Purpose: It was reported that the novel preoperative systemic immune-inflammation index (SII) can predict survival in cases of many malignant tumors. However, the prognostic significance of preoperative SII in breast cancer remains unclear. The purpose of this study was to investigate the relationship between SII and survival in breast cancer patients. Methods: Breast cancer patients (1,026) who underwent a mastectomy at Sun Yat-sen University Cancer Center were retrospectively studied. The SII was determined using the following formula: neutrophil count × platelet count/lymphocyte count. The receiver operating characteristic (ROC) curve was used to determine the optimal cut-off value for SII. Propensity score matching (PSM) was applied to develop comparable cohorts of high SII group and low SII group. Results: A total of 1,026 patients were included as the primary cohort, and 894 patients were matched and regarded as the matched cohort. Patients were divided into two groups based on SII value: SII 601.7. In the primary cohort, the 5-years overall survival (OS), recurrence-free survival (RFS), and distant metastasis-free survival (DMFS) rates for high SII group and low SII group were (85.6% vs. 91.3%, P = 0.016), (95.8% vs. 96.4%, P = 0.684), and (83.5% vs. 90.6%, P = 0.007), respectively. Univariate analysis showed that histological type, T stage, N stage, PR, HER2, Ki67, and SII all showed significant associations with OS; and histological type, T stage, N stage, and SII all showed significant associations with DMFS. Multivariate survival analysis revealed that SII can independently predict OS (P = 0.017) and DMFS (P = 0.007). Similar results were found in PSM cohort. Conclusions: Preoperative SII may be a reliable predictor of OS and DMFS in patients with operable breast cancer to provide personalized prognostication and assist in formulation of the clinical treatment strategy.

Background: The nutritional risk index (NRI) is an independent prognostic factor for overall survival in various cancers, but its prognostic value in breast cancer remains unclear. This study aimed to explore the relationship between the NRI and overall survival (OS) in breast cancer and to develop a predictive nomogram. Methods: We retrospectively enrolled 1347 breast cancer patients who underwent mastectomy or lumpectomy between January 2011 and November 2012. Using a cutoff value of 110.59, patients were divided into a high-NRI group and a low-NRI group. OS was compared between the two groups. Clinicopathological factors independently associated with survival were used to construct a predictive nomogram. Results: Of the 1347 patients, 534 patients were classified as high NRI and 813 as low NRI. OS was significantly shorter in low-NRI patients. The 3- and 5-year OS rates were 87.3% and 73.4%, respectively, in the high-NRI group whereas they were 83.0% and 67.2%, respectively, in the low-NRI group. Cox regression analysis found that histopathological type, tumor size, lymph node status, progesterone receptor (PR) status, Ki-67, and NRI were independently associated with OS. Conclusions: NRI is an independent prognostic factor of OS in breast cancer patients. The proposed nomogram model may be a useful tool for individualized survival prediction.

Background: Recently, there has been a growing focus on the prognostic significance of nutrition-related biomarkers. We attempted to explore the association between a novel albumin-related nutrition marker called “lymphocyte × albumin (LA)” and disease-free survival (DFS) in breast cancer patients undergoing neoadjuvant chemotherapy (NAC). Methods: In total, 711 non-metastatic breast cancer patients who underwent NAC at two medical centers were retrospectively analyzed. We performed least absolute shrinkage and selection operator (LASSO) Cox regression analysis as well as multivariate Cox regression analyses to identify the variables associated with DFS and to establish a predictive nomogram. Results: The nomogram incorporated four variables based on the multivariate analysis of DFS in the training cohort: LA, ypN stage, ypT stage, and hormone receptor status. In comparison with the traditional TNM staging system, the nomogram demonstrated superior discrimination, calibration ability, and clinical usefulness in both the training set and internal and external validation sets. Furthermore, patients stratified into different risk groups resulted in significant differences in DFS. Conclusions: LA is an independent prognostic biomarker, and LA-based prognostic nomogram offers a more precise assessment of DFS for breast cancer patients treated with NAC, potentially serving as a valuable tool for personalized prognostic predictions.

