Liu K, Zhang XH, Zhou XY, Liu YX, Pan SQ, Liu TX, Russell R, Wang XH, Yao YP, Zhao XJ, Sun HY, Ju CL, Liu JP, Liu ZL. Clinical features and biomarkers associated with ulcerative colitis: A systematic review and meta-analysis. World J Gastroenterol 2026; 32(46): 123374 [DOI: 10.3748/wjg.123374]
Corresponding Author of This Article
Zhao-Lan Liu, PhD, Professor, Center for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, No. 11 East Road of North Third Ring Road, Chaoyang District, Beijing 100029, China. lzl1019@163.com
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Liu K, Zhang XH, Zhou XY, Liu YX, Pan SQ, Liu TX, Russell R, Wang XH, Yao YP, Zhao XJ, Sun HY, Ju CL, Liu JP, Liu ZL. Clinical features and biomarkers associated with ulcerative colitis: A systematic review and meta-analysis. World J Gastroenterol 2026; 32(46): 123374 [DOI: 10.3748/wjg.123374]
Kai Liu, Xiao-Han Zhang, Ting-Xiu Liu, Jian-Ping Liu, Zhao-Lan Liu, Center for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China
Xiang-Yu Zhou, Yu-Xuan Liu, Shi-Qi Pan, School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China
Robb Russell, Southern California University of Health Sciences, Whittier, CA 90604, United States
Xue-Hui Wang, Third Affiliated Hospital, Beijing University of Chinese Medicine, Beijing 100029, China
Yu-Pu Yao, Xing-Jie Zhao, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing 100078, China
Hui-Yi Sun, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China
Chuan-Lan Ju, Department of Public Health, Yantai Hospital of Traditional Chinese Medicine, Yantai 264000, Shandong Province, China
Jian-Ping Liu, Center for Evidence-Based Medicine, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu 610072, Sichuan Province, China
Author contributions: Liu K and Zhang XH contributed equally, as they are co-first authors; Liu K designed the study, was responsible for formal analysis, and revised the manuscript; Zhang XH designed the study, was responsible for data curation, and wrote and revised the manuscript; Zhou XY and Liu YX contributed to data curation, validated the data, and revised the manuscript; Pan SQ and Liu TX contributed to data curation, and revised the manuscript; Russell R, Wang XH, Yao YP, Zhao XJ, Sun HY, and Ju CL interpreted the data and revised the manuscript; Liu JP and Liu ZL supervised the study, and revised the manuscript; all authors reviewed and approved the final version of the manuscript.
AI contribution statement: The authors declare that no generative AI or AI-assisted technologies were used in the preparation of this manuscript.
Supported by The National Natural Science Foundation of China, No. 82374298.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
Corresponding author: Zhao-Lan Liu, PhD, Professor, Center for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, No. 11 East Road of North Third Ring Road, Chaoyang District, Beijing 100029, China. lzl1019@163.com
Received: May 18, 2026 Revised: July 19, 2026 Accepted: September 4, 2026 Published online: December 14, 2026 Processing time: 157 Days and 10.7 Hours
Abstract
BACKGROUND
Diagnosing ulcerative colitis (UC) remains a clinical challenge due to overlapping presentation with other intestinal disorders. While endoscopy serves as the reference standard, its routine application for initial assessment is constrained by its invasiveness. Improved recognition of non-invasive indicators associated with UC could facilitate timely patient stratification, but their association strengths relative to differential diagnoses have not been systematically quantified.
AIM
To systematically quantify the association strengths of clinical features and biomarkers with UC relative to its differential diagnoses.
METHODS
PubMed, EMBASE, Web of Science, the Cochrane Library, and four Chinese databases were systematically searched from inception up to October 15, 2025. Eligible studies evaluated the association strengths of clinical features and biomarkers with UC vs other differential diagnoses. Pooled odds ratios (ORs) and mean differences (MDs) were calculated as the primary outcomes using a random-effects model. Heterogeneity was evaluated through subgroup analyses, and sensitivity analyses were conducted by omitting high-risk studies and employing generalized linear mixed models.
