Introduction

Oncology Letters

1792-1074 1792-1082

D.A. Spandidos

10.3892/ol.2025.15112

OL-30-1-15112

Articles

Factors influencing pathological complete response to neoadjuvant chemotherapy in resectable breast cancer: A retrospective study

Kang

Jian

1 * Xiong

Huifen

1 * Jiang

Xiaoliu

1 Huang

Zhaohui

1 Guo

Yonghong

2 Cao

Yali

3 Ding

Jingxian

1Department of Radiation Oncology, The Breast Cancer Institute, Nanchang People's Hospital, Nanchang, Jiangxi 330025, P.R. China 2Department of Radiation Oncology, Affiliated Rehabilitation Hospital of Nanchang University, Nanchang, Jiangxi 330006, P.R. China 3Department of Breast Surgery, The Breast Cancer Institute, Nanchang People's Hospital, Nanchang, Jiangxi 330025, P.R. China

Correspondence to: Professor Yali Cao, Department of Breast Surgery, The Breast Cancer Institute, Nanchang People's Hospital, 1268 Jiuzhou Street, Nanchang, Jiangxi 330025, P.R. China, E-mail: caoyali1964@126.com Professor Jingxian Ding, Department of Radiation Oncology, The Breast Cancer Institute, Nanchang People's Hospital, 1268 Jiuzhou Street, Nanchang, Jiangxi 330025, P.R. China, E-mail: jingxianding10@fudan.edu.cn *

Contributed equally

072025

27052025

30 1

366

19112024 01052025

2025

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Neoadjuvant chemotherapy (NAC) is widely used to treat breast cancer and a pathological complete response (pCR) following NAC is associated with an optimal prognosis; however, pCR rates vary significantly. In the present study, the effects of clinicopathological factors and the administration of different taxanes on pCR rates in patients with resectable breast cancer were assessed. A total of 552 patients with breast cancer who received NAC between May 2019 and June 2024 were included in the present study. The clinicopathological traits of the patients were retrieved from medical records and their association with the pCR rate was evaluated using univariate and multivariate regression analyses. The efficacy of nanoparticle albumin-bound (Nab)-paclitaxel, docetaxel and paclitaxel liposomes in different subtypes of breast cancer were further evaluated. A total of 189 of 552 (34.2%) patients achieved pCR following NAC. The pCR rate varied significantly among different molecular subtypes as follows: 58.9% (96/163), 40.7% (37/91), 35.6% (37/104) and 9.8% (19/298) among patients with hormone receptor (HR) negative (−) human epidermal growth factor receptor 2 (HER2) positive (+), HR⁺HER2⁺, HR⁻HER2⁻ and HR⁺HER2⁻ breast cancer, respectively. The factors estrogen receptor (ER), progesterone receptor and HER2 status, Ki-67 index and taxane regimen were all significantly associated with pCR in the univariate analysis. In the multivariate regression analysis, ER⁻, HER2⁺, Ki-67 index ≥30% and Nab-paclitaxel were independent predictors of pCR. The multivariate regression analysis model had an area under the receiver operating characteristic curve area under the curve of 0.774 (95% confidence interval, 0.735–0.813). The pCR rates were 41.3, 38.2 and 25.1% among the Nab-paclitaxel, docetaxel and paclitaxel liposome groups, respectively. Patients with ER⁻, HER2⁺, Ki-67 index ≥30% were associated with high pCR rates. Moreover, patients who received Nab-paclitaxel and docetaxel were more likely to achieve pCR compared with paclitaxel liposomes, particularly for those with HER2⁺ and HR⁻HER2⁻ statuses. In conclusion, molecular subtypes (ER/HER2 status, high Ki-67) and different taxanes significantly influence pCR likelihood. Nab-paclitaxel and docetaxel were identified as effective taxanes, highlighting their potential clinical preference, especially in HER2⁺ and HR⁻HER2⁻ breast cancer.

breast cancer neoadjuvant chemotherapy taxane pathological complete response

National Natural Science Foundation of China

82060482

Natural Science Foundation of Jiangxi Province

20171BAB205057

The present study was supported by grants from the National Natural Science Foundation of China (grant no. 82060482) and the Natural Science Foundation of Jiangxi Province (grant no. 20171BAB205057).

Introduction

Breast cancer is one of the most common cancer types worldwide, including in China; it has an incidence rate of ~60 cases in 10,000, which ranks second among all cancer types and mortality rate of 11 in 10,000 cases, which ranks fifth among female tumors (1,2). The incidence of breast cancer continues to rise; it is estimated that numerous people will be diagnosed with breast cancer in the next decades (3). Neoadjuvant chemotherapy (NAC), initially introduced in the 1970s, has become a widely employed therapeutic approach for patients with operable and locally advanced breast cancer (4). NAC has demonstrated efficacy in improving the rate of breast-conserving surgery and obviating the need for axillary lymph node dissection via tumor downstaging, particularly among patients with human epidermal growth factor receptor 2 (HER2) positive (+) status (5–7). Furthermore, NAC can provide valuable information on the drug sensitivity of diverse chemotherapy regimens, thereby facilitating the guidance of subsequent treatment strategies (8).

Pathological complete response (pCR) rate is the standard for evaluating the efficacy of NAC. The pCR rate among different subtypes of breast cancer ranges from 2 to 68% (9). The prognosis of patients achieving pCR is significantly improved compared with that of patients with residual cancer burden, leading to prolonged survival and reduced risk of distant metastasis (10). For patients with invasive breast cancer, such as triple-negative and HER2⁺ types, attaining a pCR is closely associated with long-term clinical benefit (11). The prediction of the patients who will achieve pCR could guide personalized treatment based on clinical and pathological factors. Numerous studies have explored the relationship between patient characteristics, clinical tumor stage, lymph node status, HER2 status and hormonal receptor status with pCR in patients with breast cancer who have been treated with NAC (12–14). A previous retrospective study indicated that age and subtypes of breast cancer were associated with pCR; following NAC, patients with younger age, luminal B2 HER2⁺, HER2 upregulation and triple-negative subtype were more likely to achieve pCR (15). By contrast, another study indicated that only clinical tumor stage, progesterone receptor (PR) negative (−) status and HER2⁺ status were associated with pCR, while age, clinical lymph node stage, estrogen receptor (ER) status and Ki-67 index indicated no significant correlation (16). Furthermore, the findings of a real-world study involving 7,711 patients differed from those reported in the aforementioned study, as clinical lymph node stage, ER, PR, HER2 status, Ki-67 index and NAC treatment cycle correlated with pCR (17). The findings from various studies regarding the factors influencing pCR exhibit considerable variability. Therefore, additional research is required to clarify the factors influencing pCR.

