Quantification of Ki67 Change as a Valid Prognostic Indicator of Luminal B Type Breast Cancer After Neoadjuvant Therapy
- 1Department of Breast Surgery, The First Affiliated Hospital of China Medical University, Shenyang, China
- 2Department of Breast Surgery, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, China
- 3Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, China
- 4Breast Cancer Center, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
- 5Breast Center, The Affiliated Hospital of Qingdao University, Qingdao, China
Introduction: Ki67 value and its variation before and after neoadjuvant chemotherapy are commonly tested in relation to breast cancer patient prognosis. This study aims to quantify the extent of changes in Ki67 proliferation pre- and post-neoadjuvant chemotherapy, confirm an optimal cut-off point, and evaluate its potential value for predicting survival outcomes in patients with different molecular subtypes of breast cancer.
Methods: This retrospective real-world study recruited 828 patients at the Department of Breast Surgery of the First Affiliated Hospital of China Medical University and the Cancer Hospital of China Medical University from Jan 2014 to Nov 2020. Patient demographic features and disease pathology characteristics were recorded, and biomarkers were verified through immunohistochemistry. Various statistical methods were used to validate the relationships between different characteristics and survival outcomes irrespective of disease-free and overall survival.
Results: Among 828 patients, statistically significant effects between pathological complete response and survival outcome were found in both HER2-enriched and triple-negative breast cancer (p < 0.05) but not in Luminal breast cancer (p > 0.05). Evident decrease of Ki67 was confirmed after neoadjuvant chemotherapy. To quantify the extent of Ki67 changes between pre- and post-NAC timepoints, we adopted a computational equation termed ΔKi67% for research. We found the optimal cut-off value to be “ΔKi67% = −63%” via the operating characteristic curve, defining ΔKi67% ≤ −63% as positive status and ΔKi67% > −63% as negative status. Patients with positive ΔKi67% status were 37.1% of the entire cohort. Additionally, 4.7, 39.9, 34.5 and 39.6% of patients with Luminal A, Luminal B, HER2-enriched and triple negative breast cancer were also validated with positive ΔKi67% status. The statistically significant differences between ΔKi67% status and prognostic outcomes were confirmed by univariate and multivariate analysis in Luminal B (univariate and multivariate analysis: p < 0.05) and triple negative breast cancer (univariate and multivariate analysis: p < 0.05). We proved ΔKi67% as a statistically significant independent prognostic factor irrespective of disease-free or overall survival among patients with Luminal B and triple-negative breast cancer.
Conclusions: ΔKi67% can aid in predicting patient prognostic outcome, provide a measurement of NAC efficacy, and assist in further clinical decisions, especially for patients with Luminal B breast cancer.
Breast cancer is the highest cause of cancer-related morbidity among women worldwide . Established biomarkers, including hormone receptors (HR), estrogen receptor (ER), progesterone receptor (PR), human epidermal growth receptor-2(HER-2), and Ki67 labeling index classify breast cancer into four subtypes: HER2-enriched, triple-negative (TN), and Luminal A and B types [2,3]. Neoadjuvant chemotherapy (NAC) is a standard therapeutic strategy for inoperable breast cancer and for some operable patients who seek decreased primary tumor burden and breast conservation . Patient response to NAC also provides guidance for the long-term systemic therapeutic strategy for each individual patient . A achievement of pathological complete response (pCR), disease-free survival (DFS), and overall survival (OS)  were used to estimate treatment efficacy. Only 15–20% of patients who receive NAC reach pCR [7–9]. Although pCR plays an important role in prognostic prediction and assists in treatment decisions for TN and HER2-enriched breast cancer, it is less effective in Luminal breast cancer subtypes [10–12]. Luminal breast cancer still lacks indicators to classify patients who will benefit from NAC.
Ki67, a nuclear indicator of cellular proliferation, has been extensively studied and scrutinized for several years. Although some studies criticize Ki67 for its lack of reproducibility [13,14], many demonstrate that proliferation index relates to patient outcomes [2,4,15–17]. These study showKi67 expression as useful indicator for breast cancer and a useful prognostic factor for patients with Luminal B and node-positive breast cancer, assisting in clinical decision regarding neoadjuvant endocrine therapy [18,19]. Some studies indicates that Ki67 levels pre-NAC can be an independent prognostic predictor for OS and DFS [12,16]. Endocrine therapy can decrease cell proliferation, presenting as changed Ki67 level pre- and post-NAC [20,21]. In the POETIC clinical phase-3 trial, this change in Ki67 levels was able to guide endocrine therapy decisions for women with ER-positive breast cancer . One commonality across studies was that decreased levels of Ki67 post-NAC compared to pre-NAC holds significant prognostic predictive value [12,18,22–25]. However, some researchers contend that post-NAC Ki67 may hold limited prognostic value .
