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Record W2901314939 · doi:10.1200/jco.18.01160

Adjuvant Endocrine Therapy for Women With Hormone Receptor–Positive Breast Cancer: ASCO Clinical Practice Guideline Focused Update

2018· article· en· W2901314939 on OpenAlex

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

VenueJournal of Clinical Oncology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsMedicineBreast cancerGuidelineTolerabilityOncologyInternal medicineAdjuvant therapyCancerAromatase inhibitorAdjuvantClinical trialGynecologyRandomized controlled trialAromataseAdverse effectPathology

Abstract

fetched live from OpenAlex

PURPOSE: To update the ASCO clinical practice guideline on adjuvant endocrine therapy based on emerging data about the optimal duration of aromatase inhibitor (AI) treatment. METHODS: ASCO conducted a systematic review of randomized clinical trials from 2012 to 2018. Guideline recommendations were based on the Panel's review of the evidence from six trials. RESULTS: The six included studies of AI treatment beyond 5 years of therapy demonstrated that extension of AI treatment was not associated with an overall survival advantage but was significantly associated with lower risks of breast cancer recurrence and contralateral breast cancer compared with placebo. Bone-related toxic effects were more common with extended AI treatment. RECOMMENDATIONS: The Panel recommends that women with node-positive breast cancer receive extended therapy, including an AI, for up to a total of 10 years of adjuvant endocrine treatment. Many women with node-negative breast cancer should consider extended therapy for up to a total of 10 years of adjuvant endocrine treatment based on considerations of recurrence risk using established prognostic factors. The Panel noted that the benefits in absolute risk of reduction were modest and that, for lower-risk node-negative or limited node-positive cancers, an individualized approach to treatment duration that is based on considerations of risk reduction and tolerability was appropriate. A substantial portion of the benefit for extended adjuvant AI therapy was derived from prevention of second breast cancers. Shared decision making between clinicians and patients is appropriate for decisions about extended adjuvant endocrine treatment, including discussions about the absolute benefits in the reduction of breast cancer recurrence, the prevention of second breast cancers, and the impact of adverse effects of treatment. Additional information can be found at www.asco.org/breast-cancer-guidelines .

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.722
Threshold uncertainty score0.754

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.046
GPT teacher head0.451
Teacher spread0.405 · 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