Accuracy of Combined Visual Inspection with Acetic Acid and Cervical Cytology Testing as a Primary Screening Tool for Cervical Cancer: a Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: The performance of combined testing visual inspection with acetic acid (VIA) and cervical cytology tests might differ from one setting to another. The average estimate of the testing accuracy across studies is informative, but no meta-analysis has been carried out to assess this combined method. OBJECTIVE: The objective of this study was to estimate the average sensitivity and specificity of the combined VIA and cervical cytology tests for the detection of cervical precancerous lesions. MATERIALS AND METHODS: We conducted a systematic review and a meta-analysis, according to the Cochrane Handbook for Systematic Review of Diagnostic Test Accuracy. We considered two cases. In the either-positive result case, a positive result implies positivity in at least one of the tests. A negative result implies negativity in both tests. In the both-positive case, a positive result implies having both tests positive. Eligible studies were identified using Pubmed, Embase, Website of Science, CINHAL and COCRANE databases. True positive, false positive, false negative and true negative values were extracted. Estimates of sensitivity and specificity, positive and negative likelihood (LR) and diagnostic odds ratios (DOR) were pooled using a hierarchical random effect model. Hierarchical summary receiver operating characteristics (HSROC) were generated and heterogeneity was verified through covariates potentially influencing the diagnostic odds ratio. FINDINGS: Nine studies fulfilled inclusion criteria and were included in the analysis. Pooled estimates of the sensitivities of the combined tests in either-positive and both-positive cases were 0.87 (95% CI: 0.83-0.90) and 0.38 (95% CI: 0.29-0.48), respectively. Corresponding specificities were 0.79 (95% CI: 0.63-0.89) and 0.98 (95% CI: 0.96-0.99) respectively. The DORs of the combined tests in either-positive or both-positive result cases were 27.7 (95% CI: 12.5-61.5) and 52 (95% CI: 22.1-122.2), respectively. When including only articles without partial verification bias and also a high-grade cervical intraepithelial neoplasia as a threshold of the disease, DOR of combined test in both-positive result cases remained the highest. However, DORs decreased to 12.1 (95% CI: 6.05-24.1) and 13.8 (95% CI: 7.92-23.9) in studies without partial verification bias for the combined tests in the either-positive and both-positive result cases, respectively. The screener, the place of study and the size of the population significantly influenced the DOR of combined tests in the both-positive result case in restriction analyses that considered only articles with CIN2+ as disease threshold. CONCLUSIONS: The combined test in the either-positive result case has a high sensitivity, but a low specificity. These results suggest that the combined test should be considered in developing countries as a primary screening test if facilities exist to confirm, through colposcopy and biopsy, a positive result.
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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 | 0.020 | 0.060 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.045 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".