Variability in Placebo Response Across Biologic and Small Molecule Classes in Induction Randomized Controlled Trials for Ulcerative Colitis: A Systematic Review and Meta-Analysis

Variability in Placebo Response Across Biologic and Small Molecule Classes in Induction Randomized Controlled Trials for Ulcerative Colitis: A Systematic Review and Meta-Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Variability in Placebo Response Across Biologic and Small Molecule Classes in Induction Randomized Controlled Trials for Ulcerative Colitis: A Systematic Review and Meta-Analysis Mohammad Adam, Fatima Elmustafa, Harpreet Kaur, Yasmin Ali, Miqdad Dafaallah, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7050637/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Placebo response is crucial in interpreting treatment efficacy in ulcerative colitis (UC) trials. While it has been broadly studied, it remains underexplored in trials involving the growing number of biologics and small molecules for ulcerative colitis. Methods: We systematically searched PubMed, Embase, Scopus, Web of Science, and Cochrane CENTRAL from inception to November 13, 2024. Eligible studies were induction-phase RCTs, including adult patients with moderate-to-severe UC who received a biologic and a small-molecule against a placebo. Primary outcomes were pooled clinical and endoscopic response and remission rates. Safety outcomes included adverse events (AEs), serious adverse events (SAEs), and withdrawal rates. Random-effect models were used for meta-analysis. Meta-regression identified predictors of placebo outcomes. Results: 26 induction RCTs with 3,937 placebo-treated patients were included. IL inhibitor trials had the highest placebo clinical response (36%) and endoscopic remission (21%), while JAK inhibitors had the lowest (21% and 2%). Overall placebo rates were 34% for clinical response, 8% for clinical remission, 19% for endoscopic response, and 11% for endoscopic remission. Adverse events occurred in 54%, SAEs in 8%, and withdrawals in 18%. Younger age and longer follow-up were linked to higher placebo responses; recent trials showed reduced endoscopic effects. Conclusion: These findings highlight the need to account for placebo variability in trial design and interpretation, particularly as biologic and small-molecule therapies continue to expand in UC treatment. Gastroenterology & Hepatology Ulcerative colitis placebo response biologics small molecules systematic review meta-analysis induction trials clinical remission Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Study Highlights WHAT IS KNOWN Placebo response rates in UC trials vary widely by endpoint and trial design. Previous meta-analyses included both non-biologic and biologic therapies. WHAT IS NEW HERE Focused analysis on biologics and small molecules in UC induction trials. IL inhibitor trials had the highest placebo response; JAK inhibitors had the lowest. Longer follow-ups and younger ages increase placebo clinical and endoscopic responses. I. Introduction The treatment landscape of ulcerative colitis (UC) has been transformed by the introduction of biologics and small molecules, offering improved efficacy and reshaping therapeutic strategies over the past two decades( 1 , 2 ). A critical aspect of assessing the efficacy and safety of these treatments in randomized controlled trials (RCTs) is the choice of an appropriate comparison group. When ethically and practically feasible, the placebo control groups remain the gold standard for establishing a benchmark for treatment efficacy( 3 , 4 ). A thorough understanding of placebo response rates is not only crucial for accurately interpreting trial outcomes but also for optimizing study design, improving patient selection, and mitigating biases in future RCTs ( 5 – 7 ). Placebo response rates are influenced by multiple factors that either amplify or diminish the response; these factors include study design, population characteristics, and baseline disease severity 5,7 . These responses can also vary based on the type of therapeutic mechanism being evaluated and the criteria used to define outcomes such as clinical remission or endoscopic improvement ( 8 ). The introduction of biologics and small molecules has further highlighted the importance of carefully analyzing placebo outcomes, as these studies differ in design & methodology from traditional non-biologic therapies, potentially influencing placebo response rates in trials ( 9 – 11 ). While earlier meta-analyses primarily focused on placebo responses in the pre-biologics era, reporting a placebo clinical response rate of 28%( 12 ), more recent analyses, including trials of biologics, small molecules, and non-biologic therapies, have shown a higher placebo response rate of 32%. These studies have identified key determinants of placebo response, such as centralized endoscopy readings, baseline disease severity, prior biologic exposure, and follow-up duration( 7 ). Given these evolving placebo response patterns and the increasing use of biologics and small molecules, a contemporary analysis is warranted. Unlike prior meta-analyses, which included non-biologic therapies and did not include newly approved therapies, our meta-analysis focuses exclusively on biologics and small molecules, incorporating recent RCTs evaluating newer agents such as Filgotinib, Ozanimod, Etrolizumab, Etrasimod, Mirikizumab, Upadacitinib, and Risankizumab. This updated analysis provides a more contemporary and targeted assessment of placebo responses in trials of advanced therapies. II. Methods Search Strategy This systematic review and meta-analysis adhered to the PRISMA guidelines. A comprehensive literature search was conducted across five databases: PubMed, Embase, Scopus, Web of Science, and Cochrane CENTRAL. The search covered studies published from database inception to November 13, 2024, using a combination of keywords and MeSH terms related to "Ulcerative Colitis", "placebo effect," and "Adverse effect." Detailed search strategies are available in the supplementary material (Supplementary Table 1). Study Selection and Eligibility Criteria Studies were eligible for inclusion, provided they fulfilled the following criteria: 1) Induction Randomized controlled Trials; 2) Population includes adults aged 18 years or older with moderate-to-severe ulcerative colitis; 3) Intervention focused on placebo arms of randomized controlled trials, while 4) Comparator included biologic agents or small molecules. Exclusion criteria encompassed phase 1 or 2 RCTs, nonrandomized trials, studies involving pediatric populations, observational studies, case series, qualitative data, and conference abstracts lacking complete datasets. Four reviewers screened Titles and abstracts independently (Y.A., M.D., A.A. & A.I.) using predefined eligibility criteria. Full-text articles were reviewed to confirm inclusion, with any disagreements resolved by the principal Author (M.A.) through discussion. The entire selection process was documented using a PRISMA flow diagram. Data Extraction and Study Outcomes Two reviewers independently (H.K. & F.A.) extracted data, which was then cross-verified for accuracy. The extracted variables included study characteristics (publication year, phase, follow-up duration, and sample size), patient characteristics (age, sex ratio, disease severity, and prior biologic exposure), and outcomes (clinical and endoscopic placebo response/remission rates, adverse events [AEs], serious adverse events [SAEs], and withdrawal rates). Information on the intervention drug and its pharmacologic therapeutic class in the comparison arm was also recorded. All data were extracted into Microsoft Excel® [Version 2412 Build 16.0.18324.20092]. Outcome proportions were analyzed using an intention-to-treat approach, and the definitions used by each trial for clinical response, clinical remission, and endoscopic response outcomes included in our meta-analysis are detailed in ( Supplementary Table 8) . Statistical Analysis The statistical analysis evaluated pooled placebo response, remission, and safety outcomes in clinical trials for moderate-to-severe ulcerative colitis. Pooled proportions for clinical remission, clinical response, endoscopic remission, endoscopic response, adverse events (AEs), serious adverse events (SAEs), and withdrawal rates were calculated using random-effects models, with effect sizes (ES) and 95% confidence intervals (CIs) reported. Heterogeneity was assessed using the I 2 statistics. Subgroup pooled proportion based on drug intervention & pharmacologic therapeutic class was also calculated. Meta-regression analyses explored study-level predictors of placebo response, remission, and safety outcomes, including mean age, follow-up duration, year of publication, sample size, gender ratio, disease duration, and prior TNF inhibitor exposure. Statistical analyses and visualizations, including forest plots, were conducted using Stata 18, providing valuable insights into the efficacy and safety of placebos in ulcerative colitis trials. III. Results Search Result & Study Selection A total of 3,460 records were identified through database searches across PubMed, Cochrane, WOS, SCOPUS, and EMBASE. After removing 1,520 duplicates and 89 records deemed ineligible by automation tools, 2,439 reports were assessed for retrieval. Among these, 