Mengfei Liu, Yi Huang, Hongrui Tian, Chuanhai Guo, Zhen Liu, Anxiang Liu, Haijun Yang, Fenglei Li, Liping Duan, Lin Shen, Qi Wu, Chao Shi, Yaqi Pan, Fangfang Liu, Ying Liu, Huanyu Chen, Zhe Hu, Hong Cai, Zhonghu He, Yang Ke
{"title":"食管鳞状细胞癌的绝对风险预测适应不同地区的区域疾病负担。","authors":"Mengfei Liu, Yi Huang, Hongrui Tian, Chuanhai Guo, Zhen Liu, Anxiang Liu, Haijun Yang, Fenglei Li, Liping Duan, Lin Shen, Qi Wu, Chao Shi, Yaqi Pan, Fangfang Liu, Ying Liu, Huanyu Chen, Zhe Hu, Hong Cai, Zhonghu He, Yang Ke","doi":"10.1158/1055-9965.EPI-24-1465","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Esophageal squamous cell carcinoma (ESCC) exhibits a long latency period and has a significant geographic disparity in incidence, which underscores the need for models predicting the long-term absolute risk adaptable to the regional disease burden.</p><p><strong>Methods: </strong>A total of 31,883 participants in a large-scale population-based screening trial (Hua County, China) were enrolled to develop the model. Severe dysplasia and above cases identified at screening or follow-up were defined as the outcome. We calculated the absolute risk in three steps: (i) constructing a relative risk model using logistic regression, (ii) calculating the age-specific baseline hazard, and (iii) adjusting for the competing risk of all-cause death excluding ESCC. Flexible incidence rate parameters were integrated into the model to ensure its relevance across diverse regions worldwide.</p><p><strong>Results: </strong>A total of 295 severe dysplasia and above cases were detected. The relative risk model consisted of old age, male gender, an irregular meal pattern, a preference for hot or hard food, a BMI of less than 22 kg/m2, and ESCC family history. The AUC was 0.753 (95% confidence interval, 0.749-0.757). The averaged 5-and 10-year absolute risk were 0.53% and 1.30% among participants. Based on our model, we developed an online calculator and incorporated flexible incidence rate parameters, demonstrating ideal risk stratification tailored to regions with varying disease burdens (https://pkugenetics.shinyapps.io/escc_risk_prediction/).</p><p><strong>Conclusions: </strong>We developed an absolute risk model to predict individualized long-term risk of ESCC, accounting for the local disease burden.</p><p><strong>Impact: </strong>This model has the potential to mitigate the global burden of ESCC by enabling targeted screening and personalized prevention strategies.</p>","PeriodicalId":9458,"journal":{"name":"Cancer Epidemiology Biomarkers & Prevention","volume":" ","pages":"510-517"},"PeriodicalIF":3.7000,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Absolute Risk Prediction for Esophageal Squamous Cell Carcinoma Adaptable to Regional Disease Burden across Diverse Regions.\",\"authors\":\"Mengfei Liu, Yi Huang, Hongrui Tian, Chuanhai Guo, Zhen Liu, Anxiang Liu, Haijun Yang, Fenglei Li, Liping Duan, Lin Shen, Qi Wu, Chao Shi, Yaqi Pan, Fangfang Liu, Ying Liu, Huanyu Chen, Zhe Hu, Hong Cai, Zhonghu He, Yang Ke\",\"doi\":\"10.1158/1055-9965.EPI-24-1465\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Esophageal squamous cell carcinoma (ESCC) exhibits a long latency period and has a significant geographic disparity in incidence, which underscores the need for models predicting the long-term absolute risk adaptable to the regional disease burden.</p><p><strong>Methods: </strong>A total of 31,883 participants in a large-scale population-based screening trial (Hua County, China) were enrolled to develop the model. Severe dysplasia and above cases identified at screening or follow-up were defined as the outcome. We calculated the absolute risk in three steps: (i) constructing a relative risk model using logistic regression, (ii) calculating the age-specific baseline hazard, and (iii) adjusting for the competing risk of all-cause death excluding ESCC. Flexible incidence rate parameters were integrated into the model to ensure its relevance across diverse regions worldwide.