The predictive value of systemic immune-inflammatory markers before and after treatment for pathological complete response in patients undergoing neoadjuvant therapy for breast cancer: a retrospective study of 1994 patients.

Purpose: Systemic immune-inflammatory markers have a certain predictive role in pathological complete response (pCR) after neoadjuvant treatment (NAT) in breast cancer. However, there is a lack of research exploring the predictive value of markers after treatment.

Methods: This retrospective study collected data from 1994 breast cancer patients who underwent NAT. Relevant clinical and pathological characteristics were included, and pre- and post-treatment complete blood cell counts were evaluated to calculate four systemic immune-inflammatory markers: neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune-inflammation index (SII). The optimal cutoff values for these markers were determined using ROC curves, and patients were classified into high-value and low-value groups based on these cutoff values. Univariate and multivariate logistic regression analyses were conducted to analyze factors influencing pCR. The factors with independent predictive value were used to construct a nomogram.

Results: After NAT, 383 (19.2%) patients achieved pCR. The area under the ROC curve is generally larger for post-treatment markers compared to pre-treatment markers. Pre-treatment NLR and PLR, as well as post-treatment LMR and SII, were identified as independent predictive factors for pCR, along with Ki-67, clinical tumor stage, clinical lymph node stage, molecular subtype, and clinical response. Higher pre-NLR (OR = 1.320; 95% CI 1.016-1.716; P = 0.038), pre-PLR (OR = 1.474; 95% CI 1.058-2.052; P = 0.022), post-LMR (OR = 1.532; 95% CI 1.175-1.996; P = 0.002), and lower post-SII (OR = 0.596; 95% CI 0.429-0.827; P = 0.002) are associated with a higher likelihood of achieving pCR. The established nomogram had a good predictive performance with an area under the ROC curve of 0.754 (95% CI 0.674-0.835).

Conclusion: Both pre- and post-treatment systemic immune-inflammatory markers have a significant predictive role in achieving pCR after NAT in breast cancer patients. Indeed, it is possible that post-treatment markers have stronger predictive ability compared to pre-treatment markers.