Development and validation of a prediction model for malnutrition risk in postoperative patients with esophageal cancer

Guo Cuicui; Ding Yanhong; Wang Yingzhi; Zhuang Ye; Huang Ying; Liang Feng; Shen Hui

doi:10.16689/j.cnki.cn11-9349/r.2026.02.017

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Electronic Journal of Metabolism and Nutrition of Cancer ›› 2026, Vol. 13 ›› Issue (2) : 299-309. DOI: 10.16689/j.cnki.cn11-9349/r.2026.02.017

Original Articles

Development and validation of a prediction model for malnutrition risk in postoperative patients with esophageal cancer

¹Guo Cuicui, ¹Ding Yanhong, ¹Wang Yingzhi, ¹Zhuang Ye, ²Huang Ying, ¹Liang Feng, ¹Shen Hui

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Abstract

Objective To develop a predictive model for postoperative malnutrition in patients with esophageal cancer. Method A total of 295 patients who underwent esophageal cancer surgery at The Second People's Hospital Of Huai'an from January 2021 to January 2025 were retrospectively enrolled and randomly divided into a development cohort and a validation cohort at a 7:3 ratio. Based on the occurrence of postoperative malnutrition, patients in the development cohort were further divided into a malnutrition group(n=124) and a normal nutrition group(n=82). Clinical data were collected and compared between the two groups. Logistic regression analysis was used to identify independent risk factors for postoperative malnutrition and to construct a predictive model. The model's performance was evaluated using the receiver operating characteristic (ROC) curve, area under the curve (AUC), calibration curve, and decision curve analysis. Result Baseline characteristics were comparable between the development and validation cohorts (P>0.05). In the development cohort, 124 patients developed postoperative malnutrition (malnutrition group), while 82 patients did not (normal nutrition group). Compared to the normal nutrition group, the malnutrition group had a higher proportion of patients with swallowing dysfunction and higher Hamilton depression rating scale (HAMD) scores, but a lower proportion of patients meeting nutritional behavior targets and lower strategies used by people to promote health (SUPHH) scores. Logistic regression analysis identified swallowing dysfunction and high HAMD scores as significant risk factors for postoperative malnutrition (P<0.05), while meeting nutritional behavior targets and high SUPHH scores were protective factors (P<0.05). A predictive model was constructed based on these factors. Validation in the validation cohort showed that the model had good discrimination, with an AUC of 0.938 in the development cohort and 0.964 in the validation cohort. The calibration curves for both cohorts demonstrated good agreement between predicted probabilities and actual observations, with minimal deviation from the ideal curve. Decision curve analysis indicated that the predictive model provided a high net benefit within a threshold probability range of 0.3-0.6 in both cohorts. Conclusion Swallowing dysfunction and high HAMD scores are independent risk factors for postoperative malnutrition in patients with esophageal cancer, whereas meeting nutritional behavior targets and high SUPHH scores are protective factors. The predictive model constructed based on these factors exhibits good predictive performance.

Key words

Esophageal cancer / Malnutrition / Influencing factors / Predictive model / Calibration curve / Decision curve analysis / Swallowing dysfunction / Nutritional behavior

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Guo Cuicui, Ding Yanhong, Wang Yingzhi, Zhuang Ye, Huang Ying, Liang Feng, Shen Hui. Development and validation of a prediction model for malnutrition risk in postoperative patients with esophageal cancer[J]. Electronic Journal of Metabolism and Nutrition of Cancer. 2026, 13(2): 299-309 https://doi.org/10.16689/j.cnki.cn11-9349/r.2026.02.017

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