RESULTS
Across 389 studies, bloody mucopurulent stools showed a strong positive association with UC vs intestinal tuberculosis [OR = 43.14, 95% confidence interval (CI): 5.75-323.92]. Conversely, perianal fistulas were inversely associated with UC vs Crohn’s disease (OR = 0.08, 95%CI: 0.04-0.14). Fecal calprotectin distinguished UC from irritable bowel syndrome (MD = 696.31 μg/g, 95%CI: 512.38-880.23), while perinuclear anti-neutrophil cytoplasmic antibodies were strongly associated with UC vs Crohn’s disease (OR = 8.70, 95%CI: 6.70-11.31). Comparing active UC with disease remission, fecal calprotectin (MD = 387.04 μg/g, 95%CI: 292.55-481.54) and C-reactive protein (MD = 12.94 mg/L, 95%CI: 10.48-15.41) were significantly elevated.
CONCLUSION
This meta-analysis systematically quantifies the multidimensional clinical and laboratory association strengths with UC, establishing a non-invasive framework that facilitates pre-endoscopic risk stratification and optimizes clinical resource allocation.
Core Tip: This systematic meta-analysis quantifies the associations of non-invasive clinical features and laboratory biomarkers with ulcerative colitis (UC). Based on 389 studies, bloody mucopurulent stools and tenesmus are strongly associated with UC, while perianal fistulae and abdominal masses link more directly to Crohn’s disease. Furthermore, fecal calprotectin, erythrocyte sedimentation rate, and C-reactive protein show significant associations with UC activity and differential risks. Mapping these clinical and biomarker associations offers an evidence-based framework to optimize patient prioritization for invasive endoscopy.
Citation: Liu K, Zhang XH, Zhou XY, Liu YX, Pan SQ, Liu TX, Russell R, Wang XH, Yao YP, Zhao XJ, Sun HY, Ju CL, Liu JP, Liu ZL. Clinical features and biomarkers associated with ulcerative colitis: A systematic review and meta-analysis. World J Gastroenterol 2026; 32(46): 123374
Ulcerative colitis (UC), a chronic, relapsing inflammatory condition of the colonic mucosa[1], has demonstrated a rising global incidence, particularly in newly industrialized countries[2,3]. Timely diagnosis is critical, as a favorable long-term prognosis depends heavily on the prompt initiation of therapy[4,5]. However, the early differential diagnosis of UC remains challenging, with its clinical symptoms frequently overlapping with those of other intestinal diseases, including Crohn’s disease (CD), ischemic colitis (IC), and infectious enterocolitis (IE)[6,7]. While ileocolonoscopy with histopathology remains the definitive reference standard[1,3], its utility for routine evaluation in primary care triage is often constrained by cost, invasiveness, and limited availability[8]. Consequently, elucidating the association strengths of specific clinical features and routine biomarkers is valued for their risk-stratification potential, serving as preliminary, non-invasive indicators that assist in prioritizing patients for definitive endoscopic evaluations[9].
However, implementing this non-invasive strategy presents significant challenges. In real-world clinical settings, primary care clinicians are frequently required to identify high-suspicion patient profiles from these shared symptoms[6], yet the evidence for non-invasive biomarkers remains largely fragmented, leaving their true association strengths poorly quantified[10,11]. Such clinical complexity and fragmented evidence have hindered the consensus on these indicators[7,12], thereby impeding timely and accurate referral decisions[13-15]. Therefore, systematically quantifying the association strengths between these common clinical signs and UC is critical for optimizing clinical practice.
To bridge these gaps, we conducted a systematic review and meta-analysis to systematically quantify the association strengths of clinical features and laboratory biomarkers with UC relative to other intestinal disorders. Additionally, we evaluated the variations in biomarker levels across patients with active UC, those in disease remission, and healthy controls. Ultimately, these findings aim to provide an evidence-based reference to optimize initial outpatient triage and prioritize endoscopic referrals.
MATERIALS AND METHODS
This systematic review followed the preferred reporting items for systematic reviews and meta-analyses guidelines and the Meta-analysis of Observational Studies in Epidemiology reporting checklist[16,17]. The protocol was registered with PROSPERO (No. CRD420261284610).
Data sources and search strategy
We systematically searched PubMed, EMBASE, Web of Science, the Cochrane Library, the China National Knowledge Infrastructure, the WanFang Database, the Chinese Scientific Journals Full-Text Database, and the Chinese Biomedical Literature Database from their inception to October 15, 2025. The complete search strategies are available in the Supplementary Table 1.