Previous researches often define the extent of Ki67 change between pre- and post-NAC simply by subtracting the two values. This definition is simple but insufficient, as illustrated in two scenarios. The first is if pre- and post-NAC Ki67 proliferation are both relatively low, then the extent of the change may not reach the set threshold. In the second, the change may be comparatively large but not large enough to reach the cut-off value. Furthermore, high variation of pre- and post-NAC Ki67 have been classified by several groups, with studies proposing different thresholds of variation based on the attempts.
In this retrospective study, we evaluate the usefulness of Ki67 change before and after NAC for predicting survival outcome across breast cancer molecular subtypes. We further quantify the change in Ki67 by percentage before and after NAC and calculate an optimal threshold to assess its predictive function for long-term survival and its ability to aid in deciding further adjuvant therapy modification across breast cancer subtypes.
Patient Selection Criterion
This retrospective study included patients with primary breast cancer who were treated with NAC from Jan 2014 to Nov 2020 at the Department of Breast Surgery of the First Affiliated Hospital of China Medical University and the Cancer Hospital of China Medical University.
Patient Inclusion Criteria
All patients received a minimum of one cycle of NAC ahead of surgery. Patients with cancer in situ were excluded, as were patients with invasive breast cancer before NAC could be incorporated in cohort. Patients who received any kind of treatment prior to NAC or who presented with progressive or metastatic breast cancer were excluded. Patients with previous breast cancer, male patients, and those with synchronous invasion, bilateral, or inflammatory breast cancer were also excluded. 68 cases with incomplete or deficient IHC analysis were also excluded. In total, 828 patients met the above restriction standards and were included.
Classifications of Patients
This retrospective study received permission from the institutional review board (IRB) of the First Affiliated Hospital and was in accordance with the Helsinki Declaration. All patients involved in the research gave informed consent in written agreements of specimens used for scientific research. The informed consent of retrospective research involvement could be waived based on the retrospective nature of the study. Pre-NAC core needle biopsy pathology and post-surgery regular pathology was extracted and saved in a database. Patient characteristics were collected including gender, age at diagnosis, body mass index (BMI), maximum tumor diameter, tumor grade and stage, axillary lymph node status, histologic type, NAC schedule and cycle number, histology grade, and clinical response to NAC. The local extent of breast cancer was measured via breast ultrasound, mammography, breast MRI, chest CT, bone scan and/or hepatobiliary and splenic ultrasound to verify distant metastasis. The final size of local breast cancer in our database was adopted following priorities: breast MRI > breast ultrasound > mammography. Every patient with suspicious lymph-node metastasis suggested by imaging examinations underwent ultrasound-guided core biopsy of ultrasound-graphically abnormal nodes for axillary node metastasis confirmation before starting NAC. The final histological assessments were all analyzed using hematoxylin and eosin staining and immunohistochemical (IHC). The histological type of specimens from incorporated patients was distinguished between two subgroups: general invasive breast carcinoma of no special type (IBC-NST) and Others. The latter group contained special subtypes such as lobular, mucinous and tubular carcinomas with ≥90% of the tumor as a pure special tumor type and mixed IBC-NST with special subtypes. Lymph nodes with micro-metastasis were considered positive, including the maximum diameter over 0.2 mm or the number of tumor cells over 200. Isolated tumor cells were considered negative.
Assessment of Clinical Effectiveness of Chemotherapy
Pathological complete response (pCR) was defined as no residual invasive tumor upon hematoxylin and eosin evaluation of the complete resected breast specimen and all sampled lymph nodes (noninvasive breast residuals) (ypT0/is, ypN0).
