Abstract P2-07-02: A newly derived combined clinical treatment score and immunohistochemical-4 prognostic tool
Notice bibliographique
Résumé
Abstract AIM To determine whether a modified Clinical Treatment Score (CTS) based on continuous tumor size and 5 lymph node categories provided more prognostic information in an independent test set than the original CTS with and without the Immunohistochemical-4 (IHC4) algorithm for prediction of residual distant recurrence risk over 10-years. BACKGROUND Risk of recurrence information in patients with estrogen receptor-positive (ER+), early breast cancer informs decision-making on chemotherapy use. The CTS and IHC4 algorithms provide such information, particularly when used in combination (IHC4+C). Their derivation in the translational cohort of the Arimidex Tamoxifen Alone or in Combination trial (TransATAC) was described by Cuzick et al in 2011. In the original model tumor size and nodal status were each classified into three categories, causing prognostic information to be lost. METHODS We modeled a novel CTSn algorithm on outcome data from patients in the anastrozole and tamoxifen arms in ATAC incorporating tumor size as a continuous variable and sub-dividing nodal status into five categories. IHC4n was re-derived in the TransATAC cohort independent of CTSn. Patients were chemotherapy-naïve. We compared ability to predict risk of residual distant recurrence of the new IHC4n+Cn model with that of the original one when tested in a training cohort and in a validation set of chemotherapy-naïve patients from the Tamoxifen vs. Exemestane Adjuvant Multicentre (TEAM) trial using Cox regression models and the C-index. RESULTS The ATAC training set for CTSn comprised 4056 patients, the TransATAC training set for IHC4n comprised 1125 patients; 2591 patients were in the TEAM validation set. Patients in the TEAM set were older (median age in TransATAC: 63.5, TEAM: 68.3 years), had a higher nodal-burden (node-positive in TransATAC: 29.4%, TEAM: 51.8%) and had more Grade 3 tumors (TransATAC: 18.3%, TEAM: 32.2%). The new IHC4n+Cn was significantly prognostic, and non-significantly more prognostic than the original IHC4+C in both the training and validation cohorts. When assessed using the C-index statistic, IHC4n+Cn had a higher discriminatory ability than the original algorithm (Table 1). Table 1 TransATAC (N=1125)TEAM (N=2591) HR* (95% CI)C-indexHR* (95% CI)C-indexOld Models CTS2.26 (2.01-2.53)0.6811.88 (1.73-2.03)0.650IHC41.67 (1.46-1.91)0.6301.49 (1.35-1.63)0.604IHC4+C2.76 (2.40-3.18)0.7242.03 (1.87-2.21)0.671New Models CTSn2.64 (2.26-3.09)0.7212.16 (1.96-2.39)0.687IHC4n1.74 (1.52-2.01)0.6421.51 (1.36-1.68)0.603IHC4n+Cn2.91 (2.47-3.42)0.7382.28 (2.06-2.51)0.695(*Hazard Ratio for change in one Standard Deviation). CONCLUSION By separately remodellng the part of the IHC4+C score based on clinicopathological characteristics using the whole ATAC chemo-naïve cohort, and the part that uses IHC-derived information in chemo-naïve TransATAC patients, we increased the precision of the individual risk estimates produced by both CTSn and IHC4n compared to those given by the original algorithms. The new IHC4n+Cn shows a trend for improved prognostic ability compared to the original IHC4+C. Like its predecessor, it relies on information that is readily available to clinicians and integrates it in an evidence-based way to improve prognostication in ER+ early breast cancer. Citation Format: Dodson A, Sestak I, Bayani J, Dowsett M, Bartlett J, Cuzick J. A newly derived combined clinical treatment score and immunohistochemical-4 prognostic tool [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P2-07-02.
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 | 0,003 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».