A nomogram to predict pathological complete response of neoadjuvant systemic therapy in HER2-positive breast cancer based on clinicopathologic characteristics and pretreatment systemic inflammation response index: A dual-center study.

Abstract Purpose: Multiple pretreatment systemic inflammatory markers (SIMs) have been reported as predictors of pathological complete response (pCR) after neoadjuvant systemic therapy (NST) in patients with breast cancer (BC). However, the most significant SIM remains to be conclusively identified, and variations among different molecular subtypes remain unknown. The objective of the study was to identify the most significant SIM in patients with human epidermal growth factor receptor 2 (HER2) positive BC, and to construct a pCR-predictive nomogram combining it with other clinicopathological factors. Methods: We retrospectively reviewed the findings for 240 patients with stage I–III HER2-positive BC who underwent NST and subsequent surgery at Kaohsiung and Taichung Veterans General Hospital from 2011 to 2021. Clinicopathological factors were analyzed by stepwise logistic regression with forward selection. The data were used to construct a nomogram plot for determining the probability of pCR. Results: Among the pretreatment SIMs, only SIRI was significantly related to pCR, with an optimal cutoff value of 1.27 × 10 9 /L. Stepwise logistic analyses indicated that clinical N stage, HER2 immunohistochemistry (IHC) score, hormone receptor status, targeted therapy regimen, and SIRI were independent predictors of pCR, with an area under the curve (AUC) of 0.722. The Hosmer–Lemeshow test and calibration curve revealed that the predictive ability was a good fit to actual observations. A nomogram was constructed based on the logistic model. Conclusions: Pretreatment SIRI < 1.27 is predictive of pCR in HER2-positive BC. Our nomogram could efficiently predict pCR and facilitate clinical decision-making before neoadjuvant treatment.