Successful Implementation of Combined Treatment Methods for a Rare Recurrence of Waldenstrom Macroglobulinemia With Extramedullary Lesions
Bibliographic record
Abstract
A 67-year-old woman was admitted to the Hematology Department in 2014 with complaints of weakness and a low-grade fever. After conducting various tests, it was confirmed that she had Waldenstrom macroglobulinemia. She underwent several rounds of chemotherapy and maintenance therapy with rituximab, which resulted in a good clinical response. However, in 2019, an abnormal growth in the soft tissues of patient's frontal region was discovered, which was diagnosed as lymphoplasmacytic lymphoma. This later progressed to an intracranial lesion. The patient underwent radiation therapy for both the extramedullary and intracranial growths, which had a positive effect. A year later, she developed a lesion in her lymph nodes and soft tissues of her right leg, which was confirmed to be a recurrence of Waldenstrom disease. She underwent further treatment and is currently in complete remission. This case highlights the rare occurrence of relapse in Waldenstrom disease and the challenges in diagnosing extramedullary lesions. It also demonstrates the success of modern treatment approaches using a combination of therapies.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".