Intensified anti-TNF treatment downregulates the phenotype in ulcerative colitis: a 13-year prospective follow-up study

Abstract

BackgroundModerate to severe ulcerative colitis (UC) is generally treated with a step-up algorithm from 5-aminosalicylic acid (5-ASA) to biological agents. There is no general recommendation if or when to de-escalate or discontinue biological therapy. In this study, we performed biological therapy with anti-tumor necrosis factor (TNF) treatment to endoscopic remission followed by discontinuation of therapy. This is a 13- year follow-up study performed for this treatment algorithm.AimThis study aimed to assess whether the treatment algorithm outlined above influences the UC phenotype toward a milder form and identify potential biomarkers for altering the disease phenotype.MethodsPatients with moderate to severe UC were enrolled from 2004 to 2015 and followed up until 2023 to evaluate disease outcomes. Patients were categorized into subgroups based on the highest treatment level required to attain remission: non-biological therapy, biological therapy, or colectomy. Mucosal TNF mRNA expression levels were measured using real-time PCR.ResultsOut of the 116 patients from the original cohort, 71 individuals who had previously undergone anti-TNF treatment to endoscopic remission and subsequently discontinued anti-TNF therapy were included in the present study. Disease outcomes were registered until 2023. By the end of the observation period, 62% of participants were in remission without biological treatment. Among the 71 patients, 39% never experienced a relapse, 23% relapsed but successfully attained remission with untargeted treatment, 18% relapsed and subsequently received a new sequence of biological therapy, and 20% had colectomy. Normalized mucosal TNF mRNA expression was identified as a significant predictor for clinical outcomes.ConclusionMost UC patients transitioned to a milder disease phenotype without requiring biological therapy. Treating to normalize mucosal TNF expression emerges as a potential biomarker, predicting the downregulation of disease severity.