1,423 reports were excluded, and 246 were excluded due to phase 1 or 2 status, secondary analysis, or post hoc studies. A total of 26 trials were included in this analysis following a systematic review process (Supplementary Fig. 1). Across all trials, 3,937 participants were randomized to placebo. Studies Characteristics The mean follow-up duration was 16.58 weeks (6–54 weeks), with placebo group populations ranging from 41 to 331 patients per trial. The mean participant age was 40.28 years (34.5–44.5), and disease duration averaged 6.28 years (range: 1.0–10.2). The total number of males was 2,441 and females 1,496, resulting in a male-to-female ratio of 1.63:1. Interventions comparison included TNF inhibitors (Infliximab, Adalimumab, Golimumab), integrin inhibitors (Vedolizumab, Etrolizumab), IL inhibitors (Ustekinumab, Risankizumab, Mirikizumab), JAK inhibitors (Tofacitinib, Upadacitinib, Filgotinib) and S1P receptor modulators (Ozanimod, Etrasimod) ( Table 1 ). Table 1 Summary characteristics of the included RCTs. Trial Name (Identifier) Study ID Intervention Follow-up Duration (Weeks) Total population of the Placebo Group Mean Age (Yrs) M/F (No.) Disease Duration (Yrs, Mean) ACT1 Rutgeerts, 2005 Infliximab 54 121 41.5 72/49 6.2 ACT2 Rutgeerts, 2005 Infliximab 30 123 40.5 71/52 6.5 No Name Reinisch, 2011 Adalimumab 8 130 37 246 5.4 ULTRA 2 Sandborn, 2012 Adalimumab 8 246 41.3 152/94 8.5 GEMINI 1 Feagan, 2013 Vedolizumab 6 149 41.2 92/57 7.1 No Name Suzuki, 2013 Adalimumab 52 96 42.7 70/26 8 The PURSUIT-SC Sandborn, 2014 Golimumab 6 331 40 175/156 6.3 No Name Jiang, 2015 Infliximab 30 41 34.5 25/16 4.4 No Name Kobayashi, 2015 Infliximab 38 104 38.9 133/75 7.6 OCTAVE 1 Sandborn, 2017 Tofacitinib 8 122 41.8 77/45 6 OCTAVE 2 Sandborn, 2017 Tofacitinib 8 112 40.4 55/57 6.2 UNIFI Sands, 2019 Ustekinumab 8 319 41.2 197/122 8 SELECTION (A) Feagan, 2021 Filgotinib 10 137 41 87/50 6.4 SELECTION (B) Feagan, 2021 Filgotinib 10 142 44 86/56 10.2 TRUE NORTH Sandborn, 2021 Ozanimod 10 216 41.9 143/73 6.8 U-ACHIEVE Danese 2022 Upadacitinib 8 154 44.5 97/57 6 U-ACCOMPLISH Danese 2022 Upadacitinib 8 174 42 107/67 4.9 HIBISCUS I Rubin 2022 Etrolizumab 10 72 36 39/33 4.7 HIBISCUS II Rubin 2022 Etrolizumab 10 72 36.5 38/34 4 HICKORY Peyrin-Biroulet, 2022 Etrolizumab 14 95 36 54/41 7.4 LUCENT D'Haens, 2023 Mirikizumab 12 294 41.3 165/129 6.9 EARNEST Travis, 2023 Vedolizumab 34 51 43.5 32/19 1 TACOS Singh,2023 Tofacitinib 13 51 37.5 30/21 2.5 ELEVATE UC 52 Sandborn, 2023 Etrasimod 12 144 38.9 88/56 7.7 ELEVATE UC 12 Sandborn, 2023 Etrasimod 12 116 40.4 73/43 5.9 INSPIRE & COMMAND Louis, 2024 Risankizumab 12 325 42.8 201/124 8.4 Placebo Response Rates Clinical Response The pooled rate across 24 studies evaluating clinical response was 34% (95% CI: 31–38%, I² = 76.04) ( Fig. 1 ). Response rates have fluctuated between 30% and 50% over time, with notable variations among drug classes. IL inhibitors studies exhibited the highest placebo response rate at 36% (95% CI: 33–39%), followed by Anti-TNF agents & integrin inhibitors studies at 33% (95% CI: 31–36%, 29%-38% respectively). S1P receptor modulators demonstrated response rates of 31% (95% CI: 27–35%). Meanwhile, JAK inhibitors recorded the lowest response at 21% (95% CI: 18–24%), ( Fig. 2 ). Individual drug-level analysis revealed Mirikizumab (42%) and Etrolizumab (39%) as having the highest placebo response rates, whereas Golimumab (23%) had the lowest rate ( Fig. 3 ). Clinical Remission In 25 studies assessing clinical remission, the pooled rate was 8% (95% CI: 7–10%, I² = 70.31%) ( Fig. 4 ). Across therapeutic categories, remission rates were relatively consistent (6–9%), with JAK inhibitors studies showing the lowest rate at 6% (95% CI: 5–8%), while Anti-TNF agents, IL inhibitors, and S1P receptor modulators exhibited remission rates between 8% and 9% (Fig. 5 ). Drug-specific analysis showed remission rates ranging from 4% (Upadacitinib) to 13% (Mirikizumab and Infliximab) ( Fig. 6 ) . Endoscopic Response Eighteen studies investigated endoscopic response, revealing a pooled rate of 19% (95% CI: 15–23%, I² = 90.18%) ( Fig. 7 ). Response rates varied widely (12–42%). Anti TNF trials demonstrated the highest response at 16% (95% CI: 14–19%), followed by integrin inhibitor and S1P receptor modulator trials (14% each, 95% CI: 11–17%). JAK inhibitors recorded the lowest response at 6% (95% CI: 5–8%) ( Fig. 8 ). Among individual drugs, Etrolizumab (26%) and Golimumab (22%) studies had the highest response rates, whereas Upadacitinib (8%) and Infliximab (10%) trials exhibited the lowest ( Fig. 9 ). Endoscopic Remission Placebo-induced endoscopic remission was assessed in 19 studies, with a pooled rate of 11% (95% CI: 6–15%, I² = 97.87%) ( Fig. 10 ). Anti TNF and Integrin inhibitors RCTs showed the highest placebo remission rate at 13%, followed by IL inhibitors at 11% (95% CI: 9–13%). JAK inhibitors, in contrast, had the lowest remission rate at just 2% (95% CI: 1–3%) ( Fig. 11 ). Among the individual therapies, Mirikizumab and Infliximab studies demonstrated the highest response rate at 21% and 20%, respectively, whereas Upadacitinib and tofacitinib had the lowest response rate at 2% and 1%, respectively ( Fig. 12 ). Placebo Safety Adverse Effect The pooled rate in 25 studies assessing adverse events in placebo arms was 54% (95% CI: 45–63%, I² = 97.95%) (Supplementary Fig. 2). Among therapeutic classes, Anti-TNF agents had the highest placebo adverse event rate (64%, 95% CI: 61–66%), followed by integrin inhibitors (54%, 95% CI: 49–58%) and JAK inhibitors (52%, 95% CI: 49–55%) studies. S1P receptor modulators reported the lowest rates at 29% (95% CI: 25–33%) (Supplementary Fig. 3). The highest rates were observed in trials involving Infliximab (78%) and Adalimumab (69%), while the lowest was seen with Etrasimod (21%) (Supplementary Fig. 4). Placebo Severe Adverse Event Rates Twenty-three studies reported severe adverse events, with a pooled SAE rate of 8% (95% CI: 6–10%, I² = 92.03%) (Supplementary Fig. 5). Across therapeutic classes, Anti-TNF agents exhibited the highest SAE rate at 12% (95% CI: 10–14%), whereas S1P receptor modulators had the lowest at 2% (95% CI: 1–3%) (Supplementary Fig. 6). The highest SAE rate was observed in placebo-treated participants from Infliximab trials (20%), while the lowest was in Etrasimod trials (1%) (Supplementary Fig. 7). Withdrawal Rates Withdrawal due to placebo treatment was analyzed in 19 studies, yielding a pooled rate of 18% (95% CI: 9–27%, I² = 99.07%) (Supplementary Fig. 8). Among therapeutic classes, Anti-Integrin agents had the highest withdrawal rates (19%, 95% CI: 15–23%), whereas S1P receptor modulators and JAK inhibitors had the lowest at 5% and 6%, respectively (Supplementary Fig. 9) . Infliximab studies reported the highest withdrawal rate at 38%, while Adalimumab trials had the lowest at 2% (Supplementary Fig. 10). Factors Affecting Placebo Response Clinical Response and Remission Predictors The meta-regression analysis identified several factors influencing placebo-induced clinical response and remission rates. For clinical response, a higher mean age was associated with lower odds of response (OR = 0.984, p = 0.010), while a longer follow-up duration was associated with higher odds of placebo response (OR = 1.063, p = 0.040). Other variables, including year of publication, sample size, sex ratio, disease duration, and prior TNF exposure, were not statistically significant ( Table 2 ). For clinical remission, longer follow-up duration was associated with higher odds of achieving placebo-induced remission (OR = 1.002, p = 0.001). However, year of publication, sample size, sex ratio, mean age, disease duration, and prior TNF exposure did not significantly influence clinical remission rates (Supplementary Table 2). Table 2 Multivariate Meta-Regression Analysis of Study Characteristics for Predicting Clinical Response Clinical Response Predictors Study Characteristics Odd Ratio P Value [95% conf. interval] Year of Publication 1.001 0.626 0.996 1.007 Sample Size 0.999 0.147 1.000 Gender Ratio (M/F) 0.993 0.895 0.901 1.095 Mean Age (Y) 0.984 0.010 0.972 0.996 Follow-up Duration (Weeks) 1.063 0.040 1.003 1.127 Duration Disease (Weeks) 0.990 0.286 0.971 1.009 Previous TNF Exposure 0.958 0.244 0.892 1.029 Endoscopic Response and Remission Predictors For endoscopic response, a longer follow-up duration (OR = 1.004, p = 0.042) and younger age (OR = 0.978, p < 0.001) were associated with higher odds of placebo-induced endoscopic improvement. Later years of publication (OR = 0.986, p = 0.001) and prior TNF exposure (OR = 0.873, p < 0.001) were associated with lower odds of endoscopic response (Supplementary Table 3). For endoscopic remission, a longer follow-up duration was associated with increased odds of remission (OR = 1.006, p = 0.002), whereas more recent trial publication years were associated with lower odds of placebo-induced remission (OR = 0.985, p < 0.001) (Supplementary Table 4). Adverse Effects & Withdrawal Effects Predictors The occurrence of any adverse events showed lower odds in more recently published trials (OR = 0.986, p = 0.089), although this did not reach statistical significance (Supplementary Table 5). Severe adverse events were associated with higher odds with longer follow-up duration (OR = 1.003, p < 0.001) but lower odds in more recent trials (OR = 0.993, p < 0.001) and among patients with prior TNF inhibitor exposure (OR = 0.951, p = 0.014). Withdrawal due to adverse effects followed a similar pattern, with younger age (OR = 0.962, p = 0.045) and longer follow-up duration (OR = 1.013, p < 0.001) associated with higher odds of withdrawal, whereas more recent trial publication years were associated with lower odds (OR = 0.983, p = 0.026) (Supplementary Tables 6 & 7). IV. Discussion We found substantial placebo effects across clinical and endoscopic endpoints in this systematic review and meta-analysis of 26 induction RCTs involving biologics and small molecules for ulcerative colitis (UC). Among 3,937 placebo-treated patients, the pooled clinical response rate was 34%, with a markedly lower clinical remission rate of 8%. Endoscopic response and remission rates were also modest, at 19% and 11%, respectively. These results emphysize the ongoing influence of placebo effects in UC trials, even in the setting of advanced, targeted therapies( 7 , 13 ). Also there were meaningful variability in placebo outcomes across therapeutic classes. Trials involving IL inhibitors exhibited the highest placebo clinical response (36%) and endoscopic remission (21%), while JAK inhibitor trials had the lowest placebo effects (21% clinical response, 2% endoscopic remission). These differences may be driven by trial design, route of administration, patient expectations, or disease phenotype. For instance, drugs administered intravenously or perceived as more potent may elicit stronger placebo responses( 7 ). At the drug level, Mirikizumab and Infliximab were associated with higher placebo effects, while Upadacitinib and Tofacitinib consistently showed the lowest. Meta-regression further identified younger patient age and longer trial duration as independent predictors of higher placebo response and remission rates( 14 ). Conversely, more recent trials and prior TNF exposure were associated with lower endoscopic placebo effects. These findings suggest that advancements in trial methodology, such as central reading of endoscopy and objective endpoint definitions, may help attenuate placebo signals over time (16). Our study aligns with prior meta-analyses but offers a narrower, class-specific lens focused exclusively on biologics and small molecules, making it particularly relevant to modern UC trial design. Despite its strengths, this analysis has limitations. Heterogeneity across studies in population characteristics, outcome definitions, and follow-up periods may have influenced pooled estimates. While meta-regression helped adjust for key variables, residual confounding remains possible. Our focus on phase 3 RCTs enhances internal validity but may limit applicability to real-world settings. Safety outcome reporting also varied, particularly about how adverse events and withdrawals were defined Nevertheless, our findings are clinically and methodologically important, highlighting factors of placebo arms, which must be considered when interpreting both efficacy and safety outcomes in UC trials. In summary, placebo effects in UC trials remain variable and clinically meaningful, particularly across biologic and small-molecule classes. Future trials should account for placebo susceptibility as these therapies expand by incorporating standardized designs, objective endpoints, and robust blinding methods. Understanding the drivers of placebo response is essential to assess treatment efficacy and accurately improve trial design in UC. Abbreviations UC: Ulcerative colitis; AE: Adverse event; SAE: Serious adverse event; TNF: Tumor necrosis factor; RCT: Randomized controlled trial; S1P: Sphingosine-1-phosphate. Declarations Ethics approval and consent to participate Not applicable. This study used data from previously published randomized controlled trials. Consent for publication Not applicable. Availability of data and materials This published article and its supplementary information files include all data generated or analyzed during this study. Competing Interests The authors declare that they have no competing interests. Funding The authors received no specific funding for this work. Authors' contributions Mohammad Adam conceptualized the study, conducted the literature review, and drafted the original manuscript. Fatima Elmustafa, Harpreet Kaur, Yasmin Ali, Miqdad Dafaallah and Mohamed Refaat contributed to study screening, data extraction, and quality assessment. Abdellatif Ismail, Amro Abdelatif, Ali Osman, Rahul Karna, and Mouhanad Mohamed contributed to data interpretation, manuscript editing, and critical manuscript revision. Mohammad Bilal, Mohamed Abdallah, and Suha Abushamma supervised the study, contributed to critical intellectual input, and approved the final manuscript. All authors reviewed and approved the final version of the manuscript. References Kayal M, Shah S. Ulcerative colitis: current and emerging treatment strategies. J Clin Med. 2019;9(1):94. Aslam N, Lo SW, Sikafi R, Barnes T, Segal J, Smith PJ, et al. A review of the therapeutic management of ulcerative colitis. Therap Adv Gastroenterol. 2022;15:17562848221138160. Millum J, Grady C. The ethics of placebo-controlled trials: methodological justifications. Contemp Clin Trials. 2013;36(2):510–4. Gros B, Blackwell J, Segal J, Black CJ, Ford AC, Din S. Harms with placebo in trials of biological therapies and small molecules as maintenance therapy in inflammatory bowel disease: a systematic review and meta-analysis. Lancet Gastroenterol Hepatol. 2024; Jairath V, Zou G, Parker CE, Macdonald JK, Mosli MH, Khanna R, et al. Systematic review and meta-analysis: placebo rates in induction and maintenance trials of ulcerative colitis. J Crohns Colitis. 2016;10(5):607–18. Ma C, Guizzetti L, Panaccione R, Fedorak RN, Pai RK, Parker CE, et al. Systematic review with meta‐analysis: endoscopic and histologic placebo rates in induction and maintenance trials of ulcerative colitis. Aliment Pharmacol Ther. 2018;47(12):1578–96. Sedano R, Hogan M, Nguyen TM, Chang J, Zou GY, Macdonald JK, et al. Systematic review and meta-analysis: clinical, endoscopic, histological and safety placebo rates in induction and maintenance trials of ulcerative colitis. J Crohns Colitis. 2022;16(2):224–43. Garud S, Brown A, Cheifetz A, Levitan EB, Kelly CP. Meta-analysis of the placebo response in ulcerative colitis. Dig Dis Sci. 2008;53:875–91. Bonovas S, Pansieri C, Piovani D, Macaluso FS, Orlando A, Festa S, et al. Use of biologics and small molecule drugs for the management of moderate to severe ulcerative colitis: IG-IBD technical review based on the GRADE methodology. Digestive and Liver Disease [Internet]. 2022;54(4):428–39. Available from: https://www.sciencedirect.com/science/article/pii/S1590865822001347 Xu YH, Zhu WM, Guo Z. Current status of novel biologics and small molecule drugs in the individualized treatment of inflammatory bowel disease. World J Gastroenterol. 2022;28(48):6888. AlAmeel T, AlMutairdi A, Al-Bawardy B. Emerging therapies for ulcerative colitis: updates from recent clinical trials. Clin Exp Gastroenterol. 2023;147–67. Su C, Lewis JD, Goldberg B, Brensinger C, Lichtenstein GR. A meta-analysis of the placebo rates of remission and response in clinical trials of active ulcerative colitis. Gastroenterology. 2007;132(2):516–26. Din S, Segal J, Blackwell J, Gros B, Black CJ, Ford AC. Harms with placebo in trials of biological therapies and small molecules as induction therapy in inflammatory bowel disease: a systematic review and meta-analysis. Lancet Gastroenterol Hepatol. 2024 Nov 1; Weimer K, Colloca L, Enck P. Age and sex as moderators of the placebo response-an evaluation of systematic reviews and meta-analyses across medicine. Gerontology. 2015;61(2):97–108. Additional Declarations The authors declare no competing interests. Supplementary Files Supplementary.docx Supplementary figures & Tables Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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confidence interval\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7050637/v1/a314f77e8f8007fc09fc8d11.png"},{"id":86240585,"identity":"8da52c54-a242-45aa-bc9e-1e35f6a86cd9","added_by":"auto","created_at":"2025-07-08 10:35:57","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":164145,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePooled placebo Clinical Response among therapeutic class subgroup analysis,, CI: confidence interval\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7050637/v1/bc97b6ee6c8348802aa40b92.png"},{"id":86240584,"identity":"9fa8eee9-abd3-4551-baa3-9c2b4d8d7b5a","added_by":"auto","created_at":"2025-07-08 10:35:57","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":221876,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePooled placebo Clinical Response based on drug class subgroup analysis, CI: confidence interval\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7050637/v1/4b1a42bca3ecbd4b20c941bc.png"},{"id":86240591,"identity":"3f0ee7f8-5948-4847-bf23-23d0a6305748","added_by":"auto","created_at":"2025-07-08 10:35:57","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":443036,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePooled placebo Clinical Remission among RCTs, CI: confidence interval\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7050637/v1/f47f694a6c3f925f426f68d5.png"},{"id":86241510,"identity":"a5325330-883f-489d-bf3a-e1516394afad","added_by":"auto","created_at":"2025-07-08 