Affiliation:
1. Xiamen Hospital of Traditional Chinese Medicine, Peking University Third Hospital
2. Peking University Third Hospital
Abstract
Abstract
Objective:This study aimed to develop a model utilizing ultrasonic characterizations and clinical indicators and assess its effectiveness in predicting refractory diffuse large B-cell lymphoma (R DLBCL).
Methods:This study enrolled a total of 140 cases for analysis. Following histopathological examination,ultrasound, positron emission tomography/computed tomography, and standard chemotherapy,the patients were categorized into either the refractory group or non-refractory group based on the Lugano criteria. Differences in clinicopathological characteristics,ultrasonic characterizations,maximum standardized uptake values and laboratory indexes were assessed . The diagnostic efficacy of the predictive model was analyzed through the construction of a receiver operating characteristic (ROC) curve .
Results:In the univariate analysis,statistically significant differences were observed in lesion diameter, lactate dehydrogenase levels, margin blur , peripheral tissue echo enhancement, stage, International Prognostic Index score, and bone marrow involvement between the refractory group and non-refractory groups (P < 0.05). Multifactor analysis identified margin blur and peripheral tissue echo enhancement as independent predictors. The establishment of the risk prediction model histogram through multivariate logistic regression analysis yielded an area under the ROC curve of 0.773, indicative of the prediction models robust differentiation capabilities . In the decision curve analysis,configuring threshold probability to 42.2% resulted in a clinical net benefit rate of 23.5% .
Conclusion:The prediction model of the R DLBCL prediction model,amalgamating ultrasonic characterizations and clinical indicators ,proves instrumental in identifying high-risk DLBCL groups .This identification holdssignificant value for the tailored selection of personalized treatment strategies.
Publisher
Research Square Platform LLC