Controlling Nutritional Status (CONUT) as a Novel Postoperative Prognostic Marker in Breast Cancer Patients: A Retrospective Study.

Purpose: This investigation seeks to elucidate the potential prognostic significance as well as the clinical utility of the controlling nutritional status (CONUT) score in breast cancer patients. Methods: Breast cancer patients managed in our center between January 2010 and December 2016 were recruited for our study. They comprised 187 patients who did not undergo neoadjuvant chemotherapy and 194 who did. A receiver operating characteristic curve (ROC) was utilized in identifying the ideal cut-off CONUT value. This cut-off score was then used to reclassify patients into those with high CONUT scores (≥1) and low CONUT scores (<1). The outcomes were analyzed by statistical methods. Results: Univariate and multivariate Cox regression survival analyses revealed that a CONUT score cut-off of 1 was able to significantly predict duration of disease-free survival (DFS) (p < 0.001; hazard ratio [HR]: 3.184; 95% CI: 1.786-5.677; and p < 0.001; HR: 2.465; 95% CI: 1.642-3.700) and overall survival (OS) (p < 0.001; HR: 2.326; 95% CI: 1.578-3.429; and p < 0.001; HR: 2.775; 95% CI: 1.791-4.300). The mean DFS and OS in those with lower CONUT scores were 41.59 (95% CI: 37.66-45.51 months) and 77.34 months (95% CI: 71.79-82.90 months), respectively. On the other hand, the average DFS and OS for all individuals in the raised CONUT score group were 39.18 (95% CI: 34.41-43.95 months) and 71.30 months (95% CI: 65.47-77.12 months), respectively. Moreover, Kaplan-Meier survival analysis revealed that those in the raised CONUT score cohort had remarkably worse DFS and OS survival rates compared to individuals in the low CONUT score cohort (Log-rank test, DFS: χ 2 = 12.900, p = 0.0003, and OS: χ 2 = 16.270, p < 0.0001). Conclusion: The survival times of breast cancer patients may be reliably predicted using the CONUT score. This score is an easy, convenient, readily accessible, and clinically significant means of prognosticating patients with breast cancer.

PD-L1 Protein Expression Is Associated With Good Clinical Outcomes and Nomogram for Prediction of Disease Free Survival and Overall Survival in Breast Cancer Patients Received Neoadjuvant Chemotherapy.

Objective: This study aims to investigate the potential prognostic significance of programmed death ligand-1 (PD-L1) protein expression in tumor cells of breast cancer patients received neoadjuvant chemotherapy (NACT). Methods: Using semiquantitative immunohistochemistry, the PD-L1 protein expression in breast cancer tissues was analyzed. The correlations between PD-L1 protein expression and clinicopathologic characteristics were analyzed using Chi-square test or Fisher's exact test. The survival curve was stemmed from Kaplan-Meier assay, and the log-rank test was used to compare survival distributions against individual index levels. Univariate and multivariate Cox proportional hazards regression models were accessed to analyze the associations between PD-L1 protein expression and survival outcomes. A predictive nomogram model was constructed in accordance with the results of multivariate Cox model. Calibration analyses and decision curve analyses (DCA) were performed for the calibration of the nomogram model, and subsequently adopted to assess the accuracy and benefits of the nomogram model. Results: A total of 104 breast cancer patients received NACT were enrolled into this study. According to semiquantitative scoring for IHC, patients were divided into: low PD-L1 group (61 cases) and high PD-L1 group (43 cases). Patients with high PD-L1 protein expression were associated with longer disease free survival (DFS) (mean: 48.21 months vs. 31.16 months; P=0.011) and overall survival (OS) (mean: 83.18 months vs. 63.31 months; P=0.019) than those with low PD-L1 protein expression. Univariate and multivariate analyses indicated that PD-L1, duration of neoadjuvant therapy, E-Cadherin, targeted therapy were the independent prognostic factors for patients' DFS and OS. Nomogram based on these independent prognostic factors was used to evaluate the DFS and OS time. The calibration plots shown PD-L1 based nomogram predictions were basically consistent with actual observations for assessments of 1-, 3-, and 5-year DFS and OS time. The DCA curves indicated the PD-L1 based nomogram had better predictive clinical applications regarding prognostic assessments of 3- and 5-year DFS and OS, respectively. Conclusion: High PD-L1 protein expression was associated with significantly better prognoses and longer DFS and OS in breast cancer patients. Furthermore, PD-L1 protein expression was found to be a significant prognostic factor for patients who received NACT.

