Cost-Effectiveness of Extending Human Papillomavirus Vaccination to Population Subgroups Older Than 26 Years Who Are at Higher Risk for Human Papillomavirus Infection in the United States
Bibliographic record
Abstract
BACKGROUND: In June 2019, the U.S. Advisory Committee on Immunization Practices recommended shared clinical decision making regarding potential human papillomavirus (HPV) vaccination of men and women aged 27 to 45 years ("mid-adults"). OBJECTIVE: To examine the incremental cost-effectiveness ratios (ICERs) and number needed to vaccinate (NNV) to prevent 1 HPV-related cancer case of expanding HPV vaccination to subgroups of mid-adults at increased risk for HPV-related diseases in the United States. DESIGN: Individual-based transmission dynamic modeling of HPV transmission and associated diseases using HPV-ADVISE (Agent-based Dynamic model for VaccInation and Screening Evaluation). DATA SOURCES: Published data. TARGET POPULATION: All U.S. mid-adults and higher-risk subgroups within this population. TIME HORIZON: 100 years. PERSPECTIVE: Health care sector. INTERVENTION: Expanding 9-valent HPV vaccination to mid-adults and higher-risk subgroups. OUTCOME MEASURES: ICERs and NNVs. RESULTS OF BASE-CASE ANALYSIS: Expanding 9-valent HPV vaccination to all mid-adults, those with more lifetime partners, and those who have just separated was projected to cost an additional $2 005 000, $763 000, and $1 164 000 per quality-adjusted life-year (QALY) gained, respectively. The NNVs to prevent 1 additional HPV-related cancer case were 7670, 3190, and 5150, respectively, compared with 223 for vaccination of persons aged 9 to 26 years (vs. no vaccination). RESULTS OF SENSITIVITY ANALYSIS: The mid-adult strategy with the lowest ICER and NNV was vaccinating infrequently screened mid-adult women who have just separated and have a higher number of lifetime sex partners (ICER, $86 000 per QALY gained; NNV, 470). LIMITATION: Uncertainty about rate of new sex partners and natural history of HPV among mid-adults. CONCLUSION: Vaccination of mid-adults against HPV is substantially less cost-effective and produces higher NNVs than vaccination of persons younger than 26 years under all scenarios investigated. However, cost-effectiveness and NNV are projected to improve when higher-risk mid-adult subgroups are vaccinated, such as mid-adults with more sex partners and who have recently separated, and women who are underscreened. PRIMARY FUNDING SOURCE: Centers for Disease Control and Prevention.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".