The cost effectiveness of palivizumab in term Inuit infants in the Eastern Canadian Arctic
Bibliographic record
Abstract
INTRODUCTION: Canadian, Inuit, full term infants have the highest rate of respiratory syncytial virus (RSV) infection globally, which results in substantial costs associated hospitalisation. METHODS: Decision-analytical techniques were used to estimate the incremental cost-effectiveness ratio (ICER) for palivizumab compared to no prophylaxis for Inuit infants of all gestational age. The time horizon was that of life-time follow-up, and costs and effectiveness were discounted at 5% per year. Costs (2007 CAD$) for palivizumab, hospitalisation (including medical evacuation, intensive care unit [ICU]), physician visits, and transportation were calculated based on the Canadian payer's perspective. Benefits on decreasing RSV hospitalisation were expressed as quality-adjusted life-years (QALYs). One-way and probabilistic sensitivity analysis (PSA) were conducted, varying: mortality rates, utilities, length of stay in hospital and ICU. RESULTS: For all of Baffin Island infants (<1 year), the ICER was $39,435/QALY. However, when infants were grouped by age and area of residence, those residing in Iqaluit (<1 year) had an ICER of $152,145/QALY, while those residing in rural areas (outside of Iqaluit) had an ICER of $24,750/QALY. Prophylaxis was a dominant strategy (cost saving) for rural infants under 6 months of age, with the PSA demonstrating that it was dominant 98% of the time. CONCLUSIONS: The ICERs suggested that palivizumab is a cost-effective option for the prevention of RSV for Inuit infants on Baffin Island compared to no prophylaxis. Palivizumab is highly cost effective in Arctic infants <1 year of age specifically residing outside of Iqaluit and is a dominant strategy for those under 6 months of age in rural areas. However, palivizumab is not cost effective compared to no treatment for infants of all ages residing in Iqaluit.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".