Safety of infliximab for the treatment of inflammatory bowel disease: current understanding of the potential for serious adverse events
Bibliographic record
Abstract
INTRODUCTION: Infliximab , a chimeric monoclonal antibody directed towards TNF-α, has revolutionized the treatment of inflammatory bowel disease (IBD). Since this therapy suppresses the immune system by neutralizing the immunological activity of TNF, concerns exist regarding the potential for infection, malignancy and immune disorders. AREAS COVERED: Comprehensive data from randomized controlled trials, meta-analyses and cohort studies have defined the risk of infection and malignancy with infliximab. Additional data regarding associations with immune disorders, such as drug-induced lupus, demyelinating syndromes and psoriaform skin disease have emerged, primarily from case reports. We report evidence from the most robust data sources that have examined these adverse events. EXPERT OPINION: A modest increase in the incidence of serious infection with infliximab and TNF-antagonists has been observed in methodologically rigorous studies. Combination therapy with an immunosuppressant does not confer a higher risk of serious infection than infliximab monotherapy. TNF-antagonist therapy alone with an immunosuppressant is not associated with higher rates of malignancy. Additional data are required to define causality, the magnitude and determinants of risk for other immune-related complications. Available data suggest the therapeutic index of infliximab is favorable for treatment of moderate-to-severe IBD.
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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) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".