Immunohistochemistry for Biomarker Detection
Histopathology is regarded as the gold standard for diagnosis. All breast tumor specimens were acquired from core needle biopsy or surgical resections, and every specimen was affixed into formalin-fixed, paraffin-embedded tissue sections for preservation. IHC staining was performed using Dako Autostainer Plus and EnVision Dual Link detection reagent (DAKO; Carpinteria, CA) with DAB (Dako). Biomarker status, including ER, PR and HER2, were defined by IHC in strict accordance with European Quality Assurance guidelines. ER and PR staining were assessed based on the American Society of Clinical Oncology/College of American Pathologists Guidelines [27,28]. Antibodies used in IHC include as anti-ER (Clone SP1, Dako), anti-PR (Clone PgR636, Dako), and Ki67 (Clone Mib-1, Dako). Hematoxylin II (Dako As Link 48) was used to counterstain specimens automatically. All tests incorporated external positive and negative controls. ER and PR stains were considered positive if immunostaining was seen in more than 1% of immunoreactive cells. HER2 status was ascertained via IHC using the Hercep Test ™kit (code K5204, Dako). HER2 expression was scored as 0, 1+, 2+, and 3 + according to ASCO guidelines. A score of 3+ was regarded as HER2+, with 0/1+ defined as HER2-. For cases scoring HER2 2+, a fluorescent in situ hybridization (FISH) test could be conducted. The measurement of Ki67 index was based on the spot with the highest intensity in a high-power field (400x) and 500–2000 cells were counted .
Following the St. Gallen guidelines 2013 , high expression of PR was set as ≥20% and low expression of PR was defined as <20%. In accordance with the International Ki67 in Breast Cancer Working Group , Ki67 index was classified into two groups: low (<30%), and high (≥30%). To quantify the extent of Ki67 changes between pre- and post-NAC timepoints, we used the following equation: [define post-NAC Ki67 as A, define pre-NAC Ki67 as B, computational formula: ΔKi67%=(A−B)/B × 100%, maintaining sign]. If a patient achieved pCR after NAC, the post-NAC Ki67 index was defined as 0% and ΔKi67% was mathematically −100%. Representative IHC staining images of Ki67 subgroups are shown in Supplementary Figure S2.
Breast Cancer Subtypes Definitions
We classified breast cancers into four subtypes based on HR status, HER2 status and Ki67 index according to the St. Gallen guidelines as follow [2,31]: Luminal A: (ER and PR positive, HER2 negative, “low” Ki-67, and a “low” recurrence risk based on multi-gene-expression assay results if available), Luminal B [“Luminal B-like (HER2 negative)”: ER positive, HER2 negative, and at least one of the following: “high” Ki-67, “negative or low” PR, or “high” recurrence risk based on multi-gene-expression assay if available. “Luminal B-like (HER2 positive)”: ER positive, HER2 over-expressed or amplified with any Ki-67, and any PR]. HER2-enriched (HER2 over-expressed or amplified, ER and PR absent) and TN (Negative ER, PR and HER2). The cut-point between “high” and “low” values for Ki67 varies and lacks conclusion. 14% cut-off value of Ki67 for subtype classification was adopted in St. Gallen guidelines 2013.
Statistical Data Analysis
Multiple demographic features were analyzed using the Chi-square test. The survival-related indicators studied were DFS and OS. DFS was calculated from the date of initiation of the first regimen to the date of first event (locoregional relapse, distant relapse, or death) and OS was calculated from the date of surgery to the date of death or last follow-up. The Kaplan–Meier method was used to define the difference ratio, and survival curves were compared using the log-rank test . Significance was assigned as p value < 0.05. Receiver operating characteristic curve (ROC) and area under the curve (AUC) were performed to calculate the optimal cut-off value determined by the Youden index with maximum sensitivity and specificity. Cox proportional hazards regression models were used to estimate relapse and survival risk between subgroups. The multivariate Cox proportional hazards model was implemented for Hazard Ratio (HR) and 95% confidence intervals (CI) to identify independent prognostic factors. Net reclassification improvement (NRI) was used to verify classification accuracy. All statistical data analysis was performed using SPSS 26.0 (SPSS Inc., Chicago, IL, United States) and R programming language (version 3.5.3; https://www.r-project.org/).
Basic Demographic Features and Baseline Characteristics
Patients with primary breast cancer who were treated with NAC were selected based on strict standards. 942 patients were initially included in the cohort, but 114 patients were eliminated for various reasons. A total of 828 female patients with primary breast cancer who received NAC were ultimately included in this retrospective study (Figure 1).
