Abstract 5906: Epidemiologic risk factors and survival trajectories among epithelial ovarian cancer survivors: A population-based cohort study
Notice bibliographique
Résumé
Abstract Background: Despite a poor 5-year survival rate of 45%, survival following a diagnosis of epithelial ovarian cancer stabilizes after 10 years. Although various clinical and tumor characteristics are established prognostic factors, the role of epidemiologic risk factors on short- versus long-term survival are unclear. The aim of this study was to evaluate the association between various hormonal, reproductive, and lifestyle risk factors on ovarian cancer mortality by survival trajectory time intervals across the survivorship phase. Methods: This population-based retrospective cohort study included 1,421 unselected women diagnosed with epithelial ovarian cancer from 1995 to 2004 in Ontario, Canada. Clinical information was obtained from medical records, risk factor information from telephone interview, and vital status was updated by linkage to the Ontario Cancer Registry up until 2020. We examined clinical risk factors, hormonal and reproductive related factors, lifestyle factors, and family history. Extended Cox proportional hazards models with Heaviside functions were used to estimate the association between risk factors and mortality by survival trajectory time interval (<3, 3-<6, 6-<10, and ≥10 years). Results: After a mean follow-up of 11.6 years, 65% (n=926) subjects died of which 51% (n=731) were due to ovarian cancer. Clinical factors such as late stage and presence of residual disease were strongly associated with short-term mortality, which attenuated over survival time. Stage IV disease significantly increased the risk of mortality compared to stage I disease for the survival interval within 3 years of diagnosis (HR 50.05; 95% CI 6.78, 369.57), however this association declined for survival beyond 10 years (HR 2.76; 95% CI 1.35, 5.65). Similarly, presence of residual disease increased the risk of mortality in the short-term (HR 2.47; 95% CI 1.40, 4.34), yet attenuated for long-term survival (HR 1.26; 95% CI 0.83, 1.93). Risk factors such as breastfeeding, smoking, and BMI were not associated with short-term survival, but significantly associated with long-term survival. History of breastfeeding decreased the risk of mortality (HR 0.65; 95% CI 0.46, 0.93), while a history of smoking (HR 1.75; 95% CI 1.27, 2.40) and obesity (HR 1.81; 95% CI 1.24, 2.65) increased the risk of mortality among long-term survivors. Conclusions: This study confirmed that clinical risk factors such as stage at ovarian cancer diagnosis and residual disease following debulking surgery are important prognostic factors in the short-term survival trajectory while breastfeeding, smoking, and BMI play a stronger role for long-term ovarian cancer survival. These findings suggest a role of modifiable factors in improving long-term outcomes across the survivorship phase. Citation Format: Shana Jean Kim, Barry Rosen, John R. McLaughlin, Harvey Risch, Shelly S. Tworoger, Steven A. Narod, Joanne Kotsopoulos. Epidemiologic risk factors and survival trajectories among epithelial ovarian cancer survivors: A population-based cohort study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5906.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».