Study selection and selection criteria
We included observational studies (including cohort, cross-sectional, and case-control studies) with a comparative design. Eligible studies were required to compare patients with UC against specific differential diagnoses, including other inflammatory or infectious conditions, such as CD, inflammatory bowel disease unclassified (IBD-U), and intestinal tuberculosis (ITB), as well as IE, IC, and irritable bowel syndrome (IBS). Studies evaluating different disease activity states, specifically active UC vs clinical remission, or comparing UC patients with healthy controls, were also eligible. The diagnosis of UC was established based on standardized clinical guidelines or a combination of clinical, endoscopic, and histopathological findings[18-23].
The primary outcomes were the association strengths of clinical features and biomarkers with UC, quantified by comparing their prevalence or concentrations between patients with UC and their differential diagnoses. The evaluated clinical features were categorized into gastrointestinal symptoms, extraintestinal manifestations (EIMs), and systemic signs. The target biomarkers comprised fecal calprotectin (FC), perinuclear anti-neutrophil cytoplasmic antibodies (p-ANCA), C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR). Studies were required to provide sufficient quantitative data to compute odds ratios (ORs) and mean differences (MDs).
We excluded preclinical investigations (animal or in vitro models), meeting abstracts, reviews, and non-original research. When duplicate publications or overlapping study populations were identified, only the largest or most comprehensive report was retained.
After automatic deduplication using EndNote software (version X9), four reviewers (Zhang XH, Zhou XY, Pan SQ, and Liu YX) independently screened titles and abstracts, followed by full-text evaluation, based on the selection criteria. Any disagreements were resolved by a senior reviewer (Liu K).
Data extraction and quality assessment
Four investigators (Liu TX, Zhou XY, Pan SQ, and Liu YX) independently extracted data using a pre-designed data extraction form. The extracted information included study characteristics, participant demographics, and quantitative outcomes. Two reviewers (Zhou XY and Liu YX) independently evaluated the methodological quality of the included studies using the Joanna Briggs Institute (JBI) critical appraisal tools[24]. These assessments focused on internal validity, confounding control, and compliance with reporting standards. Each study was subsequently categorized as having a low, moderate, or high risk of bias according to JBI benchmarks. Any disagreements were resolved by a senior reviewer (Zhang XH).
Statistical analysis
Statistical analyses were performed using R software 3.4.3. Dichotomous and continuous outcomes were synthesized using pooled ORs and MDs with 95% confidence intervals (95%CIs), respectively. To handle studies with zero-event cells, a continuity correction of 0.5 was applied. Given the anticipated clinical and methodological heterogeneity, all meta-analyses were performed using random-effects models. We assessed heterogeneity using Cochran’s Q test and the I2 statistic, with I2 values of 25%, 50%, and 75% indicating low, moderate, and high heterogeneity, respectively[25]. We explored potential sources of heterogeneity by predefined covariates, including geographical region (China vs non-China), diagnostic standards (use of standardized clinical guidelines vs none), and study design (prospective study vs retrospective study). These factors were evaluated through subgroup analyses and meta-regression, and the results were assessed via the test of moderators statistic and residual heterogeneity[26]. For these secondary analyses, P value < 0.10 was considered to indicate a statistically significant difference. Sensitivity analyses were conducted by excluding studies with a high risk of bias and by re-estimating pooled ORs using generalized linear mixed models[27]. Publication bias was evaluated using funnel plots and Egger’s test only for outcomes that included at least 10 original studies[28].
Certainty of evidence assessment
Two independent investigators (Liu YX and Zhou XY) assessed the certainty of evidence for each outcome using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework[29]. The rationale for upgrading or downgrading the certainty of evidence was based on relevant literature[30-32]. Any disagreements were resolved by a third researcher (Zhang XH).
RESULTS
Study characteristics and quality
The initial literature search identified 8093 records, of which 911 full texts were reviewed, and 389 studies were ultimately included (Figure 1). Geographically, the included studies spanned five continents, with a predominant concentration within China (n = 300). The final analysis comprised 118349 patients diagnosed with UC and 183071 controls. The control groups encompassed a diverse spectrum of conditions, including patients with CD, IC, ITB, IE, IBS, and IBD-U, as well as healthy controls (Table 1). The studies were published between 1970 and 2024, with a notable increase in publication volume after 2008. The characteristics of the included studies are available in Supplementary Table 2.
