Chronicity of Immune Checkpoint Inhibitor–Associated Inflammatory Arthritis After Immunotherapy Discontinuation: Results From the Canadian Research Group of Rheumatology in Immuno‐Oncology Database
Bibliographic record
Abstract
OBJECTIVE: Immune checkpoint inhibitors (ICIs) improve overall survival (OS) and progression-free survival (PFS) in many types of malignancies but can result in off-target immune-related adverse events including inflammatory arthritis (ICI-associated inflammatory arthritis [ICI-IA]), which can persist even after ICI cessation. We aimed to examine the proportion of patients with ICI-IA who develop chronic ICI-IA and describe characteristics and outcomes associated with chronic ICI-IA. METHODS: We identified patients from the Canadian Research Group of Rheumatology in Immuno-Oncology retrospective cohort who developed de novo ICI-IA with at least three months of follow-up after ICI cessation. Chronic ICI-IA was defined as symptoms or ongoing immunosuppression lasting beyond three months after ICI discontinuation. Acute ICI-IA was defined as resolution of ICI-IA symptoms and discontinuation of immunosuppression within three months of ICI discontinuation. OS and PFS were assessed with Kaplan-Meier curves. Landmark multivariable Cox proportional hazard models for OS and PFS were conducted. RESULTS: The study cohort included 119 patients. A total of 15 patients (13%) had acute ICI-IA, whereas 104 (87%) had chronic ICI-IA. Patients with chronic ICI-IA were more likely to be White and to have polyarthritis at presentation. After adjusting for age, sex, tumor type, stage of cancer, ICI-IA treatment, and time from ICI initiation to ICI-IA onset, patients with chronic ICI-IA had greater PFS from ICI initiation (adjusted hazard ratio 0.27, 95% confidence interval 0.08-0.98; P = 0.046). Adjusted hazard ratio for OS was similar between those with acute versus chronic ICI-IA. CONCLUSION: ICI-IA frequently persists after ICI discontinuation. Chronic ICI-IA is associated with improved PFS, but not OS, as compared to acute ICI-IA.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".