Disproportionality analysis of progestogens and estrogens demonstrates increased meningioma risk
Bibliographic record
Abstract
OBJECTIVE: This study aims to clarify the relationship between the use of various progestogens and estrogens and the risk of developing meningiomas, given the widespread prescription of hormonal contraceptives and their potential implications in tumour proliferation. METHODS: Data from the FDA Adverse Event Reporting System (FAERS) was analyzed using disproportionality analysis to assess the association between specific progestogens and estrogens and meningioma risk. Reporting odds ratios (RORs) and 95% confidence intervals (CIs) were calculated to quantify these associations. RESULTS: Among progestogens, promegestone showed the highest risk with an ROR of 2620.651 (95% CI: 982.032, 6993.474), followed by medrogestone with an ROR of 871.475 (95% CI: 256.382, 2962.253) and dydrogesterone with moderate risk (ROR 113.802; 95% CI: 60.676, 213.444). For estrogens, estradiol exhibited the highest risk (ROR 17.786; 95% CI: 14.875, 21.266), followed by ethinyl estradiol (ROR 7.441; 95% CI: 6.099, 9.080), while conjugated estrogens showed a lower risk (ROR 1.736; 95% CI: 1.043, 2.889). No cases were reported for estriol, estrone, or mestranol, indicating a potentially lower risk profile for these estrogens. CONCLUSION: The study reveals significant variations in meningioma risk associated with different hormonal therapies. Certain progestogens and estrogens present notably higher risks, emphasizing the need for personalized risk assessments in hormonal therapy prescriptions. These findings advocate for further research to better understand meningioma risk linked to hormone-based contraceptives, supporting safer clinical decision-making.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".