본 연구는 미국 국립암연구소의 SEER 프로그램에서 제공하는 위암 3기 자료에 대해 항암치료의 효과를 비교하고 위암 생존율에 유의한 영향을 미치는 요인을 알아보고자 한다. 본 연구에서 ...
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https://www.riss.kr/link?id=A107643740
김빛나
(강원대학교)
;
이민정
(강원대학교)
;
Kim, Bitna
;
Lee, Minjung
2021
Korean
KCI등재,ESCI
학술저널
255-266(12쪽)
0
0
상세조회0
다운로드국문 초록 (Abstract)
본 연구는 미국 국립암연구소의 SEER 프로그램에서 제공하는 위암 3기 자료에 대해 항암치료의 효과를 비교하고 위암 생존율에 유의한 영향을 미치는 요인을 알아보고자 한다. 본 연구에서 ...
본 연구는 미국 국립암연구소의 SEER 프로그램에서 제공하는 위암 3기 자료에 대해 항암치료의 효과를 비교하고 위암 생존율에 유의한 영향을 미치는 요인을 알아보고자 한다. 본 연구에서 분석한 위암 3기 자료는 비례위험 가정이 성립하지 않아 대안으로 제한된 평균 생존시간을 이용한 분석 방법을 자료 분석에 적용하였다. 의사-관측들을 이용하여 제한된 평균 생존시간을 추정하였고, 제한된 평균 생존시간 추정량에 기반한 검정통계량을 이용하여 항암치료의 효과를 파악하였다. 일반화 선형모형을 이용한 회귀모형을 통해 위암 3기 환자의 평균 생존시간에 유의한 영향을 미치는 공변량들의 효과를 추정하였다. 항암치료법에 따라 위암 3기 환자의 평균 생존시간에 유의한 차이가 있음을 확인하였고, 진단연령, 인종, 세분화병기, 분화도, 종양의 크기, 수술여부, 항암치료가 위암 3기 환자의 평균 생존시간에 유의한 영향을 미치는 요인들이였으며, 그 중 수술여부가 위암 3기 환자의 평균 생존시간을 늘리는데 가장 큰 영향을 미치는 요인임을 확인하였다.
다국어 초록 (Multilingual Abstract)
The purpose of this study is to compare the effects of treatment on stage III stomach cancer data obtained from the SEER program of the National Cancer Institute and to identify the significant risk factors for the survival rates of stage III stomach ...
The purpose of this study is to compare the effects of treatment on stage III stomach cancer data obtained from the SEER program of the National Cancer Institute and to identify the significant risk factors for the survival rates of stage III stomach cancer. Since the proportional hazards assumption was violated for treatment, we used the restricted mean survival time as an alternative to the proportional hazards model. The restricted mean survival time was estimated using pseudo-observations, and the effects of treatment were compared using a test statistic based on the estimated restricted mean survival times. We conducted the regression analysis using a generalized linear model to investigate the significant predictors for the restricted mean survival time of patients with stage III stomach cancer. We found that there was a significant difference between the restricted mean survival times of treatment groups. Age at diagnosis, race, substage, grade, tumor size, surgery, and treatment were significant predictors for the restricted mean survival time of patients with stage III stomach cancer. Surgery was the most significant predictor for increasing the restricted mean survival time of patients with stage III stomach cancer.