The Systemic Immune-Inflammation Index is an Independent Predictor of Survival in Breast Cancer Patients.

PURPOSE: The current investigation examines the potential clinical value and prognostic significance of a systemic immune-inflammation index (SII) in patients with breast cancer. PATIENTS AND METHODS: A total of 477 individuals underwent neoadjuvant chemotherapy, and 308 individuals did not at our center between January 1998 and December 2016 were selected. An optimized SII threshold was generated using a receiver operating characteristic curve (ROC). The relationship between various factors and breast cancer in predicting disease-free survival (DFS) and overall survival (OS) were analyzed. RESULTS: The SII < 560 group (Low SII group) and SII ≥ 560 group (High SII group) are divided according to the threshold value. SII was an independent predictor for breast cancer DFS and OS based on univariate and multivariate analyses. Low SII patients had higher mean DFS and OS in contrast to those in the high SII groups (46.65 vs 27.37 months and 69.92 vs 49.53 months). Those in the low SII cohort who also had early or advanced breast cancer, different molecular subtypes, and with or without lymph vessel invasion all had higher mean survival time of DFS and OS in contrast to those with raised SII values (P<0.05). The mean DFS and OS durations also varied based on different Miller and Payne grades (MPG) (P <0.005), and different response groups (P<0.05). CONCLUSION: SII can be used as an easily accessible and minimally invasive potential prognostic factor in individuals with breast cancer and may also guide clinicians in treating and prognosticating patients with breast cancer.

Preoperative Breast Immune Prognostic Index as Prognostic Factor Predicts the Clinical Outcomes of Breast Cancer Patients Receiving Neoadjuvant Chemotherapy.

Objective: This study aims at investigating the potential prognostic significance of the breast immune prognostic index (BIPI) in breast cancer patients who received neoadjuvant chemotherapy (NACT). Methods: The optimal cutoff value was calculated through the receiver operating characteristic curve (ROC). The correlations between BIPI and clinicopathologic characteristics were determined by the chi-square test or Fisher's exact test. The Kaplan-Meier method was used to estimate the survival probability, and the log-rank test was used to analyze the differences in the survival probability among patients. The univariate and multivariate Cox proportional hazard regression model was used to screen the independent prognostic factors. A prognostic nomogram for disease-free survival (DFS) and overall survival (OS) was built on the basis of the multivariate analyses. Furthermore, the calibration curve and decision curve analysis (DCA) were used to assess the predictive performance of the nomogram. Results: All enrolled patients were split into three subgroups based on the BIPI score. The mean DFS and OS of the BIPI score 0 group and BIPI score 1 group were significantly longer than those of the BIPI score 2 group (42.02 vs. 38.61 vs. 26.01 months, 77.61 vs. 71.83 vs. 53.15 months; p < 0.05). Univariate and multivariate analyses indicated that BIPI was an independent prognostic factor for patients' DFS and OS (DFS, hazard ratio (HR): 6.720, 95% confidence interval (CI): 1.629-27.717; OS, HR: 8.006, 95% CI: 1.638-39.119). A nomogram with a C-index of 0.873 (95% CI: 0.779-0.966) and 0.801 (95% CI: 0.702-0.901) had a favorable performance for predicting DFS and OS survival rates for clinical use by combining immune scores with other clinical features. The calibration curves at 1-, 3-, and 5-year survival suggested a good consistency between the predicted and actual DFS and OS probability. The DCA demonstrated that the constructed nomogram had better clinical predictive usefulness than only BIPI in predictive clinical applications of 5-year DFS and OS prognostic assessments. Conclusions: The patients with low BIPI score have better prognoses and longer DFS and OS. Furthermore, the BIPI-based nomogram may serve as a convenient prognostic tool for breast cancer and help in clinical decision-making.

