Pathological complete response and associated factors in breast cancer after neoadjuvant chemotherapy: A retrospective study

Abstract

Objective: This study aimed to determine clinical and pathological factors that identify a pathological complete response (pCR) in breast cancer patients undergoing neoadjuvant chemotherapy (NAC).

Material and Methods: A retrospective, single-center study was conducted in women over the age of 18 who had been diagnosed with pathologically confirmed invasive breast cancer and who had received NAC between July 2016 and October 2021. Patient demographics, clinical, radiological, treatment, and pathological data were reviewed from the electronic hospital records. The primary outcome of interest was pCR, defined as the absence of residual invasive breast cancer in both the breast and axillary lymph nodes. Multivariable logistic regression analysis was used to identify factors associated with pCR.

Results: A total of 119 patients were included in the analysis. The distribution of age was 54.5 ± 11.5 years. pCR was observed in 33 (27.7%) patients. pCR for breast tissue was observed in 43 (36.1%) patients. There was no statistically significant relation between the clinical stage and pCR. Age, age at first labor, extent of disease in the breast, NAC completeness, clinical tumor size (cT) stage, clinical lymph node (cN) stage, and molecular subtype were analyzed in a multivariable model. Analysis showed that molecular subtype was the only independent factor related to pCR. pCR rates across molecular subtypes were: 8.7% in luminal-A, 10.8% in luminal-B, 54.5% in human epidermal growth factor receptor 2 (HER-2)-positive, 42.4% in luminal-B (HER-2 positive) and 46.7% in triple-negative. There was no statistically significant difference between luminal-A and luminal-B subgroups (odds ratio 1.15, 95% confidence interval, 0.19-9.35, p= 0.881). Despite the limited number of patients in HER2-positive and triple-negative groups, both demonstrated statistically significant higher odds compared to reference group.

Conclusion: The presented study underscores the relevance of molecular subtypes in determining the response to neoadjuvant chemotherapy in breast cancer patients. Particularly HER2-positive and triple-negative subtypes may demonstrate more favorable response rates.

Keywords: Breast cancer, neoadjuvant chemotherapy, pathological complete response, molecular subtypes

Introduction

Several treatment options including chemotherapy, hormone therapy, radiation therapy, and surgery are used in the treatment of breast cancer (1,2). However, the efficacy of these treatments can vary significantly from patient to patient, highlighting the necessity for personalized treatment strategies. Important variables such as age, genetic composition, and individual characteristics are critical to the treatment’s success (3-5). Modern treatment regimens may include a combination of several treatment strategies (6). By considering these individual factors, healthcare professionals work to create treatment plans that are customized to meet the specific needs of each patient. Such personalized approaches are crucial in improving the survival rates of breast cancer patients (7).

Several parameters need to be evaluated during the initial treatment planning phase (8). In recent years, tumor molecular subtypes have emerged as one of the most extensively researched factors in this regard. Molecular subtyping provides valuable insights into the heterogeneity of breast cancer, enabling healthcare professionals to better understand the underlying biology and tailor treatment strategies accordingly. By categorizing breast cancer into distinct molecular subtypes, such as luminal A, luminal B, human epidermal growth factor receptor 2 (HER2)-positive tumors, and triple-negative breast cancer (TNBC), clinicians can identify specific characteristics and response patterns to different therapies (5,8,9).

This information aids in the selection of appropriate treatment modalities based on the molecular profile of the tumor.

The aim of the study was to evaluate the clinical and pathological factors contributing to achieving a pathological complete response (pCR) for breast cancer patients who received neoadjuvant chemotherapy (NAC). By doing this, the research aimed at increasing our understanding of the underlying factors, which might significantly improve our ability to predict which patients would benefit from NAC the most.

Material and Methods

The study was designed as a single-center, observational study and included the retrospective analysis of all female patients over the age of 18 diagnosed with invasive breast cancer that was pathologically confirmed and who received NAC between July 2016 and October 2021 at Karadeniz Technical University, Faculty of Medicine, Farabi Hospital.

The study was approved by the ethics committee of the university. Exclusion criteria were defined as metastatic disease at the time of diagnosis, previous treatment for breast cancer, and inability to access patient data after neoadjuvant therapy.

Electronic hospital records were reviewed for patient demographics, clinical data, radiological data, treatment data and pathological data. The TNM Classification System of the Union for International Cancer Control (8^th edition) was used for pathological analysis (10). Subsequently, clinical results were verified by radiological evaluations to improve diagnosis accuracy. In order to assess the effectiveness of treatment, treatment data such as details about chemotherapy protocols and surgical procedures was categorized. In order to reduce data missingness, patients were contacted and invited to the hospital.

pCR was defined as the absence of residual invasive breast cancer in histopathological samples from both the breast and axillary lymph nodes (ypT0/ypTis-ypN0) (11). Systemic treatment was given by evaluating the analyzed clinical and biological factors according to factors such as age, preNAC clinical tumor size (cT) stage, clinical lymph node (cN) stage and histopathological molecular subtype. Systemically, cyclophosphamide, anthracycline and taxane treatments were administered to patients with HER2 expression, trastuzumab and/or pertuzumab treatment, and patients with TNBC were treated with carboplatin according to the National Comprehensive Cancer Network (NCCN) and American Society of Clinical Oncology (ASCO) guidelines. Lesions were marked with clips before systemic treatment. The patients were analyzed in two groups according to their NAC treatment response as non-pCR and pCR.

Estrogen receptor (ER), progesterone receptor (PR) and HER2 status were assessed using immunohistochemistry (IHC) analysis. Positivity for ER and PR status was defined as expression in >1% of tumor cells. ER positive and PR positive tumors were classified as luminal type A or B according to their Ki-67 proliferation index < or ≥14. HER2 expression was determined by IHC or fluorescent in situ hybridization (FISH), depending on the situation. The molecular subtypes were classified as luminal-A, luminal-B, luminal-B (HER2-positive), HER2-positive, and triple-negative. As a surgical method, breast-conserving surgery (BCS) or mastectomy was performed according to the results of multicentricity, patient preference and pathological data. As axillary surgical procedure, sentinel lymph node biopsy (SLNB) was performed in case of cN0, with axillary lymph node dissection (ALND) applied if there was a SLNB positivity; for cN positive cases axillary surgical methods (SLNB or ALND) were preferred based on the surgeon’s choice.

Statistical Analysis

Open-source statistical programming language R software (Vienna, Austria) was used to analyze the data. In the presentation of numerical data, mean ± standard deviation or median (Q1- Q3) was used according to distribution. Categorical data were presented as n (%). T- test or Mann-Whitney U test was used for numerical data when comparing the two groups. Chi-square or Fisher tests were used to evaluate categorical data. Logistic regression test was used to examine the factors related with pCR (uni-and multivariable). Beyond parameters with a p-value below 0.10 in univariable analysis, clinically important factors were added into the multivariable analysis. When parameters were correlated with each other or used in the definition of a factor, the most important one among them was included in the model. The effect sizes were expressed as odds ratio (OR) with the corresponding 95% confidence interval (CI) and p value. P value <0.05 was considered statistically significant.

Results

The current study included 119 female patients diagnosed with breast cancer, with a mean age of 54.5 ± 11.5 years. In 64 (%53.8) patients, the tumor was located in left breast, and the most common locations in the breast were the outer and upper quadrants. A total of 62 (%52.1) patients were in the premenopausal period.

pCR was observed in 33 (27.7%) patients. pCR for breast was 43 (36.1%) patients and for axilla 58 (48.7%) patients (Figure 1). Among all patients, 51 (42.9%) did not show pCR neither in the breast nor axilla. For 10 (8.4%) patients, there was pCR in the breast but not in the axilla. Demographics and clinical characteristics of patients were presented in Table 1. There was not a statistically significant difference between pCR and nonpCR groups in terms of demographics and personal history.

Figure 1. pCR and non-pCR rates for the breast, axilla and overall.

Table 1. Demographics and clinical characteristics of the patients

Radiological and histopathological characteristics are presented in Table 2. Tumor size was lower in the pCR group [2.1 (1.9-2.8) cm] compared to the non-pCR group [2.8 (1.9-3.8) cm] (p= 0.022). Luminal-B [37 (31.1) patients] and luminal-B (HER2-positive) [33 (27.7) patients] subtypes were the most common molecular subtypes. There was a statistically significant difference for ER status (p= 0.001), PR status (p= 0.006), HER2 status (p= 0.004), and Ki-67 (p= 0.016) between the pCR and non-pCR groups.

Table 2. Radiological/pathological characteristics of the patients

pCR rates demonstrated a statistically significant difference among the subgroups. Luminal-A and luminal-B showed the highest non-pCR rates. pCR rates according to the molecular subtypes are shown in Figure 2. Treatment- related characteristics are shown in Table 3. The completeness rate of NAC treatment was comparable between the groups (78.8% in pCR and 74.4% in non-pCR groups, p= 0.796). While the surgical management of the breast was similar, management for the axilla showed difference between the groups.

Figure 2. pCR rates according to molecular subtypes.

Table 3. Treatment-related characteristics

In multivariable regression analysis, the molecular subtype was identified as the sole statistically significant factor for pCR. When the luminal-A group was taken as the reference, no difference was found in terms of pCR for luminal-B [1.15 (0.19-9.35), 0.881]. However, in the luminal-B (HER2-positive) [11.36 (2.31-88.38), 0.007], HER2-positive [11.87 (1.85- 109.53), 0.014], and triplenegative [12.51 (1.99-115.14), 0.012] subgroups, the odds of pCR were higher compared to the luminal-A subgroup. The results of logistic regression analysis for pCR are presented in Table 4.

Table 4. Logistic regression analysis for pCR

Discussion

In the study evaluating breast cancer patients undergoing NAC, pCR rate, defined as the absence of residual invasive cancer in both breast and axillary lymph nodes, was found to be 27.7%. Despite cT and cN not exhibiting statistical significance in relation to pCR, factors such as tumor size, ER status, PR status, HER2 status, and Ki-67 index were identified as potential factors with pCR. In multivariable analysis, the molecular subtype emerged as a significant risk factor. Notably, while pCR rates were low in luminal-A and luminal-B subtypes, higher pCR rates were observed in HER2-positive and triple-negative groups.

In breast cancer treatment, achieving pCR is vital as it means that no cancer remains in the breast and lymph nodes after treatment. The general approach to pCR involves treatment strategies for both the primary tumor and lymph nodes. The presented study, in line with the existing literature, reveals that 36.1% of the patients achieved breast pCR, while 48.7% achieved axillary pCR (8,12). Remarkably, 8.4% achieved breast pCR without an axillary response. The significance of achieving axillary pCR after primary systemic treatment cannot be overstated, as it plays a crucial role in reducing the risk of relapse and improving overall survival, particularly in the axillary region. Research at the University of Texas MD Anderson Cancer Center has underscored the significance of axillary pCR, linking it to improved 10-year survival following systemic therapy (13). However, there is an ongoing debate about whether pCR should also indicate the absence of ductal carcinoma in situ (DCIS). Findings from the I-SPY2 trial suggest that the presence or absence of DCIS does not significantly impact the outcomes (7). Standardizing pCR definition and learning more about its clinical effects are important for managing and predicting the prognosis of breast cancer patients who are going through neoadjuvant therapy.

Breast cancer treatments incorporating carboplatin, pembrolizumab, and anti-HER agents have notably increased pCR rates in triple-negative and HER2 subtypes (14,15). According to the data from the presented study, receptors for ER, PR, and HER2 may play pivotal roles in achieving pCR, with the literature corroborating lower pCR rates in luminal-A and luminal-B subtypes (8,9,16). Conversely, luminal-B (HER2- positive), HER2-positive, and triple-negative subtypes have demonstrated appreciably higher pCR rates, underscoring the importance of subtypes in treatment to the success of a complete response. The study also demonstrated that Ki67 levels, along with the molecular subtype, is a significant factor of pCR (17). Similarly, the EORTC 10994/BIG 1-00 study emphasized that pCR following chemotherapy is robustly linked with both breast cancer subtype and long-term survival, further illuminating the prognostic implications of pCR (18).

In the presented study, not completing NAC did not significantly affect pCR rates likely due to the small patient sample. However, a meta-analysis has shown that patients who do not complete NAC often have lower pCR rates (19). Adding to the prognostic factors affecting pCR, recent studies have indicated a possible link between higher body mass index (BMI) and decreased pCR rates in breast cancer patients undergoing NAC (20) though the presented study did not find BMI to significantly alter pCR outcomes. The number of patients in the presented study may not be sufficient to determine the true prognostic value of BMI on treatment effectiveness. Analysis from the presented study suggested that neither age nor menopausal status significantly differentiated pCR from non-pCR groups. While some studies point to age as a potential influencer of pCR rates in NAC, other studies, including the one discussed, report no meaningful correlation (3,21,22). Studies also indicate, aligning with the findings from the current study, that menopausal status does not play a crucial role in pCR (21,22).

NAC aims to reduce surgical extent in breast cancer treatment, as established by previous research. Contrarily, the presented study observed a preference for more extensive surgeries, including ALND, even when NAC was administered. The ACOSOG Z1071 (Alliance) trial has demonstrated an association of tumor biology with higher rates of BCS (8). Additionally, axillary pCR rates post-NAC are significantly affected by breast cancer subtypes, particularly in hormone receptor (HR) negative/HER2-positive and triple-negative cases (23). Patients undergoing ALND report more frequent adverse effects like motor neuropathy, sensory neuropathy, and lymphedema (24). Due to these complications, there is a shifting preference towards less invasive treatments over ALND (25). The presented study showed high rates of ALND and mastectomy based on physician and patient preferences.

The presented study had limited radiological access opportunities and did not include survival and recurrence analyses with a retrospective nature. Sample sizes for certain breast cancer subtypes and biomarker groups were small, which might limit the generalizability of our results. The research was confined to a single center, which could influence the applicability of the findings to a wider population. Future studies should aim to incorporate the relation between pCR and survival outcomes.

Conclusion

The presented study demonstrates variations in pCR rates among molecular subtypes, highlighting more favorable responses in HER2-positive and triple-negative patients compared to other subtypes. Luminal-type breast tumors exhibited significantly lower pCR rates. Future investigations should focus on these findings, emphasizing personalized treatment strategies targeting molecular subtypes for enhanced responses to NAC.

Cite this article as: Gündoğdu A, Uluşahin M, Çekiç AB, Kazaz SN, Güner A. Pathological complete response and associated factors in breast cancer after neoadjuvant chemotherapy: A retrospective study. Turk J Surg 2024; 40 (1): 73-81.

This study was approved by Karadeniz Technical University Faculty of Medicine Scientific Research Ethics Committee (Decision date: 01.02.2022, No: 24237859-51).

Externally peer-reviewed.

Concept - All of authors; Design - All of authors; Supervision - AG, AG; Data Collection and/or Processing - AG, AG; Analysis and/or Interpretation - All of authors; Literature Search - AG, MU, AG; Writing Manuscript - AG, AG; Critical Reviews - All of authors.

The authors have no conflicts of interest to declare.

The authors declared that this study has received no financial support.

References

1. Asselain B, Barlow W, Bartlett J, Bergh J, Bergsten-Nordström E, Bliss J, et al. Long-term outcomes for neoadjuvant versus adjuvant chemotherapy in early breast cancer: Meta-analysis of individual patient data from ten randomised trials. Lancet Oncol 2018; 19(1): 27-39.
2. Arslan B, Tazeoğlu D, Dağ A, Berkeşoğlu M, Özdemir AA. Is there an increasing trend of risk-reducing prophylactic mastectomy procedure in preventing breast cancer among women? Turk J Surg 2021; 37(4): 347-54. https://doi.org/10.47717/turkjsurg.2021.4963
3. Villarreal-Garza C, Bargallo-Rocha JE, Soto-Perez-de-Celis E, LasaGonsebatt F, Arce-Salinas C, Lara-Medina F, et al. Real-world outcomes in young women with breast cancer treated with neoadjuvant chemotherapy. Breast Cancer Res Treat 2016; 157(2): 385-94. https:// doi.org/10.1007/s10549-016-3811-2
4. Swain SM, Tang G, Brauer HA, Goerlitz DS, Lucas PC, Robidoux A, et al. NSABP B-41, a randomized neoadjuvant trial: Genes and signatures associated with pathologic complete response. Clin Cancer Res 2020; 26(16): 4233-41. https://doi.org/10.1158/1078-0432.CCR-20-0152
5. Esserman LJ, Berry DA, Cheang MC, Yau C, Perou CM, Carey L, et al. Chemotherapy response and recurrence-free survival in neoadjuvant breast cancer depends on biomarker profiles: Results from the I-SPY 1 TRIAL (CALGB 150007/150012; ACRIN 6657). BreastCancer Res Treat 2012; 132(3): 1049-62.
6. Waks AG, Winer EP. Breast Cancer Treatment: A Review. JAMA 2019; 321(3): 288-300. https://doi.org/10.1001/jama.2018.19323
7. Osdoit M, Yau C, Symmans WF, Boughey JC, Ewing CA, Balassanian R, et al. Association of residual ductal carcinoma in situ with breast cancer recurrence in the neoadjuvant I- SPY2 trial. JAMA Surg 2022; 157(11): 1034-41.
8. Boughey JC, McCall LM, Ballman KV, Mittendorf EA, Ahrendt GM, Wilke LG, et al. Tumor biology correlates with rates of breast-conserving surgery and pathologic complete response after neoadjuvant chemotherapy for breast cancer: Findings from the ACOSOG Z1071 (Alliance) prospective multicenter clinical trial. Ann Surg 2014; 260(4): 608-14; discussion 14-6. https://doi.org/10.1097/ SLA.0000000000000924
9. von Minckwitz G, Untch M, Blohmer JU, Costa SD, Eidtmann H, Fasching PA, et al. Definition and impact of pathologic complete response on prognosis after neoadjuvant chemotherapy in various intrinsic breast cancer subtypes. J Clin Oncol 2012; 30(15): 1796-804. https:// doi.org/10.1200/JCO.2011.38.8595
10. Amin MB, Greene FL, Edge SB, Compton CC, Gershenwald JE, Brookland RK, et al. The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population-based to a more “personalized” approach to cancer staging. CA Cancer J Clin 2017; 67(2): 93-9.
11. Spring LM, Fell G, Arfe A, Sharma C, Greenup R, Reynolds KL, et al. Pathologic complete response after neoadjuvant chemotherapy and impact on breast cancer recurrence and survival: A comprehensive meta-analysis. Clin Cancer Res 2020; 26(12): 2838-48. https://doi. org/10.1158/1078-0432.CCR-19-3492
12. Lim DW, Greene BD, Look Hong NJ. Relationship Between breast and axillary pathologic complete response in women receiving neoadjuvant chemotherapy for breast cancer. Ann Surg Oncol 2021; 28(10): 5495-506. https://doi.org/10.1245/s10434-021-10519-8
13. Mougalian SS, Hernandez M, Lei X, Lynch S, Kuerer HM, Symmans WF, et al. Ten-year outcomes of patients with breast cancer with cytologically confirmed axillary lymph node metastases and pathologic complete response after primary systemic chemotherapy. JAMA Oncology 2016; 2(4): 508-16. https://doi.org/10.1001/jamaoncol.2015.4919
14. Lin C, Cui J, Peng Z, Qian K, Wu R, Cheng Y, et al. Efficacy of platinumbased and non-platinum-based drugs on triple-negative breast cancer: Meta-analysis. Eur J Med Res 2022; 27(1): 201.
15. Mittendorf EA, Philips AV, Meric-Bernstam F, Qiao N, Wu Y, Harrington S, et al. PD-L1 expression in triple-negative breast cancer. Cancer Immunol Res 2014; 2(4): 361-70.
16. de Haas SL, Slamon DJ, Martin M, Press MF, Lewis GD, Lambertini C, et al. Tumor biomarkers and efficacy in patients treated with trastuzumab emtansine + pertuzumab versus standard of care in HER2- positive early breast cancer: an open-label, phase III study (KRISTINE). Breast Cancer Res 2023; 25(1): 2.
17. Fasching PA, Heusinger K, Haeberle L, Niklos M, Hein A, Bayer CM, et al. Ki67, chemotherapy response, and prognosis in breast cancer patients receiving neoadjuvant treatment. BMC Cancer 2011; 11: 486.
18. Bonnefoi H, Litière S, Piccart M, MacGrogan G, Fumoleau P, Brain E, et al. Pathological complete response after neoadjuvant chemotherapy is an independent predictive factor irrespective of simplified breast cancer intrinsic subtypes: a landmark and two-step approach analyses from the EORTC 10994/BIG 1-00 phase III trial. Ann Oncol 2014; 25(6): 1128-36. https://doi.org/10.1093/annonc/mdu118
19. Battisti NML, True V, Chaabouni N, Chopra N, Lee K, Shepherd S, et al. Pathological complete response to neoadjuvant systemic therapy in 789 early and locally advanced breast cancer patients: The Royal Marsden experience. Breast Cancer Res and Treat 2020; 179(1): 101- 11.
20. Wang H, Zhang S, Yee D, Basu S, Beckwith H, Potter D, et al. Impact of body mass index on pathological complete response following neoadjuvant chemotherapy in operable breast cancer: a meta-analysis. Breast Cancer 2021; 28(3): 618-29. https://doi.org/10.1007/s12282- 020-01194-w
21. Cullinane C, Brien AO, Shrestha A, Hanlon EO, Walshe J, Geraghty J, et al. The association between breast density and breast cancer pathological response to neoadjuvant chemotherapy. Breast Cancer Res Treat 2022; 194(2): 385-92. https://doi.org/10.1007/s10549-022- 06616-1
22. Resende U, Cabello C, Ramalho SOB, Zeferino LC. Prognostic assessment of breast carcinoma submitted to neoadjuvant chemotherapy with pathological non-complete response. BMC Cancer 2019; 19(1): 601.
23. Samiei S, Simons JM, Engelen SME, Beets-Tan RGH, Classe JM, Smidt ML. Axillary pathologic complete response after neoadjuvant systemic therapy by breast cancer subtype in patients with initially clinically node-positive disease: A systematic review and meta-analysis. JAMA Surg 2021; 156(6): e210891. https://doi.org/10.1001/jamasurg.2021.0891
24. Galimberti V, Cole BF, Viale G, Veronesi P, Vicini E, Intra M, et al. Axillary dissection versus no axillary dissection in patients with breast cancer and sentinel-node micrometastases (IBCSG 23-01): 10-year followup of a randomised, controlled phase 3 trial. Lancet Oncol 2018; 19(10): 1385-93. https://doi.org/10.1016/S1470-2045(18)30705-8
25. Bartels SAL, Donker M, Poncet C, Sauvé N, Straver ME, van de Velde CJH, et al. Radiotherapy or surgery of the axilla after a positive sentinel node in breast cancer: 10-year results of the randomized controlled EORTC 10981-22023 AMAROS trial. J Clin Oncol 2023; 41(12): 2159-65. https://doi.org/10.21037/cco-23-50