Abstract PD03-04: Effects of Diabetes (DM), Hypertension (HTN) and Coronary Artery Disease (CAD) on Prognosis after 5 Years of Adjuvant Tamoxifen (TAM) and on Treatment Outcomes with the Use of Extended Letrozole (LET): NCIC CTG MA.17
Bibliographic record
Abstract
Abstract Background: Women with early stage breast cancer and DM have poorer survival compared to non-DM women (Lipscombe 2008). Mechanisms include insulin dysregulation and/or DM related comorbidities such as HTN and CAD. MA.17 showed that adjuvant LET after five yrs of TAM reduced the risk of recurrence in women with ER+ early stage breast cancer and improved survival in node +ve disease. We evaluated the impact of DM, HTN, or CAD on prognosis after 5 yrs of TAM and the efficacy of LET in MA.17. Methods: All 5170 women randomized to MA.17 were included. Four year disease free survival (DFS), distant disease free survival (DDFS) and overall survival (OS) were compared using Cox regression model adjusting for other prognostic factors: a) in women treated with placebo (PLAC) based on the presence or absence of baseline DM (n=462), HTN (n=1627), CAD (n=604) or any one of these comorbidities (n=2049), and b) between LET and PLAC groups in each comorbidity. Analyses based on nodal status were also performed. Test for interaction assessed for differential treatment effects in comorbidity groups. Results: Women with DM on PLAC had non-significant lower DFS (89.7 vs. 89.9%, p=0.68), DDFS (92.1 vs 93.9%, p=0.85), and OS (92.1 vs 95.2, p=0.37) than those without DM on PLAC. Treatment effect outcomes were similar between those with and without DM. Women with HTN on PLAC trended toward lower DDFS (92.2 vs 94.4%, HR=1.50, 95%CI: 0.98-2.3, p=0.06) and OS (93.7 vs. 95.5%, HR=1.61, 95%CI: 0.95-2.72, p=0.08) than non-HTN women on PLAC. The interaction between treatment and HTN status was significant for DDFS (p=0.004) with HTN women having significantly better outcome on LET vs PLAC (HR=0.27, 95%CI: 0.13 to 0.54; p=0.0002) compared to non-HTN women on LET vs PLAC (HR=0.82, 95%CI: 0.56-1.20; p=0.31). Women with CAD on PLAC did not have worse outcome, nor did CAD status have a treatment related effect. Women with at least one co-morbidity on PLAC had significantly lower OS (93.6 vs. 95.8%, HR=2.10, 95%CI:1.26-3.51, p=0.004) than those free of comorbidity. For node +ve women, the difference between LET and PLAC in DDFS was greater among women with at least one co-morbidity (HR=0.30, 95%CI:0.15-0.60, p=0.001) compared to those without any co-morbidity (HR=0.72, 95%CI:0.45-1.16, p=0.17) with interaction p=0.04. Conclusions: Having at least one comorbidity was a negative prognostic indicator for OS after 5 yrs of TAM and led to improved DDFS for node +ve women taking LET. DM was not prognostic nor did it predict treatment outcomes. Explanations include not controlling for DM medications; as well, MA.17 enrolled women 5 yrs after TAM with evidence suggesting hyperinsulinemia being a risk for early rather than late recurrence. HTN was a potential risk factor with a trend for worse DDFS and OS. HTN also predicted for treatment benefit: HTN women on LET had improved DDFS compared to non-HTN women on LET. Hypothesis include antihypertensive agents slowing the metabolism of LET; alternatively there may be variations in VEGF levels between groups. HTN predictive effects will be further explored in MA.27 with potential to correlate with VEGF levels. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr PD03-04.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".