Basic demographic and pathologic features are shown in Table 1. The median age of entire cohort was 51 ± 9.65 years old (range: 23–76 years), of which 10.0% of patients were under 40 years old at diagnosis. Body mass index was used to distinguish subjects: overweight patients with index greater than or equal to 24.9 accounted for 48.2%, underweight patients with index under 18.9 accounted for 8.2 and 43.6% of patients had a healthy BMI between 18.9–24.9. Breast cancer pathological subtype was confirmed as invasive carcinoma of NST for 84.4% of patients. All other histological types represented 15.6% of the full cohort. A median of 4 NAC cycles were received (range: 1–9), with NAC classified into three groups: texane-based (10.7%), anthracycline-based (18.1%) and texane + anthracycline (71.1%). The average maximum tumor diameters before and after NAC were 3.41 ± 1.651 and 2.26 ± 1.648 cm, respectively. 81.9% patients presented with node-positive status at diagnosis. Finally, 138 subjects (16.7%) who received NAC achieved pCR, a commonly used measurement of NAC efficacy.
We next analyzed IHC biomarkers. Patients with ER positivity made up 59.5% of the cohort. Patients with PR < 20%, or negative status, represented 62.8% of the cohort. Based on strict IHC staining, subjects positive for HER2 accounted for 31.5% of cases 87.6% of all cases had Ki67 expression ≥30% before NAC, while only 58.9% of the cohort had ≥30% Ki67 after NAC. 18.8% of HER2-positive patients received anti-HER2 therapy.
Based on biomarker status, patients were categorized into four subtypes: 43 subjects (5.2%) were categorized as Luminal A subtype breast cancer, 489 subjects (59.1%) had a Luminal B breast cancer, 148 subjects (17.9%) had HER2-enriched breast cancer, and 148 cases (17.9%) had TN breast cancer. IHC status and subtypes distribution are shown in Table 1.
Correlation Between Patient Features and Pathological Response to NAC or Survival
We chose pCR as our evaluation criterion of pathological response to NAC. The median follow-up time was 62.00 ± 21.43 months. A associations between patient features and pathological response to NAC or survival were assessed via the Chi-square test (χ2), with results shown in Table 2. Age, body mass index, maximum tumor diameter before NAC, and HER2 status all had p values > 0.05, indicating no significant influence on prognosis. However, different carcinoma pathology subtypes, maximum diameter after NAC, and nodal status at diagnosis were all significantly associated with pCR, with all p values < 0.05. The IHC biomarkers ER, PR and Ki67 status before and after NAC, all associated with pathological response to NAC. The log-rank test was used for in analysis of different parameters with DFS and OS fully considering the follow-up time (Table 3). For DFS and OS, BMI and Ki67 after NAC both presented p value < 0.05.
Histological subtype further affected both pCR rates and survival status. Each subtype resulted in different pathological responses, as validated by the Chi-square test (p < 0.05), but there was no obvious change on patient prognosis (p = 0.244 > 0.05). Rates of pCR across subtypes are shown in Figure 2. The left side of the picture presents the relation between pCR and DFS. The right side of the picture presents the univariate analysis of the relationship between OS and pCR based on the Kaplan-Meier method. We calculated survival rates for patients with each subtype using the Kaplan–Meier method. pCR status had no impact on DFS outcome for patients with Luminal A (p = 0.784 > 0.05, Figure 2A) or Luminal B subtypes (p = 0.427 > 0.05, Figure 2B). However, both HER2-enriched and TN breast cancer subtype patients showed a significant association between pathological response to NAC and survival outcome (p = 0.043 < 0.05, and p = 0.042 < 0.05, respectively, Figures 2C,D). The corresponding Kaplan-Meier curves of pCR with OS outcome for four subtypes are presented in Figures 2E–H. The multivariate Cox analysis for the full cohort is available in Supplementary Table S1. The visual result of univariate analysis displayed via Kaplan-Meier curves is in Supplementary Figure S1.
FIGURE 2. Kaplan-Meier curve of survival in patients with pCR status; Luminal A subtype (A, B), Luminal B subtype (C, D), HER2-enriched subtype (E, F), TN breast cancer subtype (G, H). Blue lines: achieving pCR; Red lines: not achieving pCR. The left side of figure represented the relationship between pCR status and DFS. The right side presented the relationship between pCR status and OS. Abbreviations: pCR, pathological complete response; HER2, human epidermal growth factor receptor 2; TN breast cancer, triple negative breast cancer; DFS, disease-free survival; OS, overall survival.
