Study Of Systemic Inflammatory Response Index In Predicting Pathological Remission Of Breast Cancer After Neoadjuvant Chemotherapy

Objective:Take the neutrophil to lymphocyte-to-ratio(NLR),platelet-to-lymphocyte ratio(PLR),lymphocyte to monocyte-to-ratio(LMR),hemoglobin/red cell distribution width ratio(HRR),systemic immune-inflammation index(SII),systemic inflammation response index(SIRI),and pan immune-inflammation value(PIV)as the index,to investigate the predictive efficacy of this method for pathological response after neoadjuvant chemotherapy(NAC)for breast cancer.Methods:Retrospective analysis of clinicopathological data of 172 female breast cancer cases who underwent NAC in parallel with surgery at our hospital from January 2014 to December 2020 was performed,and pathological complete remission(pCR)was used as an index for judging the efficacy of NAC.The cut-off values of NLR,PLR,LMR,SII,SIRI,PIV and HRR levels before chemotherapy were determined by the Youden index of the receiver operating characteristic(ROC)curve,and according to the cut-off values,the inflammatory markers were divided into high level group and low level group,and the correlation with pCR was analyzed by univariate analysis and multivariate logistic regression analysis to select the predictors of pCR,and by the receiver operating characteristic(ROC)curve analysis.Results:A total of 172 patients receiving NAC were included in this study,with an age range of 28 to 72 years,a median age of 52 years,and a pCR rate of24.4%(42/172).Univariate analysis showed that pCR was significantly correlated with histological grade,lymph node status,ER,PR,HER-2 status,NLR,PLR,LMR,SII,SIRI,PIV,and HRR levels(P < 0.05);the low NLR group(< 1.95),low PLR group(< 185.36),low SII group(< 634.04),and low PIV group(<251.81)were observed to have higher pCR rates in breast cancer patients.Multifactorial analysis showed that: histological grade(OR: 3.946,95% CI: 1.130-13.785,P=0.031),HER-2 status(OR: 0.031,95% CI:0.02-0.435,P=0.01),LMR level(OR: 5.448,95% CI: 1.115-26.629,P=0.036),SIRI level(OR: 0.133,95% CI: 0.20-0.893,P=0.033),and HRR level(OR: 34.721,95% CI: 4.377-275.435,P<0.001)were independent predictors of pCR after NAC in breast cancer patients.Breast cancer patients with high histological grade,high HER-2 expression,high LMR(≥3.9),high HRR(≥3.09),and low SIRI(<0.76)were more likely to achieve pCR.incorporating the indicators affecting pCR into the ROC curve for predicting pCR after NAC by plotting logistic models yielded an AUC value of 0.924,95% confidence interval : 0.876-0.971,with a specificity of 83.8% and a sensitivity of 90.5%.Conclusions:1.In breast cancer patients receiving NAC,histological grade,HER-2expression status,LMR,SIRI and HRR levels were independent predictors of pCR after NAC(P<0.05),which could be used as effective reference indicators for predicting PCR after NAC in breast cancer patients.2.Compared with other indicators,SIRI has a better predictive efficacy for pCR.3.Integration of pre-NAC clinicopathological features and LMR,SIRI,and HRR levels can help predict post-NAC pCR.