GUAN Guilin , WU Jiaxing , GUO Xiaodie , ZUO Huaiquan
  • 1. Department of Breast surgery, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan 646000, P. R. China;
ZUO Huaiquan, Email: 13982772996@163.com
invasive breast cancer; neoadjuvant therapy; nutrition; immunity; pathological complete response; predictive factor
10.7507/1007-9424.202312045
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Objective To analyze the association between nutritional and immune-related laboratory indices and pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer patients and focused on constructing a combination of laboratory indices to serve as a clinical predictor of pCR after NAC in breast cancer. Methods Retrospectively collected the pre-NAC laboratory indices [albumin (ALB), total cholesterol, triglyceride, high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol, apolipoprotein A- Ⅰ, apolipoprotein B, white blood cell, neutrophil, lymphocyte, monocyte (MON), and platelet ] and clinicopathologic data of 310 patients with invasive breast cancer who had received NAC in the Department of Breast Surgery, Affiliated Hospital of Southwest Medical University, from September 1, 2020 to October 31, 2022. Logistic regression analysis was conducted to determine the correlation between laboratory indices and post-NAC pCR. The combinations of laboratory indices were constructed by simple mathematical operation. The area under the receiver operating characteristic curve (AUC) was used to evaluate the efficacy of different combinations of laboratory indices in predicting pCR and to determine the optimal combination of liboratory indices. Multivariate logistic regression analysis was used to analysis the relevance between clinicopathologic features and post-NAC pCR in breast cancer patients and to determine the independent predictor of post-NAC pCR. Results Among the 310 patients, 49.4% (153/310) of them achieved pCR after NAC. Logistic regression analysis revealed that ALB (Z=5.203, P<0.001) and HDL-C (Z=2.129, P=0.033) were positively correlated with post-NAC pCR, while MON (Z=–4.883, P<0.001) was negatively correlated with post-NAC pCR. The AUC analysis of 6 different combinations of laboratory indices showed that the ALB/MON combination (the optimal combination of liboratory indices) had the highest predictive performance (median AUC=0.708) and was determined to be the neoadjuvant therapy predictive index (NTPI). Multivariate logistic regression analysis showed that estrogen receptor (Z=–3.273, P=0.001), human epidermal growth factor 2 (Z=7.041, P<0.001), Ki-67 (Z=2.457, P=0.014), and NTPI (Z=4.661, P<0.001) were the independent predictors for post-NAC pCR. Conclusion NTPI could serve as a predictive index for post-NAC pCR in patients with breast cancer.