ArticleFrontiers in oncology2021
Development and Validation of an Esophageal Squamous Cell Carcinoma Risk Prediction Model for Rural Chinese: Multicenter Cohort Study.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.
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Who cites it
5 citing papers in PubMed, 2 syntheses or guidelines pooled it, 10 citations in OpenAlex.
- Prediction of esophageal cancer risk based on genetic variants and environmental risk factors in Chinese population.BMC cancer · 2024Pooled it
- Risk Prediction Model for Esophageal Cancer Among General Population: A Systematic Review.Frontiers in public health · 2021Pooled it
- Integrating genetic and lifestyle determinants in a risk prediction model for esophageal squamous cell carcinoma in Taiwan.Scientific reports · 2026Article
- A model for projecting individuals' risk of esophageal squamous cell carcinoma in a high-risk Chinese population.Gastroenterology report · 2026Article
- Study protocol for artificial intelligence-assisted sponge cytology as pre-endoscopy screening for early esophegeal squmaous epithelial lesions in China.BMC cancer · 2022Article
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere are rare prediction models for esophageal squamous cell carcinoma (ESCC) for rural Chinese population. We aimed to develop and validate a prediction model for ESCC based on a cohort study for the population.
methodsData of 115,686 participants were collected from esophageal cancer (EC) early diagnosis and treatment of cancer program as derivation cohort while data of 54,750 participants were collected as validation cohort. Risk factors considered included age, sex, smoking status, alcohol drinking status, body mass index (BMI), tea drinking status, marital status, annual household income, source of drinking water, education level, and diet habit. Cox proportional hazards model was used to develop ESCC prediction model at 5 years. Calibration ability, discrimination ability, and decision curve analysis were analyzed in both derivation and validation cohort. A score model was developed based on prediction model.
resultsOne hundred eighty-six cases were diagnosed during 556,949.40 person-years follow-up in the derivation cohort while 120 cases from 277,302.70 in the validation cohort. Prediction model included the following variables: age, sex, alcohol drinking status, BMI, tea drinking status, and fresh fruit. The model had good discrimination and calibration performance:
conclusionsWe developed and validated an ESCC prediction model using cohort study with good discrimination and calibration capability which can be used for EC screening for rural Chinese population.
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