Abstract
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Background/Aims
- To determine time to diagnosis (TTD) and its impact on surgery and advanced therapy (AT) burden in inflammatory bowel disease (IBD) in a multi-ethnic United Arab Emirates (UAE) cohort, a region in the acceleration phase of IBD incidence.
-
Methods
- Retrospective analysis of the UAE Epi-IBD registry. TTD was calculated from patient-reported symptom onset to diagnosis. Logistic, Poisson regression and Cox proportional hazards models were used. Sensitivity analyses using 6- and 18-month thresholds and TTD quartiles were performed.
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Results
- Among 243 patients (148 Crohn’s disease [CD], 95 ulcerative colitis [UC]), median TTD was 4.0 months (interquartile range [IQR], 1.5–9.0 months) for CD and 3.0 months (IQR, 1.0–7.0 months) for UC (P=0.111, Wilcoxon; log-rank P=0.054), shorter than pooled estimates from high-income countries. UC TTD accelerated significantly post-2021 (2.0 months vs. 5.5 months; P=0.006), while CD remained stable (P=0.646). Diagnostic speed was identical between tertiary and non-tertiary settings (P=0.943). Diagnostic delay did not predict AT exposure (P=0.986) or surgical risk (P=0.586); instead, penetrating CD phenotype drove therapy burden (P=0.019). Time to first AT was rapid (median 4.5 months for CD, 14.0 months for UC). Era-stratified analysis showed a trend toward higher AT use in 2021 to 2025 (incidence rate ratio, 1.36; 95% CI, 0.98–1.89; P=0.071), consistent with expanding therapeutic availability, though null association between delay and outcomes persisted after adjustment.
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Conclusions
- TTD in this cohort is shorter than global benchmarks and comparable to recent Asian data. Diagnostic delay did not predict adverse outcomes, though limited surgical events and short follow-up preclude definitive conclusions. Multiple factors beyond healthcare system architecture may contribute, and larger multicenter studies are needed.
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Keywords: Crohn disease; Delayed diagnosis; Delivery of health care; Inflammatory bowel diseases; Ulcerative colitis
Graphical abstract
INTRODUCTION
The diagnostic trajectory of inflammatory bowel disease (IBD) is often characterized by missed opportunities. The concept of the “window of opportunity” posits that early intervention, specifically within the first 18 months of disease onset, can halt the progression from inflammation to irreversible bowel damage [1-3]. Recent global meta-analyses have quantified the cost of hesitation: delays in Crohn’s disease (CD) diagnosis are associated with an 88% increase in the odds of stricturing disease and a 124% increase in intestinal surgery [4].
While Western cohorts have established benchmarks for these intervals, reporting median delays of 6.2 to 9 months for CD and 3.2 to 6 months for ulcerative colitis (UC) in high-income countries, the epidemiological landscape is shifting. The Middle East is currently in the “acceleration of incidence” phase of epidemiological transition [5-8]. Historically, data from this region has been fragmented, with previous reports from the region and South Asia suggesting diagnostic intervals exceeding 11 months, often attributed to limited specialist access or confusion with infectious mimics like intestinal tuberculosis [9-11]. Recent data from the UAE Epi-IBD study has confirmed a nearly 13-fold increase in new IBD diagnoses over the last two decades, with a high prevalence of aggressive phenotypes [12,13].
The United Arab Emirates (UAE) presents a unique natural experiment for studying diagnostic efficiency in IBD. Unlike most Western healthcare systems that employ primary care gatekeeping and specialist referral pathways, the UAE permits direct self-referral to gastroenterologists, potentially eliminating a major source of diagnostic delay [14]. Its multi-ethnic population, comprising Emirati nationals with comprehensive government insurance and a large expatriate workforce with variable private insurance, provides an opportunity to examine the influence of healthcare access and equity on diagnostic and therapeutic timelines. To date, no study has systematically characterized time to diagnosis (TTD) in this setting, nor examined whether the Western-derived association between diagnostic delay and adverse outcomes applies to this high-resource, rapid-access environment. We aimed to benchmark TTD in a multi-ethnic UAE cohort and to determine whether diagnostic latency drives surgery and advanced therapy (AT) burden in this context.
METHODS
1. Study Design and Setting
The study was conducted at Sheikh Shakhbout Medical City (SSMC), Abu Dhabi, a large tertiary referral center in the UAE and is based on the UAE Epi-IBD study which maintains an ambispective registry [12]. The center receives patients from a wide network of primary care clinics, private hospitals, and other public health facilities across the UAE. Consequently, the diagnostic timelines analyzed reflect the cumulative patient journey through the broader healthcare system, incorporating initial presentation and workup at external facilities, rather than solely the internal processes of a single institution. The protocol for this research project was approved by the Institutional Review Board at SSMC (IRB No. SSMCREC-585). This study was performed in accordance with the ethical standards of the Declaration of Helsinki. Informed consent was waived by the board due to the retrospective nature of the study, and all data were anonymized to protect patient confidentiality.
