Synchronous dual hematological malignancies: new or underreported entity?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Patients with a single hematological malignancy may be unexpectedly diagnosed with a clonally unrelated synchronous dual hematological malignancy (SDHM). The presence of a secondary hematological malignancy may be overlooked and only identified in situations presenting with discordant clinical or laboratory findings. Clinical management of these patients can be challenging, in part due to the relatively unknown etiopathology of SDHM and the impact of therapy on the secondary malignancy. OBJECTIVES: To assess, characterize patients with synchronous double hematological malignancies and share our experience with this challenging group of patients. METHODS: We performed a retrospective chart review of 3036 patients with hematological malignancy at our cancer center between February 2013 and July 2017. RESULTS AND DISCUSSION: We identified 46 patients with SDHM, a prevalence of 1.51% among patients diagnosed with any hematological malignancy. We identify several heterogeneous combinations of SDHM comprised of myeloid and/or lymphoid lineages and provide our experience with managing patients with these underreported conditions. CONCLUSION: SDHMs are not uncommon and should be suspected in situations presenting with unusual or unexpected findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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 it