Sarcoid-like Reaction Discovered on EBUS-TBNA of Intrathoracic Lymph Nodes During Immunotherapy for Metastatic Melanoma
Bibliographic record
Abstract
The use of immune checkpoint inhibitors has dramatically improved outcomes for patients with advanced melanoma and other malignancies. Checkpoint inhibitors are associated with a unique set of toxicities collectively known as immune-related adverse events, the incidence of which is rising in parallel with their increasing use in clinical practice. Immune-related adverse events are widely variable in their presentation and can affect virtually any organ system in the body. Sarcoid-like reactions in patients being treated with immune checkpoint inhibitors are rare and are typically multisystemic in nature with isolated pulmonary involvement representing only a small minority of cases reported in the literature. Herein we describe 2 patients who developed progressively enlarging lymphadenopathy while receiving checkpoint inhibitors for metastatic melanoma. Both patients were initially noted to have an excellent clinical response to immunotherapy but their treatment was interrupted pending further investigation as they were suspected to have progressive disease. They were ultimately diagnosed with sarcoid-like reactions after an endobronchial ultrasound-guided lymph node biopsy revealed noncaseating granulomas and were able to resume their immunotherapy without any further interventions or negative effect on their disease course. These 2 cases illustrate the importance of obtaining a tissue diagnosis when imaging reveals enlarging lymph nodes while on immunotherapy for solid malignancies as the differential diagnosis includes benign entities such as sarcoid-like reactions in addition to disease progression. Timely diagnosis through minimally invasive tissue sampling techniques, such as endobronchial ultrasound, can help rule out malignant etiologies of lymphadenopathy and minimize interruptions in treatment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".