Construction and validation of a dynamic model for individualized prediction of postoperative incisional infection risk score nomogram for breast cancer
LIAN Yaqin
YANG Weijuan
HU Jingjing
ZHU Xiaoyu
WANG Rongrong
Abstract：Objective To construct a nomogram for incisional infections occurring after breast cancer surgery and further validate the model.Methods The data of 877 breast cancer patients admitted from January 2020 to October 2024 were retrospectively extracted and divided into training set(n=614)and validation set(n=263)according to the ratio of 7∶3.The risk factors of postoperative incisional infection in breast cancer were analyzed by using univariate and multivariate Logistic regression,and the nomogram was constructed and internally and externally validated by using R software.Results In the 614 patients with postoperative breast cancer of training set,incisional infection was occurred in 52 patients(8.5%).Surgery time>2 h,normal negative pressure drainage,drainage time≥10 d,postoperative chemotherapy and albumin≤35 g/L were independent risk factors for postoperative incisional infection for breast cancer(P<0.05).The model of the nomgram showed that 86 points for surgery time>2 h,98 points for normal negative pressure drainage,82 points for drainage time≥10 d,100 points for postoperative chemotherapy,and 84 points for albumin≤35 g/L.The model validation showed a C-index of 0.838,and the calibration curve tended to be close to the ideal curve with an area under the curve of 0.815.Conclusion The constructed nomogram model can accurately quantify the risk of incisional infection after breast cancer surgery,which meets the clinical needs for an integrated model.
Keywords：Breast cancerIncisional infectionPredictionRisk factorsNomogram model
Publication Date：2025-01-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 38-43 )