The Systemic Inflammation Response Index as an Independent Predictor of Survival in Breast Cancer Patients: A Retrospective Study.

There is a close relationship between inflammatory cells and tumors, but the pathways that connect the two remain unclear. This research explores the clinical and prognostic value of the systemic inflammation response index (SIRI) in breast cancer patients. The study included 477 breast cancer patients who underwent neoadjuvant chemotherapy and 308 breast cancer patients who did not in our center between January 1998 and December 2016. Optimal SIRI threshold values were determined using the receiver operating characteristic curve (ROC). Patients were then reclassified as SIRI ≥0.80 group (High SIRI group) and SIRI <0.80 group (Low SIRI group). The outcomes were analyzed by statistical methods. The univariate and multivariate analyses demonstrated that SIRI independently predicted survival in breast cancer. The disease-free survival (DFS) and overall survival (OS) in patients with low SIRI scores were significantly longer in contrast to those with high SIRI scores (41.50 vs. 37.63 months, and 64.57 vs. 58.42 months). Further subgroup analyses revealed that low SIRI score patients who also had either early breast cancer, advanced breast cancer, or different molecular subtypes also possessed longer mean survival time of DFS and OS in contrast to those with high SIRI levels (χ2 = 2.379, p = 0.123, and χ2 = 5.153, p = 0.023; χ2 = 11.080, p = 0.0009 and χ2 = 15.900, p < 0.0001; χ2 = 16.020, p < 0.0001 and χ2 = 22.050, p < 0.0001, respectively). SIRI serves as an easily accessible, replicable, and minimally invasive prognostic tool in breast cancer patients. Lower SIRI scores were predictive of a longer DFS and OS after surgery in breast cancer patients. SIRI may serve as a marker to guide clinical management and prognostication of breast cancer.

Subsequent risk of suicide among 9,300,812 cancer survivors in US: A population-based cohort study covering 40 years of data.

BACKGROUND: Large cohort studies that estimate the variation in suicide risk among cancer patients, depending on disease type and patient characteristics, are lacking. We aimed to investigate suicide risk among patients with different cancers types in the United States (US) and to identify subsets of patients at particularly high risk. METHODS: A total of 9,300,812 cases of cancer in the Surveillance, Epidemiology, and End Results (SEER) database that were diagnosed between 1975 and 2016 were included in the study. Standardized mortality ratio (SMR) and absolute excess risk (AER) of suicide were estimated. FINDINGS: From the included cases, 14,423 cancer patients were identified as having died by suicide, representing 0.26% of all deaths. We found that cancer patients had a higher risk of suicide compared with the general population, which equated to 0.8 excess deaths per 10,000 person-years. Greater suicide risk was correlated with the following: specific cancer sites, male sex, American Indian/Alaskan Native ancestry, being divorced, being uninsured, distance of metastasis, aged between 60 and 69 at diagnosis, and having a more recent diagnosis. The greatest SMR and AER were found in patients with cancers of the respiratory system, followed by those of the oral cavity and pharynx, myeloma, bones and joints, digestive system, and brain and other nervous system cancers. INTERPRETATION: Suicide risk among cancer patients varies greatly and depends on both disease type and patient characteristics. A tailored clinical management should be considered for patients at a higher risk of suicide. FUNDING: Natural Science Foundation of China.

[Research Progress of Discoidin Domain Receptor 1 in Breast Cancer and Other Malignant Tumors].

Discoidin domain receptor 1(DDR1)is a critical member of the receptor tyrosine kinase family.It may be related to tumor invasion and metastasis,and the abnormal activation of DDR1 can lead to the occurrence and development of malignant tumors,inflammation,and fibrosis.DDR1 are involved in cell adhesion,migration,proliferation,secretion of cytokines,and remodeling of extracellular matrix,thus playing a critical role in various pathophysiological processes of the human body.In this review,we demonstrate the research progress of DDR1 in breast cancer and other malignant tumors,in order to provide a new theoretical basis for the prevention and treatment of breast cancer and other tumors.