Optimising data completeness and quality in multicentre randomised clinical trials using central data monitoring: a pragmatic approach

BACKGROUND: Randomised clinical trial data monitoring is essential for ensuring quality and adherence to protocols, often achieved through on-site methods. However, challenges like the COVID-19 pandemic have highlighted limitations. Central data monitoring offers an alternative, leveraging digital capabilities and diverse expertise. METHODS: The SafeBoosC-III trial, randomising 1,601 preterm infants across 70 sites, was a pragmatic trial offering detailed education of the investigators before launch. During the trial, we conducted pre-protocolised central data monitoring encompassing monthly data checks, data completeness assessments, and statistical analyses. Discrepancies were primarily identified through visual interpretation of data. RESULTS: Throughout the trial, meticulous central monitoring helped keeping missing data at only 1.4%. Of 43,965 data points reviewed, 338 were flagged, with 81 (0.2% of all data and 24.0% of flagged data) corrected after investigation. CONCLUSIONS: The methodology of combining manual investigation with statistical tools effectively minimised data errors, enhancing validity. This approach in the SafeBoosC-III trial emphasises the importance of ongoing central data monitoring in clinical trials. Standardised protocols for such monitoring are crucial for ensuring data quality and accelerating the validation process in future trials.

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Publication Details

Journal
BMC Medical Research Methodology
Published
2026-06-24
DOI
https://doi.org/10.1186/s12874-026-02932-y
Primary Topic
Ethics in Clinical Research
Type
article
Field-Weighted Citation Impact
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article

Optimising data completeness and quality in multicentre randomised clinical trials using central data monitoring: a pragmatic approach

Olalla Otero, Chantal Lecart, Martin Stocker, Pamela Zafra et al.
BMC Medical Research Methodology
Ethics in Clinical Research
article

Optimising data completeness and quality in multicentre randomised clinical trials using central data monitoring: a pragmatic approach

Olalla Otero, Chantal Lecart, Martin Stocker, Pamela Zafra, Agata Bargiel, Ruth del Rio Florentino, Kosmas Sarafidis, Luis Arruza, Merih Çetınkaya, Renaud Viellevoye, Gunnar Naulaers, Iwona Sadowska-Krawczenko, Anne Marie Heuchan, Salvador Piris‐Borregas, Evangelina Papathoma, Peter Agergaard, Anja Klamer, Jan Širc, Bergona Loureiro, Markus Harboe Olsen, Olivier Baud, Giovanni Vento, Shujuan Zeng, Janus Engstrøm, Lars Bender, Julie De Buyst, Adelina Pellicer, Silvia Pisoni, Olalla Lóepez Suarez, Laura Serrano Lopez, Pierre Maton, Simon Hyttel-Sørensen, Ryszard Lauterbach, Siv Fredly, Emmanuele Mastretta, Gerhard Pichler, Jakub Tkaczyk, Beata Rzepecka, Monica Fumagalli, Gabriel Dimitriou, Hilal Özkan, Klaudiusz Bober, Mathias Lühr Hansen, Miguel Alsina, Tomasz Szczapa, Jinhua Zhang, Ling Yang, Fang Luo, Xiaoyan Gao, Zhaoqing Yin, Gitte Holst Hahn, Tanja Karen, Christian Gluud, Barbara Królak-Olejnik, Isabel De Las Cuevas, Saudamini Nesargi, Eleftheria Hatzidaki, Cornelia Hagmann, Andrew Hopper, Lina Chalak, Xin Xu, Guoqiang Cheng, Gorm Greisen, Jonathan Mintzer, Sanam Safi-Rasmussen, Karen McCall, Ebru Ergenekon, Anita C. Truttmann, Suna Oguz, Mariana Baserga, Hans Fuchs, Shashidhar Rao, Asli Memisoglu, Massimo Agosti, Luc Cornette, the SafeBoosC-III Trial Group, Segundo Rite, Eugene Dempsey
article en

Abstract

BACKGROUND: Randomised clinical trial data monitoring is essential for ensuring quality and adherence to protocols, often achieved through on-site methods. However, challenges like the COVID-19 pandemic have highlighted limitations. Central data monitoring offers an alternative, leveraging digital capabilities and diverse expertise. METHODS: The SafeBoosC-III trial, randomising 1,601 preterm infants across 70 sites, was a pragmatic trial offering detailed education of the investigators before launch. During the trial, we conducted pre-protocolised central data monitoring encompassing monthly data checks, data completeness assessments, and statistical analyses. Discrepancies were primarily identified through visual interpretation of data. RESULTS: Throughout the trial, meticulous central monitoring helped keeping missing data at only 1.4%. Of 43,965 data points reviewed, 338 were flagged, with 81 (0.2% of all data and 24.0% of flagged data) corrected after investigation. CONCLUSIONS: The methodology of combining manual investigation with statistical tools effectively minimised data errors, enhancing validity. This approach in the SafeBoosC-III trial emphasises the importance of ongoing central data monitoring in clinical trials. Standardised protocols for such monitoring are crucial for ensuring data quality and accelerating the validation process in future trials.

BMC Medical Research Methodology
University of Southern Denmark (DK), Copenhagen University Hospital (DK), Rigshospitalet (DK)
Good health and well-being
Openalex Percentile: Top 6%
Ethics in Clinical Research
DOIOpen Access PDFOpenAlex
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