Predictors of Non-response or Loss of Response to Tumour Necrosis Factor Antagonist Therapies in Inflammatory Bowel Disease
Bibliographic record
Abstract
Introduction: Tumour necrosis factor antagonists (anti-TNFs) are effective at inducing and maintaining disease remission in patients with moderate to severe ulcerative colitis (UC) or Crohn's disease (CD). However, considerable proportions of patients do not respond to therapy or lose response over time. This study uses real-world data to identify predictors of non- or loss of response to anti-TNF therapy. Methods: The study included UC and CD patients from 6 countries (Canada, France, Germany, Italy, Spain, and the United Kingdom (UK)) aged ≥18 years who initiated anti-TNFs (infliximab/adalimumab) from June 2009 to June 2013 (UC) or June 2009 to June 2011 (CD). Data were collected on patient demographics, clinical characteristics and healthcare resource use. Patients were classified as having non- or loss of response if they: were hospitalized or required UC/CD surgery whilst on therapy, discontinued anti-TNF due to UC or CD flare, required anti-TNF dose-escalation or augmentation with steroids/immunosuppressants 4 months after anti-TNF initiation, or disease severity became worse after therapy initiation. Multilevel multivariate logistic regression was used to identify predictors of non- or loss of response. Results: The study included 1195 patients (45% UC, 55% CD; 9.6% Canada, 13% France, 22% Germany, 23% Italy, 19% Spain and 14% UK). Mean age: 40.3(SD=13.7); 51%: male. Most patients had a Charlson comorbidity index (CCI) score of 0-1 (83%), 16% were current smokers, mean BMI was 24.8 (SD=7.18) and mean disease duration was 8 years (SD=8.07). Most patients had a physician global assessment of moderate disease (45%) at baseline. Mean follow-up was 3.4 (UC) and 4.4 years (CD), respectively. Overall, 22% of patients had a primary non-response and 71% were classified as having non- or loss of response to anti-TNF therapy in the maintenance period (4 months after initiating anti-TNF) over a mean follow-up period of 32 months. Significant predictors of non-/loss of response are shown in Table 1.Table 1: Predictors of non-response or loss of response among patients with ulcerative colitis and Crohn's diseaseConclusion: In this cohort the majority of patients did not respond or lost response to anti-TNF therapy over time. Predictors for patients with UC included the absence of rectal bleeding and moderate/severe endoscopic scores, and for patients with CD included higher CRP and higher number of liquid or soft stools per day. These predictors should be considered when evaluating treatment options for patients.
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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 | 0.002 | 0.005 |
| 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".