Multidimensional Prognostic Risk Assessment Identifies Association Between IL12B Variation and Surgery in Crohn’s Disease
Bibliographic record
Abstract
BACKGROUND: The ability to identify patients with Crohn's disease (CD) at highest risk of surgery would be invaluable in guiding therapy. Genome-wide association studies have identified multiple IBD loci with unknown phenotypic consequences. The aims of this study were to: (1) identify associations between known and novel CD loci with early resective CD surgery and (2) develop the best predictive model for time to surgery using a combination of phenotypic, serologic, and genetic variables. METHODS: Genotyping was performed on 1,115 subjects using Illumina-based genome-wide technology. Univariate and multivariate analyses tested genetic associations with need for surgery within 5 years. Analyses were performed by testing known CD loci (n = 71) and by performing a genome-wide association study. Time to surgery was analyzed using Cox regression modeling. Clinical and serologic variables were included along with genotype to build predictive models for time to surgery. RESULTS: Surgery occurred within 5 years in 239 subjects at a median time of 12 months. Three CD susceptibility loci were independently associated with surgery within 5 years (IL12B, IL23R, and C11orf30). Genome-wide association identified novel putative loci associated with early surgery: 7q21 (CACNA2D1) and 9q34 (RXRA, COL5A1). The most predictive models of time to surgery included genetic and clinical risk factors. More than a 20% difference in frequency of progression to surgery was seen between the lowest and highest risk groups. CONCLUSIONS: Progression to surgery is faster in patients with CD with both genetic and clinical risk factors. IL12B is independently associated with need and time to early surgery in CD patients and justifies the investigation of novel and existing therapies that affect this pathway.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".