Abstract P3-07-16: Comparing surrogates of oncotype Dx recurrence scores in invasive ductal carcinoma: How complicated does it have to be?
Notice bibliographique
Résumé
Abstract Background: The Oncotype DX Recurrence Score (ODX) is commonly used to estimate recurrence risk and chemotherapy benefit in ER positive, node negative breast cancer but is associated with significant cost. The Magee score (MS), a free online calculation using numerical values of commonly assessed pathological features (ER, PR, Her2/neu, and Ki-67), has been validated as an ODX surrogate. This includes the MS using classic H scores (HMagee) or Surrogate H scores derived from total % positive cells and average intensity or our use of Surrogate H scores derived from Allred scores (SMagee). Also Gage et al (2015) used a simple algorithm based on tumor grade, PR >1% and ER>20%. Here we compare three methods of predicting ODX scores. Design: 61 patients from The Ottawa Hospital with ER positive HER2/neu negative invasive ductal carcinoma (IDC), known ODX were assessed. Classic H scores (CH) were assessed using Image analysis. All cases had Ki67 (1000 cell hot spot score), tumor size, grade, and Allred scores available. Surrogate H scores (SH) were derived (average reported intensity x midpoint of reported Allred positive score range or absolute percentage if between 1-10%). The three MS were calculated with CH giving classic MS (HMagee) and with SH giving surrogate scores (SMagee). Each case was also categorized using rules published by Gage (2015): LOW predicted if Low Grade and PR positive (>1%), HIGH predicted if High Grade or Low ER (<20%). Agreement with classic ODX categories of low (<18), intermediate (18-30) and high risk (≥ 31) was assessed. Results: ODX included 35 low, 20 intermediate and 6 high risk (Mean 17.4, sd=10). There was a good correlation between corresponding HMagee and SMagee 1-3(0.820, 0.73, 0.84). Concentrating on the theoretically best MS1 that includes Ki67 and all clinical variables (Table 1); HMagee1 predicted 32 cases as low grade with 78% accuracy and SMagee1 predicted 26 low grade with 92.3% accuracy. Of note, all intermediate ODX predicted low by MS were ODX 18-20. None of the MS falsely predicted high risk in low risk ODX. The one case of high ODX which MS predicted low (false negative) is controversial as an Allred ER&PR 8 tumor gave low ODX PR score. Using SMagee1 in this population would safely leave 32 (52.5%) in the intermediate category. Of note, all intermediate ODX predicted low by MS were borderline ODX 18-20. The Gage algorithm in our population is less useful with higher discordance rate and left 69% in the intermediate category. Table 1TestMagee RiskNODX LowODX IntermediateODX High%DiscordantHMagee1Low (<18)3225/78%7/22%07/22% Moderate(≥18-30)2810/36%15/54%3/11%13/46% High (≥31)1001/1.6%0SMagee1Low (<18)2624/92%1/4%1/4%2/8% Moderate(≥18-30)3211/33%19/58%3/9%14/44% High (≥31)2002/100%0GageLow108/80%1/10%1/10%2/20% Moderate4225/60%16/38%1/2.4%26/62% High92/22%3/33%4/44%5/56% Conclusions: In IDC, while simpler algorithms without proliferation markers do not perform as well; SMagee1 based on Allred, performs at least as well in prediction of ODX as an MS based on classic H score and can potentially save considerable time and money. In our hands the simpler Gage algorithm does not perform as well. Citation Format: Robertson SJ, Petkiewicz SL, Arnaout A, Clemons M, Gravel DH, Pond GR. Comparing surrogates of oncotype Dx recurrence scores in invasive ductal carcinoma: How complicated does it have to be?. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P3-07-16.
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 | 0,011 | 0,021 |
| 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 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».