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Early Identification of Pediatric Inflammatory Bowel Disease Based on a Noninvasive Multivariable Predictive Model
Hailin Wu1, Yinghua Sun2, Zifei Tang1
1Department of Gastroenterology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, People's Republic of China.
Insights
This study developed a noninvasive model to aid early pediatric inflammatory bowel disease (IBD) diagnosis. The model uses symptoms, lab tests, and ultrasound to improve diagnostic accuracy and reduce delays in identifying IBD in children.
Area of Science:
- Pediatric Gastroenterology
- Diagnostic Imaging
- Biomarkers
Background:
- Diagnostic delays in pediatric inflammatory bowel disease (IBD) negatively impact long-term outcomes.
- Noninvasive evaluation methods are crucial for early IBD detection in children.
- Current diagnostic approaches often involve delays, necessitating improved early identification strategies.
Purpose of the Study:
- To establish and validate an optimal model for noninvasive evaluation tests for early pediatric IBD identification.
- To develop a predictive model utilizing clinical symptoms, laboratory tests, and ultrasound findings.
- To reduce diagnostic delays and improve outcomes for children with IBD.
Main Methods:
- Retrospective development and prospective temporal validation design.
- Logistic regression model developed using data from 314 pediatric patients (103 IBD, 211 non-IBD).
- Incorporated IBD symptoms, routine labs, and transabdominal ultrasound (Limberg score >1, mesenteric fat, wall layering, lymph nodes).
- Validated in a prospective cohort of 66 children (19 IBD, 47 non-IBD).
Main Results:
- The ultrasound feature Limberg level >1 was the most valuable predictor.
- Key features included erythrocyte sedimentation rate, fecal calprotectin, C-reactive protein, hypoalbuminemia, and perianal abscess/fistula.
- The model achieved high accuracy: AUC 0.97 (internal) and 0.94 (external validation).
- Demonstrated good calibration in external validation (slope 0.86, Brier score 0.08).
Conclusions:
- A nomogram based on noninvasive factors can effectively identify children with IBD in early stages.
- Accessible noninvasive testing can facilitate early diagnosis of pediatric IBD.
- The validated model offers a promising tool for clinicians to improve pediatric IBD detection.
Background:
Early identification of pediatric inflammatory bowel disease (IBD) improves long-term outcomes; yet, significant diagnostic delays persist. This study aimed to establish and validate the optimal model of noninvasive evaluation tests to help clinicians with the early identification of pediatric IBD.
Methods:
The study adopted a retrospective development and prospective temporal validation design within the same clinical center. A cohort of 314 pediatric patients (IBD, 103; non-IBD, 211) was used to develop a logistic regression model. The model based on noninvasive features, including IBD-related symptoms, routine laboratory tests, and transabdominal ultrasound findings. Ultrasound parameters included Limberg score >1 (bowel wall thickening with blood flow), increased mesenteric fat, disrupted wall layering, and enlarged lymph nodes. The ultrasound operator was blinded to laboratory and endoscopic results. Feature selection was performed using logistic regression and random forest methods. Model performance was assessed via bootstrapped internal validation (1000 resamples), and temporally validated in a prospective cohort of 66 children (IBD, 19; non-IBD, 47).
Results:
In the importance assessment, the ultrasound feature of Limberg level >1 was identified as the most valuable feature, followed by the erythrocyte sedimentation rate, fecal calprotectin, C-reactive protein and hypoalbuminemia. The most valuable clinical symptom identified was active perianal abscess or fistula. The model, constructed from these features, demonstrated high accuracy and robustness in both internal validation (area under the curve, 0.97 [95% confidence interval: 0.95-0.98]) and temporal external validation (area under the curve, 0.94 [95% confidence interval: 0.86-1.00]). In the external validation set, the model showed good calibration, with a calibration slope of 0.86, and a Brier score of 0.08.
Conclusion:
The nomogram, based on noninvasive factors, can identify children with IBD at early stages using accessible noninvasive testing.
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