Risk of diverticulitis and gastrointestinal perforation in rheumatoid arthritis treated with tocilizumab compared to rituximab or abatacept
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To compare the risk of diverticulitis and gastrointestinal perforation (GIP) in RA treated with tocilizumab (TCZ) compared with rituximab (RTX) and abatacept (ABA). METHODS: We conducted a population-based study using three observational French registries on TCZ, RTX and ABA in RA. Using a propensity score approach, we compared the risk of diverticulitis or GIP in these patients. RESULTS: With inverse probability weighting, there was an increased risk of diverticulitis in TCZ-treated patients compared with RTX- or ABA-treated patients [hazard ratio (HR)=3.1 (95% CI: 1.5, 6.3), P =0.002]. Moreover, patients treated with TCZ had also an increased risk of GIP due to diverticulitis compared with those treated with RTX or ABA [HR=3.8 (1.1-13.6), P =0.04], resulting in an overall increased risk of GIP [HR=2.9 (1.1-7.8), P =0.03], while no significant increased risk of GIP due to any other aetiology was found in TCZ treated patients. Diverticulitis and GIP occurred earlier with TCZ than other drugs after the last perfusion (P =0.01), with atypical clinical presentation (slow transit in 30%, P =0.04) and lower acute-phase reactants at the time of the event (P =0.005). CONCLUSION: TCZ for RA was associated with increased odds of diverticulitis as well as GIP due to diverticulitis as compared with RTX and ABA. Our study confirms the increased odds of GIP in patients receiving TCZ, which might be explained by an increased risk of diverticulitis with misleading clinical presentation.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it