scholarly journals Prognostic Value of Metabolic Activity of the Psoas Muscle Evaluated By Preoperative 18 F- FDG PET-CT in Breast Cancer: A Retrospective Cross-Sectional Study

2021 ◽  
Author(s):  
Keunyoung Kim ◽  
In-Ju Kim ◽  
Kyoungjune Pak ◽  
Taewoo Kang ◽  
Young Mi Seol ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Metabolic Activity ◽  
Cox Regression ◽  
Surrogate Marker ◽  
Psoas Muscle ◽  
University Hospital ◽  
Cox Regression Analysis ◽  
Standardized Uptake Values ◽  
The Mean ◽  
Receptor Negativity

Abstract Background: This study aimed to evaluate the potential of metabolic activity of the psoas muscle measured by 18F-fluorodeoxyglucose positron emission tomography-computed tomography to predict treatment outcomes in patients with resectable breast cancer.Methods: The medical records of 288 patients who had undergone surgical resection for stages I–III invasive ductal carcinoma of the breast between January 2014 and December 2014 in Pusan National University Hospital were reviewed. The standardized uptake values (SUVs) of the bilateral psoas muscle were normalized using the mean SUV of the liver. SUVRmax was calculated as the ratio of the maximum SUV of the average bilateral psoas muscle to the mean SUV of the liver. SUVRmean was calculated as the ratio of the averaged bilateral psoas muscle to the mean SUV of the liver.Results: Univariate analyses identified a higher T stage, higher N stage, estrogen receptor negativity, progesterone receptor negativity, human epidermal growth factor receptor 2 positivity, triple-negative breast cancer, mastectomy (rather than breast-conserving surgery), SUVRmean > 0.464, and SUVRmax > 0.565 as significant adverse factors for progression-free survival (PFS). Multivariate Cox regression analysis revealed that N3 stage (hazard ratio [HR] = 5.347, P = 0.031) was an independent factor for recurrence. An SUVRmax > 0.565 (HR = 4.987, P = 0.050) seemed to have a correlation with shorter PFS.Conclusions: A higher SUVRmax of the psoas muscle, which could be a surrogate marker of insulin resistance, showed strong potential as an independent prognostic factor for recurrence in patients with resectable breast cancer.

scholarly journals Prognostic value of metabolic activity of the psoas muscle evaluated by preoperative 18F-FDG PET-CT in breast cancer: a retrospective cross-sectional study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Keunyoung Kim ◽  
In-Joo Kim ◽  
Kyoungjune Pak ◽  
Taewoo Kang ◽  
Young Mi Seol ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Metabolic Activity ◽  
Cox Regression ◽  
Surrogate Marker ◽  
Disease Free Survival ◽  
Psoas Muscle ◽  
Cox Regression Analysis ◽  
Standardized Uptake Values ◽  
The Mean ◽  
Receptor Negativity

Abstract Background This study aimed to evaluate the potential of metabolic activity of the psoas muscle measured by 18F-fluorodeoxyglucose positron emission tomography-computed tomography to predict treatment outcomes in patients with resectable breast cancer. Methods The medical records of 288 patients who had undergone surgical resection for stages I–III invasive ductal carcinoma of the breast between January 2014 and December 2014 in Pusan National University Hospital were reviewed. The standardized uptake values (SUVs) of the bilateral psoas muscle were normalized using the mean SUV of the liver. SUVRmax was calculated as the ratio of the maximum SUV of the average bilateral psoas muscle to the mean SUV of the liver. SUVRmean was calculated as the ratio of the mean SUV of the bilateral psoas muscle to the mean SUV of the liver. Results Univariate analyses identified a higher T stage, higher N stage, estrogen receptor negativity, progesterone receptor negativity, human epidermal growth factor receptor 2 positivity, triple-negative breast cancer, mastectomy (rather than breast-conserving surgery), SUVRmean > 0.464, and SUVRmax > 0.565 as significant adverse factors for disease-free survival (DFS). Multivariate Cox regression analysis revealed that N3 stage (hazard ratio [HR] = 5.347, P = 0.031) was an independent factor for recurrence. An SUVRmax > 0.565 (HR = 4.987, P = 0.050) seemed to have a correlation with shorter DFS. Conclusions A higher SUVRmax of the psoas muscle, which could be a surrogate marker of insulin resistance, showed strong potential as an independent prognostic factor for recurrence in patients with resectable breast cancer.

