Conventional Karyotyping and Fluorescence <i>In Situ</i> Hybridization for Detection of Chromosomal Abnormalities in Multiple Myeloma
Bibliographic record
Abstract
Background: hybridization (FISH) analysis and/or G-banded karyotyping. The two methods produce unique and overlapping information, and the clinical utility of using both is investigated here. Methods: Seventy patients diagnosed with MM at a hospital in Southern California were retrospectively reviewed for the FISH and G-banded karyotyping results obtained from bone marrow specimens. Results: Karyotype was normal in 71% (50/70), abnormal in 27% (19/70), and inadequate in 1% (1/70). Among patients with abnormal karyotype, FISH provided additional information about genetic aberrations in 95% of cases (18/19). Among cases with abnormal FISH, karyotype provided additional information about genetic aberrations in 27% of cases (18/66). When numerical abnormalities were present (detected by FISH and/or karyotype), FISH detected them in 95% (54/57), of which karyotype missed 70% (38/54) of the time. Karyotyping detected numerical abnormalities in 33% (19/57), which FISH missed 16% (3/19) of the time. Conclusions: Karyotyping and FISH analysis in MM each provide unique information. For most patients, performing both tests together will provide more information than either test alone.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.000 | 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 teacher head, 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".