2. Description of Participants and Data Sources
Only patients under active follow-up at our IBD center who had a comprehensive and accurately documented longitudinal treatment history and a definitive diagnosis of IBD established between January 2016 and November 2025 based on standard clinical, endoscopic, histological, and radiological criteria were included. Strict inclusion criteria were applied to ensure timeline accuracy: patients were required to have documented dates for both the onset of symptoms attributed to IBD and the definitive diagnosis. Importantly, we excluded patients with IBD unclassified, incidental diagnoses (asymptomatic), and incomplete covariate data. The date of symptom onset was ascertained from clinical documentation at the time of diagnosis, recorded by the treating physician based on patient-reported history. For patients diagnosed before the transition to prospective enrollment in 2021, symptom onset dates were extracted from retrospective chart review. This approach is inherently subject to recall bias, particularly for patients with insidious or intermittent symptoms such as mild diarrhea or non-specific abdominal pain.
3. Definition of Variables and Outcomes
The primary exposure variable, TTD, was defined as the interval in months between patient-reported symptom onset and the date of definitive diagnosis. Symptom onset was determined via review of initial consultation notes (e.g., chronic diarrhea, rectal bleeding, abdominal pain). This definition captures the “total diagnostic lag,” incorporating both the patient interval (time to seek care) and the system interval (time from contact to diagnosis), aligning with methodologies from the Swiss IBD Cohort and EPIMAD registry [15,16]. “Prolonged Delay” was defined as TTD >12 months. This threshold was selected based on the 75th percentile of diagnostic intervals reported in the definitive meta-analysis by Jayasooriya et al. [4], which established pooled medians of 7.0 months for CD and 4.6 months for UC across 101 studies, and aligns with the dose-response relationship between delay duration and adverse outcomes demonstrated by Vavricka et al. [15]. Secondary metrics included time to AT (diagnosis to first biologic/small molecule). Clinical outcomes were cumulative AT burden (count of distinct therapies) and risk of IBD-related surgery (major abdominal resection). Disease phenotype was classified according to the Montreal classification. Impact of diagnostic setting (tertiary care versus other facilities) on these variables was assessed.
Treatment strategies were classified as “accelerated step-up” (initiation of AT after an initial trial of conventional therapy) or “early first-line escalation” (initiation of AT within 3 months of diagnosis without prior conventional therapy). Time to first AT was measured from the date of diagnosis to the date of first biologic or small molecule prescription. The availability of advanced therapies in the UAE has expanded substantially over the study period, from infliximab (2002) and adalimumab (2011) to vedolizumab (2015), ustekinumab (2016 CD, 2019 UC), tofacitinib (2018), risankizumab (2022 CD, 2024 UC), and upadacitinib (2022 CD, 2023 UC). To evaluate temporal trends in diagnostic efficiency and account for this evolving treatment landscape, the study period was stratified at a 2021 cut-point into a historical era (2016–2020) and a recent era (2021–2025), corresponding to the transition from predominantly retrospective to prospective enrollment, the rapid therapeutic expansion from 2020 onward, and the potential impact of COVID-19 (coronavirus disease 2019) on diagnostic pathways.
To assess the robustness of primary findings, pre-specified sensitivity analyses included: (1) threshold sensitivity, re-analyzing prolonged delay at 6-month and 18-month cutoffs; (2) restriction to patients with at least 12 months of follow-up; (3) era-adjusted models adding diagnosis period (2016–2020 vs. 2021–2025) as a covariate; (4) era-restricted analysis limited to 2021–2025; and (5) a quartile-based approach examining outcomes across TTD quartiles to detect dose-response relationships.
4. Statistical Analysis
All statistical analyses were performed using R software (version 4.3.2, R Foundation for Statistical Computing, Vienna, Austria) with the tidyverse, survival, and gtsummary packages [17]. Continuous variables were presented as medians with interquartile ranges (IQRs) due to non-normal distribution. Differences in median TTD between groups were assessed using the Mann-Whitney U test (2 groups) and Kruskal-Wallis test (3 or more groups). To evaluate the impact of diagnostic delay on outcomes, we used Poisson regression for therapy counts (estimating incidence rate ratios [IRRs]) and Cox proportional hazards models for time-to-surgery (estimating hazard ratios [HRs]). Logistic and Poisson regression models for CD were adjusted for age at diagnosis, CD behavior (Montreal classification), and perianal disease. The CD Cox model was simplified to diagnostic delay and age due to convergence constraints (17 surgery events). UC models were adjusted for age at diagnosis. Kaplan-Meier survival curves were generated to visualize time-to-event distributions. Statistical significance was set at P<0.05 (two-tailed).
The time origin for survival analyses was the date of IBD diagnosis. Patients were followed from diagnosis until the first occurrence of IBD-related surgery, death, loss to follow-up, or the study end date (November 2025), whichever occurred first. Right-censoring was applied at the end of study or last known clinical contact for patients without events.
RESULTS
1. Diagnostic Intervals and Cohort Characteristics
Of a total of 491 patients in the disease registry, the final analysis included 243 patients who had complete diagnostic timeline data (Table 1). Patients with CD (n=148) had a median TTD of 4.0 months (IQR, 1.5–9.0 months). For patients with UC (n=95), median TTD was 3.0 months (IQR, 1.0–7.0 months).