Clinical Outcome With Correlation to Disseminated Tumor Cell (DTC) Status After DTC-Guided Secondary Adjuvant Treatment With Docetaxel in Early Breast Cancer

2014 ◽  
Vol 32 (34) ◽  
pp. 3848-3857 ◽  
Author(s):  
Bjørn Naume ◽  
Marit Synnestvedt ◽  
Ragnhild Sørum Falk ◽  
Gro Wiedswang ◽  
Kjetil Weyde ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Early Breast Cancer ◽  
Adjuvant Treatment ◽  
Cox Regression ◽  
Surrogate Marker ◽  
Disseminated Tumor Cells ◽  
Rank Test ◽  
Cox Regression Analysis ◽  
Risk Patients

Purpose The presence of disseminated tumor cells (DTCs) in bone marrow (BM) predicts survival in early breast cancer. This study explores the use of DTCs for identification of patients insufficiently treated with adjuvant therapy so they can be offered secondary adjuvant treatment and the subsequent surrogate marker potential of DTCs for outcome determination. Patients and Methods Patients with early breast cancer who had completed six cycles of adjuvant fluorouracil, epirubicin, and cyclophosphamide (FEC) chemotherapy underwent BM aspiration 2 to 3 months (BM1) and 8 to 9 months (BM2) after FEC. Presence of DTCs in BM was determined by immunocytochemistry using pan-cytokeratin monoclonal antibodies. If one or more DTCs were present at BM2, six cycles of docetaxel (100 mg/m2, once every 3 weeks) were administered, followed by DTC analysis 1 and 13 months after the last docetaxel infusion (after treatment). Cox regression analysis was used to evaluate disease-free interval (DFI). Results Of 1,066 patients with a DTC result at BM2 and available follow-up information (median follow-up, 71.9 months from the time of BM2), 7.2% were DTC positive. Of 72 docetaxel-treated patients analyzed for DTCs after treatment, 15 (20.8%) had persistent DTCs. Patients with remaining DTCs had markedly reduced DFI (46.7% experienced relapse) compared with patients with no DTCs after treatment (adjusted hazard ratio, 7.58; 95% CI, 2.3 to 24.7). The docetaxel-treated patients with no DTCs after treatment had comparable DFI (8.8% experienced relapse) compared with those with no DTCs both at BM1 and BM2 (12.7% experienced relapse; P = .377, log-rank test). Conclusion DTC status identifies high-risk patients after FEC chemotherapy, and DTC monitoring status after secondary treatment with docetaxel correlated strongly with survival. This emphasizes the potential for DTC analysis as a surrogate marker for adjuvant treatment effect in breast cancer.

scholarly journals Identification and development of an independent immune-related genes prognostic model for breast cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lin Chen ◽  
Yuxiang Dong ◽  
Yitong Pan ◽  
Yuhan Zhang ◽  
Ping Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Validation Dataset ◽  
Immune Gene ◽  
Cox Regression Analysis ◽  
Immune Genes ◽  
Immune Related Genes

Abstract Background Breast cancer is one of the main malignant tumors that threaten the lives of women, which has received more and more clinical attention worldwide. There are increasing evidences showing that the immune micro-environment of breast cancer (BC) seriously affects the clinical outcome. This study aims to explore the role of tumor immune genes in the prognosis of BC patients and construct an immune-related genes prognostic index. Methods The list of 2498 immune genes was obtained from ImmPort database. In addition, gene expression data and clinical characteristics data of BC patients were also obtained from the TCGA database. The prognostic correlation of the differential genes was analyzed through Survival package. Cox regression analysis was performed to analyze the prognostic effect of immune genes. According to the regression coefficients of prognostic immune genes in regression analysis, an immune risk scores model was established. Gene set enrichment analysis (GSEA) was performed to probe the biological correlation of immune gene scores. P < 0.05 was considered to be statistically significant. Results In total, 556 immune genes were differentially expressed between normal tissues and BC tissues (p < 0. 05). According to the univariate cox regression analysis, a total of 66 immune genes were statistically significant for survival risk, of which 30 were associated with overall survival (P < 0.05). Finally, a 15 immune genes risk scores model was established. All patients were divided into high- and low-groups. KM survival analysis revealed that high immune risk scores represented worse survival (p < 0.001). ROC curve indicated that the immune genes risk scores model had a good reliability in predicting prognosis (5-year OS, AUC = 0.752). The established risk model showed splendid AUC value in the validation dataset (3-year over survival (OS) AUC = 0.685, 5-year OS AUC = 0.717, P = 0.00048). Moreover, the immune risk signature was proved to be an independent prognostic factor for BC patients. Finally, it was found that 15 immune genes and risk scores had significant clinical correlations, and were involved in a variety of carcinogenic pathways. Conclusion In conclusion, our study provides a new perspective for the expression of immune genes in BC. The constructed model has potential value for the prognostic prediction of BC patients and may provide some references for the clinical precision immunotherapy of patients.

