27P Impact of chemotherapy (CT) use and stromal tumor-infiltrating lymphocytes (sTILs) in stage I triple-negative breast cancer (TNBC)
Bibliographic record
Abstract
The optimal systemic treatment for stage I TNBC remains unclear, given the lack of well-designed randomized trials. sTILs have emerged as a prognostic biomarker in early TNBC. We aimed to study the impact of (neo)adjuvant CT use and sTILs in the prognosis of pts with stage I TNBC. Pts with stage I TNBC (ER<10% and HER2-0/low) treated at Vall d’Hebron Hospital between 2006 and 2021 were reviewed. sTILs were evaluated at the surgery specimen and/or at the diagnostic biopsy, as per the international immuno-oncology working group guidelines. The effect of (neo)adjuvant CT and sTILs on invasive disease-free survival (iDFS), distant disease-free survival (DDFS), and overall survival (OS) was evaluated. Statistical significance (p<0.05) was determined using the log-rank test. 108 patients were identified (median age 56, 35% pre-menopausal). The majority of patients had tumors ≥10mm (75%), grade 3 (61%), and received CT (79%). Patients not receiving CT had a median age of 75, 17% were pT1a tumors and 30% had favorable histotypes. sTILs could be assessed in 79/108 (73%); 34% had sTILs >50%, which associated with higher grade and Ki67. With a median follow-up of 7.2 years (IC: 3.0 – 21.8), 19/108 (18%) had a progression event, 9 (8%) distant metastases. 5y iDFS, DDFS, and OS rates are presented in the table. (Neo)adjuvant CT was not associated with better iDFS (p=.53), DDFS (p=.66) or OS (p=.89). In multivariate analyses for the survival endpoints, no interaction was observed between sTILs (both as categorical and continuous variables) and CT use.Table: 27P5-year ratesNiDFS (%)DDFS (%)OS (%)Overall population10883.691.298.9sTILs >50%2788.7100100sTILs <50%5285.6∗p=.63.93.8†p=.34.97.6‡p=.68.CT, overall8583.191.3100CT and sTILs>50%2387100100CT and sTILs<50%368997100No CT, overall2386.190.995.2No CT and sTILs>50%4100100100No CT and sTILs<50%16808793∗ p=.63.† p=.34.‡ p=.68. Open table in a new tab In this retrospective cohort, a high proportion of patients with stage I TNBC received CT, which was not associated with better outcomes, irrespectively of the abundance of sTILs. The role of (neo)adjuvant CT in stage I TNBC should be studied in prospective trials to identify patients that can be spared systemic treatment.
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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) | 0.002 | 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".