Anthracycline plus taxane regimens serves as the cornerstone regimen for both neoadjuvant and adjuvant treatment of breast cancer, effectively reducing recurrence and mortality (18). Taxanes are antitumor drugs isolated from plants; it includes mainly paclitaxel, docetaxel, nanoparticle albumin-bound (Nab)-paclitaxel and paclitaxel liposome, which are essential agents used in NAC regimens (19). The National Comprehensive Cancer Network guidelines (version 3; 2024) (20) recommend paclitaxel and docetaxel as preferred taxane agents and Nab-paclitaxel which may be substituted with paclitaxel or docetaxel due to medical necessity (such as a hypersensitivity reaction). Paclitaxel is the standard drug for NAC used for breast cancer; however, paclitaxel injection can cause severe allergic reactions in 10–40% of patients (21). Due to these side effects, Nab-paclitaxel, liposomal paclitaxel and docetaxel have emerged as alternatives (18,22). Although the toxicity profiles of Nab-paclitaxel and paclitaxel liposomes are reduced, the differences in the efficacy of Nab-paclitaxel, paclitaxel liposomes and paclitaxel and docetaxel in breast cancer are currently uncertain. Therefore, additional studies are required to confirm their efficacy in NAC.

The present study aimed to evaluate clinicopathological data collected from patients with breast cancer following NAC to analyze the associations of age, tumor location, clinical stage, lymph node involvement, ER, PR, HER2 status, Ki-67 index and taxane regimen with pCR rate. Furthermore, the efficacy of Nab-paclitaxel, docetaxel and paclitaxel liposomes was evaluated in different subtypes of breast cancer following NAC.

Materials and methods <sec> <title>Patient selection

In July 2024, medical records of patients with breast cancer who were treated with NAC and adjuvant radiotherapy in Nanchang People's Hospital (Nanchang, China) and Affiliated Rehabilitation Hospital of Nanchang University (Nanchang, China) during May 2019 and June 2024 were reviewed. The present study included a total of 552 patients with invasive breast cancer who were diagnosed by core needle biopsy and received NAC and radiotherapy during this period. The clinical stage of all patients prior to NAC was evaluated using breast ultrasonography, chest computerized tomography and breast magnetic resonance imaging. All patients underwent lumpectomy or mastectomy and axillary lymph node dissection following completion of the planned NAC dosage. Patients with bilateral breast cancer or prior history of cancer were excluded from the present study. The present study was approved by the Institutional Review Board ethics committee of Nanchang People's Hospital (approval no. K-kt2024005; Nanchang, China) from which the patients were enrolled. The requirement for patient approval or written informed consent was waived due to the retrospective nature of the present study.

NAC regimens

The NAC regimens were selected according to the subtypes of breast cancer. Breast cancer samples with ≥10% of ER or PR positive tumor nuclei were defined as ER⁺ or PR⁺, since primary breast cancer with ER 1–9% positivity shows similar clinical behavior to ER 1% (23). HER2 protein upregulation was assessed using immunohistochemical analysis; 3 or 2+ with HER2 gene amplification assessed using in situ hybridization was defined as HER2⁺. The treatment options for patients with HR⁺HER2⁻ and HR⁻HER2⁻ included four cycles of anthracyclines and cyclophosphamide followed by four cycles of taxanes (AC-T), six cycles of taxanes, anthracyclines and cyclophosphamide (TAC) and six cycles of taxanes and carboplatin (Tcb). The regimens for patients with HER2⁺ breast cancer were composed of four cycles of anthracyclines and cyclophosphamide followed by four cycles of taxanes with trastuzumab or trastuzumab and pertuzumab (AC-TH/AC-THP), six cycles of taxanes and carboplatin with trastuzumab or trastuzumab and pertuzumab (TcbH/TcbHP) and six cycles of taxanes with trastuzumab and pertuzumab (THP). Regarding taxane-based regimens, liposomal paclitaxel was administered in both weekly and tri-weekly regimens.

Assessment of pathological response

pCR was defined as the absence of invasive disease in both primary tumor and lymph nodes and the presence of in situ cancer following treatment in the absence of residual invasive disease (ypT0/is ypN0), as per the 8th Edition of American Joint Committee on Cancer Staging Manual (24).

Statistical analysis

The data were analyzed using the SPSS software (version 23; IBM Corp.). Categorical variables age, tumor location, clinical tumor stage, Ki-67 index, molecular subtypes of breast cancer, chemotherapy regimens, taxanes and lymph node, ER, PR and HER2 status were described by percentage. The differences in pCR rate for these variables was analyzed using the χ² or Fisher's exact tests. With the exception of the subtypes of breast cancer and the chemotherapeutic regimens, the other variables were considered as alternative variables with P<0.05 in the univariate analysis. In multivariate analysis, binary regression analysis was used to analyze the role of these variables in predicting pCR. A prediction model was established using the results of the multivariate logistic regression analysis, and receiver operating characteristic (ROC) curve analysis was used to assess the prediction power of the model. P<0.05 was considered to indicate a statistically significant difference. All charts were generated using the GraphPad Prism software (version 9.5; Dotmatics).

