SAFETY PROFILE OF ANTI-TNF THERAPY IN CROHN’S DISEASE MANAGEMENT: A BRAZILIAN SINGLE-CENTER DIRECT RETROSPECTIVE COMPARISON BETWEEN INFLIXIMAB AND ADALIMUMAB
Bibliographic record
Abstract
BACKGROUND: Infliximab and adalimumab are considered effective drugs in the management of Crohn's disease. However, due to significant immunossupression, they can cause important adverse events, mostly infections. OBJECTIVE: The aim of this study was to quantify and describe adverse events derived from adalimumab and infliximab use in Crohn's disease patients, and to compare the safety profile between these two agents. METHODS: This was an observational, single-center, longitudinal, retrospective study with Crohn's disease patients under infliximab or adalimumab therapy. Variables analyzed: demographic characteristics (including the Montreal classification), type of agent used, concomitant immunomodulators, presence and types of adverse events observed. Patients were allocated in two groups (infliximab and adalimumab) and had their adverse events accessed and subsequently compared. RESULTS: A total of 130 patients were included (68 in infliximab and 62 in adalimumab groups, respectively). The groups were fully homogeneous in all baseline characteristics, with a median follow-up of 47.21±36.52 months in the infliximab group and 47.79±35.09 in the adalimumab group (P=0.512). Adverse events were found in 43/68 (63.2%) and 40/62 (64.5%) in each group, respectively (P=0.879). There were no differences between the groups regarding infections (P=0.094) or treatment interruption (P=0.091). There were higher rates of infusion reactions in the infliximab group (P=0.016). Cephalea and injection site reactions were more prevalent in adalimumab patients. CONCLUSION: Adverse events were found in approximately two thirds of Crohn's disease patients under anti-TNF therapy, and there were no significant differences between infliximab or adalimumab.
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 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".