Combination of Serological Biomarkers and Clinical Features To Predict Mucosal Healing in Crohn’s Disease: A Multicenter Cohort Study
Abstract Background Mucosal healing (MH) has become the treatment goal of patients with Crohn’s disease (CD). This study aims to develop a noninvasive and reliable clinical tool for individual evaluation of mucosal healing in patients with Crohn’s disease. Results The following variables were independently associated with the MH and were subsequently included into the prediction model: PLR (platelet to lymphocyte ratio), CAR (C-reactive protein to albumin ratio), ESR (erythrocyte sedimentation rate), HBI (Harvey-Bradshaw Index) score and infliximab treatment. A primary model and a simple model were established, respectively. The primary model performed better than the simple one in C-index (87.5% vs 83.0 %, p=0.004). There was no statistical significance between these two models in sensitivity (70.43% vs 62.61%, p=0.467), specificity (87.12% vs 80.69%, p=0.448), PPV (72.97% vs 61.54%, p=0.292), NPV (85.65% vs 81.39%, p=0.614), and accuracy (81.61% vs 74.71%, p=0.303). The primary model had good calibration and high levels of explained variation and discrimination in validation cohort. Conclusions This model can be used to predict MH in post-treatment CD patients. It can also be used as an indication of endoscopic surveillance to evaluate mucosal healing in patients with CD after treatment.