Economic evaluation of a 100% whey-based partially hydrolyzed infant formula in the prevention of atopic dermatitis among Swiss children
Bibliographic record
Abstract
OBJECTIVE: A pharmacoeconomic analysis was undertaken to determine costs, consequences, and cost-effectiveness of a partially hydrolyzed 100% whey-based infant formula, NAN-HA®, manufactured by Nestlé S.A, Switzerland (PHF-W), branded under BEBA HA® in Switzerland, in the prevention of atopic dermatitis (AD) in 'at risk' Swiss children when compared to standard cow's milk formula (SF). METHODS: Based on a 12-month time horizon including 6 months of formula consumption, an economic model was developed synthesizing treatment pathways, resource utilization, and costs associated with the treatment of AD in healthy 'at risk' Swiss newborns who could not be exclusively breastfed. Model inputs were retrieved from the literature, official formularies, and expert opinion. The treatment pathways considered a medical treatment approach, supplemented in some instances by a change of formula. The final outcome was the expected cost per avoided case of AD, yielding an incremental cost effectiveness ratio (ICER) for PHF-W vs SF. Outcomes were presented from three perspectives: the Swiss public healthcare system (MOH), the subject's family, and society (SOC). A secondary analysis compared PHF-W to whey-based extensively hydrolyzed formula (EHF) in prevention. RESULTS: The model yielded 1653 avoided AD cases by selecting PHF-W over SF in a birth cohort of 22,933 'at risk' infants. The base case analyses generated an expected ICER of CHF 982 from the MOH perspective as well as savings of CHF 2202 and CHF 1220 from the family and SOC perspectives, respectively. PHF-W yielded CHF 11.4M savings against EHF when the latter was assumed to be used in prevention. One-way and probabilistic sensitivity analyses confirmed the robustness of the model. CONCLUSION: Under a range of assumptions, this analysis has established the dominance from the family and societal perspectives and cost-effectiveness from the MOH perspective of PHF-W vs SF in the prevention of AD among 'at risk' Swiss infants.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".