Methodological quality assessment revealed frequent limitations in reporting confounding variable control and participant matching, with a substantial proportion of studies rated as ‘unclear’ or ‘no’ in these domains. Based on this evaluation, the 389 included studies were stratified into low (n = 147), moderate (n = 182), and high (n = 60) risk of bias categories (Supplementary Table 2).
Typical gastrointestinal manifestations
Bloody mucopurulent stools exhibited a strong positive association with UC across multiple comparators, demonstrating the highest magnitude of association when compared against ITB (OR = 43.14, 95%CI: 5.75-323.92), followed by IC (OR = 20.68, 95%CI: 10.92-39.17) and CD (OR = 13.33, 95%CI: 8.29-21.44). Hematochezia showed divergent associations depending on the comparator, being significantly more prevalent in UC than in both ITB (OR = 14.61, 95%CI: 1.71-124.70) and CD (OR = 4.97, 95%CI: 3.25-7.61), but demonstrated a prominent inverse association compared with IC (OR = 0.22, 95%CI: 0.09-0.52). Tenesmus was also more frequently reported in UC than in IC (OR = 11.53, 95%CI: 4.46-29.81) and CD (OR = 3.72, 95%CI: 2.75-5.02), while exhibiting an inverse relationship when compared with IBS (OR = 0.17, 95%CI: 0.07-0.40).
Conversely, several signs demonstrated strong inverse associations with UC, characterizing specific alternative diagnoses rather than UC. Most notably, the presence of perianal fistulas (OR = 0.08, 95%CI: 0.04-0.14) and perianal abscesses (OR = 0.13, 95%CI: 0.06-0.32) was predominantly linked to CD. Similarly, abdominal masses exhibited a significantly lower prevalence in UC compared with either ITB (OR = 0.09, 95%CI: 0.01-0.52) or CD (OR = 0.12, 95%CI: 0.06-0.24). Collectively, these findings identify statistically significant, comparator-dependent clinical signatures for each gastrointestinal symptom (Table 2) (Supplementary Figure 1).
Table 2 Meta-analysis of gastrointestinal manifestations in ulcerative colitis vs controls.
Notably, the sensitivity analysis for tenesmus (UC vs IC) using the generalized linear mixed models yielded an extremely inflated estimate (OR = 3065.61). Publication bias was detected in analyses evaluating diarrhea (UC vs CD), hematochezia (UC vs IC), bloody mucopurulent stool (UC vs IC), tenesmus (both UC vs CD and UC vs IC), and perianal abscesses (UC vs CD) (Supplementary Tables 3 and 4, Supplementary Figure 2).
EIMs
The prevalence of EIMs and their specific subtypes exhibited distinct variation depending on the individual comparator. In comparison with CD, patients with UC demonstrated a significantly lower prevalence of overall EIMs (OR = 0.47, 95%CI: 0.36-0.61) and its specific subtypes, including oral lesions (OR = 0.32, 95%CI: 0.23-0.44), dermatological manifestations (OR = 0.54, 95%CI: 0.45-0.64), arthritis (OR = 0.60, 95%CI: 0.51-0.72), and ocular involvement (OR = 0.61, 95%CI: 0.47-0.80) (Supplementary Figure 3).
Regarding other differential diagnoses, overall EIM involvement was more frequently associated with UC than with IC (OR = 22.88, 95%CI: 1.29-405.78) or ITB (OR = 2.98, 95%CI: 1.97-4.49), whereas individual EIM subtypes showed no distinct differentiation between UC and either IC or ITB. Notably, hepatobiliary involvement did not achieve statistical significance across any of the evaluated comparator groups (Table 3).
Table 3 Meta-analysis of extraintestinal manifestations in ulcerative colitis vs controls.
While the pooled estimates remained robust with no essential fluctuations across sensitivity analyses, significant publication bias was widespread, including analyses of overall EIMs (UC vs CD), arthritis (UC vs CD), dermatological manifestations (UC vs CD), ocular involvement (UC vs CD), and hepatobiliary involvement (UC vs CD) (Supplementary Tables 3 and 4, Supplementary Figure 4).
Systemic signs
When evaluated across different differential diagnoses, the prevalence of systemic signs exhibited distinct, disease-specific profiles. In comparison with CD, patients with UC demonstrated significantly lower prevalence rates of weight loss (OR = 0.49, 95%CI: 0.41-0.59), anemia (OR = 0.58, 95%CI: 0.49-0.70), and fever (OR = 0.61, 95%CI: 0.50-0.73) (Supplementary Figure 5). Similarly, anemia (OR = 0.24, 95%CI: 0.07-0.84) and fever (OR = 0.23, 95%CI: 0.09-0.61) demonstrated prominent inverse associations with UC when compared to ITB.
