Determinants of corticosteroid-resistance in severe pediatric ulcerative colitis
Bibliographic record
Abstract
One third of children admitted for acute severe ulcerative colitis (UC), are refractory to intravenous corticosteroids and require second line therapy or colectomy. Potential factors determining response vs. refractoriness have seldom been explored. In an attempt to elucidate the basis for corticosteroid-resistance in UC, we evaluated whether corticosteroid-bioactivity and/or specific inflammatory cytokines influence response to corticosteroids in severe pediatric UC, independent of disease severity. In a prospective multi-center study, serum samples were obtained on the third day of steroid treatment from 79 children hospitalized with severe UC. Twenty three (29%) required second line therapy (mean age 13.9±3; 56% males; median disease duration 8.2 months (IQR 3-29)). Clinical, demographic and outcome data were prospectively recorded at several times during the admission on standardized case report forms. A cytokine antibody array panel (version 3.0; TransSignal, Panomics, Fremont, CA) was constructed to include 12 cytokines, se-lected based on a systematic literature search: TNF-α INF-γ IL-1β IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12, IL-13, and IL-17. Factor analysis and logistic regression models were used to explore the relationship between the various cytokines and corticosteroid response. Biologic activity of corticosteroids was assessed using a previously established transactivation glucocorticoid bioassay (GBA) on COS-1 tranfected cells. GBA can measure the biological activity of corticosteroids by quantifying glucocorticoid response elements, reflecting the down-stream effect of the steroids. This approach eliminates differences between the various steroids regarding their ability to activate the glucocorticoid receptor. In univariate analyses, only IL-6 differed between responders and nonresponders (P= 0.003; Bonferroni corrected). The risk for steroid-refractoriness increased by 40% per each incremental unit of IL-6. In factor analysis, IL-6 loaded with IL-17 on the same component, reflecting the association of IL-6 with the Th17 pathway. However, in a multiple regression analysis IL-6 was no longer significant when adjusting for disease severity, measured by the PUCAI index (P= 0.32, PUCAI score P<0.001). In accordance, IL-6 was highly correlated with C-reactive protein (r= 0.41, P<0.001) and albumin (r= -0.64, P<0.001). Reflecting internal validity of the assay, GBA was highly correlated with the last corticosteroid dose and the time interval to bloodletting (r= -0.41 and r= -0.54, respectively; both P<0.001). There was no statistically significant difference in the GBA levels between responders and non-responders (249nM · versus 200nM · cortisol equivalent, P= 0.18). In a multivariate regression model adjusted for time elapsed from corticosteroids and the administered dose, GBA did not predict response or refractoriness to corticosteroids (P= 0.34). Disease severity is associated with response to steroid therapy, while steroid bioavailability, steroid dosing, and the type of inflammation are not. IL-6 is a strong predicting variable for refractoriness, but it merely reflects disease severity. Nonetheless, IL-6 levels may have a role in predicting response to steroids in pediatric UC, thereby influencing treatment decision making.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".