Constructing a Risk Model for Postoperative Recurrence of Endometriosis Based on the SMOTE Algorithm
Objective To investigate the construction of a risk model for postoperative recurrence of endometriosis(EMs)based on the synthetic minority over-sampling technique(SMOTE)algorithm.Methods A total of 148 patients with EMs who underwent conservative laparoscopic conservative surgery from January 2017 to March 2023 were retrospectively collected as observation subjects,and the patients with EMs were divided into a recurrence group(30 cases)and a non-recurrence group(118 cases)accord-ing to their postoperative recurrence.The data of the subjects were retrospectively analyzed,and the risk factors for postoperative recurrence of EMs patients were screened by using univariate and logistic regres-sion analyses,and then the original dataset of the influencing factors was reconstructed by the SMOTE algorithm to derive a risk warning model and validate its predictive efficacy.Results There were 30 cases of postoperative recurrence in 148 cases of EMs,with an incidence rate of 20.27％;there was no statisti-cally significant difference in the comparisons of body mass index(BMI),duration of disease,preoperative complications,history of previous gynecological surgeries,preoperative deliveries,diameter of cysts,and polycysticity between the two groups(P＞0.05);there was a statistically significant difference in age,preoperative dysmenorrhea,side of lesion,rAFS stage,postoperative pregnancy,and postoperative adju-vant medication(P＜0.05);logistic regression analysis showed that younger age,preoperative history of dysmenorrhea,bilateral lesions,postoperative pregnancy,and postoperative adjuvant medication not used were the risk factors for postoperative recurrence in patients with EMs(P＜0.05);the original early warning model was obtained,the early warning model based on the SMOTE algorithm,and the results of H-L test showed that the model fit was good.Analyzing the ROC curves of the early warning model resulted in the AUC of 0.854 and 0.869,with a DeLong P-value of 0.048(P＜0.05).Conclusion Both the early warning models built on the original data based on younger age,preoperative history of dysmenor-rhea,bilateral lesions,postoperative pregnancy,and postoperative non-use of adjuvant drug therapy,and the SMOTE algorithm have high predictability,and medical staff can make effective interventions based on them to deal with the postoperative recurrence of patients with EMs.
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