Abstract P2-08-05: Association between the neutrophil-to-lymphocyte ratio (NLR) and the 21-gene recurrence score
Bibliographic record
Abstract
Abstract Introduction: A high neutrophil-to-lymphocyte ratio (NLR) has been reported to be a poor prognostic indicator in several malignancies including breast cancer. It is unknown whether the prognosis associated with high NLR can be explained by other prognostic factors such as proliferation or estrogen receptor signalling. Here we explore the association between NLR and the 21-gene recurrence score (RS). Methods: The associations between RS, NLR, tumor size, histologic grade, and estrogen receptor (ER) and progesterone receptor (PgR) expression (assessed by immunohistochemistry) were explored in sequential women with early-stage, lymph node-negative (or with lymph node micrometastases), ER-positive and HER2-negative breast cancer treated at Princess Margaret Cancer Centre in Toronto, Canada and in whom results of the RS were available. NLR was measured prior to surgery. Patients with a documented history of pre-existing infectious/inflammatory condition were excluded. Associations were explored using simple linear regression and statistical significance was defined as p<0.05. Results: A total of 130 women diagnosed between January 2006 and April 2015 were included in the analysis. Median age was 55 (range 32-79), 87% were lymph node negative and 13% had nodal micrometastases. The median NLR was 2.2 (range 0.9-9.1) and was collected at a median of 12 days prior to surgery (range 0-60). The median RS was 18 (range 0-41). There was no association between RS and NLR (R=-0.10, p=0.31), grade (R=0.13, p=0.15), age (R=-0.05, p=0.58) or tumor size (R=0.06, p=0.48). RS was negatively associated with the magnitude of expression of both ER (R=-0.22, p=0.01) and PgR (R=-0.44, p<0.001). There was no association between NLR and grade (R=0.20, p=0.15), age (R=-0.13, p=0.17), tumor size (R=0.14, p=0.93), ER (R=0.01, p=0.94) or PgR (R=0.13, p=0.23) Conclusion: The poor outcomes associated with high NLR are unlikely explained by proliferation of estrogen receptor signalling. Citation Format: Srikanthan A, Bedard PL, Goldstein S, Templeton A, Amir E. Association between the neutrophil-to-lymphocyte ratio (NLR) and the 21-gene recurrence score. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P2-08-05.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".