A prognostic model for ovarian cancer.
A prognostic model for ovarian cancer.
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DOI：
10.1054/bjoc.2001.2030
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发表时间：
2001-09-28
影响因子：
8.8
通讯作者：
Smyth JF
中科院分区：
文献类型：
--
作者：
Clark TG;Stewart ME;Altman DG;Gabra H;Smyth JF
英国每年约有 6000 名女性罹患卵巢癌，其中约三分之二的女性会死于该病。确定患有卵巢癌的女性的预后是其评估和治疗的重要组成部分。卵巢癌的预后模型和指标应使用大型数据库来开发，理想情况下，应具有有关预后指标和长期结果的完整信息。我们利用 Cox 回归和多重插补对 1189 例上皮性卵巢癌原发病例（中位随访时间为 4.6 年）开发了一个预后模型。我们发现，总体生存率的显着（P≤0.05）预后因素是诊断时的年龄、FIGO分期、肿瘤分级、组织学（混合中胚层、透明细胞和子宫内膜样与浆液性乳头状）、是否存在腹水、白蛋白、碱性磷酸酶、ZUBROD-ECOG-WHO量表的表现状态以及肿瘤减灭。该模型与卵巢癌文献中的其他模型一致；具有较好的预测能力，经过简化和验证后可用于临床。 http://www.bjcancer.com © 2001 癌症研究运动http://www.bjcancer.com
About 6000 women in the United Kingdom develop ovarian cancer each year and about two-thirds of the women will die from the disease. Establishing the prognosis of a woman with ovarian cancer is an important part of her evaluation and treatment. Prognostic models and indices in ovarian cancer should be developed using large databases and, ideally, with complete information on both prognostic indicators and long-term outcome. We developed a prognostic model using Cox regression and multiple imputation from 1189 primary cases of epithelial ovarian cancer (with median follow-up of 4.6 years). We found that the significant (P≤ 0.05) prognostic factors for overall survival were age at diagnosis, FIGO stage, grade of tumour, histology (mixed mesodermal, clear cell and endometrioid versus serous papillary), the presence or absence of ascites, albumin, alkaline phosphatase, performance status on the ZUBROD-ECOG-WHO scale, and debulking of the tumour. This model is consistent with other models in the ovarian cancer literature; it has better predictive ability and, after simplification and validation, could be used in clinical practice. http://www.bjcancer.com © 2001 Cancer Research Campaignhttp://www.bjcancer.com
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影响因子：
8.8
作者：
Marsoni, S;Torri, V;Valsecchi, M G;Belloni, C;Bianchi, U;Bolis, G;Bonazzi, C;Colombo, N;Epis, A;Favalli, G
通讯作者：
Favalli, G
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4.7
作者：
ANSELL, SM;RAPOPORT, BL;MOEKEN, CM
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MOEKEN, CM
影响因子：
7.2
作者：
NAGELE, F;PETRU, E;SEVELDA, P
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SEVELDA, P
影响因子：
3.7
作者：
GELFAND, AE;SMITH, AFM
通讯作者：
SMITH, AFM
影响因子：
8.8
作者：
Peters-Engl, C;Obermair, A;Medl, M
通讯作者：
Medl, M