原发性肝癌患者术后癌因性疲乏的影响因素及其预测模型构建.

Objective: To analyze the influencing factors of postoperative cancer-related fatigue (CRF) in patients with primary liver cancer and to construct a prediction model. Methods: 200 primary liver cancer patients who underwent surgical treatment in the First Affiliated Hospital of Hunan Normal University from January 2020 to January 2023 were selected, patients were divided into CRF group (124 cases) and non-CRF group (76 cases) according to the presence or absence of CRF at 3 months after surgical. The factors affecting postoperative CRF in primary liver cancer patients were analyzed by univariate and multivariate logistic regression analysis and to construct its prediction model. The predictive value of the prediction model for postoperative CRF in primary liver cancer patients was analyzed by receiver operating characteristic (ROC) curve. Results: Univariate analysis showed that, the course of disease in CRF group was longer than that in non-CRF group, the Child-Pugh grade B, the Eastern Cooperative Oncology Group (ECOG) score of 1～2 points, adjuvant chemotherapy, medical payment at their own expense and the proportion of depression/anxiety were higher than those in non-CRF group, and the proportion of high school education and above, family monthly income >3 000 yuan and high social support were lower than those in non-CRF group(P<0.05). Multivariate Logistic regression analysis showed that, prolonged course of disease, Child-Pugh grade B, ECOG score of 1～2 points, adjuvant chemotherapy, medical payment at their own expense, depression/anxiety were independent risk factors for postoperative CRF in primary liver cancer patients, family monthly income >3000 yuan and high social support were independent protective factors(P＜0.05). The prediction model equation of postoperative CRF in primary liver cancer patients: Logit (P)=P/1-P=-1.252+0.409×course of disease+0.839×Child-Pugh classification+1.378×ECOG score+1.055×adjuvant chemotherapy+1.476×medical payment method-0.793×family monthly income+0.883×depression/anxiety-1.260×social support. Hosmer-Lemeshaw test P>0.05. ROC curve analysis showed that, the area under the curve of the model for predicting postoperative CRF in primary liver cancer patients was 0.910, the sensitivity was 87.10%, and the specificity was 85.53%. Conclusion: The course of disease, Child-Pugh classification, ECOG score, adjuvant chemotherapy, medical payment method, depression/anxiety, family monthly income and social support are the factors affecting postoperative CRF in primary liver cancer patients, the predictive model base on this has a high predictive value for postoperative CRF in primary liver cancer patients, which may be helpful for early clinical detection and intervention of postoperative CRF in primary liver cancer patients to improve the prognosis of patients. [ABSTRACT FROM AUTHOR]