Association of Obesity With Breast Cancer Outcome in Relation to Cancer Subtypes: A Meta-Analysis
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Obesity at breast cancer (BC) diagnosis has been associated with poor outcome, although the magnitude of effect in different BC subtypes is uncertain. We report on the association of obesity or overweight at diagnosis of nonmetastatic BC with disease-free (DFS) and overall survival (OS) in the following defined subtypes: hormone receptor positive/HER2 negative (HR+HER2-), HER2 positive (HER2+), and triple negative (TNBC). METHODS: We searched MEDLINE, EMBASE, and COCHRANE databases up to January 1, 2019. Study eligibility was performed independently by 2 authors. Studies reporting hazard ratios (HRs) of OS and/or DFS for obesity or overweight in BC subtypes were included. The pooled hazard ratio was computed and weighted using generic inverse variance and random effects models. RESULTS: Twenty-seven studies were included. Obese compared with nonobese women had worse DFS in all subtypes: the hazard ratios were 1.26 (95% confidence interval [CI] = 1.13 to 1.41, P < .001) for HR+HER2- BC, 1.16 (95% CI = 1.06 to 1.26, P < .001) for HER2+ BC, and 1.17 (95% CI = 1.06 to 1.29, P = .001) for TNBC. OS was also worse in obese vs nonobese women (HR+HER2- BC HR = 1.39, 95% CI = 1.20 to 1.62, P < .001; HER2+ BC HR = 1.18, 95% CI = 1.05 to 1.33, P = .006; and TNBC HR = 1.32, 95% CI = 1.13 to 1.53, P < .001). As opposed to obesity, overweight was not associated with either DFS or OS in HER2+ BC (HR = 1.02, 95% CI = 0.81 to 1.28, P = .85; and HR = 0.96, 95% CI = 0.76 to 1.21, P = .99, respectively) or TNBC (HR = 1.04, 95% CI = 0.93 to 1.18, P = .49; and HR = 1.08, 95% CI = 0.81 to 1.44, P = .17), respectively. In HR+HER2- BC, being overweight was associated with worse OS (HR = 1.14, 95% CI = 1.07 to 1.22, P < .001). CONCLUSIONS: Obesity was associated with modestly worse DFS and OS in all BC subtypes.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it