{"title":"本期精选文章","authors":"","doi":"10.1158/1055-9965.epi-32-11-hi","DOIUrl":null,"url":null,"abstract":"Highlights| November 01 2023 Selected Articles from This Issue Author & Article Information Online ISSN: 1538-7755 Print ISSN: 1055-9965 ©2023 American Association for Cancer Research2023American Association for Cancer Research Cancer Epidemiol Biomarkers Prev (2023) 32 (11): 1475. https://doi.org/10.1158/1055-9965.EPI-32-11-HI Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn Email Tools Icon Tools Get Permissions Cite Icon Cite Search Site Article Versions Icon Versions Version of Record November 1 2023 Citation Selected Articles from This Issue. Cancer Epidemiol Biomarkers Prev 1 November 2023; 32 (11): 1475. https://doi.org/10.1158/1055-9965.EPI-32-11-HI Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest Search Advanced Search This study by Forjaz and colleagues is the first comprehensive analysis of long-term incidence and survival trends for several cancer sites by stage. The authors created a new variable, Long-Term Site-Specific Summary Stage, and applied it to 25 cancer sites to allow analyses of long-term cancer incidence and survival trends by stage from as early as 1975. They report remarkable improvements in cancer survival since 1975, namely for cancers that have traditionally had a poor prognosis and no organized screening programs, which likely reflect advances in managing and treating these cancers. This study will be particularly useful for understanding the population-level impact of new treatments and identifying emerging trends in health disparities research. Risk prediction models may improve effective and efficient use of supplemental surveillance imaging for individuals with a personal history of breast cancer. However, using risk models to guide supplemental imaging recommendations may contribute to disparities. Using simulation... You do not currently have access to this content.","PeriodicalId":9488,"journal":{"name":"Cancer Epidemiology, Biomarkers & Prevention","volume":"285 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Selected Articles from This Issue\",\"authors\":\"\",\"doi\":\"10.1158/1055-9965.epi-32-11-hi\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Highlights| November 01 2023 Selected Articles from This Issue Author & Article Information Online ISSN: 1538-7755 Print ISSN: 1055-9965 ©2023 American Association for Cancer Research2023American Association for Cancer Research Cancer Epidemiol Biomarkers Prev (2023) 32 (11): 1475. https://doi.org/10.1158/1055-9965.EPI-32-11-HI Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn Email Tools Icon Tools Get Permissions Cite Icon Cite Search Site Article Versions Icon Versions Version of Record November 1 2023 Citation Selected Articles from This Issue. Cancer Epidemiol Biomarkers Prev 1 November 2023; 32 (11): 1475. https://doi.org/10.1158/1055-9965.EPI-32-11-HI Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest Search Advanced Search This study by Forjaz and colleagues is the first comprehensive analysis of long-term incidence and survival trends for several cancer sites by stage. The authors created a new variable, Long-Term Site-Specific Summary Stage, and applied it to 25 cancer sites to allow analyses of long-term cancer incidence and survival trends by stage from as early as 1975. They report remarkable improvements in cancer survival since 1975, namely for cancers that have traditionally had a poor prognosis and no organized screening programs, which likely reflect advances in managing and treating these cancers. This study will be particularly useful for understanding the population-level impact of new treatments and identifying emerging trends in health disparities research. Risk prediction models may improve effective and efficient use of supplemental surveillance imaging for individuals with a personal history of breast cancer. However, using risk models to guide supplemental imaging recommendations may contribute to disparities. Using simulation... 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