Assessment of the Prognostic Efficacy of Ki67 Expression Status Before and After NAC
The average Ki67 status before NAC was 39.66% ± 22.61%. In comparison, the average value after NAC was 25.00% ± 22.91%. The downward trend of Ki67 before and after NAC is displayed in Figure 3 for the whole cohort (A), Luminal subtype (B), HER2-enriched subtype (C), and TN subtype (D). As shown in the figure, Ki67 change before and after NAC presented a statistical difference (p < 0.001) in Luminal subtype. However, in HER2-enriched and TN breast cancer, the difference of Ki67 represented no statistical significance. To evaluate the degree of Ki67 decline, we compared post-NAC and pre-NAC proliferation indices [define post-NAC Ki67 as A, define pre-NAC Ki67 as B, the computational formula was
FIGURE 3. Box-plots of pre- and post-NAC Ki67 expression in diverse molecular subtypes; Ki67 variation in whole cohort (A), Luminal subtype (B), HER2 subtype (C) and TN breast cancer subtype (D). The dark blue lines are on behalf of the box-plots of Ki67 before NAC. The light blue lines represent the box-plots of Ki67 after NAC. Abbreviations: pCR, pathological complete response; HER2, human epidermal growth factor receptor 2; TN breast cancer, triple negative breast cancer.
We next used ROC curve analysis to determine the optimal cut-off value for
Therefore, we defined a reduction of greater than 63%
FIGURE 4. Kaplan Meier curve of DFS and OS in patients with
Based on the multivariate Cox analysis,
FIGURE 5. Forest plot of DFS and OS in Luminal B breast cancer; The left side of the figure is exhibiting the forest plot of DFS in Luminal B subtype. The right side of the figure presents the forest plot of OS in Luminal B subtype. The two forest plots both present the multivariate-analyses results; Abbreviations: BMI, body mass index; NAC, neoadjuvant chemotherapy; IBC-NST, invasive breast carcinoma of no special type; DFS, disease-free survival; OS, overall survival.
Not only that, we tentatively continued to explore the subgroups of Luminal B patients based on the HER2-status. In Luminal B patients from our research, who with negative HER2 status were 256 (52.4%). The patients with positive HER2 status were 113 (23.3%). The patients with unknown HER2 status were 120 (24.5%). The Kaplan-Meier curves and multivariate-analysis results of relationship between ΔKi67% and survival outcome were attached in the Supplementary Presentation S1. Based on the statistical calculation, the analytical results of all subdivisions in Luminal B tumors fully supported the statistical significance of ΔKi67% (univariate and multivariate p < 0.05) except the DFS in HER2-positive Luminal B subtypes (univariate and multivariate p > 0.05). Combined, ΔKi67% was confirmed the statistically significant relationship with disease-free and overall survival outcome.
Among patients with TN breast cancer,
FIGURE 6. Forest plot of DFS and OS in TN breast cancer. The left side of the figure is exhibiting the forest plot of DFS in triple-negative subtype. The right side of the figure presents the forest plot of OS in triple-negative breast cancer. The two forest plots both present the multivariate-analyses results. Abbreviations: TN, triple negative; BMI, body mass index; NAC, neoadjuvant chemotherapy; IBC-NST, invasive breast carcinoma of no special type; DFS, disease-free survival; OS, overall survival.
NAC is currently widely applied to shrink tumors and decrease carcinoma volume, allowing patients to preserve breasts or become operable . Moreover, the pathological response to NAC is also beneficial for optimizing chemotherapy regimens and predicting relapse possibility and survival outcomes. Patients with pCR to NAC show improved rates of relapse and better survival [33,34].
Many studies have verified correlations between the degree of Ki67 reduction and pathological response to NAC [10,35,36], yet controversies exist regarding the relationships between Ki67 index, pathological response, and survival grates. Some studies only find significant Ki67 proliferation index differences when comparing pre-NAC with post-surgery in Luminal subtypes [37,38] while other studies have demonstrated that Ki67 reduction also plays a role in TN breast cancer [39,40]. While a separate investigation mentioned
In this retrospective real-world study, we analyzed basic demographic and pathological characteristics relative to pCR following to NAC. We confirmed that breast cancer pathological subtype, chemotherapy cycle number, maximum tumor diameter after NAC, nodal state at diagnosis, and Ki67 index pre-NAC and post-NAC all presented statistically significant differences. Furthermore, ER and PR status and molecular subtypes all showed significant effects on pCR rate, as verified in previous studies .
