Real-World Evidence in Cost-Effectiveness Analysis of Enhanced Influenza Vaccines in Adults ≥ 65 Years of Age: Literature Review and Expert Opinion
Bibliographic record
Abstract
Influenza vaccination can benefit most populations, including adults ≥ 65 years of age, who are at greater risk of influenza-related complications. In many countries, enhanced vaccines, such as adjuvanted, high-dose, and recombinant trivalent/quadrivalent influenza vaccines (aTIV/aQIV, HD-TIV/HD-QIV, and QIVr, respectively), are recommended in older populations to provide higher immunogenicity and increased relative vaccine efficacy/effectiveness (rVE) than standard-dose vaccines. This review explores how efficacy and effectiveness data from randomized controlled trials and real-world evidence (RWE) are used in economic evaluations. Findings from published cost-effectiveness analyses (CEA) on enhanced influenza vaccines for older adults are summarized, and the assumptions and approaches used in these CEA are assessed alongside discussion of the importance of RWE in CEA. Results from many CEA showed that adjuvanted and high-dose enhanced vaccines were cost-effective compared with standard vaccines, and that differences in rVE estimates and acquisition price may drive differences in cost-effectiveness estimates between enhanced vaccines. Overall, RWE and CEA provide clinical and economic rationale for enhanced vaccine use in people ≥ 65 years of age, an at-risk population with substantial burden of disease. Countries that consider RWE when making vaccine recommendations have preferentially recommended aTIV/aQIV, as well as HD-TIV/HD-QIV and QIVr, to protect older individuals.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".