In contrast, while weight loss was less prevalent in UC relative to CD, it demonstrated a strong positive association with UC when compared with IC (OR = 8.00, 95%CI: 3.00-21.32). Fatigue was the only systemic feature that exhibited a comparable distribution across all individual differential diagnoses (Table 4). Except for fever, all systemic signs demonstrated high stability across sensitivity analyses and no evidence of publication bias (Supplementary Tables 3 and 4 and Supplementary Figure 6).
Table 4 Meta-analysis of systemic signs in ulcerative colitis vs controls.
Biomarkers demonstrated distinct profiles when analyzed against different control diseases, characteristically varying in both the magnitude and direction of their clinical associations (Supplementary Figure 7). Regarding FC, a pronounced positive correlation with UC was predominantly observed in comparisons involving IBS (OR = 10.09, 95%CI: 3.57-28.52; MD = 696.31 μg/g, 95%CI: 512.38-880.23). Patients with UC exhibited a weaker clinical link with both ESR (OR = 0.57, 95%CI: 0.40-0.81; MD = -2.86 mm/hour, 95%CI: -4.99 to -0.74) and CRP (OR = 0.73, 95%CI: 0.54-0.98; MD = -3.78 mg/L, 95%CI: -6.05 to -1.50) when compared with CD. A contrasting profile emerged in comparisons against IC, marked by a lower CRP burden (MD = -23.23 mg/L, 95%CI: -26.41 to -20.05) but a higher ESR level (MD = 12.53 mm/hour, 95%CI: 0.50-24.56). Furthermore, p-ANCA retained a highly robust positive association with UC across almost all evaluated conditions, demonstrating marked elevations in both seropositivity rates and quantitative titers when compared with CD (OR = 8.70, 95%CI: 6.70-11.31; MD = 27.74 U/mL, 95%CI: 14.68-40.79) (Table 5).
Table 5 Meta-analysis of biomarkers in ulcerative colitis vs controls.
Notably, the sensitivity analysis for p-ANCA positivity (UC vs healthy controls) using the generalized linear mixed models yielded an extremely inflated estimate (OR = 117.52, 95%CI: 47.31-291.92). Publication bias was detected in analyses evaluating p-ANCA positivity (UC vs CD), ESR levels (UC vs CD), and CRP positivity (UC vs CD) (Supplementary Tables 3 and 4, Supplementary Figure 8).
Biomarkers in active UC vs clinical remission and healthy controls
An assessment of disease status demonstrated that inflammatory marker concentrations increased progressively in parallel with advancing clinical activity (Supplementary Figure 9). When compared directly with patients in clinical remission, individuals with active UC exhibited a significantly higher inflammatory burden, characterized by marked elevations in FC (MD = 387.04 μg/g, 95%CI: 292.55-481.54), ESR (MD = 14.33 mm/hour, 95%CI: 11.93-16.73), and CRP (MD = 12.94 mg/L, 95%CI: 10.48-15.41).
These clinical associations became even more pronounced when active UC cohorts were analyzed against healthy controls, yielding substantial MDs across all three biomarkers. Across these distinct comparison contexts, the uniform direction of the estimated effect sizes establishes these biomarkers as robust, reproducible indicators of active mucosal and systemic inflammation (Table 6).
Table 6 Meta-analysis of inflammatory markers in active ulcerative colitis compared with clinical remission and healthy controls.
No substantial fluctuations in effect sizes were observed when high-bias-risk studies were excluded. Significant publication bias was detected in analyses of CRP and ESR levels for the Active UC vs UC in Remission comparison (Supplementary Tables 3 and 4, Supplementary Figure 10).
Subgroup analysis
According to the above results, we performed pre-specified subgroup analyses stratified by geographical location, diagnostic criteria, and study design (Supplementary Tables 5 and 6).
