메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
Purpose We aimed to assess prognostic value of metastatic pelvic lymph node (mPLN) in early-stage cervical cancer treated with radical surgery followed by postoperative chemoradiotherapy. Also, we sought to define a high-risk group using prognosticators for recurrence. Materials and Methods A multicenter retrospective study was conducted using the data from 13 Korean institutions from 2000 to 2010. A total of 249 IB-IIA patients with high-risk factors were included. We evaluated distant metastasis-free survival (DMFS) and disease-free survival (DFS) in relation to clinicopathologic factors including pN stage, number of mPLN, lymph node (LN) ratio (number of positive LN/number of harvested LN), and log odds of mPLNs (log(number of positive LN+0.5/number of negative LN+0.5)). Results In univariate analysis, histology (squamous cell carcinoma [SqCC] vs. others), lymphovascular invasion (LVI), number of mPLNs ( 3 vs. > 3), LN ratio ( 17% vs. > 17%), and log odds of mPLNs ( 0.58 vs. > 0.58) were significant prognosticators for DMFS and DFS. Resection margin involvement only affected DFS. No significant survival difference was observed between pN0 patients and patients with 1-3 mPLNs. Multivariate analysis revealed that mPLN > 3, LVI, and non-SqCC were unfavorable index for both DMFS (p < 0.001, p=0.020, and p=0.031, respectively) and DFS (p < 0.001, p=0.017, and p=0.001, respectively). A scoring system using these three factors predicts risk of recurrence with relatively high concordance index (DMFS, 0.69; DFS, 0.71). Conclusion mPLN > 3 in early-stage cervical cancer affects DMFS and DFS. A scoring system using mPLNs > 3, LVI, and non-SqCC could stratify risk groups of recurrence in surgically resected early-stage cervix cancer with high-risk factors.

목차

등록된 정보가 없습니다.

참고문헌 (30)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0