Suppr超能文献

卵巢癌患者的预后及条件无病生存率

Prognosis and conditional disease-free survival among patients with ovarian cancer.

作者信息

Kurta Michelle L, Edwards Robert P, Moysich Kirsten B, McDonough Kathleen, Bertolet Marnie, Weissfeld Joel L, Catov Janet M, Modugno Francesmary, Bunker Clareann H, Ness Roberta B, Diergaarde Brenda

机构信息

Michelle L. Kurta, Marnie Bertolet, Joel L. Weissfeld, Janet M. Catov, Francesmary Modugno, Clareann H. Bunker, Brenda Diergaarde, Graduate School of Public Health; Marnie Bertolet, Clinical & Translational Science Institute, University of Pittsburgh; Robert P. Edwards, Kathleen McDonough, Joel L. Weissfeld, Brenda Diergaarde, University of Pittsburgh Cancer Institute; Robert P. Edwards, Janet M. Catov, Francesmary Modugno, Gynecology & Reproductive Sciences, University of Pittsburgh School of Medicine; Robert P. Edwards, Francesmary Modugno, Magee-Womens Research Institute Ovarian Cancer Center of Excellence, Pittsburgh, PA; Kirsten B. Moysich, Roswell Park Cancer Institute, Buffalo, NY; and Roberta B. Ness, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX.

出版信息

J Clin Oncol. 2014 Dec 20;32(36):4102-12. doi: 10.1200/JCO.2014.55.1713. Epub 2014 Nov 17.

Abstract

PURPOSE

Traditional disease-free survival (DFS) does not reflect changes in prognosis over time. Conditional DFS accounts for elapsed time since achieving remission and may provide more relevant prognostic information for patients and clinicians. This study aimed to estimate conditional DFS among patients with ovarian cancer and to evaluate the impact of patient characteristics.

PATIENTS AND METHODS

Patients were recruited as part of the Hormones and Ovarian Cancer Prediction case-control study and were included in the current study if they had achieved remission after a diagnosis of cancer of the ovary, fallopian tube, or peritoneum (N = 404). Demographic and lifestyle information was collected at enrollment; disease, treatment, and outcome information was abstracted from medical records. DFS was calculated using the Kaplan-Meier method. Conditional DFS estimates were computed using cumulative DFS estimates.

RESULTS

Median DFS was 2.54 years (range, 0.03-9.96 years) and 3-year DFS was 48.2%. The probability of surviving an additional 3 years without recurrence, conditioned on having already survived 1, 2, 3, 4, and 5 years after remission, was 63.8%, 80.5%, 90.4%, 97.0%, and 97.7%, respectively. Initial differences in 3-year DFS at time of remission between age, stage, histology, and grade groups decreased over time.

CONCLUSION

DFS estimates for patients with ovarian cancer improved dramatically over time, in particular among those with poorer initial prognoses. Conditional DFS is a more relevant measure of prognosis for patients with ovarian cancer who have already achieved a period of remission, and time elapsed since remission should be taken into account when making follow-up care decisions.

摘要

目的

传统的无病生存期(DFS)不能反映预后随时间的变化。条件DFS考虑了自缓解以来的经过时间,可能为患者和临床医生提供更相关的预后信息。本研究旨在估计卵巢癌患者的条件DFS,并评估患者特征的影响。

患者与方法

患者作为激素与卵巢癌预测病例对照研究的一部分被招募,如果他们在卵巢、输卵管或腹膜癌诊断后实现缓解,则纳入本研究(N = 404)。在入组时收集人口统计学和生活方式信息;从医疗记录中提取疾病、治疗和结局信息。使用Kaplan-Meier方法计算DFS。使用累积DFS估计值计算条件DFS估计值。

结果

中位DFS为2.54年(范围为0.03 - 9.96年),3年DFS为48.2%。在缓解后已存活1、2、3、4和5年的条件下,再存活3年无复发的概率分别为63.8%、80.5%、90.4%、97.0%和97.7%。年龄、分期、组织学和分级组在缓解时3年DFS的初始差异随时间减小。

结论

卵巢癌患者的DFS估计值随时间显著改善,尤其是那些初始预后较差的患者。条件DFS是已实现一段时间缓解的卵巢癌患者更相关的预后指标,在做出后续护理决策时应考虑自缓解以来的经过时间。

相似文献

1
Prognosis and conditional disease-free survival among patients with ovarian cancer.卵巢癌患者的预后及条件无病生存率
J Clin Oncol. 2014 Dec 20;32(36):4102-12. doi: 10.1200/JCO.2014.55.1713. Epub 2014 Nov 17.
9

引用本文的文献

本文引用的文献

1
Dynamic prognostication using conditional survival estimates.使用条件生存估计进行动态预后。
Cancer. 2013 Oct 15;119(20):3589-92. doi: 10.1002/cncr.28273. Epub 2013 Aug 1.
2
Cancer statistics, 2013.癌症统计数据,2013 年。
CA Cancer J Clin. 2013 Jan;63(1):11-30. doi: 10.3322/caac.21166. Epub 2013 Jan 17.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验