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Record W2940866702 · doi:10.1002/oby.22458

Adipose Tissue Distribution and Survival Among Women with Nonmetastatic Breast Cancer

2019· article· en· W2940866702 on OpenAlexaff
Patrick T. Bradshaw, Elizabeth M. Cespedes Feliciano, Carla M. Prado, Stacey Alexeeff, Kathleen B. Albers, Wendy Y. Chen, Bette J. Caan

Bibliographic record

VenueObesity · 2019
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsUniversity of Alberta
FundersNational Cancer Institute
KeywordsMedicineBreast cancerAdipose tissueHazard ratioProportional hazards modelStage (stratigraphy)Internal medicineCancerOncologyConfidence interval

Abstract

fetched live from OpenAlex

OBJECTIVE: Previous studies of breast cancer survival have not considered specific depots of adipose tissue such as subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT). METHODS: This study assessed these relationships among 3,235 women with stage II and III breast cancer diagnosed between 2005 and 2013 at Kaiser Permanente Northern California and between 2000 and 2012 at Dana Farber Cancer Institute. SAT and VAT areas (in centimeters squared) were calculated from routine computed tomography scans within 6 (median: 1.2) months of diagnosis, covariates were collected from electronic health records, and vital status was assessed by death records. Hazard ratios (HRs) and 95% CIs were estimated using Cox regression. RESULTS: increase; HR [95% CI]: 1.02 [0.91-1.14]). An association with VAT was noted among women with stage II cancer (stage II: HR: 1.17 [95% CI: 0.99-1.39]; stage III: HR: 0.90 [95% CI: 0.76-1.07]; P interaction < 0.01). Joint increases in SAT and VAT were associated with mortality above either alone (simultaneous 1-SD increase: HR 1.19 [95% CI: 1.05-1.34]). CONCLUSIONS: SAT may be an underappreciated risk factor for breast cancer-related death.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.757

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.006
GPT teacher head0.243
Teacher spread0.237 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations50
Published2019
Admission routes1
Has abstractyes

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