Abstract P6-09-30: Factors influencing survival among patients with HER2-positive metastatic breast cancer treated with Trastuzumab
Bibliographic record
Abstract
Abstract Background: We have limited capability to predict survival among patients treated for metastatic HER2+ breast cancer. Individual patient survival varies and further research is warranted to identify significant prognostic and predictive factors influencing overall survival (OS). Methods: We identified HER2+ metastatic breast cancer patients receiving trastuzumab (T) at the Sunnybrook Odette Cancer Centre (SOCC) from 1999-2013 through a Cancer Care Ontario Registry (n=256) and selected patients with pathology also available at SOCC (n=154). A retrospective chart review was completed documenting clinical, pathologic, laboratory and survival outcomes. OS was defined as date of 1st T therapy to death. The Kaplan-Meier method was used to estimate time-to-event outcomes. Cox proportional hazards regression models and log-rank tests were used to identify prognostic factors for overall survival (OS). Logarithmic transformations were performed for statistical purposes. Multivariable models were constructed including known prognostic factors: 1) number of visceral metastatic sites and 2) CNS metastasis. After adjusting for these two factors, stepwise selection was used to create an optimal model for additional factors. Analyses were two-sided and statistical significance was defined at the p=0.05 level. Results: Cohort characteristics: mean age was 55 (SD: 13 years), ≥2 sites of visceral metastasis: 45%, CNS metastasis: 7%, ER positive: 53%. Median OS for the cohort was 24 months (95% CI: 21-33). Clinical factors recorded at metastatic presentation such as the presence of a visceral metastasis, having multiple sites of visceral metastasis and CNS metastasis were prognostic for overall survival in univariate models (p<0.05). ER/PR status was not of significance (p>0.05). Laboratory measures such as the neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) and alkaline phosphatase (ALP) were of significance in univariate models (p=<0.05). The multivariable model identified older age (HR=1.18 / decade, 95% CI=1.02-1.37, p=0.030), higher PLR (HR=1.75 / log-unit, 95% CI=1.25-2.46, p=0.001), increased ALP (HR=1.87 / log-unit, 95% CI=1.41-2.49, p<0.001) and ER positivity (HR=0.63, 95% CI=0.42-0.96, p=0.032), as significant prognostic factors in addition to the presence of CNS metastasis (HR=3.19, 95% CI=1.59-6.38, p=0.001) and two or more metastatic sites (HR=2.10, 95% CI=1.19-3.70, p=0.010). Conclusion: Our results have identified a number of prognostic factors influencing survival among patient with HER2+ breast cancer treated with T. Age, ALP, PLR and ER status were identified as significant prognostic factors after adjusting for presence of CNS metastasis and number of metastatic sites. Further study of PLR as a prognostic and predictive factor is warranted. Citation Format: Blanchette PS, Desautels DN, Pond G, Bartlett JMS, Nofech-Mozes S, Yaffe M, Pritchard KI. Factors influencing survival among patients with HER2-positive metastatic breast cancer treated with Trastuzumab [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P6-09-30.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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 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".