Systematic reviews and meta-analyses of the accuracy of HPV tests, visual inspection with acetic acid, cytology, and colposcopy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Cervical cancer screening is offered to women to identify and treat cervical intraepithelial neoplasia (CIN). OBJECTIVES: To support WHO guidelines, a systematic review was performed to compare test accuracy of the HPV test, cytology (cervical smear), and unaided visual inspection with acetic acid (VIA); and to determine test accuracy of HPV and colposcopy impression. SEARCH STRATEGY: Medline and Embase were searched up to September 2012, and experts were contacted for references. SELECTION CRITERIA: Studies of at least 100 nonpregnant women (aged ≥18years) not previously diagnosed with CIN were included. DATA COLLECTION AND ANALYSIS: Two investigators independently screened and collected data. Pooled sensitivity and specificity, and absolute differences were calculated, and the quality of evidence assessed using GRADE (Grading of Recommendations Assessment, Development and Evaluation). MAIN RESULTS: High to moderate quality evidence was found. The greatest difference in overtreatment occurred with VIA instead of the cervical smear (58 more per 1000 women). Differences in missed treatment ranged from 2-5 per 1000 women. For 1000 women screened positive and then sent to colposcopy, 464 would be falsely diagnosed with CIN grade 2-3 and treated. CONCLUSIONS: Although differences in sensitivity between tests could be interpreted as large, absolute differences in missed diagnoses were small. By contrast, small differences in specificity resulted in fairly large absolute differences in overtreatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 it