Pulmonary Nodulosis and Aseptic Granulomatous Lung Disease Occurring in Patients with Rheumatoid Arthritis Receiving Tumor Necrosis Factor-α-Blocking Agent: A Case Series
Bibliographic record
Abstract
OBJECTIVE: To describe cases of development of pulmonary nodulosis or aseptic granulomatous lung disease in patients with rheumatoid arthritis (RA) receiving anti-tumor necrosis factor-alpha (TNF-alpha) therapy. METHODS: A call for observation of such cases was sent to members of the French "Club Rhumatismes et Inflammation." The cases had to occur after introduction of TNF-alpha-blocking therapy. RESULTS: Eleven cases were examined: 6 patients were treated with etanercept, 2 with infliximab, and 3 with adalimumab. Pulmonary nodular lesions were observed after a mean treatment period of 23.3 +/- 15.3 months. Clinical symptoms were observed in 5 cases. Radiographs or computed tomography of the chest showed single or multiple nodular lesions in 10 cases and hilar adenopathies in 1 case. Biopsy of the nodular chest lesions or mediastinal lymphadenopathies were performed in 8 patients, and revealed typical rheumatoid nodules in 4 cases and noncaseating granulomatous lesions in 4 cases. Mycobacterial or opportunistic infections were excluded for all cases. Outcome was favorable for all the patients, with either discontinuation or maintenance of anti-TNF-alpha treatment. CONCLUSION: Aseptic pulmonary nodular inflammation corresponding to rheumatoid nodules or noncaseating granulomatous inflammation can occur during anti-TNF-alpha therapy for RA, mainly etanercept. The mechanism explaining such a reaction is not clear but certainly includes different processes. These cases of pulmonary nodular inflammation generally have a benign course and do not systematically require withdrawal of treatment.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".