Although the overall cohort median TTD was 4.0 months (IQR, 1.0–8.0 months) and the simple non-parametric comparison between subtypes did not reach statistical significance (P=0.111), the Kaplan-Meier survival analysis (Fig. 1) revealed distinct cumulative probability curves for diagnosis in CD versus UC. UC patients demonstrated a trend toward faster diagnostic resolution, with a steeper initial curve trajectory compared to CD, though this difference approached but did not reach statistical significance (log-rank test P=0.054). By 24 months, diagnosis had been achieved in virtually all patients (95% CD, 97% UC). This divergence suggests that while the median times are similar, the diagnostic trajectory differs.
The cohort was predominantly Emirati (81%), followed by non-Emirati Arabs (14%) and other nationalities (5%). Diagnostic efficiency was equitable across populations (P=0.426); median delays ranged from 3 months for Emiratis to 4 months for non-Emirati Arabs.
2. Temporal Trends and Predictors of Delay
Longitudinal analysis revealed significant improvement in efficiency for UC. In the era from 2016–2020, median TTD for UC was 5.5 months; this dropped to 2.0 months in the recent era from 2021–2025 (P=0.006). Diagnostic timelines for CD remained stable during these periods (5.0 months vs. 4.0 months; P=0.646). In multivariable logistic regression, neither age at diagnosis (OR, 0.99; 95% CI, 0.95–1.03; P=0.679) nor disease phenotype predicted prolonged delay (>12 months): penetrating behavior (OR, 1.45; 95% CI, 0.30–5.31; P=0.601), stricturing behavior (OR, 1.73; 95% CI, 0.55–5.06; P=0.324), and perianal disease (OR, 1.56; 95% CI, 0.51–4.35; P=0.407) were not associated with longer delays (Table 2). Sex and ethnicity were not retained in the final model.
3. Impact of Delay on Clinical Outcomes
During follow-up, 17 CD patients (11.5%) and 3 UC patients (3.2%) underwent IBD-related surgery. The Cox proportional hazards model for CD surgery included 17 events, providing limited statistical power to detect modest effect sizes. For UC, the 3 surgical events precluded meaningful multivariable modeling of surgery risk. A critical finding was the dissociation between diagnostic delay and adverse endpoints. In multivariable Poisson regression adjusted for disease duration and age, diagnostic delay was not associated with increased AT use for CD (IRR, 1.00; 95% CI, 0.99–1.01; P=0.986) or UC (IRR, 0.97; 95% CI, 0.93–1.01; P=0.155). Instead, phenotype drove burden: penetrating CD (B3) significantly increased therapy rates (IRR, 1.52; 95% CI, 1.06–2.13; P=0.019). Similarly, Cox modeling showed diagnostic delay did not predict IBD-related surgery risk (HR, 1.01; 95% CI, 0.97–1.05; P=0.586) (Table 2).
4. Therapeutic Efficiency and Equity
Access to advanced therapeutics was rapid. For CD patients requiring biologics (n=110), the median interval from diagnosis to first dose was 4.5 months. The primary driver for AT exposure in CD was disease phenotype, specifically penetrating (B3) disease (IRR, 1.52; 95% CI, 1.06–2.13; P=0.019). As shown in Fig. 2, time to initiation of AT illustrates this rapid escalation, with a steep initial curve indicating that a substantial proportion of patients initiate biologic therapy within the first 6 months of diagnosis. An equity signal was observed: Emirati nationals initiated biologics in a median of 6.1 months, while expatriates faced a median wait of 9.5 months (P=0.908). Paradoxically, patients with “Early Access” (<6 months) had higher surgery rates (P=0.008).
5. Impact of Diagnostic Setting
To evaluate if the site of initial presentation influenced diagnostic speed, we compared patients diagnosed at the tertiary center versus those diagnosed at primary or secondary care facilities. The majority of patients (n=141, 58%) were diagnosed in non-tertiary settings (88 CD, 53 UC), while 102 (42%) were diagnosed at the tertiary center (60 CD, 42 UC). The median TTD was identical between the 2 groups (4.0 months vs. 4.0 months; P=0.943), indicating that diagnostic efficiency is consistent across the healthcare ecosystem and not limited to tertiary centers. Patients diagnosed in non-tertiary settings had a higher proportion of complicated CD (B2/B3/perianal) at presentation (28% vs. 13%; P=0.054).
6. Selection Bias Analysis and Sensitivity Findings
A formal comparison of included (n=243) and excluded (n=248) patients revealed comparable age at diagnosis (median 25 years vs. 26 years; P=0.579) and sex distribution (42% vs. 40% female; P=0.643). Statistically significant differences were observed in disease subtype (CD 61% vs. 70%; P=0.039) and year of diagnosis (median 2022 vs. 2017; P<0.001), the latter reflecting improved capture of symptom onset dates in the prospective phase of the registry (Supplementary Table 1). The patient selection process is detailed in Supplementary Fig. 1. Sensitivity analyses demonstrated consistency across all approaches. The null association between diagnostic delay and AT burden persisted at 6-month (IRR, 0.82; 95% confidence interval [CI], 0.60–1.11; P=0.215), 12-month (IRR, 0.86; 95% CI, 0.58–1.22; P=0.361), and 18-month (IRR, 0.77; 95% CI, 0.42–1.29; P=0.361) thresholds. Restriction to patients with at least 12 months of follow-up (n=210) yielded consistent results (AT burden IRR, 1.00; 95% CI, 0.99–1.01; P=0.924; surgery HR, 1.01; 95% CI, 0.97–1.05; P=0.586). Era-adjusted models showed no change in the primary association (delay IRR, 1.00; P=0.716), with a trend toward higher AT burden in the 2021 to 2025 era (IRR, 1.36; 95% CI, 0.98–1.89; P=0.071), consistent with the expanded therapeutic armamentarium. Quartile-based analysis showed no significant trend in AT burden (Kruskal-Wallis P=0.245) or surgery rates (P=0.304) across increasing delay quartiles (Supplementary Tables 2-6).
