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Economic value of using partially hydrolysed infant formula for risk reduction of atopic dermatitis in high-risk infants not exclusively breastfed in Singapore
Introduction
Previous trials have demonstrated reductions in atopic dermatitis (AD) incidence when healthy, high-risk, non-exclusively breastfed infants were fed until four months of age with 100% whey-based partially hydrolysed formula (PHF-W) versus standard cow’s milk formula (CMF). We assessed this intervention’s cost-effectiveness in Singapore.
Methods
Modelling techniques were used to simulate, from birth to Month 30, the incidence, and clinical and economic burden of AD in high-risk, non-exclusively breastfed infants fed with PHF-W or CMF for up to four months. Epidemiologic and clinical data were from a local comparative trial. Expert opinion informed AD treatment patterns and outcomes. Outcomes included reduction in AD risk, time spent with AD, days without AD flare, quality-adjusted life years (QALYs) and direct/indirect costs. Multivariate probabilistic sensitivity analysis assessed model parameter uncertainty.
Results
Over 30 months, with the use of PHF-W instead of CMF, the proportion of children who developed AD and time spent with AD decreased by 16.0% (28.3% vs. 44.3%) and 6.4 months, respectively, while time without AD flare and QALYs increased by 14.9 days and 0.021 QALYs per patient, respectively. Estimated AD-related discounted cost per child for PHF-W and CMF was SGD 771 and SGD 1,309, respectively (net savings = SGD 538). PHF-W was less expensive and more effective than CMF for 72.5%, and costs less than SGD 50,000 per QALY for 87.2% of all multivariate simulations.
Conclusion
Early short-term nutritional intervention with PHF-W instead of CMF may reduce AD incidence and costs in healthy, high-risk, non-exclusively breastfed infants in Singapore.
Authors
M F Botteman, A J Bhanegaonkar, E G Horodnieanu, X Ji, B W Lee, L P Shek, H P van Bever, P Detzel
Journal
Singapore medical journal
Therapeutic Area
Dermatology
Center of Excellence
Health Economic Modeling & Meta-analysis
Year
2017
Region
China
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