High C-reactive protein is associated with the efficacy of neoadjuvant chemotherapy for hormone receptor-positive breast cancer

Abstract

C-reactive protein (CRP) is a nonspecific biomarker for systemic inflammatory response and is linked to the prognosis of breast cancer (BC); however, few studies have investigated the correlation between CRP and the effectiveness of neoadjuvant chemotherapy treatment for BC. We recruited 177 patients with BC who underwent neoadjuvant chemotherapy in our clinical trial. the median CRP level (0.24 mg/L), patients were categorized into high and low groups. We examined the relationship between CRP levels and various clinicopathological factors, including pathological complete response (pCR), using the chi-square test or Fisher exact test. Furthermore, we evaluated the predictive capacity of CRP for different molecular subtypes by constructing receiver operating characteristic curves. To identify the independent variables associated with pCR, we conducted logistic regression multivariate analysis. No association was found between C-reactive levels at baseline and pCR rates. CRP level was significantly associated with higher body mass index, and the high CRP group had more overweight patients (47.06% vs. 16.30%, P < .001). In hormone receptor-positive patients, the high CRP group demonstrated a significantly higher pCR rate (OR = 4.115, 95% CI: 1.481-11.36, P = .009). The areas under the curve was 0.670 (95% CI: 0.550-0.792, P < .001). Multivariate logistic analysis showed that the CRP level was a significant independent predictor of pCR (OR = 5.882, 95% CI: 1.470-28.57, P = .017). High CRP levels were found to be associated with a higher pCR rate, indicating their independent predictive value in determining the efficacy of neoadjuvant chemotherapy in hormone receptor-positive BC patients.

Figure 1.

Selection of evaluable BC patients with NACT grouped by CRP for this study. BC = Breast cancer, CRP = C-reactive protein, NACT = neoadjuvant chemotherapy treatment.

Figure 2.

Relationship between CRP levels and pCR rates and ROC curves of CRP prediction for different molecular subtypes. CRP = C-reactive protein, pCR = pathological complete response, ROC = receiver operating characteristic.

Figure 3.

Forest plot of univariate and multivariate logistic analysis.