Regarding geographical stratification, distinct regional variation emerged in the clinical association profiles. The positive association of diarrhea (UC vs CD) was more pronounced in Chinese cohorts than in international cohorts (OR = 3.19 vs OR = 1.45). For anemia (UC vs CD), UC exhibited a stronger inverse association in China (OR = 0.46), whereas the inverse association of fever was attenuated relative to other countries (OR = 0.66 vs OR = 0.22). Furthermore, overall EIMs (OR = 0.36 vs OR = 0.65) and hepatobiliary involvement (OR = 0.65 vs OR = 1.76) demonstrated tighter inverse clinical links with UC within Chinese populations. In terms of continuous biomarkers, ESR elevations against healthy controls were less marked in China than abroad (MD = 16.80 mm/hour vs MD = 24.84 mm/hour), with a similar trend observed against the clinical remission group (MD = 13.51 mm/hour vs MD = 26.31 mm/hour). Conversely, CRP levels yielded substantially larger MDs in Chinese cohorts than in foreign cohorts against both healthy controls (MD = 17.24 mg/L vs MD = 1.10 mg/L) and remission cohorts (MD = 13.42 mg/L vs MD = 0.60 mg/L).
For the diagnostic standards perspective, the implementation of explicit diagnostic guidelines moderated the observed clinical associations. The inverse association of abdominal pain (UC vs IC) was more pronounced in the subgroup explicitly utilizing established diagnostic criteria than in the cohorts without specified criteria (OR = 0.40 vs OR = 1.23). For oral lesions (UC vs CD), a tighter inverse clinical link was observed in the standardized diagnosis group than in its non-standardized counterpart (OR = 0.26 vs OR = 0.49). A significant inverse association for CRP positivity (UC vs CD) was captured exclusively in the guideline-compliant group (OR = 0.51). Furthermore, FC elevations against healthy controls yielded a smaller, more conservative MD in the subgroup adhering to explicit guidelines (MD = 358.06 μg/g vs 595.03 μg/g), whereas ESR elevations against the clinical remission group revealed an expanded MD in the standardized cohort (MD = 15.29 mm/hour vs 10.31 mm/hour).
For the study design perspective, the variations in epidemiological frameworks contributed to the observed statistical estimates. The inverse association of overall EIMs (UC vs CD) was more pronounced in retrospective designs than in prospective frameworks (OR = 0.44 vs OR = 0.80). Conversely, for continuous inflammatory kinetics, ESR elevations against healthy controls yielded a larger pooled MD in retrospective frameworks than in prospective settings (MD = 17.71 mm/hour vs 10.40 mm/hour).
Meta-regression
We further performed meta-regression on the clinical features and biomarkers aiming to identify covariates that had an impact on heterogeneity (Supplementary Tables 7 and 8). Meta-regression analyses identified geographical location as an important source across multiple clinical features. Specifically, geographical region exerted a statistically significant moderating effect on the variation of diarrhea (UC vs CD) (estimate = 1.26). For anemia (UC vs CD), the regression model demonstrated that geographical location accounted for a substantial proportion of heterogeneity with an R2 of 50.5% (estimate = -0.7203). Furthermore, geographical location significantly modified the variance of hepatobiliary involvement (UC vs CD) (estimate = -1.46).
Similarly, the regression model confirmed that the implementation of diagnostic standards exerted a moderating effect on the variance of FC levels against patients in clinical remission (estimate = -173.03). Finally, when evaluating the structural influences of epidemiological frameworks, the meta-regression models demonstrated that study design accounted for the variance observed in ocular involvement (UC vs CD) (estimate = 0.93).
Grade evidence assessment
Based on GRADE assessments (Supplementary Tables 9 and 10), high-certainty evidence supported the robustness of the inverse association between UC and perianal fistulas (against CD). Meanwhile, moderate-certainty evidence supported the association of specific clinical features, particularly hallmark gastrointestinal manifestations such as abdominal masses (against CD and ITB), abdominal distension (against IBS), and hematochezia (against IE). Furthermore, this moderate-certainty support extended to the associations observed for key biological markers, notably p-ANCA positivity (against CD, ITB, IBS, and IE) and CRP positivity (against IE).
DISCUSSION
Distinguishing UC from differential diagnoses in outpatient settings remains a significant challenge[12,33]. In this systematic review and meta-analysis, we synthesized 389 studies to integrate multi-dimensional evidence encompassing gastrointestinal manifestations, EIMs, systemic signs, and biomarkers. Our findings identified reliable clinical indicators that suggest a high probability of UC, as well as exclusionary features that suggest other diseases. Given that the invasiveness and logistical constraints of ileocolonoscopy often preclude its immediate use in primary care[8], our findings address this clinical gap by supporting non-invasive, pre-endoscopic risk stratification. This evidence-based reference assists in prioritizing individuals with strong UC-associated profiles for definitive endoscopic evaluation, thereby minimizing unnecessary invasive procedures.
