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Record W4383561158 · doi:10.14740/jh1137

Amplification of Chromosome 1q Predicts Poor Overall Survival in Newly Diagnosed Multiple Myeloma Patients

2023· article· en· W4383561158 on OpenAlexvenueno aff
Matevž Škerget, Barbara Skopec, Samo Zver, Helena Podgornik

Bibliographic record

VenueJournal of Hematology · 2023
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMultiple myelomaInternal medicineOncologyAutologous stem-cell transplantationChromosomeClinical endpointPopulationMultivariate analysisTransplantationOverall survivalClinical trialBiologyGeneticsGene

Abstract

fetched live from OpenAlex

Background: Chromosome 1q copy number alterations are common in newly diagnosed patients with multiple myeloma, and in most published studies, there is no distinction made between three copies or the addition of at least four copies. The impact of these copy number alterations on patient outcome and optimal treatment is not fully understood. Methods: We retrospectively analyzed 136 transplant eligible patients with newly diagnosed multiple myeloma from our national registry, who were treated with first autologous stem cell transplantation (aHSCT) between January 1, 2018, and December 31, 2021. The primary endpoint was overall survival. Results: Patients with at least four copies of chromosome 1q had the poorest prognosis, with an overall survival of only 28.3 months. In multivariate analysis, four copies of chromosome 1q were the only statistically significant factor for overall survival. Conclusions: Despite the use of novel agents, transplantation, and maintenance therapy, patients with a gain of four copies of chromosome 1q have a very poor survival rate. Therefore, prospective studies using immunotherapy in this patient population are necessary.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.310
Teacher spread0.278 · 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 teacher head, 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".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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