AUTHOR=Li Li , Chen Rirong , Zhang Yingfan , Zhou Gaoshi , Chen Baili , Zeng Zhirong , Chen Minhu , Zhang Shenghong TITLE=A Novel Model Based on Serum Biomarkers to Predict Primary Non-Response to Infliximab in Crohn’s Disease JOURNAL=Frontiers in Immunology VOLUME=12 YEAR=2021 URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2021.646673 DOI=10.3389/fimmu.2021.646673 ISSN=1664-3224 ABSTRACT=Background

Infliximab is effective in inducing and maintaining remission in patients with Crohn’s disease (CD), but primary non-response (PNR) occurs in 10-30% of cases. We investigated whether serum biomarkers are effective in predicting PNR in patients with CD.

Methods

From January 2016 to April 2020, a total of 260 patients were recruited to this prospective and retrospective cohort study. Serum samples were collected at baseline and week 2 of infliximab treatment. Serum levels of 35 cytokines were assessed in 18 patients from the discovery cohort and were further evaluated in the 60-patient cohort 1. Then, candidate cytokines and other serological biomarkers were used to construct a predictive model by logistic regression in a 182-patient cohort 2. PNR was defined based on the change of CD activity index or clinical symptoms.

Results

Among the 35 cytokines, matrix metalloproteinase 3(MMP3) and C-C motif ligand 2 (CCL2) were two effective serum biomarkers associated with PNR in both the discovery cohort and cohort 1. In cohort 2, serum level of MMP3, CCL2 and C-reactive protein (CRP) at 2 weeks after infliximab injection were independent predictors of PNR, with odds ratios (95% confidence interval) of 1.108(1.059-1.159), 0.940(0.920-0.965) and 1.102(1.031-1.117), respectively. A PNR classifier combining these three indicators had a large area under the curve [0.896(95% CI:0.895-0.897)] and negative predictive value [0.918(95%CI:0.917-0.919)] to predict PNR to infliximab.

Conclusions

MMP3, CCL2, and CRP are promising biomarkers in prediction of PNR to infliximab, and PNR classifier could accurately predict PNR and may be useful in clinical practice for therapy selection.