Probiotics for Preventing Relapse in Ulcerative Colitis: A Systematic Review and Bayesian Network Meta-Analysis
), Virly Nanda Muzellina(2), Nicolas Daniel Widjanarko(3), Yeong Yeh Lee(4), Olivia Wangidjaja(5),
(1) School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia
(2) Division of Gastroenterology, Pancreatobiliary, and Digestive Endoscopy, Department of Internal Medicine, Dr. Cipto Mangunkusumo National General Hospital, Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia
(3) School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia
(4) School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
(5) School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia
Corresponding Author
Abstract
Background: Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by periods of relapse and remission. Preventing relapse is critical to improving long-term outcomes. This study aimed to compare the efficacy of probiotics, 5-aminosalicylic acid (5-ASA), probiotics combined with 5-ASA, and placebo in preventing relapse in UC.
Methods: A comprehensive search from PubMed, Cochrane Library, MEDLINE, ProQuest, ScienceDirect, Clinical Trials. gov and Google Scholar databases were conducted. The primary outcome was clinical relapse. A Bayesian random-effects model calculated pooled odds ratios (ORs) with 95% CIs and treatment ranks were assessed using the surface under the cumulative ranking curve (SUCRA).
Results: Of total 552 initial papers, 37 extracted, and 26 were removed due to exclusion criteria. Eleven RCTs involving 1,099 participants were eventually included for analysis. Probiotics combined with 5-ASA had the highest efficacy (OR = 0.23, 95% CI: 0.027–1.09; SUCRA = 71.43), followed by 5-ASA alone (OR = 0.25, 95% CI: 0.035–0.95; SUCRA = 66.90) and probiotics alone (OR = 0.275, 95% CI: 0.059–0.724; SUCRA = 59.69). Placebo ranked lowest (SUCRA = 1.98). The most commonly used probiotics included E. coli Nissle 1917, Lactobacillus GG, and Bifidobacterium species. The most frequently used 5-ASA preparation was mesalazine. Interventions were generally well-tolerated, with no significant adverse events reported.
Conclusion: With the Bayesian NMA, Probiotics plus 5-ASA demonstrates the highest efficacy in preventing relapses in UC. Further research is needed to standardize probiotic regimens and to assess long-term outcomes with the combination approach.
Keywords
References
McDowell C, Farooq U, Haseeb M. Inflammatory Bowel Disease. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 [cited 2025 Aug 11]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK470312/
Colombel JF, Shin A, Gibson PR. AGA Clinical Practice Update on Functional Gastrointestinal Symptoms in Patients With Inflammatory Bowel Disease: Expert Review. Clin Gastroenterol Hepatol. 2019 Feb;17(3):380-390.e1.
Cosnes J, Gower-Rousseau C, Seksik P, Cortot A. Epidemiology and natural history of inflammatory bowel diseases. Gastroenterology. 2011 May;140(6):1785–94.
Niriella MA, De Silva AP, Dayaratne AHGK, Ariyasinghe MHADP, Navarathne MMN, Peiris RSK, et al. Prevalence of inflammatory bowel disease in two districts of Sri Lanka: a hospital based survey. BMC Gastroenterol. 2010 Mar 19;10:32.
Asakura K, Nishiwaki Y, Inoue N, Hibi T, Watanabe M, Takebayashi T. Prevalence of ulcerative colitis and Crohn’s disease in Japan. J Gastroenterol. 2009;44(7):659–65.
Muzammil MA, Fariha F, Patel T, Sohail R, Kumar M, Khan E, et al. Advancements in Inflammatory Bowel Disease: A Narrative Review of Diagnostics, Management, Epidemiology, Prevalence, Patient Outcomes, Quality of Life, and Clinical Presentation. Cureus. 2023 Jun;15(6):e41120.
Yoshimatsu Y, Yamada A, Furukawa R, Sono K, Osamura A, Nakamura K, et al. Effectiveness of probiotic therapy for the prevention of relapse in patients with inactive ulcerative colitis. World J Gastroenterol. 2015 May 21;21(19):5985–94.
