Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
Absolute Risk Prediction for Esophageal Squamous Cell Carcinoma Adaptable to Regional Disease Burden across Diverse Regions.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Liu Mengfei, Huang Yi, Tian Hongrui, Guo Chuanhai, Liu Zhen, Liu Anxiang, Yang Haijun, Li Fenglei, Duan Liping, Shen Lin, Wu Qi, Shi Chao, Pan Yaqi, Liu Fangfang, Liu Ying, Chen Huanyu, Hu Zhe, Cai Hong, He Zhonghu, Ke Yang
Аннотация
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.
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.