Abstract 854: Ovarian cancer risk factors by histologic subtypes: evidence for etiologic heterogeneity
Notice bibliographique
Résumé
Abstract Background: A subset of high grade serous carcinomas may arise from the fallopian tube, while some endometrioid and clear cell carcinomas may derive from endometrial tissue. Previous studies have suggested differences in ovarian cancer risk factors by histologic subtypes, but had limited sample sizes. In the Ovarian Cancer Cohort Consortium (OC3), we evaluated associations of reproductive, hormonal, demographic and lifestyle factors, and family history of cancer with ovarian cancer subtypes. Identification of potential differences in associations among subtypes is important for clarifying ovarian cancer etiology and for developing novel prevention and risk prediction approaches. Methods: Among over 1.2 million women from 21 cohort studies, 4,347 ovarian cancers with histology information were identified during follow-up (3223 serous, 555 endometrioid, 316 mucinous, 253 clear cell). We used competing risks Cox proportional hazards regression to compute risk factor associations by histologic subtype. Models were stratified on study and year of birth and adjusted for age, parity and oral contraceptive use; subtype heterogeneity was evaluated by a likelihood ratio test. Unsupervised hierarchical clustering was used to evaluate patterns of risk factors by histology. Results: Most risk factors showed significant heterogeneity across histologic subtypes. Higher parity was most strongly associated with lower risks of endometrioid (RR per child: 0.79; 95%CI: 0.74-0.85) and clear cell (RR: 0.69; 95%CI: 0.61-0.78) carcinomas (p-het<0.0001). Age at menopause was positively and tubal ligation was inversely associated only with endometrioid and clear cell carcinomas (p-het = 0.02 and 0.003, respectively). Long-term menopausal hormone use (>5 years) was associated with endometrioid carcinomas (RR: 2.23; 95% CI: 1.46-3.42) and serous carcinomas (RR: 1.66; 95% CI: 1.44-1.92), and inversely associated with clear cell carcinomas (RR: 0.43; 95% CI: 0.20-0.91; p-het = 0.001). Family history of breast cancer was associated with increased risk of serous carcinomas (RR:1.13; 95% CI:1.02-1.27) and endometrioid carcinomas (RR: 1.44; 95% CI: 1.12-1.87; p-het = 0.02). Smoking (per 20 pack years) showed a positive association with mucinous carcinomas (RR: 1.38; 95% CI: 1.09-1.75) and an inverse association with clear cell carcinomas (RR:0.62; 95% CI: 0.46-0.85; p-het = 0.001). In unsupervised hierarchical clustering, serous and mucinous carcinomas clustered in one group and endometrioid and clear cell carcinomas in the other. Conclusion: Our results demonstrate heterogeneous associations of risk factors with ovarian cancer subtypes, supporting the hypothesis that the subtypes develop through different pathways. Most established risk factors were more strongly associated with non-serous carcinomas, suggesting that risk prediction may be more challenging for serous cancers, the most fatal subtype. Citation Format: Nicolas A. Wentzensen, Elizabeth Poole, Alan A. Arslan, Alpa V. Patel, V Wendy Setiawan, Kala Visvanathan, Elisabete Weiderpass, Emily White, Hans-Olov Adami, Louise A. Brinton, Leslie Bernstein, Julie Buring, Lesley M. Butler, Saioa Chamosa, Tess V. Clendenen, Laure Dossus, Renee Fortner, Susan M. Gapstur, Mia M. Gaudet, Inger Torhild Gram, Patricia Hartge, Judith Hoffman-Bolton, Annika Idahl, Michael Jones, Rudolf Kaaks, Vivki Kirsh, Woon-Puay Koh, James V. Lacey, I-Min Lee, Eva Lundin, Melissa Merritt, Ulrike Peters, Jenny Poynter, Sabina Rinaldi, Kim Robien, Thomas Rohan, Dale P. Sandler, Leo J. Schouten, Louise Sjöholm, Sabina Sieri, Anthony Swerdlow, Anne Tjønneland, Britton Trabert, Lynne Wilkens, Alicja Wolk, Hannah P. Yang, Anne Zeleniuch-Jacquotte, Shelley S. Tworoger. Ovarian cancer risk factors by histologic subtypes: evidence for etiologic heterogeneity. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 854. doi:10.1158/1538-7445.AM2015-854
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 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».