Objective To analyze the risk factors of asthenic syndrome in patients with radiotherapy for esophageal cancer,and estab-lish a risk prediction model.Methods A total of 140 patients with esophageal cancer who received radiotherapy in a specialized hospital in Anhui province from April 2020 to March 2023 were selected as the study objects by convenient sampling method.Univariate analysis and lo-gistic regression were used to analyze the risk factors for developing frailty syndrome in patients with esophageal cancer radiotherapy,and the risk prediction model was constructed.Hosmer-Lemeshow was used to test the goodness of fit of the frailty model,and receiver operating char-acteristic(ROC)curve was used to test the prediction effect of the model.Results The incidence of asthenic syndrome in 140 patients with ra-diotherapy for esophageal cancer was 43.57%(62/140).Age,concurrent chemotherapy,swallowing function,anxiety,depression,nutritional risk and self-management level were independent risk factors for the development of the debilitating syndrome(P<0.05).The regression fitting equation was constructed according to the meaningful variables in the multivariate analysis as Logit(P)=-10.374+0.125×age+1.334×concur-rent chemoradiotherapy+0.593×swallowing function+0.967×HADS-A+1.038×HADS-D+1.271×nutritional risk-0.057×self-administered level.Hosmer-Lemeshow test results indicated that the risk prediction model had a good fit(χ2=6.974,P=0.539).Model verification results showed that the area under ROC curve was 0.899,95%CI was(0.847～0.952),the Yodon index was 0.717,the optimal critical value was 0.446,the sensitivity and specificity was 86.9%and 84.8%,respectively,and the actual application accuracy was 85.0%.Conclusion The estab-lished risk prediction model has a good prediction effect,which can provide a reference for clinical staff to identify the risk of debilitating syn-drome in patients with esophageal cancer radiotherapy in early stage and make preventive intervention plans.
Esophageal cancerRadiotherapyFrailty syndromeRisk factorsPrediction model
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