| Objective:To explore and analyze the main risk factors for postoperative lower limb lymphedema in patients with gynecological malignant tumors.To construct a risk prediction model for lower limb lymphedema in gynecological cancer patients after surgery and validate it.Methods:Convenience sampling was used to select 211 patients with gynecological malignant tumors who underwent surgery in a certain tertiary hospital from July 2018 to July 2022.They were divided into a modeling group(148 cases)and a validation group(63 cases)in a ratio of 7:3.The modeling group was further divided into a lymphedema group(22cases)and a non-lymphedema group(126 cases)based on the occurrence of lower limb lymphedema.Univariate and multivariate logistic regression analyses were used to construct a risk prediction model.The Hosmer-Lemeshow goodness-of-fit test and receiver operating characteristic(ROC)curve were used to evaluate the prediction model in the modeling and validation groups.Results:A total of 211 patients were included in this study(148 in the modeling group and63 in the validation group),with a total of 32 patients(25 in the modeling group and 7 in the validation group)developing lower limb lymphedema,resulting in a prevalence rate of 15.17%.Univariate analysis was conducted on the modeling group,and the results showed that there were statistically significant differences(p<0.05)in BMI,operative duration,methods of surgery,intraoperative blood loss,number of dissected lymph nodes,postoperative radiotherapy,lymphatic metastasis and FIGO tumor staging comparison.Results of multi-factor logistic regression analysis show that abnormality in BMI has the statistical significance for lymphedema of lower limbs for patients with gynecological malignant tumor.Compared with patients with a normal weight(BMI:18.5~24.9),obese patients(BMI≥30)have a higher risk of lymphedema of lower limbs(OR=113.96,95%CI:12.06~1076.875).Also,different approaches of operation have the statistical significance for lymphedema of lower limbs for patients with gynecological malignant tumor.Compared with patients undergoing laparotomy,patients undergoing the laparoscopic surgery(OR=0.023,95%CI:0.002~0.282)have a lower risk for lymphedema of lower limbs.Besides,total retrieved lymph nodes(OR=10.861,95%CI:2.735~43.133)post-operation radiotherapy(OR=26.983,95%CI:6.263~116.247),duration of operation(OR=4.577,95%CI:1.124~18.632),FIGO staging(OR=16.217,95%CI:3.938~66.783)all have statistical significance for lymphedema of lower limbs for patients with gynecological malignant tumor.In summary,BMI,approach of operation,duration of operation,total retrieved lymph nodes,post-operation radiotherapy and FIGO staging are all independent factors of risk for lymphedema of lower limbs for patients with gynecological malignant tumor.Verifying the prediction model showed that the area(AUC)under ROC curve of the modeling group was 0.934(p<0.001,95%CI:0.887~0.980),the Youden index was0.746,the sensitivity of the prediction model was 0.813,and the specificity was 0.467.Hosmer-Lemeshow goodness of fit test was used to evaluate the modeling group,and the result showed thatχ~2=11.555,p=0.172(>0.05),and the prediction probability was 93.8%.The area under ROC curve(AUC)of the verification group was 0.931(p<0.001,95%CI:0.879~0.983),the Youden index was 0.721,the sensitivity of the prediction model was0.864,and the specificity was 0.443.Hosmer-Lemeshow test showed thatχ~2=2.087,p=0.780(>0.05),and the prediction probability was 90.5%.Therefore,the model has good reliability.Conclusion:The risk prediction model for this research includes 6 independent factors of risk,namely BMI,approach of operation,duration of operation,total retrieved lymph nodes,post-operation radiotherapy and FIGO staging.The constructed model sees a good effect and can effectively predict the occurrence of lower limb lymphedema after gynecological malignant tumor surgery,thus providing a basis for early clinical screening of lower limb lymphedema(LLL)high-risk patients and early preventive intervention measures for nursing staff. |