DISCUSSION
Our study presents a comprehensive analysis of diagnostic timelines in a multi-ethnic IBD cohort within the UAE, reporting a median TTD of 4.0 months. This finding is significant for what it reveals about healthcare efficiency in a rapidly developing region. This finding is notable for being substantially shorter than both regional historical data and established Western benchmarks.
A notable finding is the significant disparity in time to AT initiation between CD (median 4.5 months) and UC (median 14.0 months). This gap likely reflects several factors: current treatment guidelines recommend earlier biologic initiation for CD, particularly in the presence of risk factors for aggressive disease such as perianal involvement, extensive small bowel disease, and young age at diagnosis. The higher proportion of penetrating and stricturing phenotypes in our CD cohort (39% B2/B3) further necessitates earlier escalation. In contrast, UC management often follows a more measured step-up approach, with 5-aminosalicylic acid therapy as first-line treatment and advanced therapies reserved for moderate-to-severe or refractory disease. However, emerging evidence increasingly supports earlier biologic initiation in UC, and this disparity may narrow in future cohorts as treatment paradigms continue to evolve. Conversely, the shorter TTD observed for UC (3.0 months vs. 4.0 months for CD) likely reflects, in part, the more alarming nature of UC symptoms such as rectal bleeding, which may prompt earlier investigation in a subset of patients.
The global landscape of IBD diagnosis is marked by significant disparity. A recent definitive meta-analysis of 101 studies established that high-income countries achieve median diagnostic delays of 6.2 months for CD and 3.2 months for UC [4]. In contrast, low-to-middle income countries lag significantly, with median delays of 11.7 months for CD and 7.8 months for UC. Our UAE cohort, with a median TTD of 4.0 months overall (4.0 for CD, 3.0 for UC), aligns firmly with the high-income Western benchmark, shorter than pooled global estimates. This performance is particularly notable when viewed against the regional backdrop. In Saudi Arabia, a mean TTD of 11 months for CD has been reported historically with only 40% of patients diagnosed within the first 3 months of symptom onset [18,19]. Similarly, diagnostic delays for pediatric IBD in the region remain substantial, with median delays of 8 months for CD [20]. Notably, recent data from other Asian healthcare settings demonstrate that comparably short diagnostic intervals are achievable under different system architectures. In a Korean multicenter cohort, Dang et al. [21] reported a median TTD of 3 months (IQR, 1–8 months) overall, with 2 months for UC and 3 months for CD, despite Korea’s national reimbursement-based referral system. Similarly, a large Chinese cohort demonstrated dramatic temporal improvements in diagnostic efficiency, with recent median TTDs falling to 1 month for UC and 3 months for CD [22]. These observations suggest that the efficiency observed in our UAE cohort may reflect a confluence of factors, including increasing disease awareness among clinicians, rising specialist density, and evolving healthcare infrastructure, rather than being attributable solely to the direct specialist-access model. While the UAE’s open-access architecture may be one contributing factor, it should be considered a hypothesis rather than a study-supported conclusion.
The dissociation between diagnostic setting and speed in our study is a critical finding. We observed identical median TTD (4.0 months) for patients diagnosed at our tertiary center and those diagnosed at primary or secondary facilities. This uniformity challenges the traditional “gatekeeper” approaches seen in nationalized systems like the UK’s National Health Service or many European models, where referral bottlenecks from primary to secondary care are a primary driver of delay in access to a specialist [23]. Recent patient experience studies demonstrate that patients perceive primary care “gatekeepers” as significant barriers to access, often due to a lack of specific IBD knowledge at the primary care level [24]. The UAE’s hybrid insurance-based model contrasts with this by facilitating a more porous and responsive diagnostic network. However, this “direct access” architecture is not without potential tradeoffs. While historical data from the US suggests that eliminating gatekeeping does not necessarily lead to an unmanageable surge in specialist utilization [25], recent systematic evidence warns that such pathways can exacerbate health inequalities [26]. Direct access mechanisms are “high-agency” interventions that disproportionately benefit younger, more educated, and affluent populations who possess the resources to navigate complex systems. This literature aligns with our observation of an equity signal regarding biologic access, suggesting that while the UAE’s open-access model accelerates diagnosis overall, it requires vigilance to ensure that less health-aware populations, are not left behind. Furthermore, the high prevalence of complicated CD phenotypes (B2/B3) at presentation in non-tertiary settings (28%) suggests that peripheral hospitals are effectively capturing acute presentations, rather than these complex cases solely filtering up to tertiary care after prolonged delays.
