Abstract P2-06-11: Ramifications of HER2/ER/PR Guidelines from ASCO/CAP for Translational Cancer Research Using a Cohort from a Tertiary Care Centre in Ontario
Notice bibliographique
Résumé
Abstract Background: A transdisciplinary team from basic science, pathology, clinical and biostatistics was assembled to establish a framework with which to take novel laboratory biomarkers and targets to clinical validation. Human epidermal growth factor receptor (HER2), estrogen (ER) and progesterone (PR) receptor are of important prognostic and predictive value and drivers of systemic therapy for breast cancer (BC). As a first step, the current ASCO/CAP guidelines were used to re-assign centrally reviewed tumour specimens and compare to the clinically assigned scores for ER/PR and HER2. Methods: With REB approval, a cohort of 62 cases of non-metastatic invasive BC with banked tumour specimens was assembled between 2005 and 2007. Clinico-pathological information for each case was retrospectively obtained from the medical file and entered into an anonymized database. Full section slides were originally stained by routine immunohistochemistry (IHC). Categorical clinical scores for ER/PR (negative-neg/weak/positive-pos) were compared to the continuous scores assigned in a blinded fashion using ASCO/CAP criteria (% pos/H-score). Categorical clinical scores obtained with duplicate IHC antibody staining of full sections for HER2 (neg/equivocal-eq/pos) were compared to those obtained from IHC assessments of triplicate 6mm cores in a tissue microarray (TMA) that were assigned to be neg/eq/pos using ASCO/CAP criteria. A senior breast pathologist adjudicated discordant specimens. Exact Fisher tests were used to compare the two sets of categorical assessments. Results: Mean age was 43.5 years, (range 29-49). The majority of the cohort (59.7%) had N0 disease and received adjuvant chemotherapy (74.2%); 72.6% of the cohort was alive at the time of this analysis. Score means and ranges of ER/PR are displayed below. Two of 16 clinically ER neg cases (12.5%) were rescored as pos and 0/43 clinically ER pos cases were rescored as neg, P<0.0001. Two of 13 clinically PR neg cases (15.4%) were rescored as pos and 4/46 clinically PR pos cases (8.7%) were rescored as neg, (P<0.0001). HER2 status was reassessed for 51 cases, 41 of which (80%) had concordant scores (P<0.0001). Thirty-nine (76%) cases were classified as HER2 neg on TMA, 7 of which (18%) were eq on routine IHC and neg by fluorescence in situ hybridization. In routine IHC, 15.7% of tumours were eq. Four TMA cases were eq (7.8%%); with routine IHC, one of these was neg, one eq, and two were pos. Eight patients were HER2 pos in both assessments. ER/PR scores Conclusions: Systemic therapy recommendations could be impacted in a small but substantive number of cases by the methodology used for biomarker assessment and scoring, particularly near threshold values. This study illustrates that the scoring criteria used may be an important contributor to variability in correlative biomarker studies. Consideration should be given to routine systematic reassessment with continuous scoring for biomarker data proposed for use in correlative science studies. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P2-06-11.
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 | 0,007 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,000 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».