scholarly journals The Investigation of Associations between TP53 rs1042522, BBC3 rs2032809, CCND1 rs9344, EGFR rs2227983 Polymorphisms and Breast Cancer Phenotype and Prognosis

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1419
Author(s):  
Justina Bekampytė ◽  
Agnė Bartnykaitė ◽  
Aistė Savukaitytė ◽  
Rasa Ugenskienė ◽  
Erika Korobeinikova ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Cancer Prognosis ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Cox Regression Analysis ◽  
Pcr Rflp ◽  
Oncological Diseases ◽  
Cancer Phenotype

Breast cancer is one of the most common oncological diseases among women worldwide. Cell cycle and apoptosis—related genes TP53, BBC3, CCND1 and EGFR play an important role in the pathogenesis of breast cancer. However, the roles of single nucleotide polymorphisms (SNPs) in these genes have not been fully defined. Therefore, this study aimed to analyze the association between TP53 rs1042522, BBC3 rs2032809, CCND1 rs9344 and EGFR rs2227983 polymorphisms and breast cancer phenotype and prognosis. For the purpose of the analysis, 171 Lithuanian women were enrolled. Genomic DNA was extracted from peripheral blood; PCR-RFLP was used for SNPs analysis. The results showed that BBC3 rs2032809 was associated with age at the time of diagnosis, disease progression, metastasis and death. CCND1 rs9344 was associated with tumor size, however an association resulted in loss of significance after Bonferroni correction. In survival analysis, significant associations were observed between BBC3 rs2032809 and OS, PFS and MFS. EGFR rs2227983 also showed some associations with OS and PFS (univariate Cox regression analysis). However, the results were in loss of significance (multivariate Cox regression analysis). In conclusion, BBC3 rs2032809 polymorphism was associated with breast cancer phenotype and prognosis. Therefore, it could be applied as potential markers for breast cancer prognosis.

scholarly journals Impact of Cardiovascular Failure in Intensive CareUnit-Acquired Pneumonia: A Single-Center, Prospective Study

Antibiotics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 798
Author(s):  
Ignacio Martin-Loeches ◽  
Adrian Ceccato ◽  
Marco Carbonara ◽  
Gianluigi li Bassi ◽  
Pierluigi di Natale ◽  
...  
Keyword(s):  
Cox Regression ◽  
University Hospital ◽  
Single Center ◽  
Cox Regression Analysis ◽  
Cardiovascular Failure ◽  
Icu Length Of Stay ◽  
Patients At Risk ◽  
Surgical Icus ◽  
Pulmonary Superinfection ◽  
The Impact

