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Circulating Tumour DNA for Detecting Minimal Residual Disease in Multiple Myeloma

2018· review· en· W2790687822 on OpenAlex
Trevor J. Pugh

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSeminars in Hematology · 2018
Typereview
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity Health NetworkUniversity of TorontoOntario Institute for Cancer ResearchPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMinimal residual diseaseMultiple myelomaBone marrowDNASomatic cellCell-free fetal DNADNA sequencingMedicineCirculating tumor DNACancer researchComputational biologyBiologyImmunologyInternal medicineCancerGeneGenetics

Abstract

fetched live from OpenAlex

Circulating tumor DNA faithfully recapitulates somatic mutations detected in bone marrow aspirates from patients with newly diagnosed or relapsed or recurrent myeloma. Extending these methods to enable detection of minimal residual disease will require increased sensitivity and breadth of genomic assays to maximize information content from small quantities of cell-free DNA; as well as definition of a clinically meaningful ctDNA concentration in comparison with conventional bone marrow cell-count thresholds. This review describes the use of cell-free DNA sequencing in myeloma to date, identifies challenges associated with pushing limit of detection of these assays into the realm of detecting minimal residual disease, and describes potential strategies to overcome these challenges.

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 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)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.833
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.083
GPT teacher head0.386
Teacher spread0.303 · 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