Overweight and prognosis in triple-negative breast cancer patients: a systematic review and meta-analysis
Why this work is in the frame
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Bibliographic record
Abstract
We conducted a systematic review and meta-analysis investigating the association between overweight and outcome in triple-negative breast cancer (TNBC) patients. We searched PubMed and Embase using variations of the search terms triple-negative breast cancer (population), overweight and/or obesity (exposure), and prognosis (outcome). Based on the World Health Organization guidelines for defining overweight, we included longitudinal observational studies, which utilized survival statistics with hazard ratios (HRs) in our analysis. The included studies measured body mass index at the time of diagnosis of TNBC and reported disease-free survival and/or overall survival. Study quality was assessed with the Newcastle-Ottawa Scale and study data were extracted using the Meta-analysis of Observational Studies in Epidemiology (MOOSE) checklist, independently by two authors. Random-effects models were used to combine the effect sizes (HRs), and the results were evaluated and adjusted for possible publication bias. Thirteen studies of 8,944 TNBC patients were included. The meta-analysis showed that overweight was associated with both shorter disease-free survival (HR = 1.26; 95%CI: 1.09-1.46) and shorter overall survival (HR = 1.29; 95%CI: 1.11c1.51) compared to normal-weight. Additionally, our Bayesian meta-analyses suggest that overweight individuals are 7.4 and 9.9 times more likely to have shorter disease-free survival and overall survival, respectively. In conclusion, the available data suggest that overweight is associated with shorter disease-free and overall survival among TNBC patients. The results should be interpreted with caution due to possible publication bias.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.003 | 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