Abstract P6-04-02: Ki67 Assessment Protocol: Companion Diagnostic Biomarker for LUMINA Prospective Cohort Study
Notice bibliographique
Résumé
Abstract Introduction: Luminal A breast cancer is associated with low proliferation, indolent disease biology and limited benefit from chemotherapy. The LUMINA prospective study recently demonstrated a very low 5 year local recurrence rate (2.3%) in women ≥55 years with grade I-II, T1N0 luminal A breast cancer (defined as ER ≥ 1%, PR>20%, HER2 negative and Ki67 index ≤ 13.25%) treated with breast conservation surgery and endocrine therapy without radiation, supporting the safe omission of radiation in this molecularly defined low risk group. Here, we report the protocol for multicentre Ki67 scoring, the embedded integral companion diagnostic employed in LUMINA. Methodology: Ki67 immunohistochemistry was performed on full-face sections at one of the 3 labs and scored by pathologists using an adaptation of the International Ki67 Working Group (IKWG) method. Prior to the start of the study, quality assurance and quality control programs were set up to standardize staining and scoring protocols. All pathologists completed the IKWG training and calibration exercise using a tissue microarray-based series of 18 breast cancers. Inter-laboratory variability was assessed annually during the study period on a set of 9 breast cancer cases with a range of Ki67 scores that purposely over-represented the 13.25% threshold. Stained slides were scanned and images annotated to demarcate invasive carcinoma. Next, 5 random, non-overlapping, 1 mm virtual cores were generated via software and 100 nuclei assessed per core using a keyboard-based counting aid. Ki67 index was derived as the percentage of all counted tumor nuclei that are positively stained. For cases with high Ki67 heterogeneity, additional virtual cores were generated and scored and a 95% confidence interval (CI) of Ki67 index was estimated. The goal was to confidently assign a case as luminal A (≤13.25%) or B (> 13.5%). If the 95% CI crossed 13.25% a recount was performed by an additional pathologist. Results: Quality Assurance Programs: Mean Ki67 index across all cases, labs and years was 13% with high concordance across specimens and score ranges. Observed intra-class correlation coefficients (ICC) were ≥ 0.9, showing near perfect agreement in quantitative Ki67 evaluation. About the 13.25% cutpoint, the observed Kappa statistics were ≥ 0.7 indicating excellent agreement for assignment of luminal A vs. B status. A sub-study was conducted to compare the method of randomly selected virtual fields with the IKWG ‘global weighted score’ method for visual assessment of full-face sections. For this purpose, the 9 quality control cases were reassessed by the same pathologist using the updated IKWG method. Results showed an ICC of 0.96 (0.95% CI: 0.91-0.98) indicating that the Ki67 score generated by the methodology employed in LUMINA trial is highly concordant with the IKWG scoring methodology validated for use on full face sections. Ki67 index summary statistics across LUMINA: Of the 724 eligible cases, 69% (n=500) were assigned as luminal A (median Ki67=7.5%; IQR 5.2-9.8%) and 31% (n=224) as luminal B (median Ki67=19%; IQR 17-23%). Median pathologist scoring time was 4 minutes/case; 45% of cases required scoring of > 5 virtual cores. Per protocol, 39% cases where the initial CI crossed 13.25% were rescored by additional pathologist for final luminal A consensus assignment. Conclusions: Ki67 is a practical biomarker for identifying molecularly defined low-risk luminal A cancers. Our structured quality assurance approach for the trial led to excellent reproducibility and concordance among decentralized labs, supporting applicability of a distributed, inexpensive methodology beyond clinical trial settings and in resource restricted environments. Citation Format: Torsten Nielson, Samuel Leung, Nazia Riaz, Zuzana Kos, Anita Bane, Timothy J. Whelan. Ki67 Assessment Protocol: Companion Diagnostic Biomarker for LUMINA Prospective Cohort Study [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-04-02.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,018 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,024 | 0,019 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».