Utility of Fine Needle Aspiration for Diagnosis of Plasmacytoma
Bibliographic record
Abstract
Plasmacytomas are rare extramedullary plasma cell neoplasms that present in bone and/or soft tissue. Diagnosis can require a variety of laboratory approaches such as serum protein electrophoresis, bone marrow biopsy, Bence Jones protein assays, and imaging. However, few case reports describe using fine needle aspiration for diagnosis. We present a case of a plasmacytoma diagnosis in a 55-year-old patient, who initially presented to the emergency room with symptoms of chest pain. Imaging revealed right apical and medial lung mass extending just posterior to the trachea with invasion and destruction of the anterolateral T3 vertebral body. Multiple smaller hypodensities were also present in thoracic vertebral bodies, ribs, and sternum. Biopsies were performed on the mediastinal mass. Fine needle aspiration revealed groups of mature and immature plasma cells at various stages of maturation. Flow cytometry demonstrated a kappa light chain-restricted plasma cell population. Paraffin immunoperoxidase studies showed that the neoplastic cells bore monotypic kappa light chains. The patient’s presentation emphasizes the utility of fine needle aspiration, in conjunction with other ancillary studies, for diagnosing plasmacytomas. J Med Cases. 2019;10(2):37-40 doi: https://doi.org/10.14740/jmc3223
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".