqiang
AU - Fuchs, Hans
AU - Ozkan, Hilal
AU - De Las Cuevas, Isabel
AU - Sadowska-Krawczenko, Iwona
AU - Tkaczyk, Jakub
AU - Sirc, Jan
AU - Zhang, Jinhua
AU - Mintzer, Jonathan
AU - De Buyst, Julie
AU - McCall, Karen
AU - Bober, Klaudiusz
AU - Sarafidis, Kosmas
AU - Bender, Lars
AU - Lopez, Laura Serrano
AU - Chalak, Lina
AU - Yang, Ling
AU - Cornette, Luc
AU - Arruza, Luis
AU - Baserga, Mariana
AU - Stocker, Martin
N1 - Publisher Copyright:
© 2021, The Author(s).
PY - 2021/12
Y1 - 2021/12
N2 - 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.
AB - 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.
KW - Central monitoring
KW - Clinical trials
KW - Data deviations
KW - Data quality
KW - Mahalanobis distance
KW - Missing data
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U2 - 10.1186/s12874-021-01344-4
DO - 10.1186/s12874-021-01344-4
M3 - Article
C2 - 34332547
AN - SCOPUS:85112340719
SN - 1471-2288
VL - 21
JO - BMC Medical Research Methodology
JF - BMC Medical Research Methodology
IS - 1
M1 - 160
ER -