Results <sec> <title>Study population and treatment regimen distribution

The clinicopathological and treatment characteristics of the enrolled 552 patients were analyzed (Table I). Overall, 274 (49.6%) patients were ER- and 366 (66.3%) patients were PR-. A total of 433 (78.4%) patients exhibited a Ki-67 index >30% and 254 (46.0%) patients were HER2⁺. The distribution of the molecular subtypes among the enrolled patients is shown in Fig. 1A. A total of 200 (36.2%) patients received the AC-T regimen, 82 (14.9%) patients received the TAC regimen, 16 patients (2.9%) received the Tcb regimen, 48 (8.7%) patients received the THP regimen, 23 (4.2%) patients received the AC-TH/TcbH regimen, 31 (5.6%) patients received the AC-THP regimen and 152 (27.5%) patients received the TcbHP regimen. Among the taxane-based regimens, 167 (30.3%) patients received Nab-paclitaxel, 178 (32.2%) patients received docetaxel and 207 (37.5%) patients received paclitaxel liposomes.

Overall and subtype-specific pCR rates

Overall, 189 of 552 (34.2%) patients achieved pCR. The pCR rates of different subtypes varied as follows: 58.9% (96/163), 40.7% (37/91), 35.6% (37/104) and 9.8% (19/298) for the patient groups of HR⁻HER2⁺, HR⁺HER2⁺, HR⁻HER2⁻ and HR⁺HER2⁻, respectively (Fig. 1B; P<0.001). Following univariate analysis, the results indicated that pCR was more likely to be achieved in patients with ER⁻ [49.3 vs. 19.7%; odds ratio (OR)=4.029; 95% confidence interval (CI), 2.755–5.891; P<0.001] and PR⁻ breast cancer (43.2 vs. 16.7%; OR=3.798; 95% CI, 2.452–5.883; P<0.001). Compared with patients with HER2⁻ breast cancer, the HER2⁺ group exhibited a significantly increased pCR rate (52.4 vs. 18.8%; OR=4.750; 95% CI, 3.245–6.952; P<0.001). In addition, the Ki-67 ≥30% group also exhibited a significantly increased pCR rate compared with the Ki-67 <30% group (40.9 vs. 10.1%; OR=6.165; 95% CI, 3.294–11.537; P<0.001; Fig. 2). The pCR rates were compared among different types of taxanes. The pCR rates of Nab-paclitaxel, docetaxel and paclitaxel liposomes were 41.3, 38.2 and 25.1%, respectively (P=0.002; Fig. 3). The pCR rates of Nab-paclitaxel (OR=2.099; 95% CI, 1.352–3.258; P=0.001) and docetaxel (OR=1.843; 95% CI, 1.192–2.850; P=0.001) were significantly increased compared with those who received paclitaxel liposomes. No significant differences were observed in the pCR rates when patients were stratified by age, tumor location, clinical T stage and lymph node status (Table II).

Comparative efficacy of taxane-based regimens

The pCR rates of different taxanes were analyzed among different molecular subtypes of breast cancer. The results demonstrated no significant difference in the pCR rate among the paclitaxel liposomes, Nab-paclitaxel and docetaxel (9.4 vs. 8.2 vs. 12.2%; P=0.78) in HR⁺HER2 group ⁻. For patients that were HER2⁺, Nab-paclitaxel (64.4%) had the highest pCR rate compared with patients who received docetaxel (47.3%; P=0.024) or paclitaxel liposomes (47.89%; P=0.047). In the HR⁻HER2⁻ group, no significant difference was observed in the pCR rates between docetaxel and Nab-paclitaxel treatments (52.63 vs. 40.00%; P=0.354); however, the pCR rate of the docetaxel group was significantly increased compared with that the paclitaxel liposomes group (52.63 vs. 22.50%; P=0.024; Table III and Fig. 3). Overall, both Nab-paclitaxel and docetaxel subgroups demonstrated increased pCR rates among patients that were HR⁻HER2⁻, while Nab-paclitaxel demonstrated the highest pCR rate in patients that were HER2⁺. By contrast, the paclitaxel liposome group had the lowest pCR rate overall, and there was no efficacy advantage in any subtypes of breast cancer.

Development and validation of a pCR predictive model

Based on the results of univariate analysis, variables with statistical significance were included, such as ER status, PR status, HER2 status, Ki-67 index and taxane regimen were used to establish a model to predict pCR. A multivariate regression analysis was performed on the variables with P<0.05 from the univariate analysis. The results indicated that the patients that achieved pCR were associated with the following characteristics: ER⁻, Ki-67 ≥30% and HER2⁺ with regard to tumor features, and taxane regimen with Nab-paclitaxel with regard to treatment administration (Table II). Based on the clinically and statistically significant variables, a model was constructed to predict pCR for patients with breast cancer treated with NAC. The area under the curve value of the ROC curve of the model was 0.774 (95% CI, 0.735–0.813; Fig. 4), which indicated that the model exhibited acceptable discriminatory power in predicting pCR. The cut-off value of this model was 0.5, with a sensitivity of 50.26% and a specificity of 82.92% (Table IV). The positive predictive value was 60.51%, negative predictive value was 76.20% and correction rate was 71.74%.

Discussion

NAC has become a widely employed therapeutic approach for patients with operable and locally advanced breast cancer (25). pCR has been applied to evaluate the efficacy of NAC. Breast cancer is a heterogeneous malignancy with distinct subtypes exhibiting varied responses to NAC. The pCR rate among different breast cancer subtypes varies significantly. The patients who achieve pCR exhibit an optimal prognosis compared with those with residual cancer burden (26). However, the prediction of pCR is challenging.

To assess the predictive value of the clinicopathological factors and different types of taxanes in predicting pCR following NAC in breast cancer, the present study conducted a retrospective analysis on patients with breast cancer who received NAC. A predictive model was developed based on the clinicopathological characteristics to estimate the rates of pCR. In the present study, distinct sensitivities were observed with regard to NAC among various subtypes of breast cancer. The highest rate of pCR was achieved in the HER2⁺ group, followed by those in the HR⁻HER2⁻ group and patients with HR⁺HER2⁻ who exhibited the lowest pCR rate, which was just 9.8% indicating that HR⁺HER2⁻ subtype breast cancer was not sensitive to chemotherapy. It was reported that patients with the HR⁺HER2⁻ subtype of breast cancer demonstrated a low response rate to NAC regimens containing taxanes and anthracyclines with pCR rates ranging from 0 to 15%, consistent with the findings of the present study (27–29). In addition, the present univariate regression analysis found that ER, PR and HER2 status, Ki-67 index, and taxane regimen were significantly associated with pCR.

