<i>HLA-DQA1*05</i> Allele Carriage and Anti-TNF Therapy Persistence in Inflammatory Bowel Disease
Bibliographic record
Abstract
INTRODUCTION: Carriage of the HLA-DQA1*05 allele is associated with development of antidrug antibodies (ADAs) to antitumor necrosis factor (anti-TNF) therapy in patients with Crohn's disease. However, ADA is not uniformly associated with treatment failure. We aimed to determine the impact of carriage of HLA-DQA1*05 allele on outcome of biologic therapy evaluated by drug persistence. METHODS: A multicenter, retrospective study of 877 patients with inflammatory bowel disease (IBD) treated with anti-TNF therapy with HLA-DQA1*05 genotypes were generated by imputation from whole genome sequence using the HIBAG package, in R. Primary end point was anti-TNF therapy persistence, (time to therapy failure), segregated by HLA-DQA1*05 allele genotype and development of a risk score to predict anti-TNF therapy failure, incorporating HLA-DQA1*05 allele genotype status (LORisk score). RESULTS: In all, 877 patients receiving anti-TNF therapy were included in our study; 543 (62%) had no copy, 281 (32%) one copy, and 53 (6%) 2 copies of HLA-DQA1*05 allele. Mean time to anti-TNF therapy failure in patients with 2 copies of HLA-DQA1*05 allele was significantly shorter compared with patients with 0 or 1 copy at 700 days' follow-up: 418 vs 541 vs 513 days, respectively (P = .012). Factors independently associated with time to anti-TNF therapy failure included carriage of HLA-DQA1*05 allele (hazard ratio [HR], 1.2, P = .02; female gender HR, 1.6, P < .001; UC phenotype HR, 1.4, P = .009; and anti-TNF therapy type [infliximab], HR, 1.5, P = .002). The LORisk score was significantly associated with shorter time to anti-TNF therapy failure (P < .001). CONCLUSIONS: Carriage of 2 HLA-DQA1*05 alleles is associated with less favorable outcomes for patients receiving anti-TNF therapy with shorter time to therapy failure. HLA-DQA1*05 genotype status in conjunction with clinical factors may aid in therapy selection in patients with IBD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".