Impact of using the International Risk Scoring Tool on the cost-utility of palivizumab for preventing severe respiratory syncytial virus infection in Canadian moderate-to-late preterm infants
Bibliographic record
Abstract
To assess the cost-utility of palivizumab versus no prophylaxis in preventing severe respiratory syncytial virus (RSV) infection in Canadian moderate-to-late preterm (32-35 weeks’ gestational age) infants using an: i) International Risk Scoring Tool (IRST); ii) Canadian RST (CRST). A decision tree was developed to assess cost-utility. Infants assessed at moderate- and high-risk of RSV-related hospitalization (RSVH) by the IRST or CRST received palivizumab or no prophylaxis and then progressed to either: i) RSVH; ii) emergency room/outpatient medically attended RSV-infection (MARI); or, iii) were uninfected/non-medically attended. Infants admitted to intensive care could incur mortality (0.43%). Respiratory morbidity was accounted in all uninfected surviving infants for 6 years or 18 years (RSVH/MARI). Palivizumab efficacy (72.2% RSVH reduction) and hospital outcomes were from the Canadian CARESS, PICNIC and RSV-Quebec studies. Palivizumab costs (50mg: CAN$752; 100mg: $1,505) were calculated from Canadian birth statistics combined with a growth algorithm. Healthcare/payer and societal costs (May 2022; 1.5% discounting) were included. Cost per quality-adjusted life year (QALY) was $29,789 with the IRST (0.79 probability of being <$50,000) and $15,833 with the CRST (0.96 probability). The model was most sensitive to utility scores, long-term sequelae, and palivizumab cost. Vial sharing improved the incremental cost-utility ratio (IRST: $22,319; CRST: $9,231). Palivizumab was highly cost-effective (vs no prophylaxis) in Canadian moderate-to-late preterm infants using either the IRST or CRST. The IRST has fewer risk factors than the CRST (3 vs 7, respectively), captures more potential RSVHs (85% vs 54%) and provides another option to guide cost-effective RSV prophylaxis 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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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) | 0.002 | 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".