Our analysis demonstrated that the clinical associations of gastrointestinal manifestations are highly contextual and dependent on the specific alternative diagnosis. Specifically, bloody mucopurulent stools emerged as feature characteristically exhibiting the most profound positive association with UC across all individual comparators, demonstrating the highest magnitude of association against ITB (OR = 43.14), followed by IC (OR = 20.68) and CD (OR = 13.33). These consistent positive associations reflect the continuous mucosal inflammation and ulceration characteristic of UC[34], which typically originates in the rectum and extends proximally[1]. Such superficial erosion leads to spontaneous bleeding and mucopurulent discharge[3]. In contrast, symptoms like tenesmus and hematochezia exhibited significant comparator-dependent variability. Localized rectal inflammation in UC lowers the sensory threshold of the defecation reflex, directly manifesting as tenesmus. Consequently, UC patients exhibited a significantly stronger positive association with tenesmus than those with IC (OR = 11.53) or CD (OR = 3.72), as the latter frequently spares the rectum and preserves its reservoir function[34,35]. IC is characterized by acute vascular hypoperfusion, which precipitates rapid mucosal necrosis and hemorrhage, clinically manifesting as acute and frank hematochezia rather than the chronic mucopurulent discharge typical of UC[36]. Conversely, the passage of mucus in IBS stems from autonomic dysregulation without mucosal injury, thereby making hematochezia a clinically rare presentation[37]. Consequently, isolated hematochezia demonstrated a stronger inverse association with UC when compared directly against IC, while the passage of bloodless mucus retained a robust positive association with IBS. Furthermore, since UC pathology is typically confined to the colorectum and spares the upper gastrointestinal tract and small intestine[34], upper gastrointestinal symptoms, weight loss, and anemia exhibited a significantly attenuated clinical association with UC relative to CD.
CD is characterized by discontinuous, transmural inflammation that can affect any segment of the gastrointestinal tract from the mouth to the anus[1,35], while UC is defined by continuous inflammation strictly confined to the colonic mucosa and submucosa[3]. This transmural progression frequently leads to structural complications, such as fibrotic strictures, inflammatory masses, or fistulous tracts[35,38]. Consequently, abdominal masses and perianal involvement exhibited robust, polarized inverse associations with UC. Furthermore, the transmural nature of CD drives a more pronounced systemic inflammatory response[35], whereas the active mycobacterial burden in ITB elicits a potent systemic release of pyrogenic cytokines, creating a distinct inflammatory signature[39]. These pathogenic mechanisms explain the attenuated magnitude of association with fever observed in UC compared with both CD and ITB. This relatively contained systemic inflammatory burden in UC accounts for its lower incidence of EIMs, which share overlapping immunopathological mechanisms with the primary intestinal lesions[40-42]. Histologically, the presence of non-caseating granulomas in extra-colonic sites suggests that CD represents a systemic disease process[43,44]. Although UC demonstrated an attenuated association with EIMs relative to CD[45], in comparison with other differential diagnoses, overall EIM involvement exhibited a significantly stronger positive association with UC than with IC or ITB. Consequently, these distinct association profiles reflect varying systemic inflammatory burdens, disease durations, and complication profiles across different IBD subtypes[45].
Regarding biomarkers, FC demonstrates a robust clinical association with intestinal inflammation[12]. As a neutrophil-derived protein, its concentration in feces provides a direct quantitative reflection of the degree of neutrophil migration into the intestinal mucosa[11,44,46]. Our meta-analysis confirms that FC exhibited a remarkably strong positive association with UC when contrasted specifically against IBS, highlighting the massive expansion of effect sizes when contrasting inflammatory conditions against functional disorders.
Moreover, FC levels were significantly higher in active UC compared with clinical remission and healthy controls. However, this magnitude of association markedly attenuates when comparing UC with CD, reflecting the shared inflammatory burden inherent to both IBD subtypes[6]. Similarly, ESR and CRP demonstrated restricted divergence in their clinical associations against CD. Instead, their marked elevations in active UC highlight their value in longitudinal monitoring. Therefore, the primary clinical utility of these biomarkers lies in triaging inflammatory states vs functional conditions and monitoring disease activity over time[6,8,12,47].
