Serum PRO-C3 and C3M with CTE: Biomarkers for phenotyping and predicting progression in Crohn's disease
Bibliographic record
Abstract
Objective : This research evaluated serum type III collagen formation (PRO-C3), degradation (C3M) biomarkers, and computed tomography enterography (CTE) scores for classifying Crohn's disease (CD) behavior, predicting primary nonresponse to infliximab, and assessing disease progression. A total of 112 CD patients admitted to Jinling Hospital from January 2021 to October 2023 were classified by Montreal behavior as B1 (n = 44), B2 (n = 46), and B3 (n = 22). Serum PRO-C3, C3M levels, and CTE scores were analyzed. Patients were followed until October 2024. Changes in serum biomarkers were monitored during infliximab therapy and in patients undergoing surgery. Significant differences in serum C3M, PRO-C3, and CTE scores were observed across the three Montreal behavior groups. The combination of PRO-C3 and CTE differentiated B1 from B2 disease (AUC = 0.76, 95 % CI: 0.66–0.86). C3M and CTE effectively distinguished B1 from B3 disease (combined AUC = 0.86, 95 % CI: 0.77–0.95), while C3M alone differentiated B2 from B3 disease (AUC = 0.80, 95 % CI: 0.69–0.91). At week 6 of infliximab treatment, C3M levels were elevated in non-responders ( P = 0.001). PRO-C3 levels, disease behavior, and smoking history were emerged as distinct predictive indicators for early surgical intervention. Serum C3M, PRO-C3, and CTE scores demonstrated strong performance in distinguishing CD behavior phenotypes. Elevated C3M levels at week 6 may predict infliximab nonresponse, while PRO-C3, disease behavior, and smoking history are correlated with an elevated risk of early surgery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".