title: A number-needed-to-treat analysis of the use of respiratory syncytial virus immune globulin to prevent hospitalization.
abstract: OBJECTIVE
  To estimate how many infants in selected high-risk subgroups would require treatment with respiratory syncytial virus immune globulin (RSV-IG) to avoid 1 hospital admission and to determine whether this is economically justified.
  
  
  METHODS
  Cost-benefit analysis. Data from 3 randomized controlled trials of RSV-IG are used to estimate the number needed to treat to prevent 1 hospital admission for respiratory syncytial virus infection. The threshold number needed to treat is computed according to a formula incorporating costs and benefits of RSV-IG prophylaxis. Estimates of the willingness to pay were obtained from a sample of 39 health care providers (35 physicians and 4 nurses).
  
  
  METHODS
  The number needed to treat to prevent 1 hospital admission for respiratory syncytial virus infection. The threshold number needed to treat that would balance costs with benefits.
  
  
  RESULTS
  More 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 syncytial virus infection, ranging from 63 for premature infants without chronic lung disease to 12 (confidence interval, 6.3-100.0) for infants with bronchopulmonary dysplasia. A sensitivity analysis of the costs and values of hospital admission for respiratory syncytial virus infection and RSV-IG treatment resulted in a weak recommendation against the treatment of infants with bronchopulmonary dysplasia and strong recommendations that the costs and risks of RSV-IG treatment outweigh the benefits for the combined sample of infants and premature infants without lung disease.
  
  
  CONCLUSIONS
  The number-needed-to-treat procedures 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 without lung disease. Institutions can examine cost and benefit assumptions that best fit their own practice setting.
authors.affiliation: Center for Applied Research and Evaluation, University of Arkansas for Medical Sciences, Arkansas Children's Hospital, Little Rock 72202, USA. jrobbins@care.ach.uams.edu
authors.forename: J M
authors.initials: JM
authors.lastname: Robbins
authors.forename: J M
authors.initials: JM
authors.lastname: Tilford
authors.forename: R F
authors.initials: RF
authors.lastname: Jacobs
authors.forename: J G
authors.initials: JG
authors.lastname: Wheeler
authors.forename: S R
authors.initials: SR
authors.lastname: Gillaspy
authors.forename: G E
authors.initials: GE
authors.lastname: Schutze
mesh_terms: D017046:Cost Savings; D003362:Cost-Benefit Analysis; D006801:Humans; D007116:Immunization, Passive / Q000191:economics / Q000706:statistics & numerical data*; D007223:Infant; D007231:Infant, Newborn; D007235:Infant, Premature, Diseases / Q000453:epidemiology / Q000276:immunology / Q000628:therapy; D008329:Managed Care Programs / Q000191:economics; D010343:Patient Admission / Q000191:economics / Q000706:statistics & numerical data*; D016032:Randomized Controlled Trials as Topic; D018357:Respiratory Syncytial Virus Infections / Q000453:epidemiology / Q000276:immunology / Q000628:therapy*; D018113:Respiratory Syncytial Virus, Human / Q000276:immunology; D012307:Risk Factors; D016896:Treatment Outcome