Targeted therapy combined with chemotherapy is the standard treatment for patients with HER2⁺ breast cancer (20). Clinical trials, such as NeoSphere, NeoALTTO and KRISTINE have demonstrated that the integration of trastuzumab and pertuzumab with chemotherapy yields a high response rate, achieving a pCR rate of up to 55% (6,10,30). The present study found that patients with HER2⁺ breast cancer were associated with a high pCR rate, especially patients with HR⁻HER2⁺ breast cancer, which reached 58.9%.

HR⁻HER2⁻ breast cancer was also more sensitive to chemotherapy compared with the HR⁺HER2⁻ subtypes, as reported by the CALGB 40603 study, with a pCR rate of 44% for patients who received the TAC regimen; the I-SPY2 study reported a pCR rate of 26% in patients who received the T-AC regimen and the BrighTNess study reported a pCR rate of 58% in patients who received the Tcb regimen (15,31,32). In the present study, AC-T, TAC and Tcb were used as NAC regimens, with an overall pCR rate of 35.6%, which was similar to that reported by aforementioned studies. Immunotherapy may also improve pCR rate in TNBCs (33). However, only 1 in 104 patients that were HR⁻HER2⁻ used pembrolizumab in combination with Nab-paclitaxel and carboplatin in the present cohort (treated May 2019 and June 2024) as local health insurance policies did not cover the treatment until late 2023 in the present center and the patient achieved pCR. As it was only an individual case in the present cohort, the case was not analyzed separately, which reflects a limitation of the present study.

Dou et al conducted a study of 879 breast cancer cases treated with NAC, reporting a significantly increased rate of pCR in patients who were ER⁻/PR⁻ compared with that of patients with ER⁺/PR⁺ (64.6 vs. 21.5%; P<0.001) (34). The findings of the present study also indicated that patients with ER⁻ or PR⁻ breast cancer exhibited a higher likelihood of achieving pCR. Although univariate analysis indicated a notable association between PR and pCR, the multivariate analysis did not demonstrate any significant associations.

A previous study reports that 15–20% of breast cancer cases exhibit amplification of HER2, resulting in an upregulation of HER2 (35). The homo- or hetero-dimerization of HER2 with one of the other three receptors (HER1 or EGFR, HER3 and HER4) triggers the activation of signaling pathways which promote cancer cell proliferation, invasion and survival (36). HER2 status is positively correlated with the pCR rate in breast cancer cases treated with NAC (37). The present study demonstrated a significantly higher pCR rate in patients with HER2⁺ breast cancer.

The Ki-67 index also exhibits important predictive value in breast cancer cases treated with NAC. Denkert et al reported pCR rates of 4.2, 12.8 and 29.0% in patients with a Ki-67 index of ≤15, 15.1–35 and >35%, respectively (38). Another predictive model that examined the response to NAC in breast cancer also demonstrated an association between Ki-67 status and the pCR rate (39). Consistent with these findings, the results of the present study demonstrated that patients with Ki-67 ≥30% expression demonstrated an increased pCR rate compared with those with Ki-67 <30% expression, which highlighted the key predictive value of Ki-67 index in NAC treatment for breast cancer.

Taxanes containing regimens are widely used as NAC for breast cancer. The toxicity profiles of different paclitaxel have been reported in previous publications (40–42). Generally, paclitaxel liposome and Nab-paclitaxel showed relatively mild side effects, especially hypersensitivity reaction. The response rate of breast cancer to NAC may be influenced by different types of taxanes (43). Zhang et al (44) conducted a retrospective study on 235 patients with breast cancer treated with NAC and indicated that Nab-paclitaxel demonstrated an advantage in improving the total and axillary-only pCR rate over liposomal paclitaxel. An additional study retrospectively analyzed the efficacy of solvent-based paclitaxel, liposomal paclitaxel, Nab-paclitaxel and docetaxel, which also indicated that the Nab-paclitaxel group exhibited the highest total pCR cases and breast pCR rates (43). The present study demonstrated that the Nab-paclitaxel group achieved the highest pCR rate across all patient cohorts analyzed. Subgroup analyses demonstrated that the Nab-paclitaxel group also exhibited the highest pCR rate in patients with HER2⁺ breast cancer. By contrast, the docetaxel group demonstrated the highest pCR rate among patients HR⁻HER2⁻ breast cancer. However, this difference was not statistically significant compared with that of the Nab-paclitaxel group. Notably, in the HR⁺HER2⁻ group, no significant differences in pCR rates were observed among the three treatment groups, which may be due to their inherent insensitivity to chemotherapy. Although paclitaxel liposome exhibits low toxicity profiles, it does not show an advantage in improving pCR in any subtypes of breast cancer (44). Therefore, the selection of taxanes according to breast cancer subtype may improve the pCR rate after NAC.

Based on these findings, a multivariate regression model was used to predict pCR. The model revealed that patients characterized by ER⁻, Ki-67 index ≥30%, HER2⁺ and taxane regimen with Nab-paclitaxel were more likely to achieve pCR. Moreover, the present findings demonstrated that Nab-paclitaxel and docetaxel exhibited a significantly increased pCR rate compared with that of paclitaxel liposomes in patients with HER2⁺ and HR⁻HER2⁻ breast cancer. Consequently, patients with HER2⁺ and HR⁻HER2⁻ breast cancer are potentially more suitable for NAC compared with those with HR⁺HER2⁻ breast cancer, especially the HR⁻HER2⁺ subgroup. The patients included in the present study were predominantly residents of the Jiangxi province, which may represent a limitation in regard to the generalization of the findings to a global population. Cancer cell differentiation degree may affect the pCR rate, however, not all of the patients enrolled in the present study had differentiation data available from the pathology reports, particularly those with core needle biopsy samples; therefore, and differentiation data were not used to analyze separate subgroups. The HR status among the HER2⁺ group were not further differentiated due to the low number of cases after subdivision. Furthermore, external validation of the predictive model was not conducted in the present study. The sensitivity and the specificity of the present model was 50.26 and 82.92% respectively, which indicated that the model exhibited a certain level of deficiency. Due to these limitations, further study regarding the different paclitaxel regimens effects on pCR rates are warranted in future.

