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Record W2563435628 · doi:10.1093/ajcp/138.suppl2.107

Plasma Cell Enrichment in the Detection of Genetic Abnormalities in Plasma Cell Myeloma by Fluorescence In Situ Hybridization: A Single-Center Experience

2012· article· en· W2563435628 on OpenAlexaboutno aff
Giovanni Insuasti‐Beltran, Amy Stokes, Huining Kang, Kaaren K. Reichard, Carla S. Wilson, F.F.B. Elder

Bibliographic record

VenueAmerican Journal of Clinical Pathology · 2012
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsFluorescence in situ hybridizationPlasma Cell MyelomaPlasma cellMultiple myelomaIn situIn situ hybridizationCellFluorescencePathologyMolecular biologyBiologyMedicineChemistryGeneticsImmunologyGeneChromosomeGene expressionPhysics

Abstract

fetched live from OpenAlex

Risk-stratification models for the treatment of plasma cell myeloma (PCM) rely on the identification of specific genetic abnormalities. Fluorescence in situ hybridization (FISH) fulfills a key role in the assessment for risk-associated genetic abnormalities (eg, deletion TP53 is high risk). The detection sensitivity for this technique is limited by the percentage of PCs in bone marrow specimens. We examined the FISH abnormality detection rate in 15 PCM bone marrow specimens before and after PC enrichment using the EasySep CD138-positive selection kit (StemCell Technologies, Vancouver, Canada). Flow cytometric analysis before enrichment identified the following PC percentages: less than 5%, n = 7; 10% to 20%, n = 3; more than 30%, n = 3. Additional assessment of 4 specimens showed that PC yields increased from 7% (range, 1%-12%) to 69% (range, 46.8%-75.4%) after enrichment. FISH probes for 6 abnormalities were examined: 11q22.3, 17p13.1, 13q14.3, 13q34, t(4:14), and t(11;14). Genetic abnormalities were identified in 7 (47%) of 15 nonenriched samples compared with 14 (93%) of 15 enriched specimens. Before enrichment, FISH abnormalities were detectable in all cases with more than 10% PCs; an atypical t(11;14) was missed in 1 case with other abnormalities. Only 1 case with fewer than 5% PCs had an abnormality. Abnormal cell percentages varied from 4% to 32% in specimens with more than 10% PCs, and the percentage was 6% in a case with fewer than 5% PCs. Percentages that did reach probe-specific cutoff values were confirmed to be positive after enrichment. The 5 different probes (excluding 17p13.1) yielded a median of 60.5% to 80.25% positive cells after enrichment. The median number of FISH abnormalities was 0 for nonenriched and 3 for enriched specimens (P = .004). Treatment decisions for patients with PCM are often based on FISH testing for specific genetic abnormalities. Our study shows that FISH abnormalities are missed in a majority of cases with fewer than 10% PCs identified by flow cytometric analysis. The routine use of PC-enrichment techniques before FISH analysis in PCM is recommended.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.038
GPT teacher head0.343
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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