Intrahepatic cholestasis of pregnancy associated with azathioprine: first quantitative disproportionality analysis using the FDA adverse event reporting system
Bibliographic record
Abstract
Introduction: Azathioprine (AZA) is an immunosuppressant approved for renal transplant rejection and rheumatoid arthritis. Recent FDA alerts have raised concerns about its link to intrahepatic cholestasis of pregnancy (ICP), a condition with serious maternal and fetal risks. This study used disproportionality analysis as a hypothesis-generating approach to evaluate the reporting association between AZA and ICP during pregnancy and to compare AZA with other drugs previously implicated in ICP. Methods: A retrospective pharmacovigilance study was conducted using the FDA Adverse Event Reporting System (FAERS) reports from 1968 to Q2 2024. Disproportionality analysis was performed using reporting odds ratios (RORs), with statistical significance defined as a lower limit of the 95% confidence interval (CI) >1 and at least three unique cases. Subgroup analyses were conducted by pregnancy status and underlying autoimmune indications, and comparative analyses were performed against drugs previously reported to induce ICP. Results: Among 35,576 AZA-related reports, 67 specifically documented ICP. A strong signal was detected for ICP ROR025 = 153.0; IC025 = 5.8; EBGM05 = 144.37), ranking among the highest AZA-associated adverse events. In pregnant women, ICP also showed a significant signal (ROR025 = 5.46; IC025 = 1.93; EBGM05 = 5.31). Subgroup analyses by indication revealed elevated risks in Crohn's disease (ROR025 = 66.99; IC025 = 4.8; EBGM05 = 64.73), and Colitis ulcerative (ROR025 = 9.01; IC025 = 1.95; EBGM05 = 9.95). Comparative analyses demonstrated that AZA had a higher proportion of ICP cases than other drugs reported to induce ICP. Conclusion: This pharmacovigilance analysis identifies a disproportionality signal suggesting a possible association between AZA and intrahepatic cholestasis of pregnancy. These hypothesis-generating findings underscore the importance of cautious use and clinical vigilance when prescribing AZA to women of reproductive age.
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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 | 0.059 | 0.134 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".