Association between ustekinumab trough concentrations and biochemical outcomes in patients with Crohn's disease. A real life study

Abstract

INTRODUCTION: numerous studies have shown a positive correlation between serum biologic drug concentrations and favorable therapeutic outcomes during the induction and maintenance period in patients with Crohn's disease (CD). To our knowledge, only a few and contradictory studies have determined the association between ustekinumab (UST) trough concentrations and biological outcomes. This study aimed to investigate the relationship between ustekinumab trough concentrations and biological outcomes in a real-world setting. METHODS: a cross-sectional cohort study was performed. All adult patients with CD who received maintenance therapy (? 24 weeks) with ustekinumab were included in the study. Clinical response was determined using the Harvey-Bradshaw Index. Biochemical remission was defined as a fecal calprotectin level < 150 µg/g in feces and a biochemical response as > 50 % reduction of fecal calprotectin. RESULTS: a total of 58 CD patients were included in the study and the median UST trough concentration was 1.78 µg/ml (IQR: 2.56). Differences in ustekinumab trough concentrations were observed for clinical (2.25 µg/ml vs 0.65 µg/ml; p = 0.006) and biochemical remission (2.33 µg/ml vs 1.03 µg/ml; p = 0.047). According to ROC analysis, a cut-off of 1.4 µg/ml (AUC: 077) and 2.0 µg/ml (AUC: 0.65) were identified for predicting clinical and biochemical remission, respectively. Likewise, ustekinumab trough levels were also higher in "composite clinical/biochemical remission" (2.38 µg/ml vs 1.08 µg/ml; p = 0.042). The trough level that was best associated with composite clinical/biochemical remission was 2.2 µg/ml (AUC: 0.69). CONCLUSION: this real-life study shows the association between ustekinumab trough concentration and clinical and biochemical remission and we suggest an optimal cut-off point higher than 2.2 µg/ml. Further studies are needed to confirm the findings and to identify the optimal cut-off in different disease outcomes and disease phenotypes.