A Narrative Review of the Putative Etiologic Role and Diagnostic Utility of the Cervicovaginal Microbiome in Human Papillomavirus‐Associated Cervical Carcinogenesis
Bibliographic record
Abstract
The cervicovaginal microbiome (CVM) may contribute to human papillomavirus (HPV)-associated cervical carcinogenesis. We summarized the literature on the CVM in cervical carcinogenesis by searching Medline, Web of Science, and Embase for articles that sequenced the CVM using metagenomics. Additionally, we identified studies assessing the diagnostic role of the CVM in cervical carcinogenesis by searching PubMed. We performed an environmental scan of Google and Google Scholar to review common CVM characterization techniques. Twenty-eight records presented or summarized associations between the CVM and HPV acquisition, prevalence, persistence, clearance, and cervical lesions or cancer, while three studies identified bacterial taxa detecting high-risk HPV prevalence or cervical lesions. The area under the curve ranged from 0.802 to 0.952. 16S ribosomal RNA gene sequencing and whole metagenome sequencing have sufficient resolution to study the CVM bacteriome. Bacterial communities may have important implications in cervical cancer; however, there is a need for methodological standardization for CVM characterization.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".