Mazziotta C, Tognon M, Martini F, Torreggiani E, Rotondo JC. Probiotics Mechanism of Action on Immune Cells and Beneficial Effects on Human Health. Cells. 2023 Jan 2;12(1):184.
Hsu CY, Mustafa MA, Moath Omar T, Taher SG, Ubaid M, Gilmanova NS, et al. Gut instinct: harnessing the power of probiotics to tame pathogenic signaling pathways in ulcerative colitis. Front Med (Lausanne). 2024;11:1396789.
Abraham BP, Quigley EMM. Probiotics in Inflammatory Bowel Disease. Gastroenterol Clin North Am. 2017 Dec;46(4):769–82.
Su GL, Ko CW, Bercik P, Falck-Ytter Y, Sultan S, Weizman AV, et al. AGA Clinical Practice Guidelines on the Role of Probiotics in the Management of Gastrointestinal Disorders. Gastroenterology. 2020 Aug;159(2):697–705.
Bischoff SC, Escher J, Hébuterne X, Kłęk S, Krznaric Z, Schneider S, et al. ESPEN practical guideline: Clinical Nutrition in inflammatory bowel disease. Clin Nutr. 2020 Mar;39(3):632–53.
Guo N, Lv LL. Mechanistic insights into the role of probiotics in modulating immune cells in ulcerative colitis. Immun Inflamm Dis. 2023 Oct;11(10):e1045.
Wirya LE, Schoeck HPG, Simatupang EP. The effect of probiotics on inflammatory bowel disease remission and relapse rate: A systematic review and meta-analysis. J Penyakit Dalam Udayana. 2024 May 5;8(1):12–8.
Kaur L, Gordon M, Baines PA, Iheozor-Ejiofor Z, Sinopoulou V, Akobeng AK. Probiotics for induction of remission in ulcerative colitis. Cochrane Database Syst Rev. 2020 Mar 4;3(3):CD005573.
Iheozor-Ejiofor Z, Kaur L, Gordon M, Baines PA, Sinopoulou V, Akobeng AK. Probiotics for maintenance of remission in ulcerative colitis. Cochrane Database Syst Rev. 2020 Mar 4;3(3):CD007443.
Cochrane Bias. RoB 2: A revised Cochrane risk-of-bias tool for randomized trials [Internet]. [cited 2025 Aug 11]. Available from: https://methods.cochrane.org/bias/resources/rob-2-revised-cochrane-risk-bias-tool-randomized-trials
Izcovich A, Chu DK, Mustafa RA, Guyatt G, Brignardello-Petersen R. A guide and pragmatic considerations for applying GRADE to network meta-analysis. BMJ. 2023 Jun 27;381:e074495.
Owen RK, Bradbury N, Xin Y, Cooper N, Sutton A. MetaInsight: An interactive web-based tool for analyzing, interrogating, and visualizing network meta-analyses using R-shiny and netmeta. Res Synth Methods. 2019 Dec;10(4):569–81.
Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009 Jul 21;6(7):e1000097.
Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al., editors. Cochrane Handbook for Systematic Reviews of Interventions [Internet]. 2nd ed. Chichester (UK): John Wiley & Sons; 2019. Available from: https://training.cochrane.org/handbook
DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986 Sep;7(3):177–88.
Rücker G, Schwarzer G. Reduce dimension or reduce weights? Comparing two approaches to multi-arm studies in network meta-analysis. Stat Med. 2014 Jan 30;33(25):4353–69.
Salanti G. Indirect and mixed-treatment comparison, network, or multiple treatments meta-analysis: many names, many benefits, many concerns for the next generation evidence synthesis tool. Res Synth Methods. 2012 Mar;3(2):80–97.
Higgins JP, Jackson D, Barrett JK, Lu G, Ades AE, White IR. Consistency and inconsistency in network meta-analysis: concepts and models for multi-arm studies. Res Synth Methods. 2012 Mar;3(2):98–110.
Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008 Apr 26;336(7650):924–6.
