Impact in delay of start of chemotherapy and surgery on pCR and survival in breast cancer: A pooled analysis of individual patient data from six prospectively randomized neoadjuvant trials.

571 Background: Time interval from diagnostic biopsy to neoadjuvant chemotherapy (NACT) start (TBC) and from last chemotherapy application to surgery (TCS) are influenced by many factors. It is unclear whether a delay of systemic therapy or surgery impacts patients (pts) outcome. Methods: 9127 pts with early BC from 6 German neoadjuvant trials receiving an anthracycline-taxane based NACT were included. pCR (ypT0/is ypN0), disease free survival (DFS) and overall survival (OS) were compared according to TBC and TCS length (cut-off of ≤4 vs >4weeks (w)), overall and in subgroups (BC subtypes [luminal, HER2+, triple-negative breast cancer (TNBC)] and pCR [yes vs no] for survival endpoints) adjusted by study. Results: Data on TBC were available for 8072 pts, on TCS for 6420, on follow-up (FU) for 7889. Median age was 49 yrs, 25.6% had cT3-4, 48.6% N+, 44.1% G3, 46.0% luminal, 26.4% TNBC, 27.6% HER2+ tumors. Median (m) FU-time was 65 months [0-201]. mTBC was 23 days [0-228] (67.5% ≤4w vs 32.5% >4w), mTCS was 28d [0-204] (53.7% ≤4w vs 46.3% >4w), with inter-study variability for mTBC ranging from 14 to 32d and for mTCS ranging from 24 to 29d from the oldest to the most recently conducted study. TBC did not influence the pCR rate, neither in all patients nor in subgroups. At multivariable logistic regression analysis TBC length did not independently predict pCR. TBC did not influence DFS or OS, neither in all patients nor in subgroups. TCS<4w was associated with a trend towards a better DFS in all patients (HR=1.11 95%CI (0.99-1.24), p=0.08) and in pts not achieving pCR (HR=1.12, 95%CI (0.99-1.26), p=0.08). No difference was observed within BC subtypes. OS was not impacted by TCS length. At multivariable Cox regression analysis TBC or TCS≤4 vs >4w did not independently influence DFS or OS. Conclusions: A delay in starting NACT does not impact the pCR rate, DFS or OS and results are independent of the subgroup. However, early surgery after NACT in pts without pCR seems to influence outcome. Our analysis is explorative, but indicates for the first time, that time interval of starting NACT and undergoing surgery might be uncritical. Further research is ongoing.

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Identification of a 9-Gene Prognostic signature for breast cancer

10.21203/rs.3.rs-26949/v1 ◽

2020 ◽

Author(s):

Zelin Tian ◽

Jianing Tang ◽

Xing Liao ◽

Qian Yang ◽

Yumin Wu ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Overall Survival ◽

Regression Analysis ◽

Cox Regression ◽

Risk Group ◽

Disease Free Survival ◽

Gene Signature ◽

Prognostic Signature ◽

Cox Regression Analysis

Abstract Background Breast cancer (BRCA) is the most common cancer among women worldwide and results in the second leading cause of woman cancer death.Methods This study sought to develop a prognostic gene signature to predict the prognosis of patients with BRCA. Studies were performed using the genome-wide data of BRCA patients from the Gene Expression Omnibus dataset (GSE20685, GSE42568, GSE20711, GSE88770). Univariate COX regression analysis was used to determine the association between gene expression levels and overall survival(OS) in each dataset. Taking P value < 0.05 as the inclusion criterion, the common genes in all datasets were selected as prognostic genes, and a 9-gene prognostic signature was developed.Results The Kaplan-Meier survival curve was constructed using log-rank test to assess survival differences. The overall survival of patients in the low-risk group was significantly higher than that in the high-risk group. ROC analysis showed that this 9-gene signature showed good diagnostic efficiency both in overall survival(OS) and disease free survival(DFS). The 9-gene signature was further validated using GSE16446 dataset. In addition, multiple Cox regression analysis showed that this 9-gene signature was an independent risk factor. Finally, we established a nomogram that integrates conventional clinicopathological features and 9-gene signature. The analysis of the calibration plots showed that the nomogram has good performance.Conclusions This study has developed a reliable 9-gene prognostic signature, which is of great value in predicting the prognosis of BRCA and will help to make personalized treatment decisions for patients at different risk score.

