Benefit-risk assessment of the TNF-antagonists adalimumab and certolizumab pegol for maintenance treatment of Crohnʼs disease
Bibliographic record
Abstract
Tumor necrosis antagonist (TNF) treatment of Crohn's disease (CD) is associated with both beneficial and adverse effects. “Net Efficacy Adjusted for Risk” (NEAR) estimate calculations have been proposed as a method for expressing the overall risk-benefit balance of a therapeutic intervention.1 The NEAR odds ratio (OR) expresses the likelihood of a patient to achieve adverse event (AE)-free treatment success with a therapeutic intervention versus a control, based on calculations of expected frequencies of that outcome for each intervention. The aim of this analysis was to calculate NEAR odds ratios (ORs) for adalimumab and certolizumab pegol maintenance treatment of CD compared with corresponding placebos. Data from maintenance trials enrolling patients with moderate to severe CD were evaluated from placebo-controlled studies of adalimumab (CHARM) and certolizumab pegol (PRECiSE-2). Patients evaluated were those who met study protocol definitions for clinical response after induction therapy. Efficacy and safety data from randomization through 26 weeks were evaluated for patients receiving adalimumab 40 mg every other week and corresponding placebo (CHARM trial database), and certolizumab pegol 400 mg every 4 weeks and corresponding placebo (PRECiSE-2 manuscript2). ORs for efficacy were calculated based on proportions of patients with clinical remission (CDAI < 150) at 26 weeks for each active drug compared with placebo. NEAR ORs were calculated for each agent based on safety ORs determined for the following AEs occurring during double-blind maintenance treatment: serious adverse events (SAEs), AEs leading to study withdrawal, and serious infections. Efficacy ORs >1 favor the active drug over placebo for achieving efficacy; safety ORs >1 indicate lower risk with the active drug compared with placebo for the AE analyzed. NEAR ORs >1 favor the active drug over placebo for AE-free treatment success. The NEAR ORs indicate a higher likelihood of achieving AE-free clinical remission (for each AE analyzed) with each agent compared with corresponding placebo (Table). These analyses demonstrate that anti-TNF therapy has a favorable risk-benefit profile for the maintenance treatment of moderate to severe CD in the two clinical trials studied. Further studies are needed to determine whether a similar risk-benefit balance is observed in long-term treatment with anti-TNF therapy in a general population of patients with moderate to severe CD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.039 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".