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Early discontinuation to adjuvant endocrine therapy in the ECOG-ACRIN TAILORx Trial.

2020· article· en· W3029352275 on OpenAlexaff
Betina R. Yanez, Robert J. Gray, Joseph A. Sparano, Ruth C. Carlos, Gelareh Sadigh, Sofia F. Garcia, Ilana F. Gareen, Timothy J. Whelan, George W. Sledge, David Cella, Lynne I. Wagner

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsCancer Care Ontario
FundersNational Institutes of Health
KeywordsMedicineDiscontinuationBreast cancerInternal medicineProportional hazards modelCancerOncologyHazard ratioGynecologyConfidence interval

Abstract

fetched live from OpenAlex

7004 Background: The TAILORx study demonstrated women with an intermediate Oncotype DX score receive the same benefit with endocrine therapy (ET) compared to chemoendocrine therapy (CET). However, early discontinuation of adjuvant ET is problematic among breast cancer survivors, with previous studies suggesting that up to 50% of women do not adhere to the full 5 years of recommended ET treatment. The aim of this study was to identify patient-level risk factors associated with early discontinuation of ET in the TAILORx study. Methods: TAILORx was coordinated by the ECOG-ACRIN Cancer Research Group. Participants were a subgroup of 954 women who completed additional measures on health-related quality of life (HRQoL) including endocrine symptoms (ES) physical well-being (PWB) and social well-being (SWB) prior to initiating ET, which categorized into three groups by tertile for analysis. All participants were diagnosed with hormone-receptor–positive, human epidermal growth factor receptor 2–negative, axillary node–negative breast cancer who started ET within a year of study entry. Early discontinuation of ET, defined as discontinuation less than 4 years from initiation for reasons other than death or recurrence, was assessed by clinician report. Rate of discontinuation was calculated using Kaplan-Meier estimates, and Cox-proportional hazards joint models were used to analyze the association between rates of adherence to ET with patient-level factors. Results: In a joint model, receipt of CET therapy (vs receipt of ET only; HR = .59, 95% CI .38-.94, p = .02) and age above 40 (versus age < = 40; HR = .30, 95% CI .14-.66, p = .003) were associated with a lower probability of early discontinuation of ET. Adjusted for these factors, a history of depression compared to no history of depression (HR 1.82, 95% CI 1.19-2.77, p = 0.005), worse ES compared to better ES (HR 1.70, 95% CI 1.06-2.74, p = 0.03), worse PWB compared to better PWB (HR 2.12, 95% CI 1.30-3.45,p = 0.003), and worse SWB compared to better SWB (HR 1.94, 95% CI 1.20-3.13, p = 0.007) were individually and significantly associated with a higher probability of early discontinuation of ET, although none reached statistical significance when all were included in a joint model. Conclusions: Younger women are at risk for early discontinuation and modifiable characteristics such as HRQoL and history of depression are potential risk factors for early discontinuation of ET. These results support systematic screening for HRQoL and depressive symptoms to identify women at risk for discontinuation of ET. Clinical trial information: NCT00310180 .

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.228
GPT teacher head0.489
Teacher spread0.261 · 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 designRandomized trial
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

Citations1
Published2020
Admission routes1
Has abstractyes

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