Background: Cardiovascular failure (CVF) may complicate intensive care unit-acquired pneumonia (ICUAP) and radically alters the empirical treatment of this condition. The aim of this study was to determine the impact of CVF on outcome in patients with ICUAP. Methods: A prospective, single-center, observational study was conducted in six medical and surgical ICUs at a University Hospital. CVS was defined as a score of 3 or more on the cardiovascular component of the Sequential Organ Failure Assessment (SOFA) score. At the onset of ICUAP, CVF was reported as absent, transient (if lasting ≤ 3 days) or persistent (>3 days). The primary outcome was 90-day mortality modelled through a Cox regression analysis. Secondary outcomes were 28-day mortality, hospital mortality, ICU length of stay (LOS) and hospital LOS. Results: 358 patients were enrolled: 203 (57%) without CVF, 82 (23%) with transient CVF, and 73 (20%) with persistent CVF. Patients with transient and persistent CVF were more severely ill and presented higher inflammatory response than those without CVF. Despite having similar severity and aetiology, the persistent CVF group more frequently received inadequate initial antibiotic treatment and presented more treatment failures than the transient CVF group. In the persistent CVF group, at day 3, a bacterial superinfection was more frequently detected. The 90-day mortality was significantly higher in the persistent CVF group (62%). The 28-day mortality rates for patients without CVF, with transient and with persistent CVF were 19, 35 and 41% respectively and ICU mortality was 60, 38 and 19% respectively. In the multivariate analysis chronic pulmonary conditions, lack of Pa02/FiO2 improvement at day 3, pulmonary superinfection at day 3 and persistent CVF were independently associated with 90-day mortality in ICUAP patients. Conclusions: Persistent CVF has a significant impact on the outcome of patients with ICUAP. Patients at risk from persistent CVF should be promptly recognized to optimize treatment and outcomes.

Expression of BCL2L12, a new member of apoptosis-related genes, in breast tumors

2003 ◽  
Vol 89 (06) ◽  
pp. 1081-1088 ◽  
Author(s):  
Maroulio Talieri ◽  
Eleftherios Diamandis ◽  
Nikos Katsaros ◽  
Dimitrios Gourgiotis ◽  
Andreas Scorilas
Keyword(s):  
Breast Cancer ◽  
Cell Death ◽  
Cox Regression ◽  
Breast Tumors ◽  
Cell Types ◽  
Research Society ◽  
Genetic Alterations ◽  
Cox Regression Analysis ◽  
Reverse Transcription Pcr ◽  
Lower Stage

SummaryApoptosis, a normal physiological form of cell death, is critically involved in the regulation of cellular homeostasis. If the delicate balance between cell death and cell proliferation is altered by a defect in the normal regulation of apoptosis signaling, a cell population is able to survive and accumulate, thereby favoring the acquisition of further genetic alterations and promoting tumorigenesis. Dysregulation of programmed cell death mechanisms plays an important role in the pathogenesis and progression of breast cancer, as well as in the responses of tumors to therapeutic intervention. Overexpression of anti-apoptotic members of the Bcl-2 family such as Bcl-2 and Bcl-XL has been implicated in cancer chemoresistance, whereas high levels of pro-apoptotic proteins such as Bax promote apoptosis and sensitize tumor cells to various anticancer therapies. Recently, a new member of the Bcl-2 family, BCL2L12, was cloned. The BCL2L12 gene is constitutively expressed in many tissues, suggesting that the encoded protein serves an important function in different cell types. In the present study, the expression of BCL2L12 gene was analyzed by reverse transcription-PCR (PT-PCR) in 70 breast cancer tissues. Our results indicate that BCL2L12 positive breast tumors are mainly of lower stage (I/II) or grade (I/II) (p=0.02 or p=0.04 respectively). Cox regression analysis revealed that BCL2L12 expression is positively related to disease-free (DFS) and overall survival (OS) at both univariate and multivariate analysis (p=0.021, p=0.029, p=0.032, p=0.044 respectively). Kaplan-Meier survival curves also demonstrated that patients with BCL2L12-positive tumors have significantly longer DFS and OS (p=0.002 and p<0.001 respectively). BCL2L12 expression may be regarded as a new independent favorable prognostic marker for breast cancer.Part of this paper was originally presented at the joint meetings of the 16th International Congress of the International Society of Fibrinolysis and Proteolysis (ISFP) and the 17th International Fibrinogen Workshop of the International Fibrinogen Research Society (IFRS) held in Munich, Germany, September, 2002.