Guyatt GH, Oxman AD, Kunz R, Vist GE, Falck-Ytter Y, Schünemann HJ, et al. What is "quality of evidence" and why is it important to clinicians? BMJ. 2008 May 3;336(7651):995–8.
Guyatt GH, Oxman AD, Kunz R, Brozek J, Alonso-Coello P, Rind D, et al. GRADE guidelines 6. Rating the quality of evidence--imprecision. J Clin Epidemiol. 2011 Dec;64(12):1283–93.
Guyatt GH, Oxman AD, Kunz R, Woodcock J, Brozek J, Helfand M, et al. GRADE guidelines: 8. Rating the quality of evidence--indirectness. J Clin Epidemiol. 2011 Dec;64(12):1303–10.
Guyatt GH, Oxman AD, Sultan S, Glasziou P, Akl EA, Alonso-Coello P, et al. GRADE guidelines: 9. Rating up the quality of evidence. J Clin Epidemiol. 2011 Dec;64(12):1311–6.
Guyatt GH, Oxman AD, Sultan S, Brozek J, Glasziou P, Alonso-Coello P, et al. GRADE guidelines: 11. Making an overall rating of confidence in effect estimates for a single outcome and for all outcomes. J Clin Epidemiol. 2013 Feb;66(2):151–7.
Guyatt GH, Oxman AD, Sultan S, Brozek J, Glasziou P, Akl EA, et al. GRADE guidelines: 12. Preparing summary of findings tables--binary outcomes. J Clin Epidemiol. 2013 Feb;66(2):158–72.
Guyatt GH, Oxman AD, Sultan S, Brozek J, Glasziou P, Akl EA, et al. GRADE guidelines: 13. Preparing summary of findings tables--continuous outcomes. J Clin Epidemiol. 2013 Feb;66(2):173–83.
Schünemann HJ, Brożek J, Guyatt G, Oxman A, editors. GRADE Handbook for Grading Quality of Evidence and Strength of Recommendations. Updated October 2013. The GRADE Working Group, 2013. Available from: https://gdt.gradepro.org/app/handbook/handbook.html
Sterne JAC, Savović J, Page MJ, Elbers RG, Blencowe NS, Boutron I, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. 2019 Aug 28;366:l4898.
IntHout J, Ioannidis JPA, Borm GF. The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian–Laird method. BMC Med Res Methodol. 2014 Feb 18;14:25.
Rücker G, Schwarzer G, Carpenter JR, Schumacher M. Undue reliance on I² in assessing heterogeneity may mislead. BMC Med Res Methodol. 2008 Dec 17;8:79.
Huedo-Medina TB, Sánchez-Meca J, Marín-Martínez F, Botella J. Assessing heterogeneity in meta-analysis: Q statistic or I² index? Psychol Methods. 2006 Jun;11(2):193–206.
Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997 Sep 13;315(7109):629–34.
Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics. 1994 Dec;50(4):1088–101.
Duval S, Tweedie R. Trim and fill: a simple funnel-plot–based method of testing and adjusting for publication bias in meta-analysis. Biometrics. 2000 Jun;56(2):455–63.
Sterne JA, Egger M, Moher D, editors. Addressing Reporting Biases. In: Higgins JPT, Green S, editors. Cochrane Handbook for Systematic Reviews of Interventions [Internet]. Chichester (UK): John Wiley & Sons; 2008 [updated Mar 2011]. Available from: https://handbook-5-1.cochrane.org/chapter_10
Thompson SG, Higgins JP. How should meta-regression analyses be undertaken and interpreted? Stat Med. 2002 Apr 30;21(11):1559–73.
Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002 Jun 15;21(11):1539–58.
Borenstein M, Hedges LV, Higgins JP, Rothstein HR. Introduction to Meta-Analysis. Chichester (UK): John Wiley & Sons; 2009.
Schwarzer G, Carpenter JR, Rücker G. Meta-Analysis with R. Cham: Springer International Publishing; 2015.
Viechtbauer W. Conducting meta-analyses in R with the metafor package. J Stat Softw. 2010;36(3):1–48.
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DOI: 10.24871/2622025130-142
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