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93例复发性卵巢癌疗效分析

王娟, 陈友国, 查雪丽, 周金华

王娟, 陈友国, 查雪丽, 周金华. 93例复发性卵巢癌疗效分析[J]. 肿瘤防治研究, 2020, 47(1): 58-62. DOI: 10.3971/j.issn.1000-8578.2020.19.0797
引用本文: 王娟, 陈友国, 查雪丽, 周金华. 93例复发性卵巢癌疗效分析[J]. 肿瘤防治研究, 2020, 47(1): 58-62. DOI: 10.3971/j.issn.1000-8578.2020.19.0797
WANG Juan, CHEN Youguo, ZHA Xueli, ZHOU Jinhua. Efficacy of 93 Cases of Recurrent Ovarian Cancer[J]. Cancer Research on Prevention and Treatment, 2020, 47(1): 58-62. DOI: 10.3971/j.issn.1000-8578.2020.19.0797
Citation: WANG Juan, CHEN Youguo, ZHA Xueli, ZHOU Jinhua. Efficacy of 93 Cases of Recurrent Ovarian Cancer[J]. Cancer Research on Prevention and Treatment, 2020, 47(1): 58-62. DOI: 10.3971/j.issn.1000-8578.2020.19.0797

93例复发性卵巢癌疗效分析

基金项目: 

国家自然科学基金 8167100306

国家自然科学基金 8177101003

详细信息
    作者简介:

    王娟(1979-), 女, 博士, 副主任医师, 主要从事妇科肿瘤的临床和基础研究

    通信作者:

    周金华(1979-), 男, 博士, 副主任医师, 主要从事妇科肿瘤的临床和基础研究, E-mail:jssuzhouwj@126.com

  • 中图分类号: R737.31

Efficacy of 93 Cases of Recurrent Ovarian Cancer

More Information
  • 摘要:
    目的 

    预测卵巢癌易复发因素, 分析复发性卵巢癌(ROC)患者的疗效与预后。

    方法 

    回顾性分析93例ROC患者的临床资料。采用单变量分析ROC患者无瘤生存期(DFI)影响因素。评估不同治疗方法对ROC患者无进展生存期(PFS)和复发后总生存时间(OS)的影响。

    结果 

    初次治疗后DFI单变量分析显示:肿瘤的组织分化程度、临床分期、初次术后残留肿瘤大小、初次手术后化疗疗程数与DFI有关(均P < 0.05)。93例ROC患者中, 手术组:44例患者行二次肿瘤细胞减灭术(SCS), 并联合化疗和(或)靶向治疗; 非手术组:49例患者行单纯化疗和(或)靶向治疗。手术组PFS和复发后OS均较非手术组有所延长; 手术组中:CA125 ≤ 150 U/L的患者OS和PFS较CA125>150 U/L的患者均有所延长(均P < 0.05);术前影像学检查提示复发肿瘤个数≤ 3的患者术后OS和PFS较复发肿瘤个数>3的患者均有所延长(P < 0.05)。

    结论 

    肿瘤病理分化程度越高、临床分期越早、初次术后残余病灶越小以及术后化疗疗程越规范足量的卵巢癌患者DFI越长、复发越晚。卵巢癌复发时CA125 ≤ 150 U/L、影像学检查复发肿瘤个数≤ 3的患者可能会从SCS术中获益。

    Abstract:
    Objective 

    To predict the recurrence of ovarian cancer (OC), to analyze the efficacy and prognosis of recurrent ovarian cancer (ROC) patients.

    Methods 

    The clinical medical records of 93 ROC patients were retrospectively analyzed. Univariate analysis was performed on the influencing factors of disease free interval (DFI) in ROC patients. We evaluated the effect of different treatments on progression free survival (PFS) and overall survival (OS) after recurrence.

    Results 

    The single factor analysis of DFI after initial treatment showed that tumor differentiation, clinical stage, residual tumor size after initial surgery, and the number of chemotherapy courses after initial surgery were related to DFI (P < 0.05). Surgery group (n=44) were treated with secondary cytoreductive surgery (SCS) with chemotherapy and (or) targeted therapy. Non-surgery group (n=49) were treated with chemotherapy and (or) targeted therapy. PFS and OS after recurrence in surgery group were longer than those in non-surgery group. In surgery group, the patients with CA125 ≤ 150 U/L had longer OS and PFS than those with CA125>150 U/L (P < 0.05); preoperative imaging examination showed that the OS and PFS of patients with recurrent tumors number ≤ 3 were longer than those with recurrent tumors number>3 (P < 0.05).

    Conclusion 

    Pathological differentiation, clinical stage, the chemotherapy course and the size of residual tumor after initial cytoreductive surgery are associated with DFI in recurrent ovarian cancer. ROC patients with recurrent tumors number ≤ 3 or CA125 ≤ 150 U/L could benefit from SCS.

  • 作者贡献
    王娟:整理资料、分析数据、书写文章
    陈友国:校对数据
    查雪丽:收集资料
    周金华:指导全文
  • 图  1   二次肿瘤细胞减灭术对复发性卵巢癌患者OS(A)和PFS(B)的影响

    Figure  1   Effect of secondary cytoreductive surgery on OS (A) and PFS(B) of patients with recurrent ovarian cancer

    图  2   复发性卵巢癌患者二次肿瘤细胞减灭术前的CA125水平(A, B)和病灶个数(C, D)对PFS和OS的影响

    Figure  2   Effect of CA125 level(A, B) and number of lesions(C, D) on PFS and OS of ROC patients before secondary tumor cytoreductive surgery

    表  1   复发性卵巢癌患者临床病理因素影响DFI的单变量分析

    Table  1   Univariate analysis of clinicopathological features on DFI of ROC patients

    下载: 导出CSV

    表  2   复发性卵巢癌患者临床病理因素影响SCS后的PFS和OS单变量分析

    Table  2   Univariate analysis of clinicopathological features on PFS and OS of ROC patients after SCS

    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-06-16
  • 修回日期:  2019-10-05
  • 网络出版日期:  2024-01-12
  • 刊出日期:  2020-01-24

目录

    Corresponding author: ZHOU Jinhua, jssuzhouwj@126.com

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