Factors Predictive of Distant Metastases in Patients With Breast Cancer Who Have a Pathologic Complete Response After Neoadjuvant Chemotherapy

2005 ◽  
Vol 23 (28) ◽  
pp. 7098-7104 ◽  
Author(s):  
Ana M. Gonzalez-Angulo ◽  
Sean E. McGuire ◽  
Thomas A. Buchholz ◽  
Susan L. Tucker ◽  
Henry M. Kuerer ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Neoadjuvant Chemotherapy ◽  
Distant Metastasis ◽  
Cox Regression ◽  
Clinical Stage ◽  
Pathologic Complete Response ◽  
Distant Metastases ◽  
Complete Response ◽  
Cox Regression Analysis

Purpose To identify clinicopathological factors predictive of distant metastasis in patients who had a pathologic complete response (pCR) after neoadjuvant chemotherapy (NC). Methods Retrospective review of 226 patients at our institution identified as having a pCR was performed. Clinical stage at diagnosis was I (2%), II (36%), IIIA (27%), IIIB (23%), and IIIC (12%). Eleven percent of all patients were inflammatory breast cancers (IBC). Ninety-five percent received anthracycline-based chemotherapy; 42% also received taxane-based therapy. The relationship of distant metastasis with clinicopathologic factors was evaluated, and Cox regression analysis was performed to identify independent predictors of development of distant metastasis. Results Median follow-up was 63 months. There were 31 distant metastases. Ten-year distant metastasis-free rate was 82%. Multivariate Cox regression analysis using combined stage revealed that clinical stages IIIB, IIIC, and IBC (hazard ratio [HR], 4.24; 95% CI, 1.96 to 9.18; P < .0001), identification of ≤ 10 lymph nodes (HR, 2.94; 95% CI, 1.40 to 6.15; P = .004), and premenopausal status (HR, 3.08; 95% CI, 1.25 to 7.59; P = .015) predicted for distant metastasis. Freedom from distant metastasis at 10 years was 97% for no factors, 88% for one factor, 77% for two factors, and 31% for three factors (P < .0001). Conclusion A small percentage of breast cancer patients with pCR experience recurrence. We identified factors that independently predicted for distant metastasis development. Our data suggest that premenopausal patients with advanced local disease and suboptimal axillary node evaluation may be candidates for clinical trials to determine whether more aggressive or investigational adjuvant therapy will be of benefit.

scholarly journals Identification of a prognostic long non-coding RNA signature in breast cancer

2020 ◽  
Author(s):  
Gaochen Lan ◽  
Xiaoling Yu ◽  
Yanna Zhao ◽  
Jinjian Lan ◽  
Wan Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cox Regression Analysis

Abstract Background: Breast cancer is the most common malignant disease among women. At present, more and more attention has been paid to long non-coding RNAs (lncRNAs) in the field of breast cancer research. We aimed to investigate the expression profiles of lncRNAs and construct a prognostic lncRNA for predicting the overall survival (OS) of breast cancer.Methods: The expression profiles of lncRNAs and clinical data with breast cancer were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were screened out by R package (limma). The survival probability was estimated by the Kaplan‑Meier Test. The Cox Regression Model was performed for univariate and multivariate analysis. The risk score (RS) was established on the basis of the lncRNAs’ expression level (exp) multiplied regression coefficient (β) from the multivariate cox regression analysis with the following formula: RS=exp a1 * β a1 + exp a2 * β a2 +……+ exp an * β an. Functional enrichment analysis was performed by Metascape.Results: A total of 3404 differentially expressed lncRNAs were identified. Among them, CYTOR, MIR4458HG and MAPT-AS1 were significantly associated with the survival of breast cancer. Finally, The RS could predict OS of breast cancer (RS=exp CYTOR * β CYTOR + exp MIR4458HG * β MIR4458HG + exp MAPT-AS1 * β MAPT-AS1). Moreover, it was confirmed that the three-lncRNA signature could be an independent prognostic biomarker for breast cancer (HR=3.040, P=0.000).Conclusions: This study established a three-lncRNA signature, which might be a novel prognostic biomarker for breast cancer.

scholarly journals Identification of a Novel Gene Model-Based Homologous Recombination Deficiency Score to Improve Survival Prediction of TNBC.

