Comparative Safety of JAK Inhibitors vs TNF Antagonists in Immune-Mediated Inflammatory Diseases
Bibliographic record
Abstract
Importance: Janus kinase (JAK) inhibitors are highly effective medications for several immune-mediated inflammatory diseases (IMIDs). However, safety concerns have led to regulatory restrictions. Objective: To compare the risk of adverse events with JAK inhibitors vs tumor necrosis factor (TNF) antagonists in patients with IMIDs in head-to-head comparative effectiveness studies. Data Sources: For this systematic review and meta-analysis, the Ovid Medline, Ovid EMBASE, and Web of Science databases were searched from inception to June 25, 2025. Study Selection: Head-to-head comparative effectiveness studies of adults (aged ≥18 years) with IMIDs (including rheumatoid arthritis, inflammatory bowel disease, psoriasis or psoriatic arthritis, or spondyloarthropathy) treated with either JAK inhibitors or TNF antagonists were included. Randomized clinical trials, noncomparative observational studies, studies not reporting outcomes of interest or focused solely on specific safety events, and studies with a sample size of less than 500 were excluded. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guideline was followed. Data Extraction and Synthesis: Four investigators independently, and in pairs, abstracted data from included studies. A random-effects meta-analysis was conducted to obtain incidence rates (IRs) and hazard ratios (HRs) for JAK inhibitors vs TNF antagonists for each safety outcome (serious infections, malignant neoplasms, major cardiovascular events [MACEs], or venous thromboembolism [VTE]), adjusting for key confounding variables. Heterogeneity was quantified using the I2 statistic. Risk of bias was assessed by 2 investigators independently using the Newcastle-Ottawa Scale. Main Outcomes and Measures: The primary outcome was risk of serious infections, malignant neoplasms, MACEs, or VTE. Results: This meta-analysis of 42 studies with low to moderate risk of bias included 813 881 patients (median age, 55.7 years [IQR, 53.0-59.0 years] for JAK inhibitor users and 51.5 years [IQR, 42.7-57.4 years] for TNF antagonist users; 76.5% female). For patients using JAK inhibitors vs TNF antagonists, there was no significant difference in risk of serious infections (IR, 3.79 [95% CI, 2.85-5.05] vs 3.03 [2.32-3.95] per 100 person-years; pooled HR, 1.05 [95% CI, 0.97-1.13]), malignant neoplasms (IR, 1.00 [0.77-1.31] vs 0.94 [0.72-1.22] per 100 person-years; pooled HR, 1.02 [0.90-1.16]), or MACEs (IR, 0.72 [0.56-0.92] vs 0.66 [0.49-0.89] per 100 person-years; pooled HR, 0.91 [0.80-1.04]), with minimal to moderate heterogeneity. There was a slightly higher risk of VTE with JAK inhibitors vs TNF antagonists (IR, 0.57 [95% CI, 0.40-0.82] vs 0.52 [0.37-0.73] per 100 person-years; pooled HR, 1.26 [95% CI, 1.03-1.54]). Effect estimates were largely stable across subgroups and on meta-regression. Conclusions and Relevance: The head-to-head studies in this systematic review and meta-analysis did not identify any meaningful difference in the risk of serious infections, malignant neoplasms, or MACEs with JAK inhibitor vs TNF antagonist use across all IMIDs, with low overall incidence. JAK inhibitor use was associated with a slightly higher risk of VTE. Further research, especially long-term studies, is needed to fully elucidate the safety of JAK inhibitors and TNF antagonists across diverse populations and optimize clinical use.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".