Background: A higher ratio of pretreatment C-reactive protein/albumin ratio (CAR) is associated with poor prognosis in nasopharyngeal carcinoma (NPC), and Epstein–Barr virus (EBV) DNA level is known to not only participate in the occurrence of nasopharyngeal carcinoma but also affect the development and prognosis of the disease. Herein, we proposed that a combination of both these markers could improve the predictive prognostic ability. Methods: In all, 842 NPC patients who received concurrent chemoradiotherapy (CCRT) were entered in this study. We collected all patients’ blood samples and EBV DNA copy numbers within one week before any treatment. Receiver operating characteristic (ROC) curve was used to determine the optimal cut-off. We employed the Kaplan–Meier method for survival analyses and the univariate and multivariate analyses (Cox proportional hazards regression model) for statistical analysis. A nomogram was constructed based on multivariate analyses results of the validation set. The model was internally validated using 1000 bootstrap samples to avoid overfitting. Another validation of 10-fold cross-validation was also applied. Calibration curves and concordance index (C-index) were calculated to determine predictive and discriminatory capacity. Results: In the whole cohort, we observed that higher CAR, EBV DNA level, and CAR-EBV DNA (C-E) grade were associated with shorter overall survival (OS) and distant metastasis-free survival (DMFS) (all P<0.05). In univariate and multivariate analyses, C-E grade was an independent prognostic factor (all P<0.05). In the training set, we gained the similar results with the whole set. According to multivariate analyses of the training set, we constructed a nomogram. The results of bootstrap samples and 10-fold cross-validation showed favorable predictive efficacy. And calibration curves of the model provided credibility to its predictive capability. Conclusion: C-E grade was confirmed as an independent prognostic predictor in patients with NPC who received CCRT. Higher level of pretreatment C-E grade could signify a higher risk of metastasis and shorter OS. The prognostic nomogram based on C-E grade was dependable in nasopharyngeal carcinoma patients.

Systemic Therapy Combined with Locoregional Therapy Improved Survival in Oligometastatic Breast Cancer: A Single-Center Retrospective Cohort Study: The optimal therapeutic options, adding locoregional therapy (LRT) to systemic therapy (ST) or not, for patients with oligometastatic breast cancer (OMBC) have not been fully elucidated. Hence, we designed a retrospective observational study which enrolled patients with measurable extracranial OMBC having less than 5 metastatic lesions not necessarily in the same organ. We retrospectively reviewed a total of 199 patients diagnosed with extracranial OMBC, including 28 receiving ST followed by LRT (ST to LRT group), 44 receiving LRT followed by ST (LRT to ST group), and 127 receiving ST alone (ST alone group). After a median follow-up of 28.7 months, patients receiving both ST and LRT had a significantly better prognosis than those receiving ST alone: the median progression-free survival (PFS) was 16.3, 14.0, and 9.3 months ( ) and the median overall survival (OS) was 39.8, 70.5, and 26.7 months ( ) in the ST to LRT, LRT to ST, and ST alone groups, respectively. Sequence of ST and LRT had no significant impact on survival among patients receiving both. Further exploratory analysis identified ST plus LRT as an independent predictor for longer PFS. In conclusion, we demonstrated that adding LRT to ST was associated with survival benefits for patients with OMBC, and further prospective studies were warranted.

Background: There are no clinically available prognostic models for patients with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) metastatic breast cancer treated with everolimus. We aimed to develop a tool to predict the progression-free survival (PFS) and overall survival (OS) of these patients and to identify optimal candidates who would benefit from everolimus-based treatment in this heterogeneous patient population. Methods: The clinical data of patients with HR+, HER2- metastatic breast cancer receiving everolimus between May 2012 and January 2018 at Sun Yat-sen University Cancer Center were retrospectively retrieved. Based on potential prognostic factors derived from multivariate Cox analysis, we established predictive nomogram models for PFS and OS and evaluated their predictive values by means of the concordance index (C-index). Calibration curves were used to estimate the consistency between the actual observations and the nomogram-predicted probabilities. Results: A total of 116 patients with HR+, HER2- metastatic breast cancer were enrolled in this study. Three independent prognostic factors, including the line of everolimus in the metastatic setting, everolimus clinical benefit rate and number of liver metastatic lesions, were identified from the multivariate Cox analysis. Prognostic models for individual survival prediction were established and graphically presented as nomograms. The C-index was 0.738 (95% confidence interval [CI]: 0.710– 0.767) for the PFS nomogram and 0.752 (95% CI: 0.717– 0.788) for the OS nomogram, which showed favourable discrimination. The calibration curves for the probabilities of 6-, 9-, and 12-month PFS and 1-, 2-, and 3-year OS suggested satisfactory consistency between the actual observations and the predicted probabilities. Conclusion: We constructed convenient nomogram models for patients with HR+, HER2- metastatic breast cancer to individually predict their potential benefits from everolimus in the metastatic setting. The models showed good performance in terms of accuracy, discrimination capacity and clinical application value.