Does Central Monitoring Lead to Higher Quality? An Analysis of Key Risk Indicator Outcomes

Author:

de Viron SylvianeORCID,Trotta Laura,Steijn William,Young Steve,Buyse Marc

Abstract

Abstract Background Central monitoring, which typically includes the use of key risk indicators (KRIs), aims at improving the quality of clinical research by pro-actively identifying and remediating emerging issues in the conduct of a clinical trial that may have an adverse impact on patient safety and/or the reliability of trial results. However, there has to-date been a relative lack of direct quantitative evidence published supporting the claim that central monitoring actually leads to improved quality. Material and Methods Nine commonly used KRIs were analyzed for evidence of quality improvement using data retrieved from a large central monitoring platform. A total of 212 studies comprising 1676 sites with KRI signals were used in the analysis, representing central monitoring activity from 23 different sponsor organizations. Two quality improvement metrics were assessed for each KRI, one based on a statistical score (p-value) and the other based on a KRI’s observed value. Results Both KRI quality metrics showed improvement in a vast majority of sites (82.9% for statistical score, 81.1% for observed KRI value). Additionally, the statistical score and the observed KRI values improved, respectively by 66.1% and 72.4% on average towards the study average for those sites showing improvement. Conclusion The results of this analysis provide clear quantitative evidence supporting the hypothesis that use of KRIs in central monitoring is leading to improved quality in clinical trial conduct and associated data across participating sites.

Publisher

Springer Science and Business Media LLC

Subject

Pharmacology (medical),Public Health, Environmental and Occupational Health,Pharmacology, Toxicology and Pharmaceutics (miscellaneous)

Reference17 articles.

1. US Department of Health and Human Services, Food and Drug Administration. Guidance for industry: oversight of clinical investigations—a risk-based approach to monitoring [Internet]. 2013. https://www.fda.gov/media/116754/download. Accessed 9 May 2022

2. EMA Guidance. Reflection paper on risk based quality management in clinical trials [Internet]. 2013. https://www.ema.europa.eu/en/documents/scientific-guideline/reflection-paper-risk-based-quality-management-clinical-trials_en.pdf. Accessed 13 May 2022

3. de Viron S, Trotta L, Schumacher H, Lomp HJ, Höppner S, Young S, et al. Detection of fraud in a clinical trial using unsupervised statistical monitoring. Ther Innov Regul Sci. 2022;56(1):130–6.

4. Venet D, Doffagne E, Burzykowski T, Beckers F, Tellier Y, Genevois-Marlin E, et al. A statistical approach to central monitoring of data quality in clinical trials. Clin Trials Lond Engl. 2012;9(6):705–13.

5. Desmet L, Venet D, Doffagne E, Timmermans C, Burzykowski T, Legrand C, et al. Linear mixed-effects models for central statistical monitoring of multicenter clinical trials. Stat Med. 2014;33:5265–79.

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