Cost-effectiveness of the next generation nonavalent human papillomavirus vaccine in the context of primary human papillomavirus screening in Australia: a comparative modelling analysis
Bibliographic record
Abstract
BACKGROUND: First generation bivalent and quadrivalent human papillomavirus (HPV) vaccines have been introduced in most developed countries. A next generation nonavalent vaccine (HPV9) has become available, just as many countries are considering transitioning from cytology-based to HPV-based cervical screening. A key driver for the cost-effectiveness of HPV9 will be a reduction in screen-detected abnormalities and surveillance tests. We aimed to evaluate the cost-effectiveness of HPV9 in Australia, a country with HPV vaccination of both sexes that is transitioning to 5-yearly HPV-based screening. METHODS: We used Policy1-Cervix and HPV-ADVISE-two dynamic models of HPV transmission, vaccination, and cervical screening-to estimate the cost-effectiveness of HPV9 versus quadrivalent vaccine (HPV4), assuming lifelong vaccine protection, two vaccine doses, and that additional costs were incurred in girls only. Policy1-Cervix was used to estimate the lifetime risk of cervical cancer diagnosis and death. Probabilistic sensitivity analysis of the cost-effectiveness outcomes was done with both models, and results are presented as the median and 10th to 90th percentiles of simulation runs (referred to as 80% uncertainty intervals [UIs]). FINDINGS: Compared with cytology-based screening, HPV screening is predicted to reduce lifetime risk of cervical cancer diagnosis by 18% and of death by 20%, even in unvaccinated cohorts. Under base-case assumptions (lifelong protection, full efficacy at two doses), HPV4 will provide a further reduction in diagnosis of 54% and in death of 53% and HPV9 will provide a further reduction in both diagnosis and death of 11%, compared with cytology-based screening in unvaccinated cohorts. For HPV9 to remain a cost-effective alternative to HPV4, the incremental cost per dose in girls should not exceed a median of AUS$35·99 (80% UI 28·47-41·18) with Policy1-Cervix or AUS$22·74 (15·49-34·45) with HPV-ADVISE, at a willingness-to-pay threshold of AUS$30 000 per quality-adjusted life-year. INTERPRETATION: Differing methods and assumptions led to some differences in the estimates produced by the two models. However, on the basis of median results, HPV9 will be a cost-effective alternative to HPV4 if the additional cost per dose is AUS$23-36 (US$18-28). These results will be important when determining the optimum price of the vaccine in Australia. FUNDING: National Health and Medical Research Council, Australia.
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.
How this classification was reachedexpand
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".