Safety and Effectiveness of Multi-Switch Between Adalimumab Originator and Biosimilars: A Multicenter (SUSTAIN) Study
Bibliographic record
Abstract
Background/Objectives: Biologic therapies have transformed the management of inflammatory bowel disease (IBD), but their high cost has prompted the introduction of biosimilars. Although switching from biologic originators to biosimilars is increasingly common, real-world evidence remains limited. We aimed to explore the safety and efficacy of switching between biologic originators and biosimilars. Methods: We conducted a retrospective chart review of patients with IBD between 2015 and 2025. Adult patients receiving adalimumab-adaz or adalimumab-atto were included. Patients who were non-medically switched once from adalimumab originator (Humira®) to any biosimilar were classified as group A. Patients who also switched back to originator (multiple switches) were classified as group B. The outcomes of the study were safety and efficacy of the biosimilars. Logistic regression identified switching predictors. Results: A total of 237 patients were included in the study. The number of patients in group A and group B was 208 and 58 patients, respectively. Sustained clinical remission was achieved in 198 (95.4%) of group A and 54 (93.6%) of group B participants. Sustained normalization of inflammatory markers was also comparable, occurring in 190 (91.5%) of group A and 54 (92.3%) of group B participants. No treatment-emergent AEs, infections, or treatment discontinuations were reported in either group (0%). Regression analysis identified older age and prior immunomodulator use as significant predictors of switching. Conclusions: Multiple switches of adalimumab biosimilars can be safely undertaken without increasing the risk of adverse reactions or treatment failure. This study provides meaningful evidence to guide policy and physician confidence in biosimilar interchangeability as a sustainable IBD therapeutic strategy.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".