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 develop and validate individual prognostic models in a large cohort of cervical cancer patients that were primarily treated with radical hysterectomy. Materials and Methods We analyzed 1,441 patients with early-stage cervical cancer treated between 2000 and 2008 from the Korean Gynecologic Oncology Group multi-institutional cohort: a train cohort (n=788) and a test cohort (n=653). Models predicting the risk for overall survival (OS), disease- free survival (DFS), lymphatic recurrence and hematogenous recurrence were developed using Cox analysis and stepwise backward selection and best-model options. The prognostic performance of each model was assessed in an independent patient cohort. Model-classified risk groups were compared to groups based on traditional risk factors. Results Independent risk factors for OS, DFS, lymphatic recurrence, and hematogenous recurrence were identified for prediction model development. Different combinations of risk factors were shown for each outcome with best predictive value. In train cohort, area under the curve (AUC) at 2 and 5 years were 0.842/0.836 for recurrence, and 0.939/0.882 for OS. When applied to a test cohort, the model also showed accurate prediction result (AUC at 2 and 5 years were 0.799/0.723 for recurrence, and 0.844/0.806 for OS, respectively). The Kaplan-Meier plot by proposed model-classified risk groups showed more distinctive survival differences between each risk group. Conclusion We developed prognostic models for OS, DFS, lymphatic and hematogenous recurrence in patients with early-stage cervical cancer. Combining weighted clinicopathologic factors, the proposed model can give more individualized predictions in clinical practice.

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