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Updated: Jun 4, 2025

Modeling Oral-Esophageal Squamous Cell Carcinoma in 3D Organoids
Published on: December 23, 2022
Constructing individualized follow-up strategies for locally advanced esophageal squamous cell carcinoma patients
Yibin Cai1, Jianming Ding2, XiaoJun Cai2
1Department of Thoracic Surgery, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China. caiyibin@fjmu.edu.cn.
Abstract:
The aim of this study was to explore the high-risk factors for recurrence in patients with locally advanced esophageal squamous cell carcinoma (ESCC) undergoing definitive chemoradiotherapy or radiotherapy (dCRT or dRT). Conditional survival (CS) was used to evaluate the dynamic survival and recurrence risk of patients after treatment, and individualized monitoring strategies were developed for patients. Logistic regression analysis was performed to determine independent recurrence risk factors. Calibration curves and receiver operating characteristic (ROC) curve were used to evaluate nomogram models. Kaplan-Meier curves were used to compare survival rates in different groups and to calculate CS rate. A total of 677 patients were included. Multivariate logistic analyses demonstrated that chemotherapy cycles, tumor length, body mass index (BMI), platelet-lymphocyte ratio (PLR), and lymphocyte-monocyte ratio (LMR) were independent recurrence risk factors (p < 0.05). Subsequently, we constructed nomogram models to predict recurrence and risk stratification. Kaplan-Meier curves showed that conditional locoregional recurrence-free survival and distant metastasis-free survival of patients in different risk groups and clinical stages progressively increased with survival time, whereas local recurrence and distant metastasis annual recurrence rates decreased yearly with increasing survival time. Finally, we developed an individualized follow-up strategy based on CS at different frequencies. Individualized follow-up strategies developed on the basis of CS can better monitor the changes in patients' conditions and contribute to timely salvage treatment and rational allocation of healthcare resources.
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