Global adverse events reported for direct-acting antiviral therapies for the treatment of hepatitis C: an analysis of the World Health Organization VigiBase
Bibliographic record
Abstract
BACKGROUND: Direct-acting antivirals (DAAs) have transformed the treatment of hepatitis C infection (HCV) globally. Exploratory studies to identify potential rare adverse drug events associated with DAAs to optimize their use are scarce. OBJECTIVE: We aimed to describe the most common serious DAA-associated adverse drug reaction (ADR) reports overall and by DAA regimen. METHODS: We conducted a cross-sectional analysis of post-market ADRs associated with DAA therapy using VigiBase, the global database of the WHO Programme for International Drug Monitoring. Reports occurring between 2013 and 2020 in which an eligible DAA brand or regimen was reported as the suspect drug were included and described. Reports of concomitant ribavirin or interferon use were excluded. The top 25 events for all reports where the outcome was indicated as 'serious' or 'life-threatening' were described overall and by drug regimen. RESULTS: We identified 56 636 global ADR reports [45% women, 38% ledipasvir/sofosbuvir use, 67% from USA/Canada, average patient age 57 (SD 13) years]. Overall, 3.8% of reports described a life-threatening event or death. Unexpected ADRs included major pulmonary (dyspnea, pneumonia, and respiratory failure) and cardiac (myocardial infarction and cardiac arrest) events. COMMENT: When examining all serious ADRs for DAAs globally, unexpected pulmonary and cardiac events were identified and may be of interest for further research on DAA safety. Future studies must examine population-level risk of ADRs for DAA therapies while accounting for confounding by indication, comorbidities, and stage of HCV disease.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".