A NUMBER-NEEDED-TO-TREAT ANALYSIS OF THE USE OF RESPIRATORY SYNCYTIALVIRUS IMMUNE GLOBULIN TO PREVENT HOSPITALIZATION

Objectives: To estimate how many infants in selected high-risk subgrou ps would require treatment with respiratory syncytial virus immune glo bulin (RSV-IG) to avoid 1 hospital admission and to determine whether this is economically justified. Design: Cost-benefit analysis. Data fr om 3 randomized controlled trials of RSV-IG are used to estimate the n umber needed to treat to prevent 1 hospital admission for respiratory syncytial virus infection. The threshold number needed to treat is com puted according to a formula incorporating costs and benefits of RSV-I G prophylaxis. Estimates of the willingness to pay were obtained from a sample of 39 health care providers (35 physicians and 4 nurses). Mai n Outcome Measures: The number needed to treat to prevent 1 hospital a dmission for respiratory syncytial virus infection. The threshold numb er needed to treat that would balance costs with benefits. Results: Mo re than 16 (95% confidence interval, 12.5-23.8) infants would need to be treated with RSV-IG to avoid 1 hospital admission for respiratory s yncytial virus infection, ranging from 63 for premature infants withou t chronic lung disease to 12 (confidence interval, 6.3-100.0) for infa nts with bronchopulmonary dysplasia. A sensitivity analysis of the cos ts and values of hospital admission for respiratory syncytial virus in fection and RSV-IG treatment resulted in a weak recommendation against the treatment of infants with bronchopulmonary dysplasia and strong r ecommendations that the costs and risks of RSV-IG treatment outweigh t he benefits for the combined sample of infants and premature infants w ithout lung disease. Conclusions: The number-needed-to-treat procedure s offer a method to assess evidence of treatment effects and decision rules for whether to accept treatment recommendations. Under plausible assumptions, treatment with RSV-IG is not recommended for infants wit hout lung disease. Institutions can examine cost and benefit assumptio ns that best fit their own practice setting.