High-dose inactivated influenza vaccine is associated with cost savings and better outcomes compared to standard-dose inactivated influenza vaccine in Canadian seniors
Bibliographic record
Abstract
Seasonal influenza infects approximately 10-20% of Canadians each year, causing an estimated 12,200 hospitalizations and 3,500 deaths annually, mostly occurring in adults ≥65 years old (seniors). A 32,000-participant, randomized controlled clinical trial (FIM12; Clinicaltrials.gov NCT01427309) showed that high-dose inactivated influenza vaccine (IIV-HD) is superior to standard-dose vaccine (SD) in preventing laboratory-confirmed influenza illness in seniors. In this study, we performed a cost-utility analysis (CUA) of IIV-HD versus SD in FIM12 participants from a Canadian perspective. Healthcare resource utilization data collected in FIM12 included: medications, non-routine/urgent care and emergency room visits, and hospitalizations. Unit costs were applied using standard Canadian cost sources to estimate the mean direct medical and societal costs associated with each vaccine (2014 CAD). Clinical illness data from the trial were mapped to quality-of-life data from the literature to estimate differences in effectiveness between vaccines. Time horizon was one influenza season, however, quality-adjusted life-years (QALYs) lost due to death during the study were captured over a lifetime. A probabilistic sensitivity analysis (PSA) was also performed. Average per-participant medical costs were $47 lower and societal costs $60 lower in the IIV-HD arm. Hospitalizations contributed 91% of the total cost and were less frequent in the IIV-HD arm. IIV-HD provided a gain in QALYs and, due to cost savings, dominated SD in the CUA. The PSA indicated that IIV-HD is 89% likely to be cost saving. In Canada, IIV-HD is expected to be a less costly and more effective alternative to SD, driven by a reduction in hospitalizations.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".