Progesterone receptor status modifies the association between body mass index and prognosis in women diagnosed with estrogen receptor positive breast cancer
Bibliographic record
Abstract
The role of progesterone receptor (PR) status on the association between obesity and prognosis of estrogen receptor positive (ER+) breast cancer (BC) remains poorly understood. We aim to examine whether this association varies according to the tumor PR status. Data for 3,747 women diagnosed with nonmetastatic ER+ invasive BC between 1995 and 2010 were analyzed. Women were classified according to their body mass index (BMI) (<18.5, 18.5–24.9, 25.0–29.9 or ≥30.0 kg/m 2 ). Tumor PR status (PR−, PR+) was evaluated by immunohistochemistry. Hazard ratios (HR) for survival outcomes were estimated using multivariable Cox regression models. Effect modification was assessed on both additive and multiplicative scales using relative excess risk due to interaction and ratio of HRs, respectively. After a median follow‐up of 5.9 years (range: 3.4–9.2), women with PR− tumors and underweight (HR = 2.76, 95% CI: 1.40–4.91), overweight (HR = 2.02, 95% CI: 1.43–2.81) or obese (HR = 2.51, 95% CI: 1.67–3.65) had increased risk of all‐cause mortality, when compared to normal weight women with PR+ tumors. A similar pattern of associations was observed for BC‐specific mortality. In contrast, women with PR+ tumors had similar risks for both mortality outcomes, regardless of BMI. On the additive scale, all‐cause mortality was modified by PR status for overweight and obese women, whereas for BC‐specific mortality, it was only modified for underweight women. The same observations were found on the multiplicative scale. These results suggest that poorer survival associated with low and high BMI among women diagnosed with ER+ BC may depend on the tumor PR status.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".