10:43:57","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":92467,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePooled placebo Clinical Remission among therapeutic class subgroup analysis,, CI: confidence interval\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7050637/v1/7aedb5f84eb4612625d5458d.png"},{"id":86240596,"identity":"135311fa-8633-424c-9b34-0c66b1685878","added_by":"auto","created_at":"2025-07-08 10:35:58","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":127131,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePooled placebo Clinical Remission based on drug class subgroup analysis, CI: confidence interval\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7050637/v1/7eabf2b9ba4540d674c79539.png"},{"id":86240597,"identity":"025033d6-c2ac-404c-a4d5-161b011dd4ec","added_by":"auto","created_at":"2025-07-08 10:35:58","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":335969,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePooled placebo Endoscopic Response among Published RCTs, CI: confidence interval\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7050637/v1/b1630787e7c88cf90b805b55.png"},{"id":86240600,"identity":"179f2a82-348e-4c23-a8af-9448914e2266","added_by":"auto","created_at":"2025-07-08 10:35:58","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":91029,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePooled placebo Endoscopic Response among therapeutic class subgroup analysis,, CI: confidence interval\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7050637/v1/11e09c31477c0f4cfcb13001.png"},{"id":86241518,"identity":"d6d39be5-7f24-476d-9ff8-0cfb2d8f1cfd","added_by":"auto","created_at":"2025-07-08 10:43:58","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":131491,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePooled placebo Endoscopic Response based on drug class subgroup analysis, CI: confidence interval\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-7050637/v1/c947b740f134a8774e45b707.png"},{"id":86240612,"identity":"a32997cd-6879-4b9d-ada0-550e992313d1","added_by":"auto","created_at":"2025-07-08 10:35:58","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":254665,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePooled placebo Endoscopic Remission among Published RCTs, CI: confidence interval\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-7050637/v1/e6f8a8b2e7a4223624b064cb.png"},{"id":86241512,"identity":"145a616f-dfe6-49c5-8900-df50b1964bfb","added_by":"auto","created_at":"2025-07-08 10:43:57","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":92264,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePooled placebo Endoscopic Remission among therapeutic class subgroup analysis,, CI: confidence interval\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-7050637/v1/d561056122c66e00f2f12297.png"},{"id":86240611,"identity":"5d112404-eda5-4ea9-8513-67997753e299","added_by":"auto","created_at":"2025-07-08 10:35:58","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":120102,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePooled placebo Endoscopic Remission based on drug class subgroup analysis, CI: confidence interval\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-7050637/v1/797710b68912b01ad611c95b.png"},{"id":86243233,"identity":"57794443-3437-4240-a700-3e469fc2b2f7","added_by":"auto","created_at":"2025-07-08 11:08:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5247038,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7050637/v1/c85b7e2f-7ffb-41f4-997f-c881ed348e64.pdf"},{"id":86241951,"identity":"6877c35a-9811-4cd9-9b6e-e4aa6b19a4dc","added_by":"auto","created_at":"2025-07-08 10:51:57","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1255973,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary figures \u0026amp; Tables\u003c/p\u003e","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-7050637/v1/3bd183adffac9f3269cb5efe.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eVariability in Placebo Response Across Biologic and Small Molecule Classes in Induction Randomized Controlled Trials for Ulcerative Colitis: A Systematic Review and Meta-Analysis\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Study Highlights","content":"\u003cp\u003e\u003cstrong\u003eWHAT IS KNOWN\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlacebo response rates in UC trials vary widely by endpoint and trial design.\u003c/p\u003e\n\u003cp\u003ePrevious meta-analyses included both non-biologic and biologic therapies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWHAT IS NEW HERE\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFocused analysis on biologics and small molecules in UC induction trials.\u003c/p\u003e\n\u003cp\u003eIL inhibitor trials had the highest placebo response; JAK inhibitors had the lowest.\u003c/p\u003e\n\u003cp\u003eLonger follow-ups and younger ages increase placebo clinical and endoscopic responses.\u003c/p\u003e"},{"header":"I. Introduction","content":"\u003cp\u003eThe treatment landscape of ulcerative colitis (UC) has been transformed by the introduction of biologics and small molecules, offering improved efficacy and reshaping therapeutic strategies over the past two decades(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). A critical aspect of assessing the efficacy and safety of these treatments in randomized controlled trials (RCTs) is the choice of an appropriate comparison group. When ethically and practically feasible, the placebo control groups remain the gold standard for establishing a benchmark for treatment efficacy(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). A thorough understanding of placebo response rates is not only crucial for accurately interpreting trial outcomes but also for optimizing study design, improving patient selection, and mitigating biases in future RCTs (\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePlacebo response rates are influenced by multiple factors that either amplify or diminish the response; these factors include study design, population characteristics, and baseline disease severity \u003csup\u003e5,7\u003c/sup\u003e. These responses can also vary based on the type of therapeutic mechanism being evaluated and the criteria used to define outcomes such as clinical remission or endoscopic improvement (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). The introduction of biologics and small molecules has further highlighted the importance of carefully analyzing placebo outcomes, as these studies differ in design \u0026amp; methodology from traditional non-biologic therapies, potentially influencing placebo response rates in trials (\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWhile earlier meta-analyses primarily focused on placebo responses in the pre-biologics era, reporting a placebo clinical response rate of 28%(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), more recent analyses, including trials of biologics, small molecules, and non-biologic therapies, have shown a higher placebo response rate of 32%. These studies have identified key determinants of placebo response, such as centralized endoscopy readings, baseline disease severity, prior biologic exposure, and follow-up duration(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Given these evolving placebo response patterns and the increasing use of biologics and small molecules, a contemporary analysis is warranted. Unlike prior meta-analyses, which included non-biologic therapies and did not include newly approved therapies, our meta-analysis focuses exclusively on biologics and small molecules, incorporating recent RCTs evaluating newer agents such as Filgotinib, Ozanimod, Etrolizumab, Etrasimod, Mirikizumab, Upadacitinib, and Risankizumab. This updated analysis provides a more contemporary and targeted assessment of placebo responses in trials of advanced therapies.\u003c/p\u003e"},{"header":"II. Methods","content":"\u003cp\u003e\u003cb\u003eSearch Strategy\u003c/b\u003e\u003c/p\u003e\u003cp\u003e This systematic review and meta-analysis adhered to the PRISMA guidelines. A comprehensive literature search was conducted across five databases: PubMed, Embase, Scopus, Web of Science, and Cochrane CENTRAL. The search covered studies published from database inception to November 13, 2024, using a combination of keywords and MeSH terms related to \"Ulcerative Colitis\", \"placebo effect,\" and \"Adverse effect.\" Detailed search strategies are available in the supplementary material \u003cb\u003e(Supplementary Table\u0026nbsp;1).\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy Selection and Eligibility Criteria\u003c/b\u003e\u003c/p\u003e\u003cp\u003e Studies were eligible for inclusion, provided they fulfilled the following criteria: 1) Induction Randomized controlled Trials; 2) Population includes adults aged 18 years or older with moderate-to-severe ulcerative colitis; 3) Intervention focused on placebo arms of randomized controlled trials, while 4) Comparator included biologic agents or small molecules. Exclusion criteria encompassed phase 1 or 2 RCTs, nonrandomized trials, studies involving pediatric populations, observational studies, case series, qualitative data, and conference abstracts lacking complete datasets. Four reviewers screened Titles and abstracts independently (Y.A., M.D., A.A. \u0026amp; A.I.) using predefined eligibility criteria. Full-text articles were reviewed to confirm inclusion, with any disagreements resolved by the principal Author (M.A.) through discussion. The entire selection process was documented using a PRISMA flow diagram.