Slowing the progression of ankylosing spondylitis during long-term therapy with netakimab: results of the international multicenter randomized double-blind phase III clinical trial BCD-085-5/ASTERA
Bibliographic record
Abstract
Objective. To evaluate the effect of long-term therapy with netakimab (NTK) on radiographic progression and reduction of inflammatory changes assessed by magnetic resonance imaging (MRI) in patients with ankylosing spondylitis (AS), and to identify factors influencing treatment response.Material and methods. A post hoc analysis was performed on 228 patients with active AS who received NTK for 156 weeks in the randomized clinical trial BCD-085-5/ASTERA. The proportion of patients without radiographic progression was determined, defined as an increase in the mSASSS (modified Stoke Ankylosing Spondylitis Spinal Score) of <2 points from baseline to week 156. Additionally, the proportion of patients without any increase in mSASSS by week 156 was calculated. The proportions of patients without increases in the ASspi-MRI-a (Ankylosing Spondylitis spine MRI activity index) and SPARCC (Spondyloarthritis Research Consortium of Canada index), as well as with positive dynamics of these indices (reaching 0 or a ≥50% reduction from baseline at weeks 52, 104 and 156), were also assessed. The influence of baseline clinical and demographic factors on achieving a response by mSASSS, ASspi-MRI-a, and SPARCC was analyzed using univariate and multivariate logistic regression models.Results and discussion. Among 228 patients, 66% showed no radiographic progression and 63% had no increase in mSASSS at week 156 compared with baseline. Positive dynamics in ASspi-MRI-a and SPARCC indices were demonstrated during two years of NTK therapy, with sustained effect through week 156. In univariate logistic regression, younger age (p=0.013) and absence of syndesmophytes or spinal ankylosis at baseline (p<0.01) were associated with lower rates of radiographic progression by mSASSS. Multivariate analysis did not reveal significant influence of baseline clinical-demographic or disease-history factors on NTK treatment response.Conclusion. Long-term therapy with NTK prevents radiographic progression and reduces active inflammatory changes by MRI in the majority of AS patients, regardless of baseline clinical and demographic characteristics or prior tumor necrosis factor α inhibitor therapy.
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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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".