Chlamydia sequelae cost estimates used in current economic evaluations: does one-size-fit-all?
Bibliographic record
Abstract
BACKGROUND: Current evidence suggests that chlamydia screening programmes can be cost-effective, conditional on assumptions within mathematical models. We explored differences in cost estimates used in published economic evaluations of chlamydia screening from seven countries (four papers each from UK and the Netherlands, two each from Sweden and Australia, and one each from Ireland, Canada and Denmark). METHODS: From these studies, we extracted management cost estimates for seven major chlamydia sequelae. In order to compare the influence of different sequelae considered in each paper and their corresponding management costs on the total cost per case of untreated chlamydia, we applied reported unit sequelae management costs considered in each paper to a set of untreated infection to sequela progression probabilities. All costs were adjusted to 2013/2014 Great British Pound (GBP) values. RESULTS: Sequelae management costs ranged from £171 to £3635 (pelvic inflammatory disease); £953 to £3615 (ectopic pregnancy); £546 to £6752 (tubal factor infertility); £159 to £3341 (chronic pelvic pain); £22 to £1008 (epididymitis); £11 to £1459 (neonatal conjunctivitis) and £433 to £3992 (neonatal pneumonia). Total cost of sequelae per case of untreated chlamydia ranged from £37 to £412. CONCLUSIONS: There was substantial variation in cost per case of chlamydia sequelae used in published chlamydia screening economic evaluations, which likely arose from different assumptions about disease management pathways and the country perspectives taken. In light of this, when interpreting these studies, the reader should be satisfied that the cost estimates used sufficiently reflect the perspective taken and current disease management for their respective context.
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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 | 0.238 | 0.634 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".