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData Extraction and Study Outcomes\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTwo reviewers independently (H.K. \u0026amp; F.A.) extracted data, which was then cross-verified for accuracy. The extracted variables included study characteristics (publication year, phase, follow-up duration, and sample size), patient characteristics (age, sex ratio, disease severity, and prior biologic exposure), and outcomes (clinical and endoscopic placebo response/remission rates, adverse events [AEs], serious adverse events [SAEs], and withdrawal rates). Information on the intervention drug and its pharmacologic therapeutic class in the comparison arm was also recorded. All data were extracted into Microsoft Excel\u0026reg; [Version 2412 Build 16.0.18324.20092]. Outcome proportions were analyzed using an intention-to-treat approach, and the definitions used by each trial for clinical response, clinical remission, and endoscopic response outcomes included in our meta-analysis are detailed in (\u003cb\u003eSupplementary Table\u0026nbsp;8)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatistical Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe statistical analysis evaluated pooled placebo response, remission, and safety outcomes in clinical trials for moderate-to-severe ulcerative colitis. Pooled proportions for clinical remission, clinical response, endoscopic remission, endoscopic response, adverse events (AEs), serious adverse events (SAEs), and withdrawal rates were calculated using random-effects models, with effect sizes (ES) and 95% confidence intervals (CIs) reported. Heterogeneity was assessed using the I\u003csup\u003e2\u003c/sup\u003e statistics. Subgroup pooled proportion based on drug intervention \u0026amp; pharmacologic therapeutic class was also calculated. Meta-regression analyses explored study-level predictors of placebo response, remission, and safety outcomes, including mean age, follow-up duration, year of publication, sample size, gender ratio, disease duration, and prior TNF inhibitor exposure. Statistical analyses and visualizations, including forest plots, were conducted using Stata 18, providing valuable insights into the efficacy and safety of placebos in ulcerative colitis trials.\u003c/p\u003e"},{"header":"III. Results","content":"\u003cp\u003e\u003cstrong\u003eSearch Result \u0026amp; Study Selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 3,460 records were identified through database searches across PubMed, Cochrane, WOS, SCOPUS, and EMBASE. After removing 1,520 duplicates and 89 records deemed ineligible by automation tools, 2,439 reports were assessed for retrieval. Among these, 1,423 reports were excluded, and 246 were excluded due to phase 1 or 2 status, secondary analysis, or post hoc studies. A total of 26 trials were included in this analysis following a systematic review process \u003cstrong\u003e(Supplementary Fig.\u0026nbsp;1).\u003c/strong\u003e Across all trials, 3,937 participants were randomized to placebo.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudies Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mean follow-up duration was 16.58 weeks (6\u0026ndash;54 weeks), with placebo group populations ranging from 41 to 331 patients per trial. The mean participant age was 40.28 years (34.5\u0026ndash;44.5), and disease duration averaged 6.28 years (range: 1.0\u0026ndash;10.2). The total number of males was 2,441 and females 1,496, resulting in a male-to-female ratio of 1.63:1. Interventions comparison included TNF inhibitors (Infliximab, Adalimumab, Golimumab), integrin inhibitors (Vedolizumab, Etrolizumab), IL inhibitors (Ustekinumab, Risankizumab, Mirikizumab), JAK inhibitors (Tofacitinib, Upadacitinib, Filgotinib) and S1P receptor modulators (Ozanimod, Etrasimod) \u003cstrong\u003e(\u003c/strong\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSummary characteristics of the included RCTs.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTrial Name (Identifier)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStudy ID\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIntervention\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFollow-up Duration (Weeks)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal population of the Placebo Group\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean Age (Yrs)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eM/F (No.)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDisease Duration (Yrs, Mean)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRutgeerts, 2005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eInfliximab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e54\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e121\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e41.5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e72/49\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACT2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRutgeerts, 2005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eInfliximab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e123\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e40.5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e71/52\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo Name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReinisch, 2011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdalimumab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e130\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e37\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e246\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eULTRA 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSandborn, 2012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdalimumab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e246\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e41.3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e152/94\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e8.5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGEMINI 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFeagan, 2013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVedolizumab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e149\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e41.2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e92/57\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo Name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSuzuki, 2013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdalimumab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e52\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e96\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e42.7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e70/26\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe PURSUIT-SC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSandborn, 2014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGolimumab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e331\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e40\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e175/156\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo Name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eJiang, 2015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eInfliximab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e41\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e34.5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e25/16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo Name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eKobayashi, 2015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eInfliximab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e38\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e104\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e38.9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e133/75\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOCTAVE 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSandborn, 2017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTofacitinib\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e122\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e41.8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e77/45\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOCTAVE 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSandborn, 2017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTofacitinib\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e112\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e40.4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e55/57\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUNIFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSands, 2019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUstekinumab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e319\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e41.2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e197/122\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSELECTION (A)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFeagan, 2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFilgotinib\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e137\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e41\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e87/50\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSELECTION (B)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFeagan, 2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFilgotinib\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e142\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e44\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e86/56\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e10.2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTRUE NORTH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSandborn, 2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOzanimod\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e216\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e41.9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e143/73\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eU-ACHIEVE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDanese 2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUpadacitinib\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e154\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e44.5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e97/57\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eU-ACCOMPLISH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDanese 2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUpadacitinib\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e174\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e42\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e107/67\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHIBISCUS I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRubin 2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEtrolizumab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e72\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e36\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e39/33\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHIBISCUS II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRubin 2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEtrolizumab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e72\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e36.5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e38/34\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHICKORY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePeyrin-Biroulet, 2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEtrolizumab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e95\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e36\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e54/41\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLUCENT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD\u0026apos;Haens, 2023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMirikizumab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e294\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e41.3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e165/129\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEARNEST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTravis, 2023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVedolizumab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e34\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e51\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e43.5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e32/19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTACOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSingh,2023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTofacitinib\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e51\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e37.5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e30/21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eELEVATE UC 52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSandborn, 2023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEtrasimod\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e144\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e38.9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e88/56\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eELEVATE UC 12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSandborn, 2023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEtrasimod\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e116\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e40.4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e73/43\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eINSPIRE \u0026amp; COMMAND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLouis, 2024\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisankizumab\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e325\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e42.8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e201/124\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e8.4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003ePlacebo Response Rates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Response\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe pooled rate across 24 studies evaluating clinical response was 34% (95% CI: 31\u0026ndash;38%, I\u0026sup2; = 76.04) \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e Response rates have fluctuated between 30% and 50% over time, with notable variations among drug classes. IL inhibitors studies exhibited the highest placebo response rate at 36% (95% CI: 33\u0026ndash;39%), followed by Anti-TNF agents \u0026amp; integrin inhibitors studies at 33% (95% CI: 31\u0026ndash;36%, 29%-38% respectively). S1P receptor modulators demonstrated response rates of 31% (95% CI: 27\u0026ndash;35%). Meanwhile, JAK inhibitors recorded the lowest response at 21% (95% CI: 18\u0026ndash;24%), \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e Individual drug-level analysis revealed Mirikizumab (42%) and Etrolizumab (39%) as having the highest placebo response rates, whereas Golimumab (23%) had the lowest rate \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Remission\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn 25 studies assessing clinical remission, the pooled rate was 8% (95% CI: 7\u0026ndash;10%, I\u0026sup2; = 70.31%) \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e Across therapeutic categories, remission rates were relatively consistent (6\u0026ndash;9%), with JAK inhibitors studies showing the lowest rate at 6% (95% CI: 5\u0026ndash;8%), while Anti-TNF agents, IL inhibitors, and S1P receptor modulators exhibited remission rates between 8% and 9% (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e Drug-specific analysis showed remission rates ranging from 4% (Upadacitinib) to 13% (Mirikizumab and Infliximab) \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cstrong\u003e)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEndoscopic Response\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEighteen studies investigated endoscopic response, revealing a pooled rate of 19% (95% CI: 15\u0026ndash;23%, I\u0026sup2; = 90.18%) \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e Response rates varied widely (12\u0026ndash;42%). Anti TNF trials demonstrated the highest response at 16% (95% CI: 14\u0026ndash;19%), followed by integrin inhibitor and S1P receptor modulator trials (14% each, 95% CI: 11\u0026ndash;17%). JAK inhibitors recorded the lowest response at 6% (95% CI: 5\u0026ndash;8%) \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e Among individual drugs, Etrolizumab (26%) and Golimumab (22%) studies had the highest response rates, whereas Upadacitinib (8%) and Infliximab (10%) trials exhibited the lowest \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEndoscopic Remission\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlacebo-induced endoscopic remission was assessed in 19 studies, with a pooled rate of 11% (95% CI: 6\u0026ndash;15%, I\u0026sup2; = 97.87%) \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e Anti TNF and Integrin inhibitors RCTs showed the highest placebo remission rate at 13%, followed by IL inhibitors at 11% (95% CI: 9\u0026ndash;13%). JAK inhibitors, in contrast, had the lowest remission rate at just 2% (95% CI: 1\u0026ndash;3%) \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e11\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e Among the individual therapies, Mirikizumab and Infliximab studies demonstrated the highest response rate at 21% and 20%, respectively, whereas Upadacitinib and tofacitinib had the lowest response rate at 2% and 1%, respectively \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e12\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePlacebo Safety\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdverse Effect\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe pooled rate in 25 studies assessing adverse events in placebo arms was 54% (95% CI: 45\u0026ndash;63%, I\u0026sup2; = 97.95%) \u003cstrong\u003e(Supplementary Fig.