As mentioned above, pCR rate ranged from 15 to 20% in previous studies [7–9]. Patients who achieved pCR following NAC represented 16.7% of our cohort, a relatively small portion of the total patients. This implies that pCR status increases the specificity of survival outcome predictions but lowered the sensitivity. Many patients were eliminated in the evaluation system, especially those with the Luminal B subtype who represent the largest portion of all breast cancer patients. This is consistent with previous large trials showing pCR rates to have limited prognostic value in patients with Luminal B subtype [11,12]. ∆Ki67% status could help improve this deficiency.
Our study has many strengths. Our fundamental statistical data of post-NAC Ki67 is in accordance with previous research about the relevance of clinical response to NAC and prognostic value [12,24,25]. Subtracting pre- and post-NAC Ki67 is insufficient to account for all situations, therefore we used
∆Ki67% is a useful indicator for more than just Luminal B subtype patients. In patients with TN breast cancer, pCR rate and
This study has inherent limitations. Missing data is a common issue in most retrospective single center studies. Hence, we excluded patients whose information was incomplete or inadequate to be incorporated in the study cohort. The second limitation when using Ki67 staining and assessment is lack of stable measurement results [13,14]. To account for this, we adopted the ‘hottest-spot’ method and performed pathological assessments strictly following international guidelines to improve reproducibility. In the future, artificial intelligence in precision pathology could dramatically improve this method.
In this study, we demonstrate that
In this study, we validated that the extent of Ki67 change before and after NAC, termed
Data Availability Statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
This study was allowed by the Ethics Committee of the First Affiliated Hospital of China Medical University. The protocol of this study was approved by the institutional review board (IRB) of the First Affiliated Hospital and was in accordance with the Helsinki Declaration (AF-SOP-07-1.1-01/2019-13). Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.
ST analyzed the collected data and wrote the first draft of the manuscript. XF wrote the first draft of the manuscript. XF, SX, PQ, and ZL collected the data and gave assistance on paper revision. YX and QZ were responsible for supervising the whole project and finalizing the manuscript. All authors have read and approved the manuscript.
This work was supported by the National Natural Science Foundation of China (81773083), Scientific and Technological Innovation Leading Talent Project of Liaoning Province (XLYC1802108), Support Project for Young and Technological Innovation Talents of Shenyang (RC190393) and Chinese Young Breast Experts Research Project (CYBER-2021-A02). These projects provided all the funds necessary for the collection of cases, analyses of results, statistical interpretation of data and for the submission of the manuscript.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The Supplementary Material for this article can be found online at: https://www.por-journal.com/articles/10.3389/pore.2021.1609972/full#supplementary-material
Supplementary Figure S1 | The Kaplan-Meier curves of
Supplementary Figure S2 | Representative immunohistochemical staining of Ki67. Ki67<30% (A, B), Ki67≥30% (C, D).
Supplementary Presentation S1 | The results of univariate and multivariate analyses in subdivisions of Luminal B patients. The PDF file contains the Kaplan-Meier curves and tabular-forms of multivariate results regardless of DFS and OS. Luminal B subtype was sorted into four subdivisions: negative HER2 status, positive HER2 status, luminal B subtype excluded HER2-positive status (containing negative and unknown HER2 status) and luminal B subtype excluded HER2-negative status (containing positive and unknown HER2 status). The blue lines are on behalf of achieving
AUC, area under the curve; BMI, body mass index; CI, confidence intervals; DFS, disease-free survival; ER, estrogen receptor; FISH, fluorescent in situ hybridization; HR, Hazard Ratio; HR, hormone receptors; HER2, human epidermal growth receptor-2; IBC-NST, invasive breast carcinoma of no special type; IRB, institutional review board; IHC, Immunohistochemical; NAC, neoadjuvant chemotherapy; NRI, net reclassification improvement; OS, overall survival; PR, progesterone receptor; pCR, pathological complete response; ROC, operating characteristic curve; TN, triple negative.
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Keywords: breast cancer, prognosis, neoadjuvant chemotherapy, Ki67, tumor response
Citation: Tan S, Fu X, Xu S, Qiu P, Lv Z, Xu Y and Zhang Q (2021) Quantification of Ki67 Change as a Valid Prognostic Indicator of Luminal B Type Breast Cancer After Neoadjuvant Therapy. Pathol. Oncol. Res. 27:1609972. doi: 10.3389/pore.2021.1609972
Received: 20 July 2021; Accepted: 28 September 2021;
Published: 20 December 2021.
Edited by:Anna Sebestyén, Semmelweis University, Hungary
Copyright © 2021 Tan, Fu, Xu, Qiu, Lv, Xu and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
†These authors share first authorship