Abstract P3-07-25: 2 year survival analysis of triple negative breast cancer from SEER data
Notice bibliographique
Résumé
Abstract Background Triple negative breast cancer (TNBC) is a heterogeneous disease characterized by the lack of receptor expression (ER, PR and Her 2/neu negative). Amongst breast cancer types TNBC has a less favourable prognosis. There is a higher incidence of TNBC in African-American women than Caucasian women. What has not been clearly elucidated is whether survival outcomes are different among women with TNBC from different ethnic background. Objective The objective of our study was to use population data to determine if significant differences exist in overall survival (OS) of TNBC patients across various ethnicities, including but not limited to–white, black, Hispanic and Asian. Methods Retrospective cohort study of patients with TNBC from 1973-2011 Surveillance, Epidemiology, and End-Results (SEER) database to examine differences in OS across ethnicities. For each case data was collected on age, race, disease stage, treatment, insurance status, time to death and cause of death. Descriptive statistics and survival analysis was carried out on the data. Multivariate analysis was carried out to take into account age, stage, treatments received. Results 12894 cases of TNBC across all ethnicities were reported in the SEER database. At two years follow-up, 720 patients (5.7%) had died of breast cancer. 9696 (78.77%) had early stage (stage 0 – II) disease, 1885 (15.31%) had locally advanced/stage III disease while 728 (5.9%) had stage IV disease. 12071 (95.53%) were insured, 11533 (91.27%) had surgery, and 5454 (43.17%) had radiation therapy. 7746 (61.53%) patients were white, 2429 (19.29%) black, 1548 (12.30%) were Hispanic and 490 (3.89%) were Asian. In multivariate analysis, increasing age, stage III or IV disease, lack of insurance, surgery or radiation all had significant hazard ratios. There was no significant survival difference found between any ethnicity compared with white patients when controlled for age, stage, insurance, surgery and radiation. Discussion After two-year follow-up of large cohort of TNBC patients no significant difference could be found between any ethnicity and the white population with this disease. While there is a large population of black and Hispanic patients in this study there are small numbers of other races. The small relatively small event rate could be masking potential differences given the majority if patients were early stage and are still alive. Longer follow-up is needed before conclusions can be made about differences between ethnic groups. if certain populations do worse will inform the medical oncology community of an area to focus greater research into how to optimize therapies for that patient group. Citation Format: Moira Rushton, Tinghua Zhang, Xinni Song. 2 year survival analysis of triple negative breast cancer from SEER data [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-07-25.
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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».