Analysis Of The Efficacy Of Gamma Knife Radiosurgery In The Treatment Of Brain Metastases From Breast Cancer And Construction Of A Clinical Risk Prediction Model

Objective:A retrospective analysis of the survival status and clinical factors of breast cancer brain metastasis(BCBM)patients treated with Gamma knife radiosurgery(GKS)in our hospital was conducted to explore the therapeutic effects and clinical independent prognostic factors of GKS treatment on BCBM patients.Then,a clinical risk prediction model was constructed to predict the survival and prognosis of BCBM patients treated with GKS based on the results of statistical analysis.Method:Fifty-nine patients with BCBM treated with GKS at the Gamma Knife Treatment Center of the Second Hospital of Shandong University Neurosurgery from May 2016 to January 2023 were selected for a retrospective study;relevant clinical data(age,pathological type,Karnofsky Performance Status(KPS)score at the time of the first treatment,the Breast cancer histological grade,etc.),categorized and summarized as clinical influencing factors;in parallel,the clinical influencing factors were collated.The clinical data of BCBM patients were analyzed by one-way log-rank test and multi-factor Cox regression was used to assess the independent prognostic factors influencing the survival of BCBM patients.Clinical independent influences obtained from multifactorial Cox regression analysis were used to construct clinical risk prediction models.Survival curves were used to validate the veracity and reliability of the clinical risk prediction model in assessing the effect of GKS on OS in patients with BCBM.Time-dependent ROC curves were used to reflect the sensitivity and specificity of the clinical risk prediction model.Decision Curve Analysis(DCA curve),Nomogram,and Calibration curve were then plotted to futher test the clinical risk prediction model.Result:According to the inclusion and exclusion criteria,59 patients with BCBM were included in the study as subjects,and their overall median survival was 25.00 months(95%CI=21.53 months to 28.47 months).The results of the one-way log-rank test showed that KPS score(χ2=4.773,P=0.029),history of radiotherapy for breast cancer(χ2=4.808,P=0.028),and motor dysfunction(χ2=4.808,P=0.005)were statistically significant(P<0.05)factors influencing the treatment effect of GKS on BCBM;according to the results of one-way log-rank test analysis,the relevant clinical factors with P<0.1 were included in the multifactor analysis,and the results of multifactor Cox regression analysis showed that age(P=0.003),KPS score(P=0.002),HER-2 expression status(P=0.008),bone metastasis(P=0.048),breast cancer endocrine therapy(P=0.003),and brainstem metastases(P=0.037)were statistically significant(P<0.05)independent influences on the effect of GKS treatment on BCBM treatment.Based on the results of multifactorial Cox regression analysis,a clinical risk prediction model was constructed and the associated survival curves were plotted.The results showed that there was a statistically significant difference between the survival of BCBM patients in the high-risk group and the low-risk group(P=0.00012),and the survival of BCBM patients included in the high-risk group was significantly lower than that of BCBM patients in the low-risk group.Risk factor plots revealed a gradual decrease in survival of BCBM patients with increasing risk scores.the AUCs at 0.5,1,and 2 years were 0.746,0.808,and 0.826,respectively,indicating that the sensitivity and specificity of the clinical risk prediction model for predicting survival and prognosis of BCBM patients treated with GKS were high,and with increasing time,the accuracy of the prediction of survival and prognosis of BCBM patients also increased gradually with time.DCA curves combined with clinical risk prediction models were used to assess and determine the benefit of interventions for BCBM patients in the high-risk group and to avoid over-intervention(or over-medication)of BCBM patients in the low-risk group.Columnar plots showed significant differences in survival and prognosis between patients with different clinical prognostic factors or high and low risk classes.Calibration curves were then used to verify the reliability of the column line plots.The sensitivity and specificity of the column plots in predicting survival and prognosis of patients with BCBM treated with GKS were further assessed by Log-rank test and ROC curves.Conclusion:GKS treatment for BCBM improved patient survival and increased survival rate;age,KPS score,HER-2 expression status,bone metastasis,breast cancer endocrine therapy,and brainstem metastases were independent factors influencing the treatment effect of GKS treatment on BCBM;a clinical risk prediction model constructed based on the results of multifactorial Cox regression analysis could be used to predict the survival and prognosis of patients with GKS-treated BCBM.