Changing costs and the impact on RSV prophylaxis
Bibliographic record
Abstract
OBJECTIVE: Acquisition costs of palivizumab have increased in Canada since 2007. This analysis aims to re-evaluate the cost effectiveness of palivizumab in Canada for premature infants born between 32 and 35 weeks' gestational age using updated 2010 healthcare costs compared to those used in a 2007 decision analytic model. METHODS: New costs (CAN$) were acquired from the same Health Canada and Ontario Ministry of Health sources that were utilized in the previously published 2007 model. Palivizumab prices were acquired from Abbott Laboratories Ltd., current as of August 2010. RESULTS: Incremental cost-effectiveness ratios (ICERs) rose by $742, going from $30,618/QALY to $31,360/QALY. ICER changes increased from a range of $801,297 to $820,701 for infants with zero risk factors to a decrease from $808 to $192 for infants with four or more risk factors. CONCLUSIONS: Palivizumab ICERs remained fairly stable from 2007 to 2010. The original recommendation stating that palivizumab is cost effective in infants born between 32 and 35 weeks' GA with two or more risk factors, or who are at moderate-to-high risk based on a risk assessment model, does not change. Analyses founded on evolving country-specific variables are needed in order to accurately reassess the cost effectiveness of interventions as costs change worldwide. LIMITATIONS: There are a limited number of publications reporting mortality in premature Canadian infants with RSV as a primary outcome. In addition, conclusions drawn from this analysis are country-specific and limited to premature infants dwelling in Canada.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 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".