Abstract B110: Racial disparities in pancreatic adenocarcinoma survival. Do they exist for patients who already survived their first year?
Notice bibliographique
Résumé
Abstract Purpose: Population-based studies indicated that prognosis of pancreatic adenocarcinoma (PAC) is worse in black patients compared to other races. Nonetheless, survival probabilities can change over time based on number of years (yr.) already survived by patients; a concept called conditional survival. This study explored the dynamic changes in risk according to patient characteristics, particularly race, on survival of PAC patients using cancer-specific survival (CSS) estimates. Methods: The Surveillance, Epidemiology, and End Results (SEER) database was queried for data on adult patients with non-metastatic PAC, diagnosed between 1988 and 2010. Patient characteristics, such as age, race, tumor grade, and stage were collected at the time of diagnosis. CSS probabilities, as well as Cox proportional hazard ratios (HRs), were computed at the time of diagnosis (Actuarial CSS and baseline HR), and after already surviving 1 to 6 yr. after diagnosis (Conditional CSS and HR). Harrell’s concordance index (C-index) was used to measure the cross-validation accuracy of the Cox models. Results: Our search retrieved data on 20,491 patients, with a mean age at diagnosis of 67.2 yr. Most of the patients were White (81.6%), followed by Black (12%) and Asians/Pacific Islander (6.4%). The stage was T1-2N0M0 in 15.9%, T3-4N0M0 in 41.8%, and T1-4N1M0 in 42.3% of patients. The 3-yr actuarial CSS calculated from time of diagnosis was significantly different across racial groups, at 11%, 10%, and 13% for Whites, Blacks, and Asians, respectively (P < 0.01). Conversely, for patients who already survived 1 yr. after diagnosis, the probability of surviving an additional 2 yr. was similar across races, at 26.2%, 27.1%, and 29.9%, for Whites, Blacks, and Asians, respectively (P = 0.218). As patients survived for longer periods of time following diagnosis, conditional CSS estimates increased similarly across different races; for White, Black, and Asian patients who already survived 3 yr. after diagnosis, the probability of surviving an additional 2 yr. was 62.6%, 60.5%, and 62.1%, respectively (P = 0.532). In multivariate cox models, the prognostic effect of race lost significance if patients already survived ≥1 yr. after diagnosis (Baseline HR = 1.114, 95%CI [1.045- 1.187], mean C-index = 67%; conditional HR at 1 yr = 1.015, 95%CI [0.919- 1.12], mean C-index = 60%). The prognostic effect of tumor grade, site, and age lost significance if patients already survived ≥2, ≥4, and ≥6 yr. after diagnosis, respectively. Tumor stage maintained its prognostic significance over time (conditional HR at 6 yr = 1.522, 95%CI [1.049- 2.208], mean C-index = 59%). Conclusion: Racial disparities in survival outcomes exist at the time of diagnosis for PAC patients. However, the survival impact of these disparities does not seem to persist over time. Other variables, such as age, tumor grade, stage, and treatment received should be taken into account when predicting future prognosis of PAC patients who have already survived ≥ 1 yr. after diagnosis. Citation Format: Anas M Saad, Maha AT Elsebaie, Mohamed Amgad, Muneer J Al-Husseini, Kyrillus S Shohdy, Omar Abdel-Rahman. Racial disparities in pancreatic adenocarcinoma survival. Do they exist for patients who already survived their first year? [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr B110.
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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».