Does pre-imatinib (IM) fluorescence in situ hybridization (FISH) predict myelosuppression and outcomes in chronic myeloid leukemia (CML)?
Bibliographic record
Abstract
7071 Background: IM-associated myelosuppression occurs in 4–40% of CML patients (pts) vs. 1–16% in GIST. Selective inhibition of predominantly Philadelphia chromosome (Ph+) driven hematopoiesis may explain development of myelosuppression. In the absence of clinically applicable methods to quantitate Ph+/Ph- progenitor ratio, we hypothesized that the pre-IM percentage of BCR-ABL+ cells measured by FISH predicts myelosuppression. Methods: FISH pre-IM was available in 58 CML pts with chronic phase (CP, n=52), or advanced phase (AP, accelerated =3, blast =3) at 2 institutions. Grade >3 myelosuppression occurred < 60 days from starting IM in 9 pts (400 mg/d=6, > 600 mg/d=3), leading to dose reduction (4), discontinuation (1) or continuation same dose IM despite myelosuppression (4). Cryopreserved marrow CD34+/CD38- cells from 14 pts with (7) or without (7) post-IM myelosuppression were sorted using flow cytometry and subjected to FISH analyses. Results: Median FISH was higher for myelosuppression (90%) vs. no myelosuppression (80%) pts (p= 0.03), and in AP vs. CP (97 % vs. 80%, p=0.003). Results of FISH on CD34+/CD38- cells will be reported. Table summarizes outcomes of CP pts. Median follow-up was 14 and 45 months for myelosuppression and no myelosuppression AP pts, respectively. Myelosuppression AP pts expired (CML=2, GVHD=1); 1 after complete hematologic (CHR) and minor cytogenetic response (CTGR), 1 after partial HR, and 1 resistant disease. All 3 pts without myelosuppression achieved CHR with major CTGR, and 2 had partial molecular response. 1 died from GVHD. Conclusions: Higher FISH pre-IM identifies a group of CML pts who develop myelosuppression and are less likely to respond to IM. [Table: see text] No significant financial relationships to disclose.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".