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

BMC Cancer ◽

10.1186/s12885-021-08041-x ◽

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.

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

Diagnostics ◽

10.3390/diagnostics11081419 ◽

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.

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

Journal of Clinical Oncology ◽

10.1200/jco.2005.11.124 ◽

2005 ◽

Vol 23 (28) ◽

pp. 7098-7104 ◽

Cited By ~ 78

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.

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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 ◽

10.1186/s12885-021-08886-2 ◽

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.

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

Frontiers in Oncology ◽

10.3389/fonc.2020.575317 ◽

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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Immune-related gene based prognostic signature for the risk stratification analysis of breast cancer

Current Bioinformatics ◽

10.2174/1574893616666211005110732 ◽

2021 ◽

Vol 16 ◽

Author(s):

Dongqing Su ◽

Qianzi Lu ◽

Yi Pan ◽

Yao Yu ◽

Shiyuan Wang ◽

...

Keyword(s):

Breast Cancer ◽

Regression Analysis ◽

Cancer Patients ◽

Risk Score ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Breast Cancer Patients ◽

Cox Regression Analysis ◽

Score Model

Background: Breast cancer has plagued women for many years and caused many deaths around the world. Method: In this study, based on the weighted correlation network analysis, univariate Cox regression analysis and least absolute shrinkage and selection operator, 12 immune-related genes were selected to construct the risk score for breast cancer patients. The multivariable Cox regression analysis, gene set enrichment analysis and nomogram were also conducted in this study. Results: Good results were obtained in the survival analysis, enrichment analysis, multivariable Cox regression analysis and immune-related feature analysis. When the risk score model was applied in 22 breast cancer cohorts, the univariate Cox regression analysis demonstrated that the risk score model was significantly associated with overall survival in most of the breast cancer cohorts. Conclusion: Based on these results, we could conclude that the proposed risk score model may be a promising method, and may improve the treatment stratification of breast cancer patients in the future work.

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Association of masseter area and radiodensity with three-month survival after proximal anterior circulation occlusion

Journal of NeuroInterventional Surgery ◽

10.1136/neurintsurg-2020-015837 ◽

2020 ◽

Vol 13 (1) ◽

pp. 25-29 ◽

Cited By ~ 1

Author(s):

Iisa Lindström ◽

Sara Protto ◽

Niina Khan ◽

Jussi Hernesniemi ◽

Niko Sillanpää ◽

...

Keyword(s):

Regression Analysis ◽

Ischemic Stroke ◽

Acute Ischemic Stroke ◽

Cox Regression ◽

Multivariable Logistic Regression Analysis ◽

Anterior Circulation ◽

Term Survival ◽

Cox Regression Analysis ◽

Kaplan Meier

BackgroundMasseter area (MA), a surrogate for sarcopenia, appears to be useful when estimating postoperative survival, but there is lack of consensus regarding the potential predictive value of sarcopenia in acute ischemic stroke (AIS) patients. We hypothesized that MA and density (MD) evaluated from pre-interventional CT angiography scans predict postinterventional survival in patients undergoing mechanical thrombectomy (MT).Materials and methods312 patients treated with MT for acute occlusions of the internal carotid artery (ICA) or the M1 segment of the middle cerebral artery (M1-MCA) between 2013 and 2018. Median follow-up was 27.4 months (range 0–70.4). Binary logistic (alive at 3 months, OR <1) and Cox regression analyses were used to study the effect of MA and MD averages (MAavg and MDavg) on survival.ResultsIn Kaplan–Meier analysis, there was a significant inverse relationship with both MDavg and MAavg and mortality (MDavg P<0.001, MAavg P=0.002). Long-term mortality was 19.6% (n=61) and 3-month mortality 12.2% (n=38). In multivariable logistic regression analysis at 3 months, per 1-SD increase MDavg (OR 0.61, 95% CI 0.41 to 0.92, P=0.018:) and MAavg (OR 0.57, 95% CI 0.35 to 0.91, P=0.019) were the independent predictors associated with lower mortality. In Cox regression analysis, MDavg and MAavg were not associated with long-term survival.ConclusionsIn acute ischemic stroke patients, MDavg and MAavg are independent predictors of 3-month survival after MT of the ICA or M1-MCA. A 1-SD increase in MDavg and MAavg was associated with a 39%–43% decrease in the probability of death during the first 3 months after MT.

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