Predictive Analysis Of Inflammatory Markers For Recurrence And Metastasis Of Breast Cancer

Background: From the point of view of all human beings around the world,the incidence of breast cancer(BC)is increasing day by day.With the advancement of modern medicine,the 5-year/10-year survival rate of BC patients has been significantly improved,but the metastasis and/or recurrence of BC are the main reasons that threaten the lives of BCpatients.Currently,BC-related biomarkers are widely studied.However,these biomarkers rely on primary tumor samples,are expensive and complicated in procedures,which limit their application in clinical work.If the indicators that can predict the recurrence and metastasis of breast cancer can be discovered in the current routine examinations,it can bring great significance to clinical diagnosis and treatment.Objective:This study mainly explores the predictive value of the systemic immune-inflammation index(SII),systemic inflammation response index(SIRI),and neutrophil to lymphocyte ratio(NLR),lymphocyte to monocyte ratio(LMR)and platelet to albumin ratio(PLR)before treatment in breast cancer patients with recurrence and metastasis.Explore the correlation between SIRI,SII,NLR,LMR,PLR and the pathological characteristics of breast cancer patients and their ability to predict recurrence and metastasis of breast cancer,and establish a predictive model to guide clinical treatment and follow-up.Methods: Retrospectively analyze the various data of female BC patients who were diagnosed and treated regularly and followed up in the Department of Thoracic Breast Surgery,Taizhou People’s Hospital of Jiangsu Province from August 2015 to February2016;collect the blood routine results of BC patients one week before treatment,and then calculate SIRI,PLR,SII,NLR and LMR value,make receiver operating characteristic curve(ROC)to determine the best cut-off value(cut-off)of SIRI,PLR,SII,NLR and LMR,based on cut-off value,all the BC patientsare divided into low-value group and high-value group,and then compare the data of low-level and high-level BC patients.According to whether breast cancer patients have recurrence or metastasis within 5 years after regular diagnosis and treatment,the subjects were divided into recurrence and metastasis group and non-recurrence and metastasis group.The ki67 positive rate,maximum tumor diameter,SII,estrogen receptor ER,whether there is lymph node metastasis,progesterone receptor PR,TNM grade,pathological type,vascular invasion,human epidermal growth factor receptor 2 HER2,nerve invasion,age,epidermal growth factor receptor EGFR,p53,SIRI,menopause status,PLR,NLR and LMR values ??are included in the univariate analysis to analyze the risk factors of recurrence and/or metastasis of breast cancer patients.The risk factors shown in the univariate analysis were incorporated into the binary logistic multivariate regression analysis to determine the independent influencing factors of recurrence and/or metastasis in breast cancer patients.Then use the R language to incorporate the independent risk factors of multivariate factors into the nomogram to build a model and verify it.Results: A total of 104 breast cancer patients were included in this study,including 41 patients with recurrence and metastasis of breast cancer and 63 patients in the non-recurrence and metastasis group.According to the ROC curve results,the cut-off values of NLR,PLR,LMR,SII,and SIRI are 2.121,149.564,3.714,449.180,1.023 respectively.The results of univariate analysis showed that the pathological type,menopause status,and age of the two groups of BC patients were not significantly different,but the maximum tumor diameter,PR status,whether there was lymph node metastasis,ER status,vascular invasion,TNM classification,HER2 The status,NLR,neural invasion,LMR,p53 expression,EGFR expression,ki67 positive rate,SIRI,PLR and SII were significantly different(P<0.05).Conclusion: 1.Tumor maximum diameter,axillary lymph node metastasis,TNM grade,vascular invasion,neural invasion,ER expression,PR expression,HER2 expression,p53 expression,EGFR expression,ki67 positive rate,NLR,PLR,LMR,SII And SIRI is associated with recurrence and metastasis of breast cancer patients.2.Tumor diameter> 2cm,vascular invasion,p53 negative,high SII and high SIRI can be used as independent factors to assess the high-risk population of breast cancer recurrence and metastasis.3.The prediction model constructed based on independent factors has good predictive ability in the local breast cancer population,and it has certain advantages for predicting the risk of recurrence and metastasis of breast cancer patients.4.To predict breast cancer patients with a higher risk,clinicians can judge whether to strengthen the treatment or follow-up of the patients based on the general conditions and clinical characteristics of the patients.