In summary, the present study demonstrated that ER, PR and HER2 status, Ki-67 index and different types of taxanes are independent predictive factors for pCR in patients with breast cancer who receive NAC. Patients with ER⁻, PR⁻, HER2⁺, Ki-67 index ≥30% breast cancer were more sensitive to NAC. Patients who received Nab-paclitaxel or docetaxel were more likely to achieve pCR compared with those who received paclitaxel liposomes, notably in the HER2⁺ and HR⁻HER2⁻ breast cancer subgroups. These findings indicated that molecular subtypes and taxane choice may significantly influence the likelihood of achieving pCR. Nab-paclitaxel and docetaxel were identified as effective taxanes, highlighting their potential clinical preference, especially in HER2⁺ and HR⁻HER2⁻ breast cancer.

Acknowledgements

Not applicable.

Availability of data and materials

The data generated in the present study may be requested from the corresponding author.

Authors' contributions

JD and YC contributed to the conception and design of the manuscript. JK, HX, XJ, ZH and YG were responsible for the acquisition, analysis and interpretation of data. XJ, YG and JD undertook the editing, drafting and writing of the manuscript. All authors confirm the authenticity of all the raw data, and read and approved the final manuscript.

Ethics approval and consent to participate

The present study was approved by the review board ethics committee of Nanchang People's Hospital (approval no. K-kt2024005; Nanchang, China). The requirement for patient approval or written informed consent was waived due to the retrospective nature of the study.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

References 1

Han

Zheng

Zeng

Wang

Sun

Chen

Wei

Cancer incidence and mortality in China, 2022

J Natl Cancer Cent447532024

10.1016/j.jncc.2024.01.006

39036382

Siegel

Giaquinto

Jemal

Cancer statistics, 2024

CA Cancer J Clin7412492024

10.3322/caac.21820

38230766

Song

Gao

Guan

Wang

Zhang

Yao

Guo

Wang

Jiang

Sun

Global, regional, and national burden of breast, cervical, uterine, and ovarian cancer and their risk factors among women from 1990 to 2021, and projections to 2050: Findings from the global burden of disease study 2021

BMC Cancer253302025

10.1186/s12885-025-13741-9

39988683

Freitas

AJA

Causin

Varuzza

Hidalgo Filho

CMT

Silva

VDD

Souza

Marques

MMC

Molecular biomarkers predict pathological complete response of neoadjuvant chemotherapy in breast cancer patients: Review

Cancers (Basel)1354772021

10.3390/cancers13215477

34771640

Dubsky

Pinker

Cardoso

Montagna

Ritter

Denkert

Rubio

de Azambuja

Curigliano

Gentilini

Breast conservation and axillary management after primary systemic therapy in patients with early-stage breast cancer: the Lucerne toolbox

Lancet Oncol22e18e282021

10.1016/S1470-2045(20)30580-5

33387500

Hurvitz

Martin

Symmans

Jung

Huang

Thompson

Harbeck

Valero

Stroyakovskiy

Wildiers

Neoadjuvant trastuzumab, pertuzumab, and chemotherapy versus trastuzumab emtansine plus pertuzumab in patients with HER2-positive breast cancer (KRISTINE): A randomised, open-label, multicentre, phase 3 trial

Lancet Oncol191151262018

10.1016/S1470-2045(17)30716-7

29175149

Kim

Dominici

Rosenberg

Zheng

Pak

Poorvu

Ruddy

Tamimi

Schapira

Come

Surgical treatment after neoadjuvant systemic therapy in young women with breast cancer: Results from a prospective cohort study

Ann Surg2761731792022

10.1097/SLA.0000000000004296

33378304

von Minckwitz

Blohmer

Costa

Denkert

Eidtmann

Eiermann

Gerber

Hanusch

Hilfrich

Huober

Response-guided neoadjuvant chemotherapy for breast cancer

J Clin Oncol31362336302013

10.1200/JCO.2012.45.0940

24002511

Conforti

Pala

Sala

Oriecuia

De Pas

Specchia

Graffeo

Pagan

Queirolo

Pennacchioli

Evaluation of pathological complete response as surrogate endpoint in neoadjuvant randomised clinical trials of early stage breast cancer: Systematic review and meta-analysis

BMJ375e0663812021

10.1136/bmj-2021-066381

34933868

de Azambuja

Holmes

Piccart-Gebhart

Holmes

Di Cosimo

Swaby

Untch

Jackisch

Lang

Smith

Lapatinib with trastuzumab for HER2-positive early breast cancer (NeoALTTO): Survival outcomes of a randomised, open-label, multicentre, phase 3 trial and their association with pathological complete response

Lancet Oncol15113711462014

10.1016/S1470-2045(14)70320-1

25130998

Cortazar

Zhang

Untch

Mehta

Costantino

Wolmark

Bonnefoi

Cameron

Gianni

Valagussa

Pathological complete response and long-term clinical benefit in breast cancer: The CTNeoBC pooled analysis

Lancet3841641722014

10.1016/S0140-6736(13)62422-8

24529560

Zheng

Yan

Wang

Zhang

Huo

Liu

Wang

Fan

An ultrasound-based nomogram for predicting axillary node pathologic complete response after neoadjuvant chemotherapy in breast cancer: Modeling and external validation

Cancer130151315232024

10.1002/cncr.35248

38427584

Değerli

Şentürk Öztaş

Alkan

Bedir

Derin

Valıkhanova

Saraç

Kacar

Demirci

Demirelli

Turna

Relationship between pathological response and molecular subtypes in locally advanced breast cancer patients receiving neoadjuvant chemotherapy

