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Fangfang Duan,* Chenge Song,* Yuyu Ma, Kuikui Jiang, Fei Xu, Xiwen Bi, Jiajia Huang, Ruoxi Hong, Zhangzan Huang, Qianyi Lu, Zhongyu Yuan, Shusen Wang, Wen Xia Departments of Medical Oncology, Sun Yat-sen University Cancer Center, The State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, People’s Republic of China*These authors contributed equally to this workCorrespondence: Wen XiaDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, The State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People’s Republic of ChinaEmail xiawen@sysucc.org.cnBackground: 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.Keywords: prognostic nomogram, metastatic breast cancer, everolimus, progression-free survival, overall survival

BACKGROUND: Breast cancer is one of the most common malignancy in women with high mortality rate. Given the growing evidence shows that immune-inflammatory system influences the survival of patients with cancer, we assessed the prognostic significance of the preoperative Controlling Nutritional Status (CONUT) score in patients with breast cancer who underwent surgery. METHODS: We conducted a retrospective analysis of 1,367 breast cancer patients who underwent surgery between December 2010 and October 2012. All individual preoperative serum albumin concentration, total cholesterol concentration, and total peripheral lymphocyte count were counted to calculate CONUT. Higher CONUT score is in line with worse nutritional status. The optimal cut-off of CONUT score was set at 3 to categorize the investigated patients into two groups, namely a high- or low-CONUT score group. We adopted univariate and multivariate analyses (Cox proportional hazards regression model) statistical method. RESULTS: Patients in the high-CONUT score group had shorter overall survival (OS) and recurrence-free survival (RFS) in comparison with those in the low-CONUT score group, 66.43 vs. 69.30 months and 54.70 vs. 59.98 months respectively (all P value

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 ( P < 0.001 ) and the median overall survival (OS) was 39.8, 70.5, and 26.7 months ( P < 0.001 ) 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.

Jing Yuan,1,&ast; Fangfang Duan,2,&ast; Wenyu Zhai,3,&ast; Chenge Song,2 Li Wang,2 Wen Xia,2 Xin Hua,2 Zhongyu Yuan,2 Xiwen Bi,2 Jiajia Huang2 1Departments of Experimental Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People’s Republic of China; 2Departments of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People’s Republic of China; 3Departments of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jiajia Huang; Xiwen BiDepartment of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People’s Republic of ChinaEmail huangjiaj@sysucc.org.cn; bixw@sysucc.org.cnBackground: Aging, an inevitable process characterized by functional decline over time, is a significant risk factor for various tumors. However, little is known about aging-related genes (ARGs) in breast cancer (BC). We aimed to explore the potential prognostic role of ARGs and to develop an ARG-based prognosis signature for BC.Methods: RNA-sequencing expression profiles and corresponding clinicopathological data of female patients with BC were obtained from public databases in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). An ARG-based risk signature was constructed in the TCGA cohort based on results of least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis, and its prognostic value was further validated in the GSE20685 cohort.Results: A six ARG-based signature, including CLU, DGAT1, MXI1, NFKBI, PIK3CA and PLAU, was developed in the TCGA cohort and significantly stratified patients into low- and high-risk groups. Patients in the former group showed significantly better prognosis than those in the latter. Multivariate Cox regression analysis demonstrated that the ARG risk score was an independent prognostic factor for BC. A predictive nomogram integrating the ARG risk score and three identified factors (age, N- and M-classification) was established in the TCGA cohort and validated in the GSE20685 cohort. Calibration plots showed good consistency between predicted survival probabilities and actual observations.Conclusion: A novel ARG-based risk signature was developed for patients with BC, which can be used for individual prognosis prediction and promoting personalized treatment.Keywords: breast cancer, aging, prognostic signature, risk stratification

The dysregulation of iron homeostasis has been explored in malignancies. However, studies focusing on the association between the serum iron level and prognosis of patients with early-stage triple-negative breast cancer (TNBC) are scarce. Accordingly, in current study, 272 patients with early-stage TNBC treated at Sun Yat-sen University Cancer Center (SYSUCC) between September 2005 and October 2016 were included as a training cohort, another 86 patients from a previous randomized trial, SYSUCC-001, were analyzed as a validation cohort (SYSUCC-001 cohort). We retrospectively collected their clinicopathological data and tested the serum iron level using blood samples at the diagnosis. In the training cohort, patients were divided into low-iron and high-iron groups according to the serum iron level cut-off of 17.84 μmol/L determined by maximally selected rank statistics. After a median follow-up of 87.10 months, patients with a low iron had a significantly longer median disease-free survival (DFS) of 89.13 [interquartile range (IQR): 66.88–117.38] months and median overall survival (OS) of 92.85 (IQR: 68.83–117.38) months than those in the high-iron group (median DFS: 75.25, IQR: 39.76–105.70 months, P = 0.015; median OS: 77.17, IQR: 59.38–110.28 months, P = 0.015). Univariate and multivariate Cox analysis demonstrated the serum iron level to be an independent predictor for DFS and OS. Then, a prognostic nomogram incorporating the serum iron level, T stage and N stage was developed for individualized prognosis predictions. It had good discriminative ability with a C-index of DFS (0.729; 95% CI 0.666–0.792) and OS (0.739; 95% CI 0.666–0.812), respectively. Furtherly, we validated the predictive model in the SYSUCC-001 cohort, which also showed excellent predictive performance with a C-index of DFS (0.735; 95% CI 0.614–0.855) and OS (0.722; 95% CI 0.577–0.867), respectively. All these suggested that the serum iron level might be a potential prognostic biomarker for patients with early-stage TNBC, the predictive model based on it might be served as a practical tool for individualized survival predictions.