The observed disparity in biologic access between nationality groups warrants further attention. Emirati nationals benefit from Thiqa insurance with broad formulary access, while expatriate insurance plans may impose step-therapy requirements, prior authorization hurdles, or restrict access to newer biologics. Although the difference in time to first biologic between Emirati nationals (median 6.1 months) and expatriates (median 9.5 months) did not reach statistical significance in this cohort, the numerical trend and its potential clinical implications merit investigation in larger studies. Most strikingly, our data reveal a median TTD of just 4.0 months for CD and 3.0 months for UC, shorter than the pooled median diagnostic intervals of 6.2 months for CD and 3.2 months for UC reported in a recent systematic review of high-income countries, with patients accessing advanced therapies rapidly (median 4.5 months from diagnosis to biologic initiation), yet multivariable analyses show no association between diagnostic delay and adverse outcomes with penetrating disease phenotype at diagnosis independently driving therapeutic burden. This differs from findings in Western cohorts where delays >18 months strongly predict stricturing and surgery [27-30] and Asian cohorts, such as a Korean study where delay was an independent risk factor for surgery in both CD and UC [31]. We hypothesize that this lack of association exists because the “window of opportunity” is being successfully utilized [1]. Additionally, the efficiency of the local health system likely creates a floor effect; with only 12% of patients experiencing delays >12 months, the cohort lacks the “extreme delay” phenotype that typically drives surgical statistics in other regional studies. In our cohort, the median time from diagnosis to first AT was just 4.5 months for CD. This rapid time to initiation of first AT acts as a circuit breaker: even if a patient experiences a moderate diagnostic delay, the system’s ability to pivot almost immediately to high-efficacy therapy neutralizes the inflammatory burden before fibrosis becomes irreversible. This contrasts with health economies where administrative hurdles (e.g., step-therapy mandates or funding approvals) introduce a second “therapeutic delay” after diagnosis. Taken together, these observations suggest that the prolonged diagnostic lag observed in a subset of our cohort is idiosyncratic rather than systemic, likely reflecting individual patient factors such as atypical presentations or delayed healthcare-seeking behavior rather than structural barriers within the UAE healthcare system.
While our findings are encouraging, they must be interpreted within the specific context of the UAE’s demographics. Our cohort is predominantly Emirati (81%), a population that benefits from comprehensive insurance coverage. The signal of a disparity in biologic initiation times (9.5 months for expatriates vs. 6.1 months for Emiratis) warns that the efficiency of the “therapeutic mitigation” we observed may not be universally accessible across all insurance tiers. Future research must specifically dissect these socioeconomic variables to ensure that the rapid care pathways available to nationals are equitable for the diverse expatriate workforce that powers the region’s economy.
This study provides several distinct contributions to the IBD literature beyond a local health-system snapshot. First, it represents the first population-based TTD data from the Middle East within a prospective registry framework, addressing a significant geographic gap in the TTD literature. Second, the UAE’s direct specialist-access model provides a natural experiment for understanding how healthcare system architecture influences diagnostic efficiency, offering a comparator to the general practitioner-referral systems predominantly studied in Europe. Third, our cohort, where 67% of patients were diagnosed within 6 months, provides a complementary perspective on outcomes in settings with short diagnostic intervals, generating the hypothesis that the prognostic impact of delay may be most relevant above a minimum threshold. Fourth, the analysis of therapeutic access across nationality groups addresses the increasingly recognized importance of healthcare equity in IBD outcomes. Finally, the characterization of AT utilization patterns provides real-world evidence on treatment strategy effectiveness in a contemporary Middle Eastern cohort.
Our study has notable strengths and limitations. A primary strength is the characterization of diagnostic timelines in a rapidly modernizing, multi-ethnic Middle Eastern cohort, a demographic underrepresented in global IBD literature. The dissociation of outcomes from delay provides novel insight into the efficacy of early treatment escalation strategies in this setting. However, these findings must be viewed in light of specific limitations. The inherent design relies on patient recall for symptom onset, a measure prone to bias. Crucially, we applied rigorous inclusion criteria that reduced our starting cohort of 491 patients to a final analysis set of 243. These exclusions predominantly involved historical referrals diagnosed at external facilities prior to 2020 where symptom onset dates were often unrecorded, or patients with incidental “silent” disease. We acknowledge that excluding patients with incomplete data risks selection bias, as it may filter out those with vague, protracted symptom histories who struggle to recall a specific onset date, potentially skewing the cohort toward shorter TTDs. However, when the analysis is restricted to the post-2021 era, characterized by comprehensive internal documentation, the median TTD remains consistently similar. This consistency suggests that the rapid diagnostic intervals observed are a genuine reflection of the healthcare landscape rather than solely an artifact of data selection.
