Pregnancy and Perinatal Outcomes Following Exposure to Antineoplastic Agents Around Pregnancy within the US FDA Adverse Event Reporting System
Bibliographic record
Abstract
Objective: To review pregnancy and perinatal outcomes associated with exposure to antineoplastic drugs around pregnancy as reported within the US FDA Adverse Event Reporting System (FAERS). Methods: The FAERS database was accessed and reports of exposure to antineoplastic drugs before/during pregnancy 2000–2020 were reviewed. An analysis of the frequency of different adverse pregnancy outcomes and perinatal outcomes was conducted for all agents as well as for specific categories of antineoplastic agents. Results: A total of 5312 reports of pregnancy exposure to antineoplastic drugs within the FAERS database were found to be eligible and were included in the current study. The most frequent adverse pregnancy outcomes included premature delivery (21.8%) and abortion (11.9%). The most frequent adverse perinatal outcomes included congenital malformations (15.9%) and fetal/neonatal death (12.9%). Conclusions: Within the limitations of the study (especially the lack of an accurate denominator), premature delivery, abortion, fetal/neonatal death and congenital malformations seemed to be the main risks associated with pregnancy exposure to antineoplastic drugs.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".