Xin Hua,1,* Fangfang Duan,1,* Wenyu Zhai,2,* Chenge Song,1 Chang Jiang,1 Li Wang,1 Jiajia Huang,1 Huanxin Lin,3 Zhongyu Yuan1 1Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People’s Republic of China; 2Department of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People’s Republic of China; 3Department of Radiotherapy, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhongyu Yuan,Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People’s Republic of China, Email yuanzhy@sysucc.org.cnHuanxin Lin,Department of Radiotherapy, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, Guangdong, 510060, People’s Republic of China, Email linhx@sysucc.org.cnPurpose: We attempted to explore the prognostic value of baseline inflammatory and nutritional biomarkers at diagnosis in patients with early-stage breast cancer and develop a novel scoring system, the inflammatory-nutritional prognostic score (INPS).Patients and Methods: We collected clinicopathological and baseline laboratory data of 1259 patients with early-stage breast cancer between December 2010 and November 2012 from Sun Yat-sen University Cancer Center. Eligible patients were randomly divided into training and validation cohorts (n = 883 and 376, respectively) in a 7:3 ratio. We selected the most valuable biomarkers to develop INPS by the least absolute shrinkage and selection operator (LASSO) Cox regression model. A prognostic nomogram incorporating INPS and other independent clinicopathological factors was developed based on the stepwise multivariate Cox regression method. Then, we used the concordance index (C-index), calibration plot, and time-dependent receiver operating characteristic (ROC) analysis to evaluate the prognostic performance and predictive accuracy of the predictive nomogram.Results: Four inflammatory-nutritional biomarkers, including neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), prognostic nutritional index (PNI), and albumin-alkaline phosphatase ratio (AAPR), were selected using the LASSO Cox analysis to construct INPS, which remained an independent prognostic indicator per the multivariate Cox regression analysis. Patients were stratified into low- and high-INPS groups based on the cutoff INPS determined by the maximally selected rank statistics. The prognostic model for overall survival consisting of INPS and other independent clinicopathological indicators showed excellent discrimination with C-indexes of 0.825 (95% confidence interval [CI]: 0.786– 0.864) and 0.740 (95% CI: 0.657– 0.822) in the training and validation cohorts, respectively. The time-dependent ROC curves showed a higher predictive accuracy of our prognostic nomogram than that of traditional tumor-node-metastasis staging.Conclusion: Baseline INPS is an independent indicator of OS in patients with early-stage breast cancer. The INPS-based prognostic nomogram could be used as a practical tool for individualized prognostic predictions.Keywords: early-stage breast cancer, LASSO Cox analysis, inflammatory-nutritional biomarker, prognostic nomograms, overall survival

Background Despite significant survival improvement in human epidermal growth factor receptor 2 (HER2) blockade for HER2-positive breast cancer, resistance to anti-HER2 remains inevitable. Subsequent anti-HER2 with continuing trastuzumab beyond progression is acceptable with limited efficacy when other anti-HER2 treatment is unavailable. This single-arm, phase II study (SYSUCC-005) aimed to explore the efficacy of switching mode for HER2-positive refractory metastatic breast cancer. Methods Patients with HER2-positive metastatic breast cancer rapidly progressing during pre-trastuzumab from six hospitals in China were designed to switch to lapatinib 1,250 mg orally once per day continuously plus capecitabine (1,000 mg/m2 orally twice per day on days 1–14) or vinorelbine (25 mg/m2 intravenously once per day on days 1 and 8) of each 21-day cycle. The primary endpoint was progression-free survival (PFS). Results Between January 5, 2015 and May 31, 2020, 159 patients were eligible in this study. The median follow-up was 33.1 months, a median PFS of 8.5 months was achieved. Brain metastases (hazard ratio [HR] = 1.582, 95% confidence interval [CI] 1.019- 2.453, P = 0.041) and ≥ 2 metastatic sites (HR = 1.679, 95% CI 1.151–2.450, P = 0.007) were independent prognostic factors for PFS. The most common grade ≥ 3 adverse events were diarrhea (3.8%) and hand-foot syndrome (9.4%). Conclusion The switching mode showed predominant efficacy, which might be a prior therapeutic option over continuing mode in subsequent anti-HER2 therapy for patients with HER2-positive refractory metastatic breast cancer. Trial registration This trial was registered on ClinicalTrials.gov (NCT02362958) on 13/02/2015.

