Equivalence and switching between biosimilars and reference molecules in rheumatoid arthritis: protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Biologic drugs such as adalimumab, etanercept, and infliximab represent major first-line and second-line treatments for rheumatoid arthritis (RA) patients. However, their high cost poses a massive burden on healthcare systems worldwide. The expiration of patents for these biologics has driven the production of biosimilar drugs, which are potentially less costly and remarkably similar, albeit not identical to the reference molecules. This paper aims to outline the protocol of a systematic review that will investigate the efficacy and safety profile of biosimilars compared to biologics (objective 1) and the impact of switching between biosimilar drugs and reference biologics on the management of RA patients (objective 2). METHODS: We will investigate the effects of any biosimilars of adalimumab, etanercept, and infliximab on RA patients. We will include randomized controlled trials (RCTs) or quasi-RCTs to assess efficacy and safety outcomes and RCTs with two- or multiple-part designs to evaluate the consequences of switching from reference biologics to biosimilar drugs (and vice-versa). Electronic searches will be performed through MEDLINE (via PubMed), EMBASE, LILACS, and CENTRAL (from inception to April 2021). Two independent reviewers will screen studies, extract data, and evaluate the risk of bias. The latter will be carried out considering specific domains from equivalence trials and switching studies. Random-effects models will be fitted to obtain summary estimates using either relative risk or standardized mean difference as a metric. The primary outcome will be the rate of treatment success according to the American College of Rheumatology 20 (ACR20), and the co-primary outcome will be the Health Assessment Questionnaire-Disability Index (HAQ-DI). Conclusions will be based on equivalence hypothesis testing using predefined margins of equivalence elicited from a group of experienced rheumatologists and prior studies. The overall certainty of the evidence will be assessed based on the GRADE system. DISCUSSION: The present investigation proposes a comprehensive, clinician-oriented approach to assess the equivalence and the impact of switching between biosimilars and biologics on the management of patients with RA. Our results will elucidate the efficacy, safety, immunogenicity of biosimilars, and the clinical consequences of substituting biologics with biosimilars in the management of RA. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42019137152 and CRD42019137155.
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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 | 0.011 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.032 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".