Diagnostic accuracy of self collected vaginal specimens for human papillomavirus compared to clinician collected human papillomavirus specimens: a meta-analysis
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Providing summary recommendations regarding self collection of vaginal specimens for human papillomavirus (HPV) testing is difficult owing to the wide range of published estimates for the diagnostic accuracy of this approach. To determine summary estimates from analyses of reported findings of the sensitivity, specificity and summary receiver operating characteristic curves (SROC) for self collected vaginal specimens for HPV testing compared to the reference standard, clinician collected HPV specimens. METHODS: Standard search criteria for a diagnostic systematic review were employed. Eligible studies were combined using a random effects model and summary ROC curves were derived for overall and for specific subgroups. RESULTS: Summary measures were determined from 12 studies. Six studies where patients used Dacron or cotton swabs or cytobrushes to obtain samples were pooled and had an overall sensitivity of 0.74 (95% CI 0.61 to 0.84) and specificity of 0.88 (95% CI 0.83 to 0.92), with diagnostic odds ratio of 22.3 and an area under the curve of 0.91. Self specimens using Dacron or cotton swabs or cytobrushes collected by women enrolled at referral clinics had an overall sensitivity of 0.81 (95% CI 0.65 to 0.91) and specificity of 0.90 (95% CI 0.80 to 0.95). Sensitivity and specificity of tampons ranged from 0.67-0.94 and 0.80-0.85 respectively. CONCLUSIONS: Our findings indicate that the combined sensitivity for HPV-DNA is more than 70% when patients use Dacron swabs, cotton swabs, or cytobrushes to obtain their own vaginal specimens for HPV-DNA evaluation. Self collected HPV-DNA swabs may be an appropriate alternative for low resource settings or in patients reluctant to undergo pelvic examinations.
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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 | 0.033 | 0.082 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.080 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".