2021 ◽  
Author(s):  
Wenxiang Zhang ◽  
Bolun Ai ◽  
Xiangyi Kong ◽  
Xiangyu Wang ◽  
Jie Zhai ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Homologous Recombination ◽  
Risk Score ◽  
Cox Regression ◽  
Roc Curves ◽  
Cox Regression Analysis ◽  
Homologous Recombination Deficiency ◽  
Ajcc Stage ◽  
Kaplan Meier

Abstract Background Triple-negative breast cancer (TNBC) is a specific histological type of breast cancer with a poor prognosis, early recurrence, which lacks durable chemotherapy responses and effective targeted therapies. We aimed to construct an accurate prognostic risk model based on homologous recombination deficiency (HRD) - gene expression profiles for improving prognosis prediction of TNBC. Methods Triple-negative breast cancer RNA sequencing data and sample clinical information were downloaded from the breast invasive carcinoma (BRCA) cohort in the Cancer Genome Atlas (TCGA) database. Combined with the HRD database, tumor samples were divided into two sets. We screened differentially expressed genes (DEGs) and then identified HRD-related prognostic genes using weighted gene co-expression network analysis (WGCNA) and Cox regression analysis. The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were used to identifying key prognostic genes. Risk scores were calculated and compared with HRD score, Kaplan–Meier (KM) survival analysis were used to assess its prognostic power. GSE103091 dataset from GEO (Gene Expression Omnibus) database was used to validate the signature. Univariate and multivariate Cox regression were performed to independently verify the prognosis of the risk score. A nomogram was constructed and revealed by time-dependent ROC curves to guide clinical practice. Results We found that HRD tumor samples (HRD score > = 42) in TNBC patients were associated with poor overall survival (p = 0.027). We identified a total of 147 differential genes including 203 up-regulated and 213 down-regulated genes, among which 29 were prognosis-related genes. Through the LASSO method, 6 key prognostic genes ((MUCL1, IVL, FAM46C, CHI3L1, PRR15L, and CLEC3A) were selected and a 6-gene risk score was constructed. We found risk score was negatively associated with homologous recombination deficiency (HRD) scores (r = -0.22, p = 0.019). Compared with the low-risk group, Kaplan-Meier survival analysis shows that the high-risk group has an obvious poorer prognosis (P < 0.0001). Finally, we integrated the risk score model and clinical factors of TNBC (AJCC-stage, HRD score, T stage, and N stage) to construct a compound nomogram. Time-dependent ROC curves showed the risk score performed better in 1-, 3- and 5-year survival predictions compared with AJCC-stage. Conclusions Based on HRD gene expression data, our six HRD-related gene signature and nomogram could be practical and reliable tools for predicting OS in patients with TNBC.

scholarly journals Analysis of CK5/6 and EGFR and Its Effect on Prognosis of Triple Negative Breast Cancer

2021 ◽  
Vol 10 ◽  
Author(s):  
Zhen Wang ◽  
Lei Liu ◽  
Ying Li ◽  
Zi’an Song ◽  
Yi Jing ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Neoadjuvant Chemotherapy ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Cox Regression ◽  
Multivariate Logistic Regression Analysis ◽  
Pathological Examination ◽  
Cox Regression Analysis ◽  
Tumor Stages

BackgroundTriple-negative breast cancer (TNBC) is considered to be higher grade, more aggressive and have a poorer prognosis than other types of breast cancer. Discover biomarkers in TNBC for risk stratification and treatments that improve prognosis are in dire need.MethodsClinical data of 195 patients with triple negative breast cancer confirmed by pathological examination and received neoadjuvant chemotherapy (NAC) were collected. The expression levels of EGFR and CK5/6 were measured before and after NAC, and the relationship between EGFR and CK5/6 expression and its effect on prognosis of chemotherapy was analyzed.ResultsThe overall response rate (ORR) was 86.2% and the pathological complete remission rate (pCR) was 29.2%. Univariate and multivariate logistic regression analysis showed that cT (clinical Tumor stages) stage was an independent factor affecting chemotherapy outcome. Multivariate Cox regression analysis showed pCR, chemotherapy effect, ypT, ypN, histological grades, and post- NAC expression of CK5/6 significantly affected prognosis. The prognosis of CK5/6-positive patients after NAC was worse than that of CK5/6-negative patients (p=0.036). Changes in CK5/6 and EGFR expression did not significantly affect the effect of chemotherapy, but changes from positive to negative expression of these two markers are associated with a tendency to improve prognosis.ConclusionFor late-stage triple negative breast cancer patients receiving NAC, patients who achieved pCR had a better prognosis than those with non- pCR. Patients with the change in expression of EGFR and CK5/6 from positive to negative after neoadjuvant chemotherapy predicted a better prognosis than the change from negative to positive group.

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