A143 SAFETY OF BIOLOGICAL THERAPIES IN ELDERLY IBD: A SYSTEMATIC REVIEW
Bibliographic record
Abstract
Abstract Background There was a significant progress in the medical therapy of inflammatory bowel disease(IBD) with the advent of biological compounds, yet patients may experience adverse events(AE): infusion reactions, serious infections and malignancies, understudied in vulnerable patient populations (e.g. elderly). Aims Our aim was to perform a systematic review to assess the safety of the biologic therapies in the elderly IBD population. Methods Medline databases and conferences proceedings were searched between January 1, 2010, and June 1, 2021. Two reviewers independently evaluated the collected studies based on inclusion and exclusion criteria. Search was focused on IBD/CD/UC, any biological therapy, and adverse events in the elderly. The methodological quality of the included studies was assessed using the Newcastle– Ottawa Scale (NOS). This study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PRISMA). Results Our search identified 2885 articles and 12 congress abstracts trough the data base search, finally 14 peer reviewed papers and 3 abstracts met the inclusion criteria. The majority of the studies were retrospective, merging IBD patients, with an age limit of 60 or 65 years for elderly, from Europe or North America. The gender ratio was equal except in the USA veteran database. The identified studies collected safety data on anti-TNF therapy, vedolizumab and ustekinumab. We selected studies with at least 1 year follow-up period. Ranges of AE rates(infliximab/adalimumab 6–39/100patient-years (PY), vedolizumab 6–26/100 PY and ustekinumab 6–18.2/100 PY), infection rates (anti TNF 2.5–31/100PY, vedolizumab 2.6–77/100 PY and ustekinumab 5.2–35.7/100 PY) or infusion/injection reactions (anti TNF 0–14/100PY, vedolizumab 0.9–5/100 PY and ustekinumab 0–2.6/100 PY), were not different among the biological medication. Conclusions We report for the first time the comparative safety of biological therapies in elderly IBD patients. Ranges of adverse events or infections were wide but not different among the medications. Current data are insufficient to suggest prioritizing among biologicals in the elderly based on the safety, larger studies in elderly IBD patients are warranted. Funding Agencies None
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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 | 0.012 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".