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Record W2058758881 · doi:10.1185/03007990802484234

The cost-effectiveness of palivizumab for respiratory syncytial virus prophylaxis in premature infants with a gestational age of 32–35 weeks: a Canadian-based analysis

2008· article· en· W2058758881 on OpenAlexaffabout
Krista L. Lanctôt, Shababa T. Masoud, Bosco Paes, Jean‐Éric Tarride, Aaron Chiu, Charles Hui, P.L. Francis, Paul Oh

Bibliographic record

VenueCurrent Medical Research and Opinion · 2008
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of ManitobaSt. Joseph’s Healthcare HamiltonMcMaster UniversityMcMaster Children's HospitalToronto Rehabilitation InstituteSunnybrook Health Science CentreHealth Sciences CentreUniversity of Toronto
FundersAbbott Laboratories
KeywordsPalivizumabMedicineGestational ageRespiratory systemPediatricsBronchopulmonary dysplasiaPregnancyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Prophylactic therapy with palivizumab, a humanized monoclonal antibody, has been shown to reduce the number of respiratory syncytial virus (RSV)-related hospitalizations in preterm infants, including those in the 32-35 weeks' gestational age (GA) subgroup. The cost-effectiveness of this therapy in Canada is unknown. OBJECTIVES: To evaluate the cost-effectiveness of palivizumab as respiratory syncytial virus prophylaxis in premature infants born at 32-35 weeks' GA. DESIGN: A decision analytic model was designed to compare both direct and indirect medical costs and benefits of prophylaxis in this subgroup of premature infants. Sensitivity analyses were performed to ascertain the robustness of the model for five point estimates: mortality rate, discounting rates, health-utility values, degree of vial-sharing and administration costs. A probabilistic sensitivity analysis (PSA) was also conducted. SETTING: Canadian publicly funded health-care system (Ministry of Health payer perspective) for base-case analysis. Societal perspective, accounting for future lost productivity, was adopted for a secondary analysis. PARTICIPANTS: Canadian infants born at 32-35 weeks' GA without chronic lung disease. INTERVENTIONS: Palivizumab prophylaxis versus no prophylaxis. MAIN OUTCOME MEASURES: Expected costs and incremental cost-effectiveness ratio expressed as cost per life-year gained (LYG) and quality-adjusted life-year (QALY) using 2007 Canadian dollars. RESULTS: The expected costs were higher for palivizumab prophylaxis as compared with no prophylaxis. The incremental cost-effectiveness ratio (ICER) for the base-case scenario was $20 924 per QALY after discounting, which is considered cost-effective in Canada. When the uncertainty of the input parameter assumptions was tested through sensitivity analyses assessing several data sources for five key parameters, no substantial differences were found from the base-case results. The PSA indicated a 0.99 probability that the ICER for palivizumab was less than $50 000/QALY. Sub-analyses that varied the number of risk factors found that for infants with two or more risk factors, or at least moderate risk, palivizumab had incremental costs per QALY that indicated moderate-to-strong evidence for adoption (range: $808-81 331, per QALY). CONCLUSIONS: Palivizumab was cost-effective and the authors' model supports prophylaxis for infants born at 32-35 weeks' GA, particularly those with more than two risk factors or at least a moderate level of risk according to a risk scoring tool.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.610

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.010
Bibliometrics0.0040.007
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.142
GPT teacher head0.459
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations75
Published2008
Admission routes2
Has abstractyes

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