Thymoma 20 Years After Hodgkin’s Lymphoma Radiation Therapy: A Case Study
Bibliographic record
Abstract
We present a case of a 48-year-old female who, over the course of 2 years, developed a recurrence of thymoma. She presented in 2013 with nausea and scalp pruritis, which progressed to generalized body pruritis. Examination was normal except for erythroderma noted on both arms and trunk sparing the lower limbs. A CT scan was performed which showed a 2.5 cm anterior mediastinal lymph node mass. A biopsy was performed which indicated a stage 2b thymoma. Her previous medical history was significant for a 1A nodular lymphocyte predominant Hodgkin’s lymphoma in 1992 for which she received mantle field radiation. Her presenting symptoms were thought to be of paraneoplastic origin. Thymectomy and excision of the pleural seeding occurred in 2013 with good results. A year later, a follow-up PET scan revealed a recurrence of her thymoma. Chemotherapy was started with good regression; however, in 2015 the thymoma had spread to the lungs, adjacent pleura and pericardium. Second line chemotherapy was initiated. This case report highlights the possible association between mantle field radiation for Hodgkin’s lymphoma leading to a future thymoma. It emphasizes the need to consider secondary malignancies in the differential diagnosis for patients presenting with unexplained symptoms and a previous history of radiation therapy. J Med Cases. 2016;7(4):153-154 doi: http://dx.doi.org/10.14740/jmc2466w
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".