The role of fecal matrix metalloprotease-9 as a non-invasive marker in diagnosis and assessment of clinical activity in inflammatory bowel disease patients
Bibliographic record
Abstract
Abstract Background Inflammatory bowel disease is characterized by chronic and relapsing inflammation of the gastrointestinal tract, including two prominent forms: Crohn’s disease and ulcerative colitis. Determining diagnostic biomarkers for predicting disease activity and treatment response remains a challenging aspect. Aim of the work The purpose of our research was to compare fecal CP and fecal MMP-9, two non-invasive biomarkers for inflammatory bowel disease (IBD), and to find out how fecal MMP-9 levels relate to disease activity by looking at how they relate to clinical, endoscopic, and histologic scores of disease activity. Patients and methods This study was performed on 80 subjects divided into 3 groups: group A: 30 patients with Crohn’s disease evidenced by endoscopy ileocolonoscopy, upper GI endoscopy, and tissue biopsy (15 patients with active disease and 15 patients in remission). Group B: 30 patients with ulcerative colitis disease evidenced by colonoscopy and tissue biopsy (15 patients with active disease and 15 patients in remission). Group C: 20 age-matched and sex-matched healthy controls. All participants underwent a thorough history review, comprehensive physical examination, complete laboratory tests, and C-reactive protein measurements. A quantitative enzyme-linked immunosorbent assay was used to determine the levels of fecal matrix metalloproteinase MMP 9 for both the patients and the controls. Ulcerative colitis was evaluated using the Mayo score, Montreal classification, and the Riley histological score. Additionally, Crohn’s disease was assessed with the Crohn’s Disease Activity Index, the Simple Endoscopic Score for Crohn’s Disease, and the D’Haens histological score. Results Comparing fecal MMP-9 with fecal calprotectin (FC), we found that fecal MMP-9 was superior to FC in differentiating active Crohn’s disease from inactive Crohn’s disease, although there was no significant difference between FC and MMP-9 (P-value = 0.561). However, in ulcerative colitis, FC was superior to MMP-9 in distinguishing active UC from inactive UC, but again, there was no significant difference between FC and MMP-9 (P-value = 0.0731).In both the ulcerative colitis and Crohn’s disease groups, fecal MMP-9 could discriminate between patients in remission and those with active disease. Fecal matrix metalloproteinase-9 (MMP-9) was discovered to be a significant marker for assessing the clinical activity of both Crohn’s disease (CD) and ulcerative colitis (UC), with an AUC of 0.998 for CD and 0.991 for UC. Fecal MMP-9 demonstrated great sensitivity (93.33%), specificity (100%), positive predictive value (PPV) of 100%, and negative predictive value (NPV) of 93.7% (with a P-value < 0.001) using cutoff values of > 0.34 ng/mL for CD and > 0.36 ng/mL for UC. There was a strong positive correlation between fecal MMP-9 and endoscopic and clinical scores of disease activity. Conclusion Fecal MMP-9 has emerged as a promising biomarker for evaluating the clinical activity of both Crohn’s disease and ulcerative colitis. It demonstrated superior diagnostic performance compared to fecal calprotectin in distinguishing active from inactive disease, especially in Crohn’s disease. Although fecal calprotectin outperformed MMP-9 in identifying active ulcerative colitis, the differences between the two markers were not statistically significant, suggesting that they may complement each other in clinical practice. Furthermore, fecal MMP-9 is capable of assessing the activity of endoscopically visible inflammatory bowel disease (IBD), which could help reduce the need for invasive endoscopic procedures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".