Diagnosis and management of concurrent metastatic melanoma and chronic myelomonocytic leukemia
Bibliographic record
Abstract
While the association between chronic lymphocytic leukemia (CLL) and a higher incidence of melanoma is well documented, the diagnosis of concurrent high-risk chronic myelomonocytic leukemia (CMML) and metastatic melanoma (MM) has not previously been described. Moreover, the treatment of MM and CMML differ greatly in the mechanism of action of their corresponding antineoplastic therapies: treatment of MM frequently involves immune checkpoint inhibitors (ICI), while patients with CMML receive myelosuppressive agents. Simultaneous management of these malignancies can be nuanced due to the potential impact of one treatment's constituents on the activity of the other and the broad and nonoverlapping array of potential adverse effects of these agents. Here, we describe the clinical course of a patient who was diagnosed with concurrent MM and CMML and our approach to the challenging balance of delivering ICI concurrently with the hypomethylating agent azacitidine and the BCL-2 inhibitor venetoclax.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".