Construction and validation of chemotherapy resistance prediction model for ovarian cancer
- VernacularTitle:卵巢癌化疗耐药预测模型的建立及效果评价
- Author:
Ping YU
1
;
Min ZHOU
;
Dan SU
Author Information
- Keywords: ovarian neoplasms; chemoradiotherapy; drug resistance,neoplasm; Logistic models; nomograms
- From: Tianjin Medical Journal 2024;52(11):1177-1183
- CountryChina
- Language:Chinese
- Abstract: Objective To investigate the influencing factors on the occurrence of chemo-resistance after postoperative chemotherapy in ovarian cancer patients,and construct a prediction model and evaluate the model efficacy.Methods The clinical data of 407 ovarian cancer patients who underwent tumor cytoreduction and chemotherapy were collected.At the endpoint of follow-up,patients were divided into the recurrence group(n=363)and the non-recurrence group(n=44).Patients in the recurrence group were re-divided into the resistant group(n=59)and the sensitive group(n=304)according to the chemotherapy resistance.Variables were screened using univariate analysis and Lasso regression.Logistic model was established.R software was used to build a nomogram and evaluate it.Results Compared with the non-recurrence group,the age of the recurrence group was lower,and the proportion of low differentiation and the proportion of FIGO stage Ⅲ-Ⅳwere higher(P＜0.05).Compared with the sensitive group,in the resistant group,lymph node enlargement,non-serous pathological type,the proportion of FIGO stage Ⅲ-Ⅳ,positive rate of immunohistochemical recombinant proteins Ki-67,protein 53(P53),vascular endothelial growth factor(VEGF)and nephroblastoma gene 1(WT-1)were higher.The change rate of glycan antigen 125(CA125)before and after surgery,the change rates of Rome index(ROMA)(premenopausal)before and after chemotherapy and the positive rate of immunohistochemical protein 16(P16)were lower(P＜0.05).The eight variables screened by Lasso regression were used as independent variables for Logistic regression.Results showed that there were enlarged lymph nodes in preoperative CT imaging,the pathological type was non-serous,the FIGO stages were Ⅲ-Ⅳ,and immunohistochemistry results of WT1 and VEGF were positive.P16 negative was an independent risk factor for chemo-resistance in ovarian cancer patients.Accordingly,the area under the receiver operating characteristic curve of the nomogram model established was 0.837(0.783-0.880),and the result of Hosmer-Lemeshow test indicated a good model fit.The calibration curve and the clinical decision curve(DCA)suggested a high calibration and clinical use of the model.Conclusion We have successfully constructed a Logistic model of chemotherapy resistance in ovarian cancer based on clinical data,and the nomogram prediction model can effectively assess the risk of chemo-resistance in ovarian cancer.
