ArticleInterdisciplinary cardiovascular and thoracic surgery2026
Clinical-Radiomics Signature Predicts Pathologic Complete Response After Neoadjuvant Therapy in Oesophageal Squamous Cell Carcinoma.
Article in Interdisciplinary cardiovascular and thoracic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Non-Operative Management of Esophageal Cancer with Complete Clinical Response After Neoadjuvant Therapy: Current Status and Future Directions.Journal of personalized medicine · 2026Review
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Authors and funding
11 authors.
Funding
Abstract
objectivesNeoadjuvant therapy (NAT) significantly improves the pathologic complete response (pCR) rates in patients with locally advanced esophageal squamous cell carcinoma (ESCC). Emerging evidence suggests that patients with pCR may experience favourable outcomes and could be considered for active surveillance strategies to delay surgery. This study aims to develop a clinical-radiomics model to predict pCR after NAT in ESCC.
methodsWe retrospectively enrolled 236 patients with locally advanced ESCC who received NAT at our centre and randomly assigned them to training and test cohorts (3:2 ratio). Radiomics features were extracted from tumour regions segmented on post-NAT contrast-enhanced computed tomography (CT) scans. After feature selection, a predictive model integrating radiomics and clinical variables was developed using logistic regression and visualized as a nomogram. Model performance was evaluated using area under the curve (AUC), accuracy, sensitivity, and specificity.
resultsThe clinical-radiomics model achieved an AUC of 0.91 (95% confidence interval [CI]: 0.86-0.95), accuracy of 0.84, sensitivity of 0.89, and specificity of 0.81 in the training cohort, and an AUC of 0.84 (95% CI: 0.76-0.92), accuracy of 0.78, sensitivity of 0.84, and specificity of 0.74 in the test cohort. Calibration curves demonstrated good agreement between predicted and observed outcomes, and decision curve analysis confirmed the model's clinical utility.
conclusionsThe clinical-radiomics model accurately predicts pCR following NAT in ESCC and may guide personalized treatment strategies.
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