Ping Chen , Wenting Zhao , Sicong Wang , Zilong Bian , Shu Li , Wenyuan Li , Huakang Tu , Chi Pang Wen , Xifeng Wu
{"title":"在一项中国前瞻性队列研究中,用一个模型预测口腔癌和食管癌。","authors":"Ping Chen , Wenting Zhao , Sicong Wang , Zilong Bian , Shu Li , Wenyuan Li , Huakang Tu , Chi Pang Wen , Xifeng Wu","doi":"10.1016/j.ypmed.2024.108119","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><p>Oral and esophageal cancers are both upper gastrointestinal cancers that share a number of risk factors. However, most previous risk prediction models only focused on one of these two types of cancer. There is no single model that could predict both cancers simultaneously. Our objective was to develop a model specifically tailored for oral and esophageal cancers.</p></div><div><h3>Methods</h3><p>From 1996 to 2007, a total of 431,460 subjects aged 20 and older without a history of cancer at baseline were included and were monitored for an average duration of 7.3 years in Taiwan, China. A total of 704 cases of oral and esophageal cancers were detected. We utilized both univariate and multivariate COX regression for screening predictors and constructing the model. We evaluated the goodness of fit of the model based on discriminatory accuracy, Harrell's C-index, and calibration.</p></div><div><h3>Results</h3><p>Finally, we developed a Cox regression model using the twelve most significant variables: age, gender, alcohol consumption, betel chewing, smoking status, history of oral ulceration, educational level, marital status, oropharynx status, family history of nasopharyngeal carcinoma, volume ratio of blood cell, and gamma-glutamyl transferase. The AUC (area under the curve) for the complete model was 0.82. Additionally, the C-index was 0.807 (with a 95 % confidence interval ranging from 0.789 to 0.824) and internal calibration results demonstrated that the model performed well.</p></div><div><h3>Conclusions</h3><p>This study identified the twelve most significant common risk factors for oral and esophageal cancers and developed a single prediction model that performs well for both types of cancer.</p></div>","PeriodicalId":20339,"journal":{"name":"Preventive medicine","volume":"189 ","pages":"Article 108119"},"PeriodicalIF":4.3000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0091743524002743/pdfft?md5=8ea8a75f48d16b787ca9f868de906263&pid=1-s2.0-S0091743524002743-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Predicting oral and esophageal cancers by one model in a Chinese prospective cohort study\",\"authors\":\"Ping Chen , Wenting Zhao , Sicong Wang , Zilong Bian , Shu Li , Wenyuan Li , Huakang Tu , Chi Pang Wen , Xifeng Wu\",\"doi\":\"10.1016/j.ypmed.2024.108119\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><p>Oral and esophageal cancers are both upper gastrointestinal cancers that share a number of risk factors. However, most previous risk prediction models only focused on one of these two types of cancer. There is no single model that could predict both cancers simultaneously. Our objective was to develop a model specifically tailored for oral and esophageal cancers.</p></div><div><h3>Methods</h3><p>From 1996 to 2007, a total of 431,460 subjects aged 20 and older without a history of cancer at baseline were included and were monitored for an average duration of 7.3 years in Taiwan, China. A total of 704 cases of oral and esophageal cancers were detected. We utilized both univariate and multivariate COX regression for screening predictors and constructing the model. We evaluated the goodness of fit of the model based on discriminatory accuracy, Harrell's C-index, and calibration.</p></div><div><h3>Results</h3><p>Finally, we developed a Cox regression model using the twelve most significant variables: age, gender, alcohol consumption, betel chewing, smoking status, history of oral ulceration, educational level, marital status, oropharynx status, family history of nasopharyngeal carcinoma, volume ratio of blood cell, and gamma-glutamyl transferase. The AUC (area under the curve) for the complete model was 0.82. Additionally, the C-index was 0.807 (with a 95 % confidence interval ranging from 0.789 to 0.824) and internal calibration results demonstrated that the model performed well.</p></div><div><h3>Conclusions</h3><p>This study identified the twelve most significant common risk factors for oral and esophageal cancers and developed a single prediction model that performs well for both types of cancer.</p></div>\",\"PeriodicalId\":20339,\"journal\":{\"name\":\"Preventive medicine\",\"volume\":\"189 \",\"pages\":\"Article 108119\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-08-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0091743524002743/pdfft?md5=8ea8a75f48d16b787ca9f868de906263&pid=1-s2.0-S0091743524002743-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Preventive medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0091743524002743\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Preventive medicine","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0091743524002743","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Predicting oral and esophageal cancers by one model in a Chinese prospective cohort study
Objective
Oral and esophageal cancers are both upper gastrointestinal cancers that share a number of risk factors. However, most previous risk prediction models only focused on one of these two types of cancer. There is no single model that could predict both cancers simultaneously. Our objective was to develop a model specifically tailored for oral and esophageal cancers.
Methods
From 1996 to 2007, a total of 431,460 subjects aged 20 and older without a history of cancer at baseline were included and were monitored for an average duration of 7.3 years in Taiwan, China. A total of 704 cases of oral and esophageal cancers were detected. We utilized both univariate and multivariate COX regression for screening predictors and constructing the model. We evaluated the goodness of fit of the model based on discriminatory accuracy, Harrell's C-index, and calibration.
Results
Finally, we developed a Cox regression model using the twelve most significant variables: age, gender, alcohol consumption, betel chewing, smoking status, history of oral ulceration, educational level, marital status, oropharynx status, family history of nasopharyngeal carcinoma, volume ratio of blood cell, and gamma-glutamyl transferase. The AUC (area under the curve) for the complete model was 0.82. Additionally, the C-index was 0.807 (with a 95 % confidence interval ranging from 0.789 to 0.824) and internal calibration results demonstrated that the model performed well.
Conclusions
This study identified the twelve most significant common risk factors for oral and esophageal cancers and developed a single prediction model that performs well for both types of cancer.
期刊介绍:
Founded in 1972 by Ernst Wynder, Preventive Medicine is an international scholarly journal that provides prompt publication of original articles on the science and practice of disease prevention, health promotion, and public health policymaking. Preventive Medicine aims to reward innovation. It will favor insightful observational studies, thoughtful explorations of health data, unsuspected new angles for existing hypotheses, robust randomized controlled trials, and impartial systematic reviews. Preventive Medicine''s ultimate goal is to publish research that will have an impact on the work of practitioners of disease prevention and health promotion, as well as of related disciplines.