Obtaining Valid Laboratory Data in Clinical Trials Conducted in Resource Diverse Settings: Lessons Learned from a Microbicide Phase III Clinical Trial
Bibliographic record
Abstract
BACKGROUND: Over the last decade several phase III microbicides trials have been conducted in developing countries. However, laboratories in resource constrained settings do not always have the experience, infrastructure, and the capacity to deliver laboratory data meeting the high standards of clinical trials. This paper describes the design and outcomes of a laboratory quality assurance program which was implemented during a phase III clinical trial evaluating the efficacy of the candidate microbicide Cellulose Sulfate 6% (CS) [1]. METHODOLOGY: In order to assess the effectiveness of CS for HIV and STI prevention, a phase III clinical trial was conducted in 5 sites: 3 in Africa and 2 in India. The trial sponsor identified an International Central Reference Laboratory (ICRL), responsible for the design and management of a quality assurance program, which would guarantee the reliability of laboratory data. The ICRL provided advice on the tests, assessed local laboratories, organized trainings, conducted supervision visits, performed re-tests, and prepared control panels. Local laboratories were provided with control panels for HIV rapid tests and Chlamydia trachomatis/Neisseria gonorrhoeae (CT/NG) amplification technique. Aliquots from respective control panels were tested by local laboratories and were compared with results obtained at the ICRL. RESULTS: Overall, good results were observed. However, discordances between the ICRL and site laboratories were identified for HIV and CT/NG results. One particular site experienced difficulties with HIV rapid testing shortly after study initiation. At all sites, DNA contamination was identified as a cause of invalid CT/NG results. Both problems were timely detected and solved. Through immediate feedback, guidance and repeated training of laboratory staff, additional inaccuracies were prevented. CONCLUSIONS: Quality control guidelines when applied in field laboratories ensured the reliability and validity of final study data. It is essential that sponsors provide adequate resources for implementation of such comprehensive technical assessment and monitoring systems. TRIAL REGISTRATION: ClinicalTrials.gov NCT00153777 and Current Controlled Trials ISRCTN95638385.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.444 | 0.474 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".