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预测子宫内膜癌女性患者初始治疗后总生存期的列线图:迈向改善个体化癌症护理

A nomogram for predicting overall survival of women with endometrial cancer following primary therapy: toward improving individualized cancer care.

作者信息

Abu-Rustum N R, Zhou Q, Gomez J D, Alektiar K M, Hensley M L, Soslow R A, Levine D A, Chi D S, Barakat R R, Iasonos A

机构信息

Department of Surgery, Gynecology Service, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA.

出版信息

Gynecol Oncol. 2010 Mar;116(3):399-403. doi: 10.1016/j.ygyno.2009.11.027.

Abstract

OBJECTIVES

Traditionally we have relied mainly on final FIGO stage to estimate overall oncologic outcome in endometrial cancer patients. However, it is well known that other patient factors may play equally important roles in outcome. Our objective was to develop a clinically useful nomogram in the hope of providing a more individualized and accurate estimation of overall survival (OS) following primary therapy.

METHODS

Using a prospectively maintained endometrial cancer database, 1735 patients treated between 1993 and 2008 were analyzed. Characteristics known to predict OS were collected. For each patient, points were assigned to each of these 5 variables. A total score was calculated. The association between each predictor and the outcome was assessed by multivariable modeling. The corresponding 3-year OS probabilities were then determined from the nomogram.

RESULTS

The median age was 62 years (range, 25-96). Final grade included: G1 (471), G2 (622), G3 (634), and missing (8). Stage included: IA (501), IB (590), IC (141), IIA (36), IIB (75), IIIA (116), IIIB (6), IIIC (135), IVA (7), and IVB (128). Histology included: adenocarcinoma (1376), carcinosarcoma (100), clear cell (62), and serous (197). Median follow-up for survivors was 29.2 months (0-162.2 months). Concordance probability estimator for the nomogram is 0.746+/-0.011.

CONCLUSION

We developed a nomogram based on 5 easily available clinical characteristics to predict OS with a high concordance probability. This nomogram incorporates other individualized patient variables beyond FIGO stage to more accurately predict outcome. This new tool may be useful to clinicians in assessing patient risk when deciding on follow-up strategies.

摘要

目的

传统上,我们主要依靠国际妇产科联盟(FIGO)最终分期来评估子宫内膜癌患者的总体肿瘤学结局。然而,众所周知,其他患者因素在结局中可能发挥同样重要的作用。我们的目标是开发一种临床实用的列线图,以期对初始治疗后的总生存期(OS)提供更个体化、准确的估计。

方法

利用一个前瞻性维护的子宫内膜癌数据库,分析了1993年至2008年间接受治疗的1735例患者。收集已知可预测OS的特征。为每位患者的这5个变量分别赋值。计算总分。通过多变量建模评估每个预测因素与结局之间的关联。然后从列线图中确定相应的3年OS概率。

结果

中位年龄为62岁(范围25 - 96岁)。最终分级包括:G1(471例)、G2(622例)、G3(634例)和缺失(8例)。分期包括:IA(501例)、IB(590例)、IC(141例)、IIA(36例)、IIB(75例)、IIIA(116例)、IIIB(6例)、IIIC(135例)、IVA(7例)和IVB(128例)。组织学类型包括:腺癌(1376例)、癌肉瘤(100例)、透明细胞癌(62例)和浆液性癌(197例)。幸存者的中位随访时间为29.2个月(0 - 162.2个月)。列线图的一致性概率估计值为0.746±0.011。

结论

我们基于5个易于获得的临床特征开发了一种列线图,以高一致性概率预测OS。该列线图纳入了FIGO分期以外的其他个体化患者变量,以更准确地预测结局。这个新工具可能有助于临床医生在决定随访策略时评估患者风险。

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