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

논문 기본 정보

자료유형
학술저널
저자정보
최윤미 (한림대학교)
저널정보
대한내분비학회 Endocrinology and Metabolism Endocrinology and Metabolism Vol.37 No.5
발행연도
2022.10
수록면
791 - 799 (9page)
DOI
https://doi.org/10.3803/EnM.2022.1533

이용수

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

초록· 키워드

오류제보하기
Background: In this study, we evaluated the recent changes in the standardized, age-specific, stage-specific incidence rates (IRs) of thyroid cancer in Korea and compared them with the incidence data reported by the Surveillance, Epidemiology, and End Results Program. Methods: The analysis was conducted using the incidence data (2005 to 2018) from the Statistics Korea and Korea Central Cancer Registry. Results: The age-standardized IR (SIR) of thyroid cancer increased from 24.09 per 100,000 in 2005 to 74.83 in 2012 (annual percent change [APC], 14.5). From 2012 to 2015, the SIR decreased to 42.52 (APC, –17.9) and then remained stable until 2018 (APC, 2.1). This trend was similar in both men and women. Regarding age-specific IRs, the IRs for ages of 30 years and older showed a trend similar to that of the SIR; however, for ages below 30 years, no significant reduction was observed from the vertex of IR in 2015. Regarding stage-specific IRs, the increase was more prominent in those with regional disease (APC, 17.4) than in those with localized disease until 2012; then, the IR decreased until 2015 (APC, –16.1). The average APC from 2005 to 2018 increased in men, those under the age of 30 years, and those with regional disease. Conclusion: The SIR in Korea peaked in 2012 and decreased until 2015 and then remained stable until 2018. However, in young individuals under the age of 30 years, the IR did not significantly decrease but tended to increase again. In terms of stage-specific IRs, the sharpest increase was seen among those with regional disease.

목차

등록된 정보가 없습니다.

참고문헌 (0)

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