J Chemother3529382023

10.1080/1120009X.2022.2043514

35220928

Zhang

Liu

Tian

Predicting pathological complete response after neoadjuvant chemotherapy in breast cancer by clinicopathological indicators and ultrasound parameters using a nomogram

Sci Rep14163482024

10.1038/s41598-024-64766-2

39013971

Sikov

Berry

Perou

Singh

Cirrincione

Tolaney

Kuzma

Pluard

Somlo

Port

Impact of the addition of carboplatin and/or bevacizumab to neoadjuvant once-per-week paclitaxel followed by dose-dense doxorubicin and cyclophosphamide on pathologic complete response rates in stage II to III triple-negative breast cancer: CALGB 40603 (Alliance)

J Clin Oncol3313212015

10.1200/JCO.2014.57.0572

25092775

Choi

Ryu

Kim

Nam

Kim

Lee

Nomogram for accurate prediction of breast and axillary pathologic response after neoadjuvant chemotherapy in node positive patients with breast cancer

Ann Surg Treat Res961691762019

10.4174/astr.2019.96.4.169

30941320

Maimaitiaili

Chai

Liu

Ling

Zhao

Yang

Liu

Zhang

A nomogram for predicting pathologic node negativity after neoadjuvant chemotherapy in breast cancer patients: A nationwide, multicenter retrospective cohort study (CSBrS-012)

Front Oncol1413263852024

10.3389/fonc.2024.1326385

38800388

Anthracycline-containing and taxane-containing chemotherapy for early-stage operable breast cancer: A patient-level meta-analysis of 100 000 women from 86 randomised trials

Lancet401127712922023

10.1016/S0140-6736(23)00285-4

37061269

Nižnanský

Osinová

Kuruc

Hengerics Szabó

Szórádová

Masár

Nižnanská

Natural taxanes: From plant composition to human pharmacology and toxicity

Int J Mol Sci23156192022

10.3390/ijms232415619

36555256

Gradishar

Moran

Abraham

Abramson

Aft

Agnese

Allison

Anderson

Bailey

Burstein

Breast cancer, version 3.2024, NCCN clinical practice guidelines in oncology

J Natl Compr Canc Netw223313572024

10.6004/jnccn.2024.0035

39019058

Symons

Heath

Duggan

Bui

Byun

Friedlander

Lee

Rates of paclitaxel hypersensitivity reactions using a modified Markman's infusion protocol as primary prophylaxis

Support Care Cancer322922024

10.1007/s00520-024-08460-z

38632132

Chen

Liu

Zhao

Sun

Song

Wang

Efficacy and safety analysis of paclitaxel, docetaxel and liposomal paclitaxel after neoadjuvant therapy in breast cancer

Breast Cancer Res Treat1843974052020

10.1007/s10549-020-05851-8

32776291

Dieci

Griguolo

Bottosso

Tsvetkova

Giorgi

Vernaci

Michieletto

Angelini

Marchet

Tasca

Impact of estrogen receptor levels on outcome in non-metastatic triple negative breast cancer patients treated with neoadjuvant/adjuvant chemotherapy

NPJ Breast Cancer71012021

10.1038/s41523-021-00308-7

34341356

Giuliano

Edge

Hortobagyi

Eighth Edition of the AJCC cancer staging manual: Breast cancer

Ann Surg Oncol25178317852018

10.1245/s10434-018-6486-6

29671136

Kerr

Dodwell

McGale

Holt

Duane

Mannu

Darby

Taylor

Adjuvant and neoadjuvant breast cancer treatments: A systematic review of their effects on mortality

Cancer Treat Rev1051023752022

10.1016/j.ctrv.2022.102375

35367784

Spring

Fell

Arfe

Sharma

Greenup

Reynolds

Smith

Alexander

Moy

Isakoff

Pathologic complete response after neoadjuvant chemotherapy and impact on breast cancer recurrence and survival: A comprehensive Meta-analysis

Clin Cancer Res26283828482020

10.1158/1078-0432.CCR-19-3492

32046998

Ortmann

Blohmer

Sibert

Brucker

Janni

Wöckel

Scharl

Dieng

Ferencz

Inwald

Current clinical practice and outcome of neoadjuvant chemotherapy for early breast cancer: Analysis of individual data from 94,638 patients treated in 55 breast cancer centers

J Cancer Res Clin Oncol149119512092023

10.1007/s00432-022-03938-x

35380257

Guan

Jie

Hong

Meng

Real-world data on breast pathologic complete response and disease-free survival after neoadjuvant chemotherapy for hormone receptor-positive, human epidermal growth factor receptor-2-negative breast cancer: A multicenter, retrospective study in China

World J Surg Oncol203262022

10.1186/s12957-022-02787-9

36175898

Villegas

Nekljudova

Pfarr

Engel

Untch

Schrodi

Holms

Ulmer

Fasching

Weber

Therapy response and prognosis of patients with early breast cancer with low positivity for hormone receptors-An analysis of 2765 patients from neoadjuvant clinical trials

Eur J Cancer1481591702021

10.1016/j.ejca.2021.02.020

33743484

Gianni

Pienkowski

Roman

Tseng

Liu

Lluch

Staroslawska

de la Haba-Rodriguez

Efficacy and safety of neoadjuvant pertuzumab and trastuzumab in women with locally advanced, inflammatory, or early HER2-positive breast cancer (NeoSphere): A randomised multicentre, open-label, phase 2 trial

Lancet Oncol1325322012

10.1016/S1470-2045(11)70336-9

22153890

Loibl

O'Shaughnessy

Untch

Sikov

Rugo

McKee

Huober

Golshan

von Minckwitz

Maag

Addition of the PARP inhibitor veliparib plus carboplatin or carboplatin alone to standard neoadjuvant chemotherapy in triple-negative breast cancer (BrighTNess): A randomised, phase 3 trial

Lancet Oncol194975092018

10.1016/S1470-2045(18)30111-6

29501363

Nanda

Liu

Yau

Shatsky

Pusztai

Wallace

Chien

Forero-Torres

Ellis

Han

Effect of pembrolizumab plus neoadjuvant chemotherapy on pathologic complete response in women with early-stage breast cancer: An analysis of the ongoing phase 2 adaptively randomized I-SPY2 trial

