Clinical Trials Update in Resectable Esophageal Cancer

Cancer research · Esophageal cancer

The treatment of resectable esophageal cancer has evolved into a multidisciplinary paradigm centered on multimodality therapy, with recent advances in perioperative chemotherapy, immunotherapy and minimally invasive surgical techniques leading to improved pathologic response rates, disease‑free survival and overall survival.

Esophageal cancer (EC) is a gastrointestinal malignancy associated with a poor prognosis worldwide. This narrative review summarizes recent advances in the application of artificial intelligence in EC, focusing on endoscopic and imaging-assisted diagnosis, prediction of treatment response, and prognostic assessment. Existing studies report promising diagnostic performance of deep learning-based endoscopic image analysis models, with performance approaching that of expert readers in detection of EC and precancerous lesions. Machine learning models integrating clinical information, radiomic features, and selected biomarkers also show promising performance in predicting treatment response and supporting risk stratification. However, most studies are retrospective, single‑center, or regionally confined, with limited external validation, poor model interpretability, and lack of prospective validation, hindering clinical translation. cancer_type_en_canonical":"Esophageal cancer","study_type_en_canonical":"Narrative review","intervention_type_en_canonical":null,"role_in_cancer_search_en_canonical":null,"risk_of_bias_analysis_en_canonical":null,"source_claim_text_original":"Existing studies report promising diagnostic performance of deep learning-based endoscopic image analysis models, with performance approaching that of expert readers in detection of EC and precancerous lesions.",

These developments underline the shift from single‑modality surgery to combined systemic and local treatments, which now improve survival and reduce recurrence in patients with potentially curable esophageal cancer.

Evidence level: Korai humán adat. Kis vagy feltáró emberi adat.

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