Tumor infiltrating lymphocytes (TILs) in HER2 positive breast cancer: Evaluation according to the new recommendations by the international TILs working group 2014.
Bibliographic record
Abstract
1037 Background: Assessment of TILS has gained interest in oncologic pathology especially as a predictor of outcome in HER2+ and triple negative breast cancer (BC). Recently, a standardized approach to assess TILs on routine histopathology slides as a biomarker in BC was recommended by an international panel of experts. Using this approach, we assessed the inter rater reliability and predictive value of TILs in HER2+ locally advanced BC cases. Methods: Core biopsies from52 HER2+ BC patients obtained prior to neoadjuvant (NAT) chemotherapy with or without trastuzumab (T) were identified. Two pathologists independently quantified stromal TILs, intratumoral heterogeneity (ITH), presence of lymphocyte predominant (LPBC, ≥ 60%) BC and tertiary lymphoid structure (TLS) using H&E-stained slides following 2014 international guidelines. Discordant results were resolved by reviewing on a double headed microscope. The association of TILs as continous and categorical (LPBC) variables with complete pathological response (pCR) rates was determined by Mann-Whitney WIlcox test. Inter rater reliability was measured using Cohen’s Kappa coefficient. Results: An average of 4 cores per case were assessed. 8/52 (15%) cases had LPBC. Heterogeneity was mild in 30, moderate in 16 and severe in 6 cases. The pathologists agreed on 90%, 96% and 88% of the cases for quantitative TILs, LPBC( ≥ 60%) and ITH, inter rater reliability was excellent (Cohen’s Kappa 0.89, 0.85 and 0.81 respectively). On univariate analysis, high levels of TILs and LPBC were associated with greater pCR rates for the cohort of patients who received NAT with T (p= 0.004, p = 0.05 respectively). Conclusions: Our results show that the levels of TILs can be reliably assessed on breast core biopsies. High levels of TILs as a continous variable and LPBC are candidate predictors of pCR in Her2+ BC patients receiving NAT T.
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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 | 0.017 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".