An important limitation is statistical power. With only 28 patients (11.5%) meeting the prolonged delay threshold and 20 surgical events during follow-up, the 95% CIs for the primary outcome (CD surgery HR, 1.01; 95% CI, 0.97–1.05) include clinically meaningful effect sizes in both directions. The absence of statistical significance should not be interpreted as evidence of absence, and the relatively short follow-up in a young cohort means complications may not yet have manifested. Larger, multicenter studies with longer follow-up are needed to confirm these findings. The exclusion of 248 patients (50.5%) due to missing symptom onset dates poses a risk of selection bias. Excluded patients were more likely diagnosed in earlier years (median 2017 vs. 2022) and included a higher proportion of CD (70% vs. 61%). Although included and excluded patients were comparable in age and sex, those with missing data may represent patients with less structured diagnostic pathways or more insidious symptom onset, potentially biasing the cohort toward shorter TTDs. The consistency of results in the era-restricted (2021–2025) analysis provides partial reassurance, though this remains a key limitation.
In this Middle Eastern cohort, IBD diagnostic timelines are shorter than regional historical data and comparable to recent Asian benchmarks. The lack of association between diagnostic delay and adverse outcomes may reflect multiple factors, including rapid therapeutic escalation and features of healthcare system architecture, though this hypothesis requires confirmation in larger multicenter studies with longer follow-up.
NOTES
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Funding Source
This work was supported by the UAE Department of Health Ma’an Research Grant (Grant title: UAE Epi-IBD–DOH/ADH RTC/2025/360) that was awarded to Quraishi MN. Jess T was supported by a National Center of Excellence Grant from the Danish National Research Foundation (DNRF148).
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Conflict of Interest
Quraishi MN has received speaker fees from Johnson and Johnson, Takeda, AbbVie, Hikma and Lilly and consultancy fees from Johnson and Johnson and Lilly. Jess T has received consultancy fees from Ferring and Pfizer. No other potential conflict of interest relevant to this article was reported.
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Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request. However, the data are not publicly available because they contain sensitive patient information that could compromise participant confidentiality and privacy.
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Author Contributions
Conceptualization: Swaid TK, Jess T, Quraishi MN. Data curation: Swaid TK, Hamzeh LR, Quraishi MN. Formal analysis: Bukasa LL. Investigation: Hamzeh LR, Jess T, Quraishi MN. Methodology: Quraishi MN, Jess T, Swaid TK. Supervision: Quraishi MN. Writing–original draft: Quraishi MN. Writing–review & editing: all authors. Approval of final manuscript: all authors.
Supplementary Material
Supplementary materials are available at the Intestinal Research website (https://www.irjournal.org).
Fig. 1.Time to diagnosis from symptom onset for Crohn’s disease and ulcerative colitis. Kaplan-Meier estimates showing the cumulative probability of receiving a definitive diagnosis over time (months) from the onset of symptoms. The blue line represents patients with Crohn’s disease, and the gold line represents patients with ulcerative colitis. Shaded regions indicate 95% confidence intervals. The difference between the 2 groups approached but did not reach statistical significance (log-rank test, P=0.054).
Fig. 2.Time to advanced therapy initiation among patients who started treatment. Kaplan-Meier estimates illustrating the cumulative probability of initiating a first advanced therapy (biologic or small molecule) following a definitive diagnosis. The blue line represents Crohn’s disease and the red line represents ulcerative colitis. Shaded regions indicate 95% confidence intervals. The difference in time to therapy initiation between the 2 subtypes was not statistically significant (log-rank test, P=0.103).
Table 1.Baseline Demographics, Diagnostic Timelines, and Therapeutic Burden
|
Characteristic |
Overall (n=243) |
Crohn’s disease (n=148) |
Ulcerative colitis (n=95) |
P-value |
|
Age at diagnosis (yr) |
25.0 (19.0–33.0) |
23.5 (18.0–33.0) |
27.0 (21.0–33.0) |
0.051a
|
|
Sex |
|
|
|
0.010b
|
|
Female |
103 (42) |
53 (36) |
50 (53) |
|
|
Male |
140 (58) |
95 (64) |
45 (47) |
|
|
Ethnicity |
|
|
|
0.142c
|
|
Emirati |
196 (81) |
122 (82) |
74 (78) |
|
|
Non-Emirati Arab |
35 (14) |
22 (15) |
13 (14) |
|
|
Other |
12 (5) |
4 (3) |
8 (8) |
|
|
Diagnostic setting |
|
|
|
0.665b
|
|
Non-tertiary facility |
141 (58) |
88 (59) |
53 (56) |
|
|
Tertiary facility |