\u0026nbsp;2).\u003c/strong\u003e Among therapeutic classes, Anti-TNF agents had the highest placebo adverse event rate (64%, 95% CI: 61\u0026ndash;66%), followed by integrin inhibitors (54%, 95% CI: 49\u0026ndash;58%) and JAK inhibitors (52%, 95% CI: 49\u0026ndash;55%) studies. S1P receptor modulators reported the lowest rates at 29% (95% CI: 25\u0026ndash;33%) \u003cstrong\u003e(Supplementary Fig.\u0026nbsp;3).\u003c/strong\u003e The highest rates were observed in trials involving Infliximab (78%) and Adalimumab (69%), while the lowest was seen with Etrasimod (21%) \u003cstrong\u003e(Supplementary Fig.\u0026nbsp;4).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePlacebo Severe Adverse Event Rates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwenty-three studies reported severe adverse events, with a pooled SAE rate of 8% (95% CI: 6\u0026ndash;10%, I\u0026sup2; = 92.03%) \u003cstrong\u003e(Supplementary Fig.\u0026nbsp;5).\u003c/strong\u003e Across therapeutic classes, Anti-TNF agents exhibited the highest SAE rate at 12% (95% CI: 10\u0026ndash;14%), whereas S1P receptor modulators had the lowest at 2% (95% CI: 1\u0026ndash;3%) \u003cstrong\u003e(Supplementary Fig.\u0026nbsp;6).\u003c/strong\u003e The highest SAE rate was observed in placebo-treated participants from Infliximab trials (20%), while the lowest was in Etrasimod trials (1%) \u003cstrong\u003e(Supplementary Fig.\u0026nbsp;7).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWithdrawal Rates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWithdrawal due to placebo treatment was analyzed in 19 studies, yielding a pooled rate of 18% (95% CI: 9\u0026ndash;27%, I\u0026sup2; = 99.07%) \u003cstrong\u003e(Supplementary Fig.\u0026nbsp;8).\u003c/strong\u003e Among therapeutic classes, Anti-Integrin agents had the highest withdrawal rates (19%, 95% CI: 15\u0026ndash;23%), whereas S1P receptor modulators and JAK inhibitors had the lowest at 5% and 6%, respectively \u003cstrong\u003e(Supplementary Fig.\u0026nbsp;9)\u003c/strong\u003e. Infliximab studies reported the highest withdrawal rate at 38%, while Adalimumab trials had the lowest at 2% \u003cstrong\u003e(Supplementary Fig.\u0026nbsp;10).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactors Affecting Placebo Response\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Response and Remission Predictors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe meta-regression analysis identified several factors influencing placebo-induced clinical response and remission rates. For clinical response, a higher mean age was associated with lower odds of response (OR\u0026thinsp;=\u0026thinsp;0.984, p\u0026thinsp;=\u0026thinsp;0.010), while a longer follow-up duration was associated with higher odds of placebo response (OR\u0026thinsp;=\u0026thinsp;1.063, p\u0026thinsp;=\u0026thinsp;0.040). Other variables, including year of publication, sample size, sex ratio, disease duration, and prior TNF exposure, were not statistically significant \u003cstrong\u003e(\u003c/strong\u003eTable \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e For clinical remission, longer follow-up duration was associated with higher odds of achieving placebo-induced remission (OR\u0026thinsp;=\u0026thinsp;1.002, p\u0026thinsp;=\u0026thinsp;0.001). However, year of publication, sample size, sex ratio, mean age, disease duration, and prior TNF exposure did not significantly influence clinical remission rates \u003cstrong\u003e(Supplementary Table\u0026nbsp;2).\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMultivariate Meta-Regression Analysis of Study Characteristics for Predicting Clinical Response\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eClinical Response Predictors\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOdd Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e[95% conf. interval]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear of Publication\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.626\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample Size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender Ratio (M/F)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.895\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.901\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.095\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean Age (Y)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.972\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFollow-up Duration (Weeks)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.127\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuration Disease (Weeks)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.971\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevious TNF Exposure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.958\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.892\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eEndoscopic Response and Remission Predictors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor endoscopic response, a longer follow-up duration (OR\u0026thinsp;=\u0026thinsp;1.004, p\u0026thinsp;=\u0026thinsp;0.042) and younger age (OR\u0026thinsp;=\u0026thinsp;0.978, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were associated with higher odds of placebo-induced endoscopic improvement. Later years of publication (OR\u0026thinsp;=\u0026thinsp;0.986, p\u0026thinsp;=\u0026thinsp;0.001) and prior TNF exposure (OR\u0026thinsp;=\u0026thinsp;0.873, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were associated with lower odds of endoscopic response \u003cstrong\u003e(Supplementary Table\u0026nbsp;3).\u003c/strong\u003e For endoscopic remission, a longer follow-up duration was associated with increased odds of remission (OR\u0026thinsp;=\u0026thinsp;1.006, p\u0026thinsp;=\u0026thinsp;0.002), whereas more recent trial publication years were associated with lower odds of placebo-induced remission (OR\u0026thinsp;=\u0026thinsp;0.985, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) \u003cstrong\u003e(Supplementary Table\u0026nbsp;4).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdverse Effects \u0026amp; Withdrawal Effects Predictors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe occurrence of any adverse events showed lower odds in more recently published trials (OR\u0026thinsp;=\u0026thinsp;0.986, p\u0026thinsp;=\u0026thinsp;0.089), although this did not reach statistical significance \u003cstrong\u003e(Supplementary Table\u0026nbsp;5).\u003c/strong\u003e Severe adverse events were associated with higher odds with longer follow-up duration (OR\u0026thinsp;=\u0026thinsp;1.003, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) but lower odds in more recent trials (OR\u0026thinsp;=\u0026thinsp;0.993, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and among patients with prior TNF inhibitor exposure (OR\u0026thinsp;=\u0026thinsp;0.951, p\u0026thinsp;=\u0026thinsp;0.014). Withdrawal due to adverse effects followed a similar pattern, with younger age (OR\u0026thinsp;=\u0026thinsp;0.962, p\u0026thinsp;=\u0026thinsp;0.045) and longer follow-up duration (OR\u0026thinsp;=\u0026thinsp;1.013, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) associated with higher odds of withdrawal, whereas more recent trial publication years were associated with lower odds (OR\u0026thinsp;=\u0026thinsp;0.983, p\u0026thinsp;=\u0026thinsp;0.026) \u003cstrong\u003e(Supplementary Tables\u0026nbsp;6 \u0026amp; 7).\u003c/strong\u003e\u003c/p\u003e"},{"header":"IV. Discussion","content":"\u003cp\u003eWe found substantial placebo effects across clinical and endoscopic endpoints in this systematic review and meta-analysis of 26 induction RCTs involving biologics and small molecules for ulcerative colitis (UC). Among 3,937 placebo-treated patients, the pooled clinical response rate was 34%, with a markedly lower clinical remission rate of 8%. Endoscopic response and remission rates were also modest, at 19% and 11%, respectively. These results emphysize the ongoing influence of placebo effects in UC trials, even in the setting of advanced, targeted therapies(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlso there were meaningful variability in placebo outcomes across therapeutic classes. Trials involving IL inhibitors exhibited the highest placebo clinical response (36%) and endoscopic remission (21%), while JAK inhibitor trials had the lowest placebo effects (21% clinical response, 2% endoscopic remission). These differences may be driven by trial design, route of administration, patient expectations, or disease phenotype. For instance, drugs administered intravenously or perceived as more potent may elicit stronger placebo responses(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). At the drug level, Mirikizumab and Infliximab were associated with higher placebo effects, while Upadacitinib and Tofacitinib consistently showed the lowest.\u003c/p\u003e\u003cp\u003eMeta-regression further identified younger patient age and longer trial duration as independent predictors of higher placebo response and remission rates(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Conversely, more recent trials and prior TNF exposure were associated with lower endoscopic placebo effects. These findings suggest that advancements in trial methodology, such as central reading of endoscopy and objective endpoint definitions, may help attenuate placebo signals over time (16). Our study aligns with prior meta-analyses but offers a narrower, class-specific lens focused exclusively on biologics and small molecules, making it particularly relevant to modern UC trial design.