Natalizumab: pharmacology, clinical efficacy and safety in the treatment of patients with Crohn’s disease
Bibliographic record
Abstract
Natalizumab is a humanized monoclonal antibody against alpha4 integrin. In preclinical and clinical studies, natalizumab, which interferes with leukocyte trafficking in the intestinal tract, demonstrated effectiveness in inducing clinical response and maintaining remission in patients with moderate-to-severely active Crohn's disease. However, during clinical trials, three natalizumab-treated patients (one Crohn's disease patient and two multiple sclerosis patients) developed progressive multifocal leukoencephalopathy (PML). As a consequence of this unexpected serious adverse event, a retrospective safety evaluation was conducted; in that safety evaluation, no new cases of PML were identified. Natalizumab returned to the market in June 2006 for the treatment of relapsing multiple sclerosis. As of May 2007, an estimated 12,000 patients worldwide had received natalizumab, with no new confirmed cases of PML or opportunistic infections reported. Natalizumab is currently being investigated for use in treating patients with Crohn's disease. If it is approved for treatment of Crohn's patients, the clinical benefit of natalizumab should be weighed carefully against the potential risk of serious adverse events.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".