102 (42) |
60 (41) |
42 (44) |
|
|
Time to diagnosis (mo) |
4.0 (1.0–8.0) |
4.0 (1.5–9.0) |
3.0 (1.0–7.0) |
0.111a
|
|
Prolonged delay (> 12 mo) |
28 (12) |
20 (14) |
8 (8) |
0.304c
|
|
Advanced therapy naive |
73 (30) |
37 (25) |
36 (38) |
0.032b
|
|
Advanced therapy lines (among users) |
|
|
|
0.067c
|
|
1 |
101 (59) |
61 (55) |
40 (68) |
|
|
2 |
38 (22) |
31 (28) |
7 (12) |
|
|
3 or more |
31 (19) |
19 (18) |
12 (20) |
|
|
Time to advanced therapy initiation (mo, among users) |
6.6 (2.0–31.2) |
4.5 (2.0–25.0) |
14.0 (2.3–40.0) |
0.034a
|
Table 2.Multivariable Regression Analyses of Diagnostic Delay, Advanced Therapy Burden, and Surgery Risk in IBD
|
Variable |
CD
|
UC
|
|
Estimate (95% CI) |
P-value |
Estimate (95% CI) |
P-value |
|
Predictors of prolonged diagnostic delay (> 12 mo)-logistic regression |
|
|
|
|
|
Age at diagnosis |
OR 0.99 (0.95–1.03) |
0.679 |
OR 1.04 (0.99–1.09) |
0.118 |
|
CD behavior |
|
|
|
|
|
Inflammatory |
Reference |
|
|
|
|
Penetrating |
OR 1.45 (0.30–5.31) |
0.601 |
|
|
|
Stricturing |
OR 1.73 (0.55–5.06) |
0.324 |
|
|
|
Perianal disease |
|
|
|
|
|
No |
Reference |
|
|
|
|
Yes |
OR 1.56 (0.51–4.35) |
0.407 |
|
|
|
Diagnostic delay and advanced therapy burden-Poisson regression (multivariable) |
|
|
|
|
|
Diagnostic delay (mo) |
IRR 1.00 (0.99–1.01) |
0.986 |
IRR 0.97 (0.93–1.01) |
0.155 |
|
Age at diagnosis |
IRR 1.00 (0.98–1.01) |
0.319 |
IRR 1.00 (0.97–1.01) |
0.588 |
|
CD behavior |
|
|
|
|
|
Inflammatory |
Reference |
|
|
|
|
Penetrating |
IRR 1.52 (1.06–2.13) |
0.019 |
|
|
|
Stricturing |
IRR 1.01 (0.70–1.42) |
0.962 |
|
|
|
Perianal disease |
|
|
|
|
|
No |
Reference |
|
|
|
|
Yes |
IRR 1.31 (0.95–1.80) |
0.096 |
|
|
|
Diagnostic delay and surgery risk-Cox regression (multivariable) |
|
|
|
|
|
Diagnostic delay (mo) |
HR 1.01 (0.97–1.05) |
0.586 |
HR 1.00 (0.84–1.19) |
0.998 |
|
Age at diagnosis |
HR 0.98 (0.93–1.02) |
0.339 |
HR 0.94 (0.81–1.10) |
0.448 |
REFERENCES
- 1. Colombel JF, Narula N, Peyrin-Biroulet L. Management strategies to improve outcomes of patients with inflammatory bowel diseases. Gastroenterology 2017;152:351–361.ArticlePubMed
- 2. Colombel JF, Reinisch W, Mantzaris GJ, et al. Randomised clinical trial: deep remission in biologic and immunomodulator naive patients with Crohn’s disease: a SONIC post hoc analysis. Aliment Pharmacol Ther 2015;41:734–746.ArticlePubMed
- 3. Noor NM, Lee JC, Bond S, et al. A biomarker-stratified comparison of top-down versus accelerated step-up treatment strategies for patients with newly diagnosed Crohn’s disease (PROFILE): a multicentre, open-label randomised controlled trial. Lancet Gastroenterol Hepatol 2024;9:415–427.PubMedPMC
- 4. Jayasooriya N, Baillie S, Blackwell J, et al. Systematic review with meta-analysis: time to diagnosis and the impact of delayed diagnosis on clinical outcomes in inflammatory bowel disease. Aliment Pharmacol Ther 2023;57:635–652.ArticlePubMedPDF
- 5. Ananthakrishnan AN, Kaplan GG, Ng SC. Changing global epidemiology of inflammatory bowel diseases: sustaining health care delivery into the 21st century. Clin Gastroenterol Hepatol 2020;18:1252–1260.ArticlePubMed
- 6. Agrawal M, Jess T. Implications of the changing epidemiology of inflammatory bowel disease in a changing world. United European Gastroenterol J 2022;10:1113–1120.ArticlePubMedPMCPDF
- 7. Hracs L, Windsor JW, Gorospe J, et al. Global evolution of inflammatory bowel disease across epidemiologic stages. Nature 2025;642:458–466.PubMedPMC
- 8. Kaplan GG, Windsor JW. The four epidemiological stages in the global evolution of inflammatory bowel disease. Nat Rev Gastroenterol Hepatol 2021;18:56–66.ArticlePubMedPDF
- 9. Mosli M, Alawadhi S, Hasan F, Abou Rached A, Sanai F, Danese S. Incidence, prevalence, and clinical epidemiology of inflammatory bowel disease in the Arab world: a systematic review and meta-analysis. Inflamm Intest Dis 2021;6:123–131.ArticlePubMedPMCPDF
- 10. Banerjee R, Pal P, Girish BG, Reddy DN. Risk factors for diagnostic delay in Crohn’s disease and their impact on long-term complications: how do they differ in a tuberculosis endemic region? Aliment Pharmacol Ther 2018;47:1367–1374.ArticlePubMedPDF
- 11. Banerjee R, Pal P, Mak JW, Ng SC. Challenges in the diagnosis and management of inflammatory bowel disease in resource-limited settings in Asia. Lancet Gastroenterol Hepatol 2020;5:1076–1088.ArticlePubMed
- 12. Ahmed HA, Alzaabi MN, Swaid TK, et al. Evolving clinical burden of inflammatory bowel disease in the United Arab Emirates: a two-decade analysis of diagnoses and disease severity. Frontline Gastroenterol 2025;Sep 16 [Epub]. https://doi.org/10.1136/flgastro-2025-103345.Article
- 13. Alzaabi MN, Swaid TK, Ahmed HA, et al. Real-world effectiveness of risankizumab in Crohn’s disease: outcome data for an IL-23 inhibitor from the Middle East. Crohns Colitis 360 2025;7–otaf062.
