Early Changes in Serum Albumin Predict Clinical and Endoscopic Outcomes in Patients With Ulcerative Colitis Starting Anti-TNF Treatment
Bibliographic record
Abstract
BACKGROUND: Up to 60% of patients with ulcerative colitis (UC) ultimately fail anti-tumor necrosis factor (TNF) treatment. We aimed to investigate early predictive markers of clinical and endoscopic outcomes in patients with UC who were anti-TNF-naïve commencing anti-TNF treatment, with particular focus on changes in albumin and C-reactive protein levels in the first 2 weeks of treatment. METHODS: We retrospectively investigated 210 patients with UC who started infliximab or adalimumab between 2009 and 2016 (male, 62.4%; median age at diagnosis, 37.9 years [interquartile range, 25.5-48.9 years]; median follow-up duration, 3.3 years [1.9-5.0 years]). Logistic and Cox proportional-hazards regressions were performed to identify variables associated with primary nonresponse (PNR), endoscopic outcomes, time-to-colectomy, and anti-TNF failure. RESULTS: Forty-one patients (19.5%) experienced PNR; week 0/week 2 ratio serum albumin was associated with PNR (adjusted odds ratio [aOR], 1.8; 95% confidence interval [CI], 1.1-2.9, per interquartile range increase). Week 0/week 2 ratio albumin was also associated with endoscopic response (aOR, 0.28; 95% CI, 0.31-0.82) and endoscopic remission (aOR, 0.61; 95% CI, 0.39-0.96) at weeks 8 to 14, time-to-colectomy (adjusted hazard ratio, 2.12; 95% CI, 1.29-3.49) and time-to-anti-TNF failure (adjusted hazard ratio, 1.54; 95% CI, 1.22-1.96), regardless of age, disease severity, or in-patient status. Association with time-to-colectomy and anti-TNF failure was externally validated in an independent cohort of inpatients with UC starting infliximab. CONCLUSIONS: Change in serum albumin within the first 2 weeks of anti-TNF treatment is predictive of PNR, endoscopic outcomes, time-to-colectomy, and anti-TNF failure in patients with UC. Timely access to this biomarker enables early identification of patients with UC at risk of anti-TNF failure and may guide early optimization of anti-TNF treatment to improve disease outcomes.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".