BackgroundA 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.MethodsIn 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.ResultsIn 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 PConclusionC-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.

Background: Tumor progression following endocrine therapy is considered to indicate resistance to endocrine drugs due to a variety of mechanisms. An insufficient dose of endocrine drugs is one of the causes for treatment failure in some patients with high hormone-receptor (HR)-expressing advanced breast cancer. This study aimed to explore the efficacy of high-dose tamoxifen (TAM) treatment in patients with advanced breast cancer with highly expressed HR. Materials & methods: This was a single-arm, phase II pilot study that enrolled patients with advanced breast cancer with high HR expression (estrogen receptor ⩾60% and/or progesterone receptor ⩾60%) following routine endocrine therapy. All enrolled patients received a high-dose of TAM (100 mg/day) until disease progression. The primary endpoint was progression-free survival (PFS). The secondary endpoints included objective response rate (ORR), clinical benefit rate (CBR), overall survival (OS), and safety. Exploratory endpoints included the predictive value of 16α-18F-17β-fluoroestradiol quantitative positron emission tomography/computed tomography (18F-FES PET/CT) for treatment efficacy. Results: A total of 30 patients were enrolled between September 2017 and February 2019. The median PFS was 6 months [95% confidence interval (CI) 4.9–7.1] and the median OS was 15.6 months (95% CI 8.3–22.9). Five patients experienced a partial response (PR) and none experienced a complete response (CR), with an ORR of 16.7% and CBR of 33.3%. No severe adverse events were observed. Lesions with 18F-FES maximum standardized uptake value (SUVmax) ⩾4 had a significantly longer PFS [median 9.2 months, (95% CI 6.9–11.6)] compared with lesions with a 18F-FES SUVmax Conclusion: A high-dose of TAM is effective and safe for patients with advanced breast cancer with high HR expression. 18F-FES SUVmax values may predict the local clinical benefits of high-dose TAM . Trial Registration: [ClinicalTrials.gov identifier: NCT0304565]

Supplemental material, sj-docx-1-tam-10.1177_1758835921993436 for High-dose tamoxifen in high-hormone-receptor-expressing advanced breast cancer patients: a phase II pilot study by Yanhong Su, Yarui Zhang, Xin Hua, Jiajia Huang, Xiwen Bi, Wen Xia, Xinyue Wang, Zhangzan Huang, Chenge Song, Yongyi Zhong, Yanxia Shi, Shusen Wang, South China Breast Cancer Group (SCBCG), Wei Fan and Zhongyu Yuan in Therapeutic Advances in Medical Oncology

Background: Systemic inflammation score (SIS) has been verified as a novel prognostic indicator in several cancer types. However, its prognostic value in breast cancer remains unknown. Furthermore, a nomogram based on SIS is yet to be constructed for breast cancer. We conducted this study to explore the association between SIS and prognosis of breast cancer, and to construct a good prognostic nomogram model. Methods: A total of 1,180 breast cancer patients who underwent curative surgery between December 2010 and January 2013 were recruited. They were randomly assigned to the training set (n = 944) or the validation set (n = 236). All patient blood samples were collected within 1 week prior to operation. According to previous reports, SIS was calculated for all patients, who were then classified into two groups: high-SIS and low-SIS. The Kaplan–Meier method was employed for survival analyses, and univariate and multivariate analyses (Cox proportional hazards regression model) were used for prognostic assessment. A nomogram was constructed based on the results of multivariate analysis. Calibration curves and concordance index (C-index) were compiled to determine predictive and discriminatory capacity. Results: In the training set, the median follow-up time was 6.07 years. Patients in the high-SIS group had an average OS time of 68.05 months, which is shorter than that of the low-SIS group (72.87 months; P = 0.033). Patients in the high-SIS group had average RFS and DMFS times of 56.04 and 54.46 months, respectively, which are shorter than those of the low-SIS group (60.85 and 59.47 months, respectively; P = 0.247 and P = 0.032). Univariate and multivariate analyses revealed SIS to be an independent prognostic factor for OS and DMFS time. The nomogram for the training set indicated OS and DMFS C-indexes of 0.794 (95% CI, 0.772–0.816) and 0.712 (95% CI, 0.684–0.740), respectively. In the validation set, the OS and DMFS C-indexes were 0.889 (95% CI, 0.845–0.933) and 0.696 (95%. CI, 0.611–0.781), respectively. Conclusions: SIS was confirmed as an independent prognostic predictor among patients with breast cancer who had undergone surgery with curative intent. Higher preoperative SIS may indicate higher risk of metastasis and shorter overall survival time. The prognostic nomogram based on SIS was dependable for breast cancer patients who underwent curative surgery.

North China is one of the country’s most important socio-economic centers, but its severe air pollution is a huge concern. In this region, precisely forecasting the daily photovoltaic power generation in winter is essential to improve equipment utilization rate and mitigate effects of power system on the environment. Considