ABSTRACT
Aim
The aim of this study was to evaluate clinical, pathological, and inflammatory markers that can predict pathological complete response (pCR) after neoadjuvant chemotherapy (NACT) in patients with hormone receptor-positive (HR+)/human epidermal growth factor receptor 2 (HER2) HER2- breast cancer.
Materials and Methods
A retrospective analysis was conducted on 109 patients aged 18-80 years with HR+/HER2- breast cancer who underwent NACT at University of Health Sciences Türkiye, Balıkesir Atatürk City Hospital between January 1, 2020, and May 1, 2025. All patients received standard anthracycline-taxane-based chemotherapy. Pre-treatment blood tests were used to calculate the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII). pCR was defined as the absence of residual invasive tumor in the breast and axillary lymph nodes. Factors affecting pCR were evaluated using logistic regression analysis.
Results
pCR was achieved in 21.1% of patients. Most of the pCR group was under 50 years of age and had the luminal B subtype. ROC analysis showed that NLR, PLR, and SII were not significant predictors of pCR (p>0.05). In univariate analysis, luminal B subtype, low estrogen receptor (ER) levels, high Ki-67, and high tumor grade were significantly associated with pCR. In multivariate analysis, only low ER levels and high Ki-67 remained independent predictors.
Conclusion
Inflammatory markers are insufficient to predict pCR in HR+/HER2- breast cancer. Low ER levels and high Ki-67 are associated with a better response to NACT. The findings highlight the importance of biomarkers in personalizing treatment response.
INTRODUCTION
Breast cancer (BC) is the most common type of cancer found in women1. More than 90% of BCs are confined to the locoregional area at the time of diagnosis, allowing for curative treatment2. One such approach, neoadjuvant therapy, involves administering systemic therapy before primary surgery and has made significant advances in recent years3. This strategy aims to reduce tumor size, enabling less invasive surgical procedures and improving patient outcomes3. Despite this, approximately 20% of patients experience recurrence after initial treatment2. Prediction of patients at risk of recurrence is primarily based on clinicopathological risk factors such as receptor status, tumor size, and nodal status2. Studies have shown that patients who achieve a pathological complete response (pCR) after neoadjuvant therapy have better long-term outcomes4.
Breast tumors behave differently depending on the biological properties of their originating cells5. The most commonly used clinical markers for tumor biology classification are estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2)5. The commonly accepted molecular subsets include luminal A [ER+/PR+/HER2-, low proliferation]; luminal B (ER+, low PR, HER2-, elevated proliferation); HER2+) (ER+ and ER- comprise unique HER2 subsets); and basal-like (commonly ER-/PR-/HER2-, triple-negative BC)6. In general, hormone receptor negative (HR-) (ER and PR negative) or HER2+ tumors are sensitive to chemotherapy and respond well to neoadjuvant chemotherapy (NACT)4. However, the indication for NACT in HR-positive (HR+)/HER2- tumors is controversial7. Although NACT is a treatment option for early-stage HR+/HER2- BC, pathological response rates are generally lower in this subtype8. pCR rates range from 0% to 18%, while breast-conserving surgery (BCS) can be achieved in up to 60% of tumors7.
BC treatment is heterogeneous, and understanding who benefits most from specific treatments is vital9. Molecular methods such as prosigna gene testing on biopsy samples can influence neoadjuvant treatment decision-making in early-stage HR+/HER2- BC10. BC gene mutation status can help personalize treatment decisions9. Unfortunately, there are currently no completely reliable predictors11. The medical need for reliable biomarkers to predict response to NACT has not been met12.
Persistent subclinical inflammation is closely associated with cancer development and progression, and neutrophils, platelets, and lymphocytes are key mediators of chronic inflammation13. Systemic inflammatory markers, such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII), have been identified as potential prognostic and predictive indicators in various malignancies, including BC14. Studies in the literature support the hypothesis that NLR, PLR, and SII may serve as predictive biomarkers for pCR in BC patients receiving NACT15. However, there are still inconsistent research results regarding the value of peripheral blood inflammatory markers in assessing the efficacy of neoadjuvant therapy in BC16.
The aim of this retrospective study was to evaluate factors, including inflammatory markers, that may predict pCR after NACT in HR+/HER2- BC patients.
MATERIALS AND METHODS
Selection and Description of Cases
In our study, we retrospectively analyzed the data of HR+/HER2- BC patients aged 18-80 who underwent NACT at University of Health Sciences Türkiye, Balıkesir Atatürk City Hospital between January 1, 2020, and May 1, 2025. Patients who received standard chemotherapy regimens (4 cycles of 600 mg/m2 cyclophosphamide + 60 mg/m2 doxorubicin every 2 weeks, followed by either 4 cycles of 175 mg/m2 paclitaxel every 2 weeks or 12 cycles of 80 mg/m2 paclitaxel weekly) were included in the study. Patients with clinical node positivity before treatment were included in the study. Patients with metastatic initial status, male gender, a second primary cancer other than BC, and those who received chemotherapy regimens other than those considered standard were excluded from the study. Patients with diseases that could affect blood results (rheumatological disease, chronic renal failure, liver cirrhosis, infection) and those taking medications (steroids, immunosuppressive therapy, chemotherapy) were excluded from the study.
The protocol for this retrospective study was approved Ethics Committee of University of Health Sciences Türkiye, Balıkesir Atatürk City Hospital (decision number: 2025/07/67, date: 24.07.2025). Since this study was a retrospective archive search, informed consent was not obtained from the patients. The study was conducted in accordance with the principles of the Declaration of Helsinki.
Technical Information
Immunohistochemistry (IHC) for ER, PR, and HER2, and double-probe fluorescence in situ hybridization (FISH) for HER2 were evaluated according to the 2018 American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) guidelines using Food and Drug Administration-approved tests17, 18. ER and PR positivity was defined as at least 1% nuclear staining in tumor cells17, 18. HER2 IHC was scored as positive (3+), equivocal (2+ or 1+ to 2+), or negative (0 or 1+) according to the 2018 ASCO/CAP guidelines17, 19. All HER2 IHC equivocal (2+ or 1+ to 2+) cases underwent reflex HER2 dual-probe FISH testing (HER2 IQFISH pharmDx; DAKO). A positive HER2 FISH result was defined as a HER2/CEP17 ratio ≥2.0 or a mean HER2 copy number ≥6.0 signals per cell17, 19 . In our study and the 2021 St. Gallen update, ER-positive cancers are sometimes classified as “luminal A-like” (lower grade, lower Ki-67, strong ER/PR expression) or “luminal B-like” (higher grade, higher Ki-67, lower ER/PR expression levels)20.
pCR was defined as no residual invasive carcinoma (ypT0/is ypN0) in the breast and axillary lymph nodes after surgical resection17. Patients with tumor and nodal pathologic stages of all other stages, including T1mi and N1mi, were considered the non-pCR group. Microinvasive BC was defined as an invasive component not exceeding 1 mm, most often in the setting of ductal carcinoma in situ21. Foci measuring ≤2 mm in the lymph node were also considered micrometastases22. Clinical and pathological tumor staging was performed based on the 8th edition of the International Union on Cancer TNM classification.
In our study, NLR, PLR, and SII were calculated according to the following equations: NLR = neutrophil count/lymphocyte count; PLR = platelet count/lymphocyte count; SII = (neutrophil count × platelet count)/lymphocyte count23. Laboratory examinations, including routine blood tests, for which data were recorded, were selected from examinations performed within the last month before the start of NACT.
Neoadjuvant treatment decisions were made in accordance with international guidelines and based on tumor biology, clinical stage, and patient-specific characteristics. All cases were evaluated in a multidisciplinary tumor board including medical oncologists, breast surgeons, radiologists, and pathologists, and treatment plans were finalized by consensus. Clinical staging was performed using the 8th edition of the American Joint Committee on Cancer staging system24. Diagnostic evaluation included physical examination, breast and axillary ultrasonography, and mammography, with breast MRI performed when indicated. To exclude distant metastasis, additional imaging such as chest computed tomography (CT), abdominal ultrasonography/CT, and bone scintigraphy or positron emission tomography-CT was used according to guideline-based indications.
Statistical Analysis
Statistical analyses and data processing were performed using the SPSS Statistics software, version 24 (SPSS Inc., Chicago, IL) and the R programming language (R Core Team, 2024). The ideal cutoff value for the logarithmic formula in distinguishing pCR from non-pCR, as well as specificity and sensitivity values, were determined using ROC analysis. Factors predicting pCR were calculated using univariate and multivariate analyses and binary logistic regression. Odds ratios (ORs) with 95% confidence intervals (CIs) were reported, and a p value of <0.05 was considered statistically significant.
RESULTS
A total of 109 patients were included in the study. pCR was achieved in 23 patients (21.1%). Among patients who achieved pCR, 14 patients (60.9%) were under 50 years of age. The majority of this group had the luminal B subtype (20 patients, 87.0%). The Ki-67 proliferation index was above 20% in 20 patients (87.0%), and 9 patients (39.1%) had grade 3 tumors. Histologically, ductal type carcinoma was observed in 21 patients (91.3%). PR levels were low (<20%) in 8 patients (34.8%) (Table 1).
ROC curve analysis was conducted to evaluate the performance of inflammatory markers (NLR, PLR, and SII) in predicting pCR. The area under the curve for PLR was 0.451 (95% CI: 0.310-0.591; p=0.469), for NLR 0.595 (95% CI: 0.465-0.726; p=0.162), and for SII 0.583 (95% CI: 0.460-0.706; p=0.223). These results indicated that NLR, PLR, and SII do not exhibit adequate diagnostic value for predicting pCR; therefore, an optimal cut-off value could not be established (Table 2, Figure 1).
Logistic regression analysis was performed to identify predictors of pCR in HR+/HER2- BC. In univariate analysis, the luminal B subtype demonstrated approximately a five-fold higher odds of achieving pCR compared with luminal A (OR: 5.03; 95% CI: 1.39-18.22; p=0.014). A significant negative association was found between ER level and pCR, indicating that higher ER levels reduced the likelihood of achieving pCR (OR: 0.97; 95% CI: 0.96-0.99; p=0.004). Additionally, patients with a high Ki-67 index had significantly increased odds of achieving pCR (OR: 1.05; 95% CI: 1.01-1.09; p=0.009). Higher tumor grade also increased the likelihood of pCR (OR: 3.04; 95% CI: 1.11-8.32; p=0.030) (Table 3).
In multivariate analysis, only ER level (OR: 0.97; 95% CI: 0.96-0.99; p=0.009) and Ki-67 (OR: 1.05; 95% CI: 1.01-1.09; p=0.024) remained independent predictors of pCR. Molecular subtype, tumor grade, histological type, menopausal status, body mass index, inflammatory indices (NLR, PLR, SII), and clinical T stage were not significant in the multivariate model (Table 3). As all VIF values were <5, no multicollinearity was detected in the regression model (Table 3).
DISCUSSION
This study investigated the factors predicting pCR after NACT in patients with HR+ BC. Univariate analysis revealed increased pCR in patients with luminal B, low ER, high Ki-67, and high-grade tumors. Multivariate analysis identified ER level and Ki-67 as independent predictors of pCR. NLR, PLR, and SII were found to have insufficient diagnostic value in predicting pCR.
pCR rates after NACT are lower in HR+/HER2- BC compared to other subtypes (7-16% in HR+/HER2- BC; 26-43% in HR+/HER2+ BC; 39-55% in triple-negative BC; and 46-90.5% in HER2+ BC)25. The 21.1% pCR achieved in our study may be attributable to the selection of patients who were relatively more suitable for NACT, with 63.3% having luminal B disease, 77.1% having Ki-67 ≥14, and 72.5% having cT2-cT3. The importance of pCR lies in the fact that large clinical trials of NACT have demonstrated improved disease-free survival (DFS) and overall survival (OS) rates in patients with pCR compared to those with residual disease26. In the National Surgical Adjuvant Breast and Bowel Project (NSABP) protocol B-18, patients achieving pCR had a DFS and OS of 75% and 85%, respectively, at a median follow-up of 9 years, compared to 58% and 73% in patients with residual disease26.
It has been reported that luminal tumors with high Ki-67 expression respond well to chemotherapy, likely reflecting their high proliferative activity27. In a study by Aktas et al.28 the Ki-67 level was identified as a guide for personalized treatment. Our study results are consistent with the literature in this regard. However, it should be noted that the European Society for Medical Oncology states that there is no consensus on a definitive cut-off value for Ki-67, but that values less than 10% are considered low and values greater than 30% are considered high29. Although stage, menopausal status, age, Ki-67, grade, HER2 expression, HR status, and even multiple gene expression analyses are used to assess whether neoadjuvant therapies will benefit a patient, identifying patients who will respond to NACT remains a challenging decision30.
The recommendation that NACT can be used instead of adjuvant chemotherapy in HR+/HER2- BC is based on data from the NSABP B-18 study, which showed no difference in DFS or OS between adjuvant and neoadjuvant treatment in patients with stage II-III BC31. Factors guiding the decision-making process for adjuvant systemic therapy (e.g., lymph node status, tumor grade, and comorbidities) can also be used to select patients with HR+/HER2- BC for whom NACT is appropriate, although it should be recognized that some factors, such as lymph node status, may be better assessed following definitive surgery31. The benefit of NACT in luminal subtype BC include performing BCS; however, whether neoadjuvant therapy improves prognosis in luminal subtype BC is controversial32.
Yang et al.13 reported that pretreatment NLR, PLR, and SII predicted pCR in BC patients undergoing NACT. Cullinane et al.33 reported in their meta-analysis that NLR was a predictor of pCR in BC patients. A study by Kaytaz Tekyol et al.34 demonstrated that low PLR levels were associated with higher chemotherapy sensitivity in NACT-treated BC, independent of molecular subtypes, but no association was found between NLR levels and pCR. A study by Eryilmaz et al.35 also found no association between pCR and pretreatment NLR values. In the study by Hu et al.36 lower pretreatment PLR was associated with higher pCR rates after NACT, but no such association was demonstrated with NLR. In the study by Wang et al.37 higher pretreatment NLR and PLR were associated with a higher probability of achieving pCR, but pretreatment SII was not associated with a higher pCR.
In our study, no association was found between NLR, PLR, and SII and pCR. In the literature, different studies use different cutoff values for inflammatory markers, and the lack of a standard cutoff value may explain the discrepancies in the results of the studies34. Furthermore, many studies evaluated BC patients of all molecular subtypes together. Our study evaluated only HR+/HER2- patients to obtain more reliable results.
Study Limitations
Limitations of the study include the small number of patients conducted at a single center and its retrospective design. In addition, due to its retrospective design, it is possible that some conditions such as diseases and medication use that could affect blood values could not be evaluated due to incomplete records and could affect the results.
CONCLUSION
Predicting patients who will respond well to NACT in BC treatment is important. Inflammatory indices are inexpensive, reproducible, and easily accessible parameters that can be calculated with routine blood count analysis. However, given the conflicting results in the literature, negative studies including ours, and the multitude of factors that can influence blood parameters, their suitability for routine use in predicting chemotherapy response is questionable. Prospective clinical studies of sufficient size are needed to determine whether inflammatory indices can be a significant prognostic indicator of pCR.
