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Record W2125254463 · doi:10.25011/cim.v36i6.20627

Prognostic significance of body mass index in breast cancer patients with hormone receptor-positive tumours after curative surgery

2013· article· en· W2125254463 on OpenAlexvenueno aff
Peng Xing, LI Ji-guang, Feng Jin, Tingting Zhao, Qun Liu, Huiting Dong, Xiao Wei

Bibliographic record

VenueClinical and investigative medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreast cancerBody mass indexInternal medicineUnderweightOncologyOverweightUnivariate analysisHormone receptorStage (stratigraphy)CancerMultivariate analysisGynecologyGastroenterology

Abstract

fetched live from OpenAlex

PURPOSE: Obesity has been recognized as a significant risk factor for postmenopausal breast cancer. The aim of this study is to investigate the prognostic significance of body mass index (BMI) in hormone receptor-positive, operable breast cancer. METHODS: In this retrospective cohort study, 1,192 consecutive patients with curative resection of primary breast cancer were enrolled. Patients were assigned to two groups according to BMI: normal or underweight (BMI < 23.0 kg/m²) and overweight or obese (BMI ≥ 23.0 kg/m²). Associations among BMI and clinicopathological characteristics and prognosis of patients were assessed. RESULTS: A high BMI was significantly (P < 0.01) correlated with age, nodal stage, ALNR, ER positivity, PR positivity and menopausal status at diagnosis. Univariate analysis revealed that BMI, pathologic T stage, nodal stage, axillary lymph node ratio (ALNR) and adjuvant radiotherapy history were significantly (P < 0.05) associated with disease-free survival and overall survival, irrespective of tumour hormone receptor status. Multivariate analysis revealed BMI as an independent prognostic factor in all cases and in hormone receptor-positive cases. CONCLUSION: A high BMI (≥ 23.0 kg/m²) is independently associated with poor prognosis in hormone receptor-positive breast cancer.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.007
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 head0.044
GPT teacher head0.301
Teacher spread0.257 · 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 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

Citations12
Published2013
Admission routes1
Has abstractyes

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