ArticleJAMA network open2023
Development and Validation of Esophageal Squamous Cell Carcinoma Risk Prediction Models Based on an Endoscopic Screening Program.
Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- The Impact of Artificial Intelligence-Assisted Endoscopy on the Detection of Upper Gastrointestinal Neoplasms: A Systematic Review and Meta-Analyses.Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2026Pooled it
- Development of a Combined Risk Factors Prediction Model for Esophageal Squamous Cell Carcinoma: A Secondary Analysis of the Linxian Nutrition Intervention Trial Cohort.Research square · 2026Article
- Five-Year Unified Risk Prediction Model for Gastric and Esophageal Cancer Based on Nationwide Health Check-Up Data in Japan: J-GESS Score.Journal of gastroenterology and hepatology · 2026Article
- The oral microbiome is associated with the diagnosis, prognosis and radiotherapy sensitivity of esophageal cancer.Journal of translational medicine · 2026Article
- A model for projecting individuals' risk of esophageal squamous cell carcinoma in a high-risk Chinese population.Gastroenterology report · 2026Article
- Liquid Biopsy and Nonendoscopic Biomarkers for Precision Early Detection of Esophageal Cancer: Evidence, Risk Stratification and Translational Challenges.Journal of Cancer · 2026Review
- A Simplified Nomogram for Primary Population-Based Screening of Esophageal Cancer: An Internally Validated Shandong Cohort Study Addressing Data Imbalance.Risk management and healthcare policy · 2026Article
- Expanding horizons in esophageal squamous cell carcinoma: The promise of induction chemoimmunotherapy with radiotherapy.World journal of clinical oncology · 2025Article
- Artificial intelligence enhances the management of esophageal squamous cell carcinoma in the precision oncology era.World journal of gastroenterology · 2024Review
- Blocking SLC7A11 attenuates the proliferation of esophageal squamous cell carcinoma cells.Animal cells and systems · 2024Article
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance: Assessment tools are lacking for screening of esophageal squamous cell cancer (ESCC) in China, especially for the follow-up stage. Risk prediction to optimize the screening procedure is urgently needed. Objective: To develop and validate ESCC prediction models for identifying people at high risk for follow-up decision-making. Design, Setting, and Participants: This open, prospective multicenter diagnostic study has been performed since September 1, 2006, in Shandong Province, China. This study used baseline and follow-up data until December 31, 2021. The data were analyzed between April 6 and May 31, 2022. Eligibility criteria consisted of rural residents aged 40 to 69 years who had no contraindications for endoscopy. Among 161 212 eligible participants, those diagnosed with cancer or who had cancer at baseline, did not complete the questionnaire, were younger than 40 years or older than 69 years, or were detected with severe dysplasia or worse lesions were eliminated from the analysis. Exposures: Risk factors obtained by questionnaire and endoscopy. Main Outcomes and Measures: Pathological diagnosis of ESCC and confirmation by cancer registry data. Results: In this diagnostic study of 104 129 participants (56.39% women; mean [SD] age, 54.31 [7.64] years), 59 481 (mean [SD] age, 53.83 [7.64] years; 58.55% women) formed the derivation set while 44 648 (mean [SD] age, 54.95 [7.60] years; 53.51% women) formed the validation set. A total of 252 new cases of ESCC were diagnosed during 424 903.50 person-years of follow-up in the derivation cohort and 61 new cases from 177 094.10 person-years follow-up in the validation cohort. Model A included the covariates age, sex, and number of lesions; model B included age, sex, smoking status, alcohol use status, body mass index, annual household income, history of gastrointestinal tract diseases, consumption of pickled food, number of lesions, distinct lesions, and mild or moderate dysplasia. The Harrell C statistic of model A was 0.80 (95% CI, 0.77-0.83) in the derivation set and 0.90 (95% CI, 0.87-0.93) in the validation set; the Harrell C statistic of model B was 0.83 (95% CI, 0.81-0.86) and 0.91 (95% CI, 0.88-0.95), respectively. The models also had good calibration performance and clinical usefulness. Conclusions and Relevance: The findings of this diagnostic study suggest that the models developed are suitable for selecting high-risk populations for follow-up decision-making and optimizing the cancer screening process.
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