Economic evaluation of strategies for managing women with equivocal cytological results in Brazil
Bibliographic record
Abstract
In Brazil, current management of women with screening results of atypical squamous cells of undetermined significance (ASC-US) is to offer repeat testing at 6-month intervals. Alternative management strategies that have been adopted in many high-income settings are to offer immediate colposcopy referral or to utilise human papillomavirus (HPV) DNA testing as a triage for colposcopy referral, and to consider different strategies according to women's age. The objective of our study was to evaluate the lifetime cost effectiveness in terms of cost per years of life saved (YLS) of these alternative strategies for a middle income setting. A Markov model was developed using data from the Ludwig-McGill cohort and calibrated to independent observational datasets and local cost estimates obtained. In the base-case analysis, repeat cytology was the least costly strategy but also the least effective. Based on the WHO threshold for very cost-effective interventions, HPV triage for women above 30 years-old was the strategy with the highest probability of being cost effective. HPV triage including younger women with ASCUS results would also be a cost-effective option. Whilst there was a slight further gain in effectiveness with immediate colposcopy referral, it was also more expensive and did not appear to be cost effective. Threshold analysis indicated that an HPV test would have to be more than twice as expensive as a cytology test for HPV triage to no longer be cost effective. In conclusion, our results indicate that in middle income settings HPV triage is likely to be the optimal strategy for managing women presenting with ASC-US results.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".