Human Papillomavirus Vaccination and Premature Ovarian Failure: A Disproportionality Analysis Using the Vaccine Adverse Event Reporting System
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: There have been public health concerns about a potential association between human papillomavirus (HPV) vaccines and premature ovarian failure (POF) in young women. OBJECTIVE: To identify a potential safety signal of POF after HPV vaccination using the United States (US) Vaccine Adverse Event Reporting System (VAERS) database. METHODS: We manually selected relevant MedDRA preferred terms related to POF and identified in VAERS all POF reports in women less than 40 years of age between 2 July 1990 and 14 May 2018, followed by a review of narratives to confirm the cases. We conducted descriptive analyses on age, POF type, HPV vaccine type (HPV2, HPV4, HPV9), time to onset of POF, and dose rank. We described trends in reporting over time and assessed a potential safety signal using the proportional reporting ratio (PRR). RESULTS: Of the 228,341 eligible POF reports, 281 (0.1%) were suspected to be associated with HPV vaccines. Median patient age was 15 years (range 11-39 years). POF events consisted mainly of amenorrhea (80.4%) and premature menopause (15.3%). Mean number of reported POF events significantly increased after the first HPV vaccine launch in 2006 with 22.2 POF cases/year up from 1.4 POF cases/year before the launch. PRR was 46.1 (95% confidence interval: 31.7-67.2) and sensitivity analyses yielded similar estimates. CONCLUSION: Our study suggests the presence of a potential safety signal of POF associated with HPV vaccination, which may only be partly attributed to notoriety bias. Due to the well-known limitations of spontaneous reporting data, further investigations are warranted.
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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 | 0.001 | 0.000 |
| 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) | 0.001 | 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 it