Evidence map›Paper›PMID 41662376›Full record

ArticlePLoS neglected tropical diseases2026

Implementation of good clinical practice in clinical research in the context of limited resources settings: Lessons learnt from the freeBILy trial using an embedded mixed methods approach.

Leonard Gunga, Pia Rausche, Rivo Andry Rakotoarivelo, Mandranto Rasamoelina, Jeannine Solonirina, Elveric Fesia, Ravo Razafindrakoto, Njary Rakotozandrindrainy, Mickael Radomanana, Valentina Marchese and 12 more

Erratum issuedAbstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

22 authors.

Leonard GungaRG Implementation Research, Bernhard Nocht Institute for Tropical Medicine (BNITM), Hamburg, Germany.
Pia RauscheRG Implementation Research, Bernhard Nocht Institute for Tropical Medicine (BNITM), Hamburg, Germany.
Rivo Andry RakotoariveloInfectious diseases service, University Hospital Tambohobe, Fianarantsoa, Madagascar.
Mandranto RasamoelinaCentre Infectiolologie Charles Mérieux (CICM), Antananarivo, Madagascar.
Jeannine SolonirinaUniversity Antananarivo, Antananarivo, Madagascar.
Elveric FesiaInfectious diseases service, University Hospital Tambohobe, Fianarantsoa, Madagascar.
Ravo RazafindrakotoCentre Infectiolologie Charles Mérieux (CICM), Antananarivo, Madagascar.
Njary RakotozandrindrainyUniversity Antananarivo, Antananarivo, Madagascar.
Mickael RadomananaInfectious diseases service, University Hospital Tambohobe, Fianarantsoa, Madagascar.
Valentina MarcheseRG Implementation Research, Bernhard Nocht Institute for Tropical Medicine (BNITM), Hamburg, Germany.
Nagham IssaRG Implementation Research, Bernhard Nocht Institute for Tropical Medicine (BNITM), Hamburg, Germany.
Jean-Marc KutzRG Implementation Research, Bernhard Nocht Institute for Tropical Medicine (BNITM), Hamburg, Germany.
Aaron RemkesRG Implementation Research, Bernhard Nocht Institute for Tropical Medicine (BNITM), Hamburg, Germany.
Anna JagerGerman Center for Infection Research (DZIF), Hamburg-Borstel-Lübeck-Riems, Hamburg, Germany.
Dewi Ismajani PuraduredjaInterdisciplinary Academy of Competence and Education for Global Health (iACE), Bernhard Nocht Institute for Tropical Medicine (BNITM), Hamburg, Germany.
Govert van DamDepartment of Parasitology, Leiden University Medical Center, Leiden, the Netherlands.
Norbert SchwarzDepartment of Infectious Diseases Epidemiology, Bernhard Nocht Institute for Tropical Medicine (BNITM), Hamburg, Germany.
Jürgen MayGerman Center for Infection Research (DZIF), Hamburg-Borstel-Lübeck-Riems, Hamburg, Germany.
Raphaël RakotozandrindrainyUniversity Antananarivo, Antananarivo, Madagascar.
Natalie FischerRG Implementation Research, Bernhard Nocht Institute for Tropical Medicine (BNITM), Hamburg, Germany.
Daniela FuscoRG Implementation Research, Bernhard Nocht Institute for Tropical Medicine (BNITM), Hamburg, Germany.ORCID https://orcid.org/0000-0001-8833-239X
freeBILy consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionLimited financial and human resources and infrastructure can affect the implementation of Good Clinical Practice (GCP), which can have a detrimental impact on data quality and the robustness and application of clinical trial outcomes. Monitoring frameworks are designed to ensure good data quality and help to guide adaptations of trial procedures over time. However, these frameworks tend to be based on datacentric approaches, which often neglect vital aspects of trials, such as social responsibility, capacity strengthening, and contextual influence. Therefore, this study analyses barriers and facilitators of the implementation of GCP in resource-limited settings to inform the establishment of adapted frameworks for trial management and monitoring.

methodsIn this multi-method analysis of the freeBILy trial, conducted in Madagascar from 2019-2022, a random subset of trial participants (n = 500) and informed consents (n = 500) was analyzed for protocol deviations through descriptive statistics and trend analysis. Framework analysis of focus group discussions and individual semi-structures interviews provided a sociological viewpoint of the study context. Findings were subsequently triangulated, merging the viewpoints on the influences towards GCP in resource-limited settings.

resultsA decreasing trend in incorrect database entries was found (z = -6.968, Mann-Kendall Test, p < 0.001) over the course of the study, with an overall rate of 1.8% incorrect data entries. Triangulation showed three key areas of GCP implementation in resource-limited settings, which extend previous frameworks: a) Context adaptation towards infra-, team- and social structures as promoting factors, b) External influences, such as external threats, study personnel attitudes and perception towards the trial require recurrent assessment, and c) Promote GCP-compliant data collection subject to regular documentation and training cycles to facilitate capacity strenghtning and data ownership.

conclusionThis study shows the limitations of datacentric clinical trial management to assess GCP performances in the frame of clinical trials in resource-limited settings. We highlight the importance of well-trained and integrated study staff, as well as thorough preparation, budgeting and context appropriate monitoring. This achieves high quality, patient centered and compliant research, implemented through alternative frameworks for monitoring and evaluation.

Indexed as

Biomedical ResearchClinical Trials as TopicFocus GroupsHumansMadagascarResearch DesignResource-Limited Settings

Identifiers

PMID41662376
PMCPMC12900435

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.