JAMA Oncol66766842020

10.1001/jamaoncol.2019.6650

32053137

Schmid

Cortes

Pusztai

McArthur

Kümmel

Bergh

Denkert

Park

Hui

Harbeck

Pembrolizumab for early Triple-negative breast cancer

N Engl J Med3828108212020

10.1056/NEJMoa1910549

32101663

Dou

Wang

Chen

Jia

Luo

Gao

Xiao

Estrogen receptor-negative/progesterone receptor-positive breast cancer has distinct characteristics and pathologic complete response rate after neoadjuvant chemotherapy

Diagn Pathol1952024

10.1186/s13000-023-01433-6

38178166

Ahn

Woo

Lee

Park

HER2 status in breast cancer: Changes in guidelines and complicating factors for interpretation

J Pathol Transl Med5434442020

10.4132/jptm.2019.11.03

31693827

Roskoski

The ErbB/HER family of protein-tyrosine kinases and cancer

Pharmacol Res7934742014

10.1016/j.phrs.2013.11.002

24269963

Baumgartner

Tausch

Hosch

Papassotiropoulos

Varga

Rageth

Baege

Ultrasound-based prediction of pathologic response to neoadjuvant chemotherapy in breast cancer patients

Breast3919232018

10.1016/j.breast.2018.02.028

29518677

Denkert

Loibl

Müller

Eidtmann

Schmitt

Eiermann

Gerber

Tesch

Hilfrich

Huober

Ki67 levels as predictive and prognostic parameters in pretherapeutic breast cancer core biopsies: A translational investigation in the neoadjuvant GeparTrio trial

Ann Oncol24278627932013

10.1093/annonc/mdt350

23970015

Kim

Cho

Choi

Lee

Kim

Chang

Moon

Factors affecting pathologic complete response following neoadjuvant chemotherapy in breast cancer: Development and validation of a predictive nomogram

Radiology2992903002021

10.1148/radiol.2021203871

33754824

Chen

Zhu

Chen

Shi

Zhang

Retrospective comparisons of nanoparticle albumin-bound paclitaxel and docetaxel neoadjuvant regimens for breast cancer

Nanomedicine (Lond)163914002021

10.2217/nnm-2020-0458

33502252

Wang

Cai

Yang

Zhou

Shen

Zhu

Liu

The efficacy and toxicity of neoadjuvant chemotherapy regimens of epirubicin plus cyclophosphamide followed by docetaxel or paclitaxel in female breast cancer patients

Cancer Manag Res13151715272021

10.2147/CMAR.S284638

33623431

Jivani

Shinde

A comprehensive review of taxane treatment in breast cancer: Clinical perspectives and toxicity profiles

Cureus16e592662024

38813284

Zhang

Wang

Chen

Wan

Shi

Huang

Wang

Zha

Efficacy comparisons of solvent-based paclitaxel, liposomal paclitaxel, nanoparticle albumin-bound paclitaxel, and docetaxel after neoadjuvant systemic treatment in breast cancer

Nanomedicine541027072023

10.1016/j.nano.2023.102707

37717927

Zhang

Shi

Huang

Chen

Shi

Wan

Wang

Nanoparticle albumin-bound paclitaxel is superior to liposomal paclitaxel in the neoadjuvant treatment of breast cancer

Nanomedicine (Lond)176836942022

10.2217/nnm-2022-0025

35393861

Figure 1.

Distribution of molecular subtypes and pCR rates in patients with breast cancer. (A) The distribution of different molecular subtypes of breast cancer among the patients enrolled; (B) The overall pCR rates among different molecular subtypes of breast cancer in pairwise comparisons. **P<0.01; ***P<0.001. ns, not significant; pCR, pathological complete response; HR, hormone receptor; HER, human epidermal growth factor receptor.

Figure 2.

pCR rates stratified by ER, PR, HER2, and Ki-67 status. (A) pCR rates in patients with different ER status; (B) pCR rates in patients with different PR status; (C) pCR rates in patients with different HER2 status; (D) pCR rates in patients with different Ki-67 status. ***P<0.001. pCR, pathological complete response; HR, hormone receptor; HER, human epidermal growth factor receptor; ER, estrogen receptor; PR, progesterone receptor.

Figure 3.

pCR rates of different taxanes among different molecular subtypes of breast cancer. The pCR rates of (A) total patients, and patients with (B) HR⁺HER2⁻, (C) HER2⁺ and (D) HR⁻HER2 patients. *P<0.05; ***P<0.001. ns, not significant; pCR, pathological complete response; HR, hormone receptor; HER, human epidermal growth factor receptor; Nab, nanoparticle albumin-bound.

Figure 4.

ROC curve of the prediction model pCR. The variables ER⁺, PR⁺, HER2⁻, Ki-67 ≤30% and liposomal paclitaxel were used as references to produce the ROC curve. ROC, receiver operating characteristic; AUC, area under curve; pCR, pathological complete response; HR, hormone receptor; HER, human epidermal growth factor receptor; ER, estrogen receptor; PR, progesterone receptor.

Table I.

Baseline characteristics of 552 patients who achieved pCR (n=189) and non-pCR (n=363).

