Tuberculous Lymphadenitis in a Patient Receiving PD-1 Inhibitor for Melanoma: A Case Report and Brief Literature Review
Bibliographic record
Abstract
Oncolytic immunotherapy is a novel and promising approach in clinical oncology practice. Currently, immune checkpoint inhibitors (ICIs) are the first-line treatment options for disseminated melanoma. Nivolumab is a well-defined ICI that blocks programmed cell death 1 (PD-1) and mainly increases anti-tumor immunity. The opportunistic infections are not expected with ICI therapies due to their immune reactivation effects. To date, only a few cancer patients have been reported with activated TB during ICI therapy. Here, we presented a young female patient diagnosed with histologically-confirmed tuberculous lymphadenitis while on nivolumab therapy for metastatic melanoma. The current case report represents the first described tuberculous lymphadenitis case related to anti-PD-1 based monoclonal antibody therapy. The mechanism underlying the development of TB with PD-1 inhibitor use has not been illuminated yet. Triggering of excessive inflammatory responses with ICIs therapy is a potential cause. Considering the increased utilization of ICI-based immunotherapies, the TB screening should be considered in all patients before starting PD-1 inhibitor therapy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".