The real-world analysis of adverse events with azacitidine: a pharmacovigilance study based on the FAERS and WHO-VigiAccess databases
Bibliographic record
Abstract
Background: Azacitidine is used to treat myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). It acts as a cytosine analog and DNA methyltransferase inhibitor, inducing DNA hypomethylation to reverse epigenetic modifications and restore normal gene expression. However, adverse events (AEs) associated with azacitidine are mainly reported in clinical trials, with limited real-world evidence. This study aims to assess the AE profile of azacitidine by utilizing data from the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) and WHO-VigiAccess databases. Methods: We extracted adverse event (AE) reports related to azacitidine from the FAERS and WHO-VigiAccess databases, covering the period from the drug's market introduction to the third quarter of 2024. We used statistical methods including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Empirical Bayesian Geometric Mean (EBGM) to analyze the association between azacitidine and documented AEs. Results: The investigation unveiled 16,056 azacitidine-related adverse event (AE) reports from FAERS and 19,867 reports from WHO-VigiAccess. The median duration for the occurrence of these AEs during the observation period was 36 days, with an interquartile range (IQR) spanning from 11 to 126 days. Our statistical analysis identified 27 organ systems associated with AEs induced by azacitidine. Among these, the notable System Organ Classes (SOCs) that met four specific criteria included: infections and infestations, blood and lymphatic system disorders, and neoplasms benign, malignant, and unspecified (including cysts and polyps). Four algorithms identified 443 significant disproportionality preferred terms (PTs), including previously unreported AEs such as death, sepsis, septic shock, respiratory failure, cardiac failure, tumor lysis syndrome, bone marrow failure, interstitial lung disease, and pericarditis. Analysis from the WHO-VigiAccess database showed a ROR of 3.65 and a PRR of 3.30 for the SOC of infections and infestations. Conclusion: This research not only confirms the widely acknowledged AEs linked to azacitidine but also uncovers several potentially new safety concerns noted in actual clinical practice. These results may offer important vigilance information for clinicians and pharmacists when addressing safety issues associated with azacitidine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".