Multiple Cytokine Profiling: A New Model to Predict Response to Tumor Necrosis Factor Antagonists in Ulcerative Colitis Patients

Abstract Background and Aims Ulcerative colitis (UC) is a form of inflammatory bowel disease, and antibodies against tumor necrosis factor (anti-TNF) are used for treatment. Many patients are refractory or lose response to anti-TNF, and predicting response would be an extremely valuable clinical tool. Unlike most biomarkers, cytokines directly mediate inflammation, and their measurement may predict the likelihood of response or no response. Methods Serum samples were obtained from 49 UC patients before infliximab infusions, and levels of 17 cytokines were measured using a multiplex assay. The Fisher linear discriminant analysis (FLDA) was applied to the cytokine values to predict which patients would respond to infliximab. “Response” was defined as clinical remission after the third infusion, and “no response” was defined as lack of remission after the third infusion. Results The Fisher linear discriminant analysis model identified a subset of seven predictor cytokines: TNF-α, IL-12, IL-8, IL-2, IL-5, IL1-β, and IFN-γ. The obtained canonical coefficients enabled to calculate discriminant scores as linear combinations of the cytokines; model classified thepatients as responders and nonresponders with a sensitivity of 84.2% and a specificity of 93.3%. Overall, the yield of the FLDA model was 89.8% of the total 49 patients. Conclusions An unbiased, statistically derived, predictive model based on measurement of serum cytokines before therapy may predict a positive or negative outcome from the administration of anti-TNF to UC patients. Because accurately measuring cytokines is simple and inexpensive, the model may be a valuable new tool to complement other laboratory parameters used in the management of IBD patients.