Abstract 1832: Associations between ovarian cancer and other malignant neoplasms in an international population-based study
Notice bibliographique
Résumé
Abstract Recent studies have suggested that different histological types of ovarian cancer develop via different pathways. Large epidemiological studies of first and second malignant neoplasms associated with ovarian cancer can quantify such risk and may provide etiologic clues in understanding these complex pathways. We analyzed ovarian cancer data from 13 different cancer registries in Europe, Australia, Canada and Singapore from 1943-2000. Cumulative risks were calculated using a competing risk model, and standardized incidence ratios (SIR) for 34 cancers were estimated based on the observed numbers of second malignancies and the expected numbers obtained from population-specific incidence rates. We observed 5,052 second malignant neoplasms in 107,038 ovarian cancer patients and 5,804 second ovarian cancers in 3,722,434 patients with cancer of other sites. Within 20 years from diagnosis of ovarian cancer, the cumulative risk of second malignant neoplasms was 4.8% (95% CI 4.6%, 5.0%) before 1980 and 7.1% (6.1, 8.0) after 1980. After sex cord-stromal, mucinous or endometrioid tumors of the ovary, the cumulative risk of second malignant neoplasms was higher [12.7% (11.2, 14.3), 10.0% (9.0, 11.0), 9.3% (7.9, 10.7), respectively] than after germ-cell tumors, serous tumors or adenocarcinoma NOS [6.2% (3.7, 8.7), 5.9% (5.5, 6.3), 5.1% (4.9, 5.4), respectively] within 20 years from diagnosis at age 45+. We observed increased SIRs for cancer of stomach [SIR=1.5 (95% CI 1.1, 2.0)], small intestine [3.2 (1.3, 6.5)], colon [1.5 (1.2, 1.8)], rectum [1.9 (1.4, 2.4)], soft tissue sarcoma [3.2 (1.5, 5.8)], non-melanoma of skin [1.4 (1.0, 1.7)], breast [1.3 (1.2, 1.5)], other female genital organ [2.2 (1.3, 3.5)], bladder [2.3 (1.7, 3.1)], kidney [1.8 (1.3, 2.6)], myeloid leukemia [3.5 (2.2, 5.4)] and other leukemia [6.4 (3.7, 10.2)] after serous tumors of the ovary. There were increased SIRs for colon [2.2 (1.7, 2.7)], rectum [1.9 (1.3, 2.6)], lung [2.1 (1.6, 2.7)] and bladder cancer [1.8 (1.0, 2.8)] after mucinous tumors. After endometrioid tumors, we observed an excess risk for cancer of colon [2.1 (1.5, 2.9)], bone [12.1 (1.5, 43.6)], soft tissue sarcoma [5.2 (1.1, 15.3)], corpus uteri [3.3 (2.2, 4.7)] and kidney [2.3 (1.1, 4.4)]. There was an association with cancer of soft tissue sarcoma [3.2 (1.0, 7.4)], bladder [2.2 (1.2, 3.4)], kidney [2.1 (1.2, 3.3)], thyroid gland [3.1 (1.5, 5.6)] and myeloid leukemia [4.2 (1.5, 9.1)] after sex cord-stromal tumors. SIRs of second ovarian cancer were increased after stomach, small intestine, colon, gallbladder, pancreas, peritoneum, non-melanoma skin and breast cancer. Women who survive ovarian cancer are at long-term risk of developing a second malignant neoplasm. The associations between specific types of ovarian cancer and other cancers may be attributed to late effects of radio- and chemotherapy, as well as to common genetic and environmental risk factors and pathways. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1832.
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 | 0,002 |
| 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 | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 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 ».