</p><p><strong>Results: </strong>A total of 295 severe dysplasia and above cases were detected. The relative risk model consisted of old age, male gender, an irregular meal pattern, a preference for hot or hard food, a BMI of less than 22 kg/m2, and ESCC family history. The AUC was 0.753 (95% confidence interval, 0.749-0.757). The averaged 5-and 10-year absolute risk were 0.53% and 1.30% among participants. Based on our model, we developed an online calculator and incorporated flexible incidence rate parameters, demonstrating ideal risk stratification tailored to regions with varying disease burdens (https://pkugenetics.shinyapps.io/escc_risk_prediction/).</p><p><strong>Conclusions: </strong>We developed an absolute risk model to predict individualized long-term risk of ESCC, accounting for the local disease burden.</p><p><strong>Impact: </strong>This model has the potential to mitigate the global burden of ESCC by enabling targeted screening and personalized prevention strategies.</p>\",\"PeriodicalId\":9458,\"journal\":{\"name\":\"Cancer Epidemiology Biomarkers & Prevention\",\"volume\":\" \",\"pages\":\"510-517\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2025-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Epidemiology Biomarkers & Prevention\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1158/1055-9965.EPI-24-1465\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Epidemiology Biomarkers & Prevention","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1158/1055-9965.EPI-24-1465","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
Absolute Risk Prediction for Esophageal Squamous Cell Carcinoma Adaptable to Regional Disease Burden across Diverse Regions.
Background: Esophageal squamous cell carcinoma (ESCC) exhibits a long latency period and has a significant geographic disparity in incidence, which underscores the need for models predicting the long-term absolute risk adaptable to the regional disease burden.
Methods: A total of 31,883 participants in a large-scale population-based screening trial (Hua County, China) were enrolled to develop the model. Severe dysplasia and above cases identified at screening or follow-up were defined as the outcome. We calculated the absolute risk in three steps: (i) constructing a relative risk model using logistic regression, (ii) calculating the age-specific baseline hazard, and (iii) adjusting for the competing risk of all-cause death excluding ESCC. Flexible incidence rate parameters were integrated into the model to ensure its relevance across diverse regions worldwide.
Results: A total of 295 severe dysplasia and above cases were detected. The relative risk model consisted of old age, male gender, an irregular meal pattern, a preference for hot or hard food, a BMI of less than 22 kg/m2, and ESCC family history. The AUC was 0.753 (95% confidence interval, 0.749-0.757). The averaged 5-and 10-year absolute risk were 0.53% and 1.30% among participants. Based on our model, we developed an online calculator and incorporated flexible incidence rate parameters, demonstrating ideal risk stratification tailored to regions with varying disease burdens (https://pkugenetics.shinyapps.io/escc_risk_prediction/).
Conclusions: We developed an absolute risk model to predict individualized long-term risk of ESCC, accounting for the local disease burden.
Impact: This model has the potential to mitigate the global burden of ESCC by enabling targeted screening and personalized prevention strategies.
期刊介绍:
Cancer Epidemiology, Biomarkers & Prevention publishes original peer-reviewed, population-based research on cancer etiology, prevention, surveillance, and survivorship. The following topics are of special interest: descriptive, analytical, and molecular epidemiology; biomarkers including assay development, validation, and application; chemoprevention and other types of prevention research in the context of descriptive and observational studies; the role of behavioral factors in cancer etiology and prevention; survivorship studies; risk factors; implementation science and cancer care delivery; and the science of cancer health disparities. Besides welcoming manuscripts that address individual subjects in any of the relevant disciplines, CEBP editors encourage the submission of manuscripts with a transdisciplinary approach.