Oncotype DX Recurrence Score Predicts Survival in Invasive Micropapillary Breast Carcinoma: A National Cancer Database Analysis
Bibliographic record
Abstract
(1) Background: Invasive micropapillary carcinoma (IMPC) is a rare, aggressive breast cancer subtype marked by high lymph node metastasis rates. While Oncotype DX recurrence score (RS) offers prognostic information for patients with hormone-receptor-positive (HR+) breast cancer, its utility in IMPC—a histology with distinct biologic behavior—remains unvalidated. This study evaluates whether Oncotype DX offers prognostic information with respect to overall survival (OS) in non-metastatic, early-stage patients with IMPC of the breast. (2) Methods: The National Cancer Database (2004–2020) was queried to select for women with ER+/HER2−, T1-T2N0-N1 IMPC who underwent Oncotype DX testing and received no neoadjuvant therapy. Patients were stratified by RS: low (≤11), intermediate (12–25), and high (>25). Kaplan–Meier survival curves and log-rank tests compared 5-year OS between groups. Multivariable Cox proportional hazards models assessed RS as an independent predictor, adjusting for age, race, comorbidities, grade, radiation, and insurance status. (3) Results: A total of 1325 women met the selection criteria. The cohort demonstrated significant survival disparities by RS (log-rank p = 0.017). Five-year OS rates were 97.5%, 97.5%, and 93.7% for low, intermediate, and high-risk patients, respectively. Adjusted multivariate analysis confirmed RS as an independent prognosticator: low (HR = 0.31, 95% CI: 0.15–0.75) and intermediate (HR = 0.32, 95% CI: 0.15–0.75) scores correlated with reduced mortality versus high RS. Omission of radiation therapy (HR = 2.68, 95% CI: 1.05–6.86) and higher comorbidity burden (0 comorbidities vs. ≥2: HR = 0.25, 95% CI: 0.10–0.61) were significantly associated with worse survival. (4) Conclusions: Oncotype DX is predictive for OS in IMPC, with high RS (>25) portending poorer outcomes. The survival detriment associated with RT omission aligns with prior studies demonstrating RT benefit in higher-risk cohorts. These findings validate RS as a prognostic tool in IMPC and underscore its potential to refine adjuvant therapy, particularly RT utilization. Future studies should explore RS-driven treatment personalization in IMPC, including comorbidity management and adjuvant radiation to improve outcomes in this distinct patient population.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".