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Record W4409361743 · doi:10.58931/cot.2025.2130

The Role of ctDNA in Breast Cancer: Prognosis and Clinical Utility

2025· article· en· W4409361743 on OpenAlexaff
Mairi Lucas, Stephen Chia

Bibliographic record

VenueCanadian oncology today. · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsBC Cancer Agency
FundersNational Cancer Institute
KeywordsBreast cancerOncologyMedicineInternal medicineCancer

Abstract

fetched live from OpenAlex

Breast cancer remains the most common cancer among women globally, with significant morbidity and mortality. Current treatment for breast cancer, both in the early stage and metastatic setting, is based on a tumour biopsy and immunohistochemical detection of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor 2 (HER2) expression. Though substantial research has been undertaken over the years to establish new prognostic and predictive biomarkers in breast cancer, most have not demonstrated significant clinical utility. Circulating tumour DNA (ctDNA) is increasingly used across various cancer types for precision medicine. In this article, we discuss the current roles of ctDNA in breast cancer prognosis and its clinical utility in treatment decision-making in early- and advanced-stage settings.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.008
GPT teacher head0.298
Teacher spread0.290 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2025
Admission routes1
Has abstractyes

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