A combined nomogram based on radiomics and hematology to predict the pathological complete response of neoadjuvant immunochemotherapy in esophageal squamous cell carcinoma

Autor: Yu Yang, Yan Yi, Zhongtang Wang, Shanshan Li, Bin Zhang, Zheng Sang, Lili Zhang, Qiang Cao, Baosheng Li
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: BMC Cancer, Vol 24, Iss 1, Pp 1-12 (2024)
Druh dokumentu: article
ISSN: 1471-2407
DOI: 10.1186/s12885-024-12239-0
Popis: Abstract Background To predict pathological complete response (pCR) in patients receiving neoadjuvant immunochemotherapy (nICT) for esophageal squamous cell carcinoma (ESCC), we explored the factors that influence pCR after nICT and established a combined nomogram model. Methods We retrospectively included 164 ESCC patients treated with nICT. The radiomics signature and hematology model were constructed utilizing least absolute shrinkage and selection operator (LASSO) regression, and the radiomics score (radScore) and hematology score (hemScore) were determined for each patient. Using the radScore, hemScore, and independent influencing factors obtained through univariate and multivariate analyses, a combined nomogram was established. The consistency and prediction ability of the nomogram were assessed utilizing calibration curve and the area under the receiver operating factor curve (AUC), and the clinical benefits were assessed utilizing decision curve analysis (DCA). Results We constructed three predictive models.The AUC values of the radiomics signature and hematology model reached 0.874 (95% CI: 0.819–0.928) and 0.772 (95% CI: 0.699–0.845), respectively. Tumor length, cN stage, the radScore, and the hemScore were found to be independent factors influencing pCR according to univariate and multivariate analyses (P
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