Variable	Non-pCR, n (%)	pCR, n (%)	Total, n	P-value
Age, years				0.477
≤35	48 (69.6)	21 (30.4)	69
>35	315 (65.2)	168 (34.8)	483
Tumor location				0.795
Left	179 (66.3)	91 (33.7)	270
Right	184 (65.2)	98 (34.8)	282
Tumor location, quadrant				0.872
Upper outer	198 (65.1)	106 (34.9)	304
Lower outer	42 (63.6)	24 (36.4)	66
Upper inner	69 (69.7)	30 (30.3)	99
Lower inner	17 (60.7)	11 (39.3)	28
Center	37 (67.3)	18 (32.7)	55
cT stage				0.755
cT1	13 (65.0)	7 (35.0)	20
cT2	222 (65.3)	118 (34.7)	340
cT3	82 (69.5)	36 (30.5)	118
cT4	46 (62.2)	28 (37.8)	74
Lymph node status				0.104
Negative	26 (78.8)	7 (21.2)	33
Positive	337 (64.9)	182 (35.1)	519
ER status				<0.001
Negative	139 (50.7)	135 (49.3)	274
Positive	224 (80.6)	54 (19.4)	278
PR status				<0.001
Negative	208 (56.8)	158 (43.2)	366
Positive	155 (83.3)	31 (16.7)	186
Ki-67 index				<0.001
<30%	107 (89.9)	12 (10.1)	119
≥30%	256 (59.1)	177 (40.9)	433
HER2 status				<0.001
Negative	242 (81.2)	56 (18.8)	298
Positive	121 (47.6)	133 (52.4)	254
Molecular subtype				<0.001
HR⁺HER2⁻	175 (90.2)	19 (9.8)	194
HR⁻HER2⁺	67 (41.1)	96 (58.9)	163
HR⁺HER2⁺	54 (59.3)	37 (40.7)	91
HR⁻HER2⁻	67 (64.4)	37 (35.6)	104
NAC regimen				<0.001
AC-T	164 (82.0)	36 (18.0)	200
TAC	66 (80.5)	16 (19.5)	82
Tcb	12 (75.0)	4 (25.0)	16
THP	24 (50.0)	24 (50.0)	48
AC-TH + TcbH	16 (69.6)	7 (30.4)	23
AC-THP	15 (48.4)	16 (51.6)	31
TcbHP	66 (43.4)	86 (56.6)	152
Taxanes				0.002
Paclitaxel liposome	155 (74.9)	52 (25.1)	207
Nab-paclitaxel	98 (58.7)	69 (41.3)	167
Docetaxel	110 (61.8)	68 (38.2)	178

AC-T, anthracyclines and cyclophosphamide followed by taxanes; TAC, taxanes, anthracyclines and cyclophosphamide; Tcb, taxanes and carboplatin; THP, taxanes with trastuzumab and pertuzumab; TcbH, taxanes and carboplatin with trastuzumab; TcbHP, TcbH with pertuzumab; AC-TH; taxanes with trastuzumab; AC-THP, AC-TH and pertuzumab; cT, clinical tumor; Nab, nanoparticle albumin-bound; ER, estrogen receptor; PR, progesterone receptor; pCR, pathological complete response; HR, hormone receptor; HER, human epidermal growth factor receptor.

Table II.

Univariate and multivariate analysis for pathologic complete response.

	Univariate analysis			Multivariate analysis

Variable	OR	95% CI	P-value	OR	95% CI	P-value
Age, years			0.477
≤35	Reference	-
>35	1.219	0.705–2.104
Tumor location			0.795
Left	Reference	-
Right	1.048	0.737–1.489
Tumor location, quadrant			0.872
Upper outer	Reference	-
Lower outer	1.067	0.613–1.858
Upper inner	0.812	0.498–1.325
Lower inner	1.209	0.546–2.674
Center	0.909	0.493–1.674
cT stage			0.755
cT1	Reference	-
cT2	0.987	0.383–2.541
cT3	0.815	0.300–2.214
cT4	1.130	0.403–3.173
Lymph node status			0.104
Negative	Reference
Positive	2.006	0.854–4.711
ER status			<0.001
Negative	4.029	2.755–5.891		2.161	1.238–3.77	0.007
Positive	Reference	-		Reference	-
PR status			<0.001
Negative	3.798	2.452–5.883		1.386	0.727–2.643	0.322
Positive	Reference	-		Reference	-
Ki-67 index			<0.001
<30%	Reference	-		Reference	-
≥30%	6.165	3.294–11.537		3.741	1.917–7.301	<0.001
HER2 status			<0.001
Negative	Reference	-		Reference	-
Positive	4.750	3.245–6.952		3.662	2.419–5.545	<0.001
Taxane			0.002
Paclitaxel liposome	Reference	-		Reference	-
Nab-paclitaxel	2.099	1.352–3.258	0.001	1.647	1.007–2.695	0.047
Docetaxel	1.843	1.192–2.850	0.006	1.093	0.666–1.795	0.725

OR, odds ratio; Nab, nanoparticle albumin-bound; cT, clinical tumor; ER, estrogen receptor; PR, progesterone receptor; HER, human epidermal growth factor receptor.

Table III.

Pathological complete response rates of types of taxane among molecular subtypes of breast cancer.

Variable	Non-pCR, n (%)	pCR, n (%)	Total, n	Odds ratio	95% CI	P-value
HR⁺HER2⁻
Paclitaxel liposome	87 (90.6)	9 (9.4)	96	Reference		0.781
Nab-paclitaxel	45 (91.8)	4 (8.2)	49	0.85	0.25–2.94	0.809
Docetaxel	43 (87.8)	6 (12.2)	49	1.34	0.45–4.03	0.592
HER2⁺
Nab-paclitaxel	26 (35.6)	47 (64.4)	73	Reference		0.054
Docetaxel	58 (52.7)	52 (47.3)	110	0.496	0.270–0.911	0.024
Paclitaxel liposome	37 (52.1)	34 (47.9)	71	0.508	0.261–0.991	0.047
HR⁻HER2⁻
Docetaxel	9 (47.4)	10 (52.6)	19	Reference		0.062
Nab-paclitaxel	27 (60.0)	18 (40.0)	45	0.6	0.203–1.767	0.353
Paclitaxel liposome	31 (77.5)	9 (22.5)	40	0.261	0.081–0.839	0.024

Nab, nanoparticle albumin-bound; HR, hormone receptor; HER, human epidermal growth factor receptor.

Table IV.

Sensitivity and specificity of the model for pCR.

Classification	Predicted non-pCR, n	Predicted pCR, n	Total, n
Observed non-pCR	301	62	363
Observed pCR	94	95	189
Total	395	157	552

Cut-off value, 0.5; sensitivity, 50.26%; specificity, 82.92%; positive predictive value, 60.51%; negative predictive value, 76.20%; correction rate, 71.74%. pCR, pathological complete response.