Lessons from Large-Scale Tolerability and Acceptability Studies of Triple Drug Mass Drug Administration Performed to Support Policy Change and Accelerate Elimination of Lymphatic Filariasis
Bibliographic record
Abstract
Early clinical trials clearly demonstrated the superior efficacy of triple drug therapy with ivermectin plus DEC and albendazole (IDA) for clearing microfilaremia (Mf) in individuals with lymphatic filariasis (LF). Although these initial pharmacokinetic and efficacy studies were necessary first steps in the clinical development of IDA, they were not sufficient to justify policy changes necessary for widespread use of this new regimen by national filariasis elimination programs. Processes and procedures that led to the World Health Organization's (WHO) endorsement of IDA as a mass drug administration (MDA) regimen for LF are reviewed elsewhere in this Supplement. However, the "guideline review process" depended heavily on preliminary results from multicenter studies that were performed to compare the safety, tolerability, and acceptability of IDA versus DA (the two-drug regimen of DEC plus albendazole that was recommended for use for filariasis elimination in countries without co-endemic onchocerciasis or loiasis). Efficacy and tolerability results from those studies have been recently published. Therefore, this paper will focus on practical aspects of the planning and conduct of the large-scale studies that were so critically important for policy change.
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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 | 0.150 | 0.207 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".