Abstract P3-05-06: A better clinical cutpoint for progesterone receptor expression in tamoxifen treated breast cancer
Notice bibliographique
Résumé
Abstract INTRODUCTION: Hormone receptors are routinely measured by immunohistochemistry (IHC) to classify breast cancers (BC) and guide treatment decisions. Both estrogen receptor (ER) and progesterone receptor (PR) are measured yet “the precise role of PR in patient management has not been strongly established” (ASCO/CAP; JCO 2010 28(16)). PR expression is under the transcriptional control of ER, and its been suggested that BC with high PR expression are more estrogen-dependent and thus more sensitive to endocrine therapy. We hypothesized that using a higher PR threshold would be prognostic in hormone therapy (HT) treated ER+/HER2- BC patients compared to the current PR cutpoint (Allred Score≥3). METHODS: We analyzed PR expression using the Calgary Tamoxifen BC Cohort (Cal-TBCC), a retrospective database that has a clinically annotated tissue microarray (TMA) series of 532 BC patients treated with HT. The NCI Stage I BC TMA set (N = 590) was obtained for validation. ER was visualized by staining with Dako ER pharmDx, and HER2 with Dako HercepTest. We visualized PR expression using ready-to-use PR assays from 3 commercial IHC vendors (Dako, Leica, Ventana) for the Cal-TBCC. The NCI validation set was stained only using the Dako assay. Allred scores were generated, capturing intensity and percentage coverage of PR expression. Only patients receiving HT that were ER+/HER2- by IHC were included for study. RESULTS: We found that ER+/HER2- patients from the Cal-TBCC stratified using a newly defined PR Allred cutpoint to capture only PR-High BC had significantly better disease free survival (DFS) compared to the current cutpoint (PR+≥3), regardless of platform used (Table 1). Multivariate analysis - adjusting for tumor grade, size and lymph node status - confirmed the improved prognostic significance of the new PR cutpoint (Table 2A). We next validated the prognostic power of the newly defined cutpoint using the NCI series. This set also has a group of ER+/HER2- BC patients who were not treated with HT, allowing us to evaluate the ability of ER+/HER2-/PR-High to predict DFS in patients treated with or without HT. We found that in patients who weren't treated with HT, PR was not prognostic using either cutpoint (Logrank p = 0.952; p = 0.611); but in the HT group, the new cutpoint was predictive of treatment response (p = 0.343; p = 0.047) (Cox Table 2B). Table 1 Current CutpointNew CutpointDako PRp = 0.024p = 0.0002Leica PRp = 0.102p = 0.0002Ventana PRp = 0.058p = 0.0001 CONCLUSIONS: We have identified a new cutpoint for PR expression in BC that is prognostic within a tamoxifen treated BC cohort, and that maintained significance across 3 commercial PR assays. Moreover, this new cutpoint seems to be predictive of HT, as the untreated NCI controls did worse than the HT treated group. We intend to continue to evaluate the clinical role for the new PR cutpoint by re-analyzing PR data from completed clinical trials. Table 2 Current Cutpoint New Cutpoint 2A: Cal-TBCCHR95% CIp-valueHR95% CIp-valueDako PR0.7020.295-1.6700.420.6390.369-1.1060.11Leica PR0.7590.301-1.9130.560.5020.283-0.8880.018Ventana PR0.4480.201-0.9980.0490.4620.253-0.8440.0122B: NCI No HT0.9690.349-2.6910.9520.8530.461-1.5770.61HT0.5980.204-1.7510.3490.4340.185-1.0150.054 Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P3-05-06.
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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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».