A cost–utility analysis of adding a bivalent or quadrivalent HPV vaccine to the Irish cervical screening programme
Bibliographic record
Abstract
BACKGROUND: Cervical cancer is a leading cause of death worldwide, and in Ireland it is the ninth most commonly diagnosed cancer in women. Almost 100% of these cancers are caused by human papillomavirus (HPV) infection. Two newly developed vaccines against HPV infection have become available. This study is a cost-utility analysis of the HPV vaccine in Ireland, and it compares the cost-effectiveness profiles of the two vaccines. METHODS: A cost-utility analysis of the HPV vaccine in Ireland was performed using a Markov model. A cohort of screened and vaccinated women was compared with an unvaccinated screened cohort, and both cohorts were followed over their lifetimes. The model looked at uptake of services related to HPV disease in both cohorts. Outcomes were measured in quality adjusted life years (QALYs). Extensive sensitivity analysis was done. RESULTS: For the base case analysis, the model showed that the incremental cost-effectiveness ratio (ICER) for quadrivalent HPV vaccination would be 25,349 euros/QALY and 30,460 euros/QALY for the bivalent vaccine. The ICER for the quadrivalent vaccine ranged from 2877 euros to 36,548 euros, and for the bivalent from 3399 euros to 45,237 euros. At current prices, the bivalent vaccine would need to be 22% cheaper than the quadrivalent vaccine in order to have equivalent cost effectiveness. CONCLUSION: HPV vaccination has the potential to be very cost effective in Ireland. The quadrivalent vaccine is more cost effective than the bivalent vaccine.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".