Treatment resistance, recurrence, and metastasis of breast cancer remain critical issues affecting long-term patient survival. Chronic psychological stress may act as a host biological driver of breast cancer treatment resistance rather than a mere comorbidity. Through the sustained activation of the sympathetic nervous system and the hypothalamic-pituitary-adrenal axis, also referred to as the "brain-tumor axis", stress signaling reshapes inflammatory, immune, and metabolic networks within the tumor microenvironment and thereby influences chemotherapy, endocrine therapy, anti-HER2 therapy, immunotherapy, and radiotherapy. Current evidence indicates that the key pathways with translational potential are mainly the β-adrenergic axis and the glucocorticoid receptor (GR) pathway. The former is more involved in amplifying inflammatory responses, promoting immunosuppression and metastasis, whereas the latter is closely associated with anti-apoptosis, maintenance of tumor stemness, and reprogramming of estrogen receptor function. This review focuses on the discrepancies in evidence regarding these pathways between population-based studies and preclinical models, and discusses clinically operable non-pharmacologic interventions such as cognitive behavioral stress management, nurse navigation and treatment adherence support, and exercise interventions during the neoadjuvant phase. Although high-level evidence for direct survival benefit remains limited, these interventions have shown favorable effects on cortisol levels, depressive symptoms, quality of life, adherence, relative dose intensity, and some biology-related intermediate endpoints, making them valuable complementary approaches in comprehensive breast cancer management.

Objective To explore the predictive value of CT image texture analysis for early enlargement of hypertensive intracerebral hemorrhage.Methods One hundred and eight patients with hypertensive intracerebral hemorrhage were divided into enlarged hematoma group (positive group)and non-enlarged hematoma group (negative group),according to whether the volume of hematoma on 24 h follow up CT scan was more than 30% or 6 mL of the baseline CT.Phillis Radiomics Tool V93 software was used to segment the hematoma on CT plain scan images of two groups,four features of first-order and three of gray-level co-occurrence matrix (GLCM),thirteen of gray-level size zone matricx (GLSZM)and eleven of gray-level run-length matricx (GLRLM)were obtained.The differences of thirty-one texture features between the two groups were compared.The ROC curves of the features with statistical differences were analyzed.The independent predictors of early enlargement of intracerebral hemorrhage were screened by Logistic multivariate regression model.Results Among the one hundred and eight patients,twenty-eight were positive group and eighty were negative group.Skewness and long run low gray-level emphasis (LRLGE)in positive group were significantly higher than those in negative group (P＜0.05).There was no significant difference in the remaining twenty-nine features between the two groups (P＞0.05).ROC curve analysis showed that the AUC of Skewness,LRLGE and their combined diagnosis were 0.634,0.814 and 0.828,respectively.The independent variables were screened by stepwise regression analysis.The LRLGE (OR＝1.238,95%CI＝1.009－1.51 9,P＜0.05)was selected as the regression model, suggesting that LRLGE was an independent predictor of the early enlargement of intracerebral hemorrhage.Conclusion Texture analysis of CT images is helpful to predict the early enlargement of hypertensive intracerebral hemorrhage,and LRLGE based on GLRLM algorithm can be used as an independent predictor.