前列腺癌放疗基准标志物置入稳定性危险因素分析及Nomogram预测模型构建OA

Objective To explore the risk factors affecting the stability of gold fiducial markers(GFM)after implantation in prostate cancer(PCa)image guided radiotherapy(IGRT)and construct a Nomogram prediction model.Methods A total of 500 patients who underwent PCa IGRT and had GFM implanted in the First Affiliated Hospital of Hebei North University from January 2016 to June 2024 were selected as the research subjects and divided into the modeling group(n=300)and the validation group(n=200).The stability of GFM after implantation was evaluated by the markers spacing.According to the evaluation results,the patients in the modeling group were divided into the GFM stable group(n=200)and the unstable group(n=100).The Logistic regression program was compiled using the R language 4.0"rms"software package to analyze the independent risk factors affecting stability.Substitute the factorized independent risk factors into the Nomogram prediction model construction program and draw the Nomogram graph;The internal verification of the model was accomplished by using the concordance index(C-index),calibration curve and decision curve.The area under the receiver operating characteristic curve(AUC)was used to evaluate and compare the efficacy of the model in predicting the stability of the modeling group and the validation group,and the external validation of the model was completed.Results There was no statistically significant difference in the baseline data between the modeling group and the validation group(P>0.05).There were statistically significant differences in baseline data such as prostate specific antigen,gleason score,prostate volume(PV),the number of GFM implants,implantation sites,and the ratio of surface distance along the central axis between the stable group and the unstable group(P<0.1).PV<25 mL,the number of GFM implants(4 markers),the implantation site of GFM(bottom),and the ratio of the surface distance of the central axis of GFM(3∶1)were independent risk factors affecting the stability after GFM implantation.Internal verification:the C-index of the Nomogram model for predicting stability was 0.846(95%CI:0.692-0.931),with a threshold>0.25.The calibration curve showed good consistency between the observed values and the predicted values,and the decision curve indicated that the model could provide clinical net benefits and was higher than each independent predictor.External verification:the AUC values of the Nomogram model for predicting the stability of the modeling group and the verification group were both higher than those of each independent predictor.There was no statistically significant difference in the AUC between the two groups(P=0.446>0.05),and the curve fitting was relatively ideal(P=0.257>0.05).Conclusion The Nomogram model has an ideal predictive effect on the stability after GFM implantation in PCa IGRT,which can provide certain references for improving the safety of GFM application.