- 14. Paulo MS, Loney T, Lapão LV. The primary health care in the emirate of Abu Dhabi: are they aligned with the chronic care model elements? BMC Health Serv Res 2017;17:725.ArticlePubMedPMCPDF
- 15. Vavricka SR, Spigaglia SM, Rogler G, et al. Systematic evaluation of risk factors for diagnostic delay in inflammatory bowel disease. Inflamm Bowel Dis 2012;18:496–505.ArticlePubMed
- 16. Gower-Rousseau C, Vasseur F, Fumery M, et al. Epidemiology of inflammatory bowel diseases: new insights from a French population-based registry (EPIMAD). Dig Liver Dis 2013;45:89–94.ArticlePubMed
- 17. R Core Team. R: A language and environment for statistical computing [Internet]. c2026;[cited 2026 Jan 1]. https://cran.rproject.org/doc/manuals/r-release/fullrefman.pdf.
- 18. Aljebreen AM, Alharbi OR, Azzam NA, Almalki AS, Alswat KA, Almadi MA. Clinical epidemiology and phenotypic characteristics of Crohn’s disease in the central region of Saudi Arabia. Saudi J Gastroenterol 2014;20:162–169.ArticlePubMedPMC
- 19. Qari YA. Clinical characteristics of Crohn’s disease in a cohort from Saudi Arabia. Saudi J Med Med Sci 2022;10:56–62.ArticlePubMedPMC
- 20. El Mouzan MI, AlSaleem BI, Hasosah MY, et al. Diagnostic delay of pediatric inflammatory bowel disease in Saudi Arabia. Saudi J Gastroenterol 2019;25:257–261.ArticlePubMedPMC
- 21. Dang LM, Soo Kim E, Kim KO, et al. Comparison of 1-year clinical course in patients with newly diagnosed inflammatory bowel disease between Vietnam and Korea: a multinational, multicenter retrospective cohort study. JGH Open 2025;9:e70106.ArticlePubMedPMC
- 22. Zhou R, Sun X, Guo M, et al. A shortened diagnostic interval and its associated clinical factors and related outcomes in inflammatory bowel disease patients from a cohort study in China. J Inflamm Res 2024;17:387–398.ArticlePubMedPMCPDF
- 23. Sripa P, Hayhoe B, Garg P, Majeed A, Greenfield G. Impact of GP gatekeeping on quality of care, and health outcomes, use, and expenditure: a systematic review. Br J Gen Pract 2019;69:e294–e303.ArticlePubMedPMC
- 24. Lalani S, Mathias H, Heisler C, et al. Improving access to inflammatory bowel disease care in Canada: the patient experience. J Health Serv Res Policy 2025;30:12–20.ArticlePubMedPDF
- 25. Ferris TG, Chang Y, Blumenthal D, Pearson SD. Leaving gatekeeping behind: effects of opening access to specialists for adults in a health maintenance organization. N Engl J Med 2001;345:1312–1317.ArticlePubMed
- 26. Harvey-Sullivan A, Lynch H, Tolley A, Gitlin-Leigh G, Kuhn I, Ford JA. What impact do self-referral and direct access pathways for patients have on health inequalities? Health Policy 2024;139:104951.ArticlePubMed
- 27. Nahon S, Lahmek P, Paupard T, et al. Diagnostic delay is associated with a greater risk of early surgery in a French cohort of Crohn’s disease patients. Dig Dis Sci 2016;61:3278–3284.ArticlePubMedPDF
- 28. Schoepfer A, Santos J, Fournier N, et al. Systematic analysis of the impact of diagnostic delay on bowel damage in paediatric versus adult onset Crohn’s disease. J Crohns Colitis 2019;13:1334–1342.ArticlePubMedPDF
- 29. Cross E, Saunders B, Farmer AD, Prior JA. Diagnostic delay in adult inflammatory bowel disease: a systematic review. Indian J Gastroenterol 2023;42:40–52.ArticlePubMedPMCPDF
- 30. Attauabi M, Madsen GR, Bendtsen F, Seidelin JB, Burisch J. Incidence, disease burden, and clinical presentation of patients newly diagnosed with inflammatory bowel disease in a population-based inception cohort. J Crohns Colitis 2025;19–jjae176.ArticlePDF
- 31. Lee DW, Koo JS, Choe JW, et al. Diagnostic delay in inflammatory bowel disease increases the risk of intestinal surgery. World J Gastroenterol 2017;23:6474–6481.ArticlePubMedPMC
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