Prospective investigations have indicated that p-ANCA can be detected in the serum years before the clinical diagnosis of UC[47], suggesting its involvement in early disease pathogenesis rather than being merely a consequence of mucosal inflammation. In our meta-analysis, p-ANCA was confirmed as a robust biological hallmark of UC, characterized by significantly higher positivity rates and quantitative titers when compared with CD[8,48]. Nevertheless, the interpretation of this association must account for substantial heterogeneity, which may be attributed to differences in assay methodologies, positivity thresholds, and disease extent[49].
Our pooled estimates revealed that the clinical association profiles and quantitative magnitudes of effect sizes varied substantially across the included studies, displaying high statistical heterogeneity. We speculated that this variation was mainly related to geographical location across different cohorts. Specifically, the clinical and biomarker association profiles exhibited marked stratification between Chinese populations and international cohorts. This regional divergence potentially stems from differences in immunogenetic architecture and healthcare delivery models. Literature indicates that the incidence of EIMs and primary sclerosing cholangitis is substantially lower in Asian IBD patients relative to European cohorts[50]. This divergence is likely driven by the distinct distribution of human leukocyte antigen (HLA) alleles. For instance, the HLA-DRB101:03 allele, strongly linked to EIMs and colonic resection in Western phenotypes, is virtually undetectable in Asian populations[51]. Conversely, Asian-specific HLA haplotypes, such as HLA-DRB115:02, may confer a protective effect that restrains the development of complex systemic complications[52]. Furthermore, in China, patients are predominantly recruited during acute hospitalization, yielding cohorts that primarily capture severe acute flares rather than mild chronic states[53,54]. Consequently, these Chinese cohorts exhibit higher levels of inflammatory markers than international counterparts.
Moreover, the heterogeneity across studies is further exacerbated by the lack of uniform diagnostic standardization and variations in study design. The reliance on retrospective vs prospective data capture significantly influences clinical findings, as retrospective cohorts often capture patients at high-acuity points of care, thereby disproportionately emphasizing clinical features and acute inflammatory marker magnitudes. Furthermore, the adoption of different diagnostic criteria often entails varying cutoff values for biochemical assessments, which directly impacts the definition of disease severity and activity. Therefore, it remains indeterminate whether variations in the absence of certain features signify genuine pathophysiological distinctions or arise from methodological artifacts and inconsistencies in threshold definitions across the pooled literature.
This study systematically evaluated and synthesized non-invasive indicators to identify their associations with UC. As previous studies have predominantly focused on isolated laboratory biomarkers without quantitative integration of clinical symptoms[11,45,55], our research addresses this gap by establishing a multidimensional association hierarchy based on pooled effect sizes. Consequently, these findings assist physician in pre-endoscopic risk stratification and optimizing outpatient triage without encroaching upon definitive diagnostic accuracy.
However, our study has several limitations. First, substantial heterogeneity persisted despite subgroup and meta-regression analyses, likely reflecting the complex interplay of diverse clinical settings and other unmeasured confounding factors, which limits the establishment of universal benchmarks for these associations in routine clinical practice. Second, the predominance of retrospective studies may introduce selection bias or documentation inaccuracies, potentially confounding the estimated magnitudes of these clinical associations. Furthermore, the scarcity of eligible studies for specific comparisons resulted in wide CIs, thereby compromising the statistical precision of these pooled effect sizes.
Future research should prioritize large-scale, prospective, multi-center cohort studies to validate long-term stability of these clinical associations across diverse populations, thereby mitigating the selection and documentation biases inherent in retrospective data. To ensure consistent symptom quantification and robust associative modeling, future trials should universally adopt validated clinical activity indices, such as the partial Mayo Score, in conjunction with standardized patient-reported outcomes.
CONCLUSION
This meta-analysis demonstrates that bloody mucopurulent stools and p-ANCA serve as key clinical and laboratory indicators closely associated with UC when distinguishing it from other mimicking conditions. Biomarkers like ESR, CRP, and FC exhibit robust clinical utility in separating inflammatory states from functional disorders like IBS as well as in tracking longitudinal disease activity. By integrating these clinical features and biomarkers, primary care physicians can achieve a more comprehensive assessment of patient profiles prior to invasive interventions. Ultimately, this evidence-based reference facilitates pre-endoscopic risk stratification, thereby promoting timely intervention for high-risk patients and the efficient allocation of medical resources.
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