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Record W3211935866 · doi:10.1016/j.breast.2021.11.007

Development of novel agents for the treatment of early estrogen receptor positive breast cancer

2021· review· en· W3211935866 on OpenAlexaff
Mitchell J. Elliott, David W. Cescon

Bibliographic record

VenueThe Breast · 2021
Typereview
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineBreast cancerEstrogen receptorOncologyAdjuvantDiseasePI3K/AKT/mTOR pathwayCancerInternal medicineBiomarkerEstrogenTargeted therapyAdjuvant therapyBioinformaticsSignal transduction

Abstract

fetched live from OpenAlex

Estrogen receptor (ER+) breast cancer is the most frequently diagnosed breast cancer subtype. Currently, adjuvant treatment for early stage disease consists of endocrine therapy, with or without chemotherapy and bone-targeted therapy, delivered in a risk-adapted manner. Despite this multimodal approach, a significant proportion of high risk patients will develop incurable distant recurrences. There is an ongoing need to develop new treatment strategies that address the biologic causes of treatment failure and to identify the individual patients who can benefit from such interventions. Here we review the clinical investigation of targeted and novel therapies, including inhibitors of the PI3K-AKT-mTOR pathway, oral selective estrogen receptor degraders (SERDs), and PARP-inhibitors for the treatment of early ER+ breast cancer. Furthermore, we highlight opportunities in biomarker development to help guide the delivery of escalated adjuvant strategies.

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)0.000
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 score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
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 head0.087
GPT teacher head0.384
Teacher spread0.297 · 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.

Study designOther design
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

Citations15
Published2021
Admission routes1
Has abstractyes

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