\u003c/p\u003e\u003cp\u003eDespite its strengths, this analysis has limitations. Heterogeneity across studies in population characteristics, outcome definitions, and follow-up periods may have influenced pooled estimates. While meta-regression helped adjust for key variables, residual confounding remains possible. Our focus on phase 3 RCTs enhances internal validity but may limit applicability to real-world settings. Safety outcome reporting also varied, particularly about how adverse events and withdrawals were defined\u003c/p\u003e\u003cp\u003eNevertheless, our findings are clinically and methodologically important, highlighting factors of placebo arms, which must be considered when interpreting both efficacy and safety outcomes in UC trials. In summary, placebo effects in UC trials remain variable and clinically meaningful, particularly across biologic and small-molecule classes. Future trials should account for placebo susceptibility as these therapies expand by incorporating standardized designs, objective endpoints, and robust blinding methods. Understanding the drivers of placebo response is essential to assess treatment efficacy and accurately improve trial design in UC.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eUC: Ulcerative colitis; AE: Adverse event; SAE: Serious adverse event; TNF: Tumor necrosis factor; RCT: Randomized controlled trial; S1P: Sphingosine-1-phosphate.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This study used data from previously published randomized controlled trials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis published article and its supplementary information files include all data generated or analyzed during this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors received no specific funding for this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMohammad Adam conceptualized the study, conducted the literature review, and drafted the original manuscript. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFatima Elmustafa, Harpreet Kaur, Yasmin Ali, Miqdad Dafaallah and Mohamed Refaat contributed to study screening, data extraction, and quality assessment. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAbdellatif Ismail, Amro Abdelatif, Ali Osman, Rahul Karna, and Mouhanad Mohamed contributed to data interpretation, manuscript editing, and critical manuscript revision. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMohammad Bilal, Mohamed Abdallah, and Suha Abushamma supervised the study, contributed to critical intellectual input, and approved the final manuscript. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors reviewed and approved the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eKayal M, Shah S. Ulcerative colitis: current and emerging treatment strategies. J Clin Med. 2019;9(1):94.\u003c/li\u003e\n \u003cli\u003eAslam N, Lo SW, Sikafi R, Barnes T, Segal J, Smith PJ, et al. A review of the therapeutic management of ulcerative colitis. Therap Adv Gastroenterol. 2022;15:17562848221138160.\u003c/li\u003e\n \u003cli\u003eMillum J, Grady C. The ethics of placebo-controlled trials: methodological justifications. Contemp Clin Trials. 2013;36(2):510\u0026ndash;4.\u003c/li\u003e\n \u003cli\u003eGros B, Blackwell J, Segal J, Black CJ, Ford AC, Din S. Harms with placebo in trials of biological therapies and small molecules as maintenance therapy in inflammatory bowel disease: a systematic review and meta-analysis. Lancet Gastroenterol Hepatol. 2024;\u003c/li\u003e\n \u003cli\u003eJairath V, Zou G, Parker CE, Macdonald JK, Mosli MH, Khanna R, et al. Systematic review and meta-analysis: placebo rates in induction and maintenance trials of ulcerative colitis. J Crohns Colitis. 2016;10(5):607\u0026ndash;18.\u003c/li\u003e\n \u003cli\u003eMa C, Guizzetti L, Panaccione R, Fedorak RN, Pai RK, Parker CE, et al. Systematic review with meta‐analysis: endoscopic and histologic placebo rates in induction and maintenance trials of ulcerative colitis. Aliment Pharmacol Ther. 2018;47(12):1578\u0026ndash;96.\u003c/li\u003e\n \u003cli\u003eSedano R, Hogan M, Nguyen TM, Chang J, Zou GY, Macdonald JK, et al. Systematic review and meta-analysis: clinical, endoscopic, histological and safety placebo rates in induction and maintenance trials of ulcerative colitis. J Crohns Colitis. 2022;16(2):224\u0026ndash;43.\u003c/li\u003e\n \u003cli\u003eGarud S, Brown A, Cheifetz A, Levitan EB, Kelly CP. Meta-analysis of the placebo response in ulcerative colitis. Dig Dis Sci. 2008;53:875\u0026ndash;91.\u003c/li\u003e\n \u003cli\u003eBonovas S, Pansieri C, Piovani D, Macaluso FS, Orlando A, Festa S, et al. Use of biologics and small molecule drugs for the management of moderate to severe ulcerative colitis: IG-IBD technical review based on the GRADE methodology. Digestive and Liver Disease [Internet]. 2022;54(4):428\u0026ndash;39. Available from: https://www.sciencedirect.com/science/article/pii/S1590865822001347\u003c/li\u003e\n \u003cli\u003eXu YH, Zhu WM, Guo Z. Current status of novel biologics and small molecule drugs in the individualized treatment of inflammatory bowel disease. World J Gastroenterol. 2022;28(48):6888.\u003c/li\u003e\n \u003cli\u003eAlAmeel T, AlMutairdi A, Al-Bawardy B. Emerging therapies for ulcerative colitis: updates from recent clinical trials. Clin Exp Gastroenterol. 2023;147\u0026ndash;67.\u003c/li\u003e\n \u003cli\u003eSu C, Lewis JD, Goldberg B, Brensinger C, Lichtenstein GR. A meta-analysis of the placebo rates of remission and response in clinical trials of active ulcerative colitis. Gastroenterology. 2007;132(2):516\u0026ndash;26.\u003c/li\u003e\n \u003cli\u003eDin S, Segal J, Blackwell J, Gros B, Black CJ, Ford AC. Harms with placebo in trials of biological therapies and small molecules as induction therapy in inflammatory bowel disease: a systematic review and meta-analysis. Lancet Gastroenterol Hepatol. 2024 Nov 1;\u003c/li\u003e\n \u003cli\u003eWeimer K, Colloca L, Enck P. Age and sex as moderators of the placebo response-an evaluation of systematic reviews and meta-analyses across medicine. Gerontology. 2015;61(2):97\u0026ndash;108.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Missouri–Kansas City","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Ulcerative colitis, placebo response, biologics, small molecules, systematic review, meta-analysis, induction trials, clinical remission","lastPublishedDoi":"10.21203/rs.3.rs-7050637/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7050637/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Placebo response is crucial in interpreting treatment efficacy in ulcerative colitis (UC) trials. While it has been broadly studied, it remains underexplored in trials involving the growing number of biologics and small molecules for ulcerative colitis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We systematically searched PubMed, Embase, Scopus, Web of Science, and Cochrane CENTRAL from inception to November 13, 2024. Eligible studies were induction-phase RCTs, including adult patients with moderate-to-severe UC who received a biologic and a small-molecule against a placebo. Primary outcomes were pooled clinical and endoscopic response and remission rates. Safety outcomes included adverse events (AEs), serious adverse events (SAEs), and withdrawal rates. Random-effect models were used for meta-analysis. Meta-regression identified predictors of placebo outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e 26 induction RCTs with 3,937 placebo-treated patients were included. IL inhibitor trials had the highest placebo clinical response (36%) and endoscopic remission (21%), while JAK inhibitors had the lowest (21% and 2%). Overall placebo rates were 34% for clinical response, 8% for clinical remission, 19% for endoscopic response, and 11% for endoscopic remission. Adverse events occurred in 54%, SAEs in 8%, and withdrawals in 18%. Younger age and longer follow-up were linked to higher placebo responses; recent trials showed reduced endoscopic effects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e These findings highlight the need to account for placebo variability in trial design and interpretation, particularly as biologic and small-molecule therapies continue to expand in UC treatment.\u003c/p\u003e","manuscriptTitle":"Variability in Placebo Response Across Biologic and Small Molecule Classes in Induction Randomized Controlled Trials for Ulcerative Colitis: A Systematic Review and Meta-Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-08 10:35:52","doi":"10.21203/rs.3.rs-7050637/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c0ad53ea-b1a1-46a4-b2d3-7dfbdae83304","owner":[],"postedDate":"July 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":51076722,"name":"Gastroenterology \u0026 Hepatology"}],"tags":[],"updatedAt":"2025-07-08T10:35:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-08 10:35:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7050637","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7050637","identity":"rs-7050637","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}