RATIONALE: Reslizumab is a humanized anti-IL-5 monoclonal antibody used as 
add-on maintenance treatment for patients with uncontrolled eosinophilic asthma.
OBJECTIVES: To predict response and nonresponse to intravenous reslizumab at 52 
weeks with an algorithm we developed based on clinical indicators from pivotal 
clinical trials.
METHODS: Patients aged 18 years and older who met Global Initiative for Asthma 4 
or 5 criteria and received intravenous reslizumab (n = 321) in two trials ( 
www.clinicaltrials.gov identifiers, NCT01287039 and NCT01285323) were selected 
as the data source. A mathematical model was constructed that was based on 
change from baseline to 16 weeks in Asthma Control Questionnaire and Asthma 
Quality of Life Questionnaire scores and FEV1, and number of clinical asthma 
exacerbations during the year before enrollment and in the first 16 weeks of 
treatment, and these measures were evaluated for their ability to predict the 
outcome at 52 weeks: responder, nonresponder, or indeterminate.
MEASUREMENTS AND MAIN RESULTS: The algorithm predicted that 276 patients would 
be classified as responders; in 248 (89.9%), the prediction was correct. In 
comparison, 26 patients were predicted to be nonresponders; 50.0% of these 
predictions were correct. Nineteen patients were classified as indeterminate. 
The algorithm had 95.4-95.5% sensitivity and 40.6-54.1% specificity. Jackknife 
and cross-study validation confirmed the robustness of the algorithm.
CONCLUSIONS: Our algorithm enabled prediction at 16 weeks of treatment of the 
response to intravenous reslizumab treatment at 52 weeks, but it was not 
suitable for predicting nonresponse. A positive score at 16 weeks should 
encourage continued treatment, and a negative score should prompt close 
monitoring to determine whether discontinuation is warranted.