Fig 1.
Overview of conceptual framework of this study, based on the concept of clinical trial quality in resource-limited settings (box above) by de Pretto-Lazarova et al. (2022) regarding the methodology applied in the scope of this study (box below).
Created in BioRender. Fusco, D. (2025) https://BioRender.com/hquc7ry.
Table 1.
Summary of incorrect data entries categorised by critical issues related to the primary endpoint of the study.
Fig 2.
Normalized CRFs incorrect data entry fields per week throughout the study: The graph shows the weekly incorrect data entry fields from May 2019 to September 2022.
The stacked colored bars (orange = T0, yellow = T1, green = T2, blue = T3, pink = T4) show the percentage of incorrect data entry fields normalized by the number of possible data entry fields per week. Vertical black lines represent the start of each of the five study time points (T0-T4). Red dashed lines illustrate the internal GCP trainings, whereas the dark blue lines represent the external monitoring visits (November 2019, on-site and February 2021, remotely due to COVID-19). The grey-shaded areas correspond to the timeframe of the COVID- 19 national health emergency lockdowns.
Table 2.
Evaluation of IC errors.
Fig 3.
Interrelated components of clinical trial quality in ressource-limited setting under implementation of GCP guideline, including factors outside of the normal trial monitoring: Major factors influencing the key elements of patient centredness and safety are displayed clockwise: a) Structures as promoting factors with the output of sustainability of the created infrastructure and establishment of longterm partnerships through team infrastructure, b) External influences as factors that require reoccuring assessment to control direct impact on trail mechnisms and safety, c) Data as the building factors of a clinical trial, together with the GCP compliant data collection bound to documentation and training cycles.
Together this leads to the output of strengthened professional and scientific capacity, while facilitating data ownership of local partners. In the sqaure box are the elements of a clinical trial covered by the required monitoring visit. Elements of quality control that ensure the integrity of the data and the soundness of the research in the laboratory and data management go beyond this monitoring. This means that even if all elements of monitoring have been fulfilled, the control of potential issues with sample collection and data management is considered essential for the reliable output of the clinical trial. Created in BioRender. Fusco, D. (2025) https://BioRender.com/8ia401e.