Predictors of Clinical Remission under Anti-tumor Necrosis Factor Treatment in Patients with Ankylosing Spondylitis: Pooled Analysis from Large Randomized Clinical Trials
Bibliographic record
Abstract
OBJECTIVE: Investigate the role and relation of disease duration of different factors for achieving clinical remission with anti-tumor necrosis factor (TNF) treatment in patients with active ankylosing spondylitis (AS). METHODS: Data pooled from 4 large (n = 1281) clinical trials were used to compare disease duration subgroups for placebo or sulfasalazine (SSZ) versus etanercept (ETN), which, in turn, were analyzed by age of diagnosis ≤ 40 versus > 40 years, HLA-B27 status, and baseline C-reactive protein (CRP) ≤ upper limit of normal (ULN) versus > ULN using chi-square tests, and ANCOVA. The primary efficacy measure was Assessments of SpondyloArthritis international Society (ASAS) partial remission (PR) after 12 weeks of treatment. Also analyzed were Bath AS Disease Activity Index and Functional Index, AS Disease Activity Scores, and ASAS response rates. RESULTS: Overall, a larger percentage of patients achieved ASAS-PR with ETN versus SSZ or placebo. More patients with ≤ 2-year disease duration treated with ETN experienced partial remission (34%) versus longer disease duration (30%, 27%, and 22% for > 2-5, > 5-10, and > 10 yrs, respectively; all p < 0.05). In the subgroup of patients with both disease duration ≤ 2 years and aged ≤ 40 years at diagnosis, the treatment response was even more pronounced. Similar results were seen in HLA-B27-positive patients in the disease duration ≤ 2-year subgroup. Overall, patients with high CRP at baseline had better treatment responses compared with patients with normal CRP. CONCLUSION: Treatment response under anti-TNF treatment with ETN at 12 weeks was greatest among patients with disease duration ≤ 2 years and even more pronounced in subgroups of patients ≤ 40 years old or HLA-B27-positive at diagnosis.
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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 | 0.035 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.019 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".