참고문헌 (Reference)
1 Zhao L, "Utilizing the integrated difference of two survival functions to quantify the treatment contrast for designing, monitoring, and analyzing a comparative clinical study" 9 : 570-577, 2012
2 Royston P, "The use of restricted mean survival time to estimate the treatment effect in randomized clinical trials when the proportional hazards assumption is in doubt" 30 : 2409-2421, 2011
3 Irwin JO, "The standard error of an estimate of expectation of life, with special reference to expectation of tumourless life in experiments with mice" 47 : 188-189, 1949
4 Surveillance, Epidemiology, and End results (SEER) program, "SEER*Stat Database : Incidence - SEER 18 Regs custom data (with additional treatment fields), Nov 2018 Sub (1975-2016 varying) - Linked to county attributes - total US, 1969-2017 counties, national cancer institute, DCCPS, Surveillance research program, released April 2019, based on the November 2018 submission"
5 Cox DR, "Regression models and life-tables(with discussion), Journal of Royal Statistical Society" 34 : 187-220, 1972
6 Andersen PK, "Regression analysis of restricted mean survival time based on pseudo-observations" 10 : 335-350, 2004
7 Andersen PK, "Pseudo-observations in survival analysis" 19 : 71-99, 2010
8 Grambsch P, "Proportional hazards tests and diagnostics based on weighted residuals" 81 : 515-526, 1994
9 Tian L, "Predicting the Restricted mean event time with the subject’s baseline covariates in survival analysis" 15 : 222-233, 2014
10 Schoenfeld D, "Partial residuals for the proportional hazards regression model" 69 : 239-241, 1982
1 Zhao L, "Utilizing the integrated difference of two survival functions to quantify the treatment contrast for designing, monitoring, and analyzing a comparative clinical study" 9 : 570-577, 2012
2 Royston P, "The use of restricted mean survival time to estimate the treatment effect in randomized clinical trials when the proportional hazards assumption is in doubt" 30 : 2409-2421, 2011
3 Irwin JO, "The standard error of an estimate of expectation of life, with special reference to expectation of tumourless life in experiments with mice" 47 : 188-189, 1949
4 Surveillance, Epidemiology, and End results (SEER) program, "SEER*Stat Database : Incidence - SEER 18 Regs custom data (with additional treatment fields), Nov 2018 Sub (1975-2016 varying) - Linked to county attributes - total US, 1969-2017 counties, national cancer institute, DCCPS, Surveillance research program, released April 2019, based on the November 2018 submission"
5 Cox DR, "Regression models and life-tables(with discussion), Journal of Royal Statistical Society" 34 : 187-220, 1972
6 Andersen PK, "Regression analysis of restricted mean survival time based on pseudo-observations" 10 : 335-350, 2004
7 Andersen PK, "Pseudo-observations in survival analysis" 19 : 71-99, 2010
8 Grambsch P, "Proportional hazards tests and diagnostics based on weighted residuals" 81 : 515-526, 1994
9 Tian L, "Predicting the Restricted mean event time with the subject’s baseline covariates in survival analysis" 15 : 222-233, 2014
10 Schoenfeld D, "Partial residuals for the proportional hazards regression model" 69 : 239-241, 1982
11 Kaplan EL, "Nonparametric estimation from incomplete observations" 53 : 457-481, 1958
12 Korea Central Cancer Registry, "National cancer center, Annual report of cancer statistics in Korea in 2017" Ministry of health and welfare 2019
13 Liang KY, "Longitudinal data analysis using generalized linear models" 73 : 13-22, 1986
14 Zeger SL, "Longitudinal data analysis for discrete and continuous outcomes" 42 : 121-130, 1986
15 Prentice RL, "Linear rank tests with right censored data" 65 : 167-180, 1978
16 Ruhl J, "Grade Manual"
17 Chen PY, "Causal inference on the difference of the restricted mean lifetime between two groups" 57 : 1030-1038, 2001
18 National Cancer Information Center, "Cancer information service"
19 Guo C, "Analyzing restricted mean survival time using SAS/STAT"
20 Nemes S, "A brief overview of restricted mean survival time estimators and ¨associated variances" 3 : 107-119, 2020
선형 회귀모형에서 벌점 추정량의 신의 성질에 대한 충분조건
학술지 이력
연월일 | 이력구분 | 이력상세 | 등재구분 |
---|---|---|---|
2027 | 평가예정 | 재인증평가 신청대상 (재인증) | |
2021-01-01 | 평가 | 등재학술지 유지 (재인증) | ![]() |
2018-01-01 | 평가 | 등재학술지 유지 (등재유지) | ![]() |
2015-01-01 | 평가 | 등재학술지 유지 (등재유지) | ![]() |
2011-01-01 | 평가 | 등재학술지 유지 (등재유지) | ![]() |
2009-01-01 | 평가 | 등재학술지 유지 (등재유지) | ![]() |
2007-01-01 | 평가 | 등재학술지 유지 (등재유지) | ![]() |
2005-01-01 | 평가 | 등재학술지 유지 (등재유지) | ![]() |
2002-07-01 | 평가 | 등재학술지 선정 (등재후보2차) | ![]() |
2000-01-01 | 평가 | 등재후보학술지 선정 (신규평가) | ![]() |
학술지 인용정보
기준연도 | WOS-KCI 통합IF(2년) | KCIF(2년) | KCIF(3년) |
---|---|---|---|
2016 | 0.38 | 0.38 | 0.38 |
KCIF(4년) | KCIF(5년) | 중심성지수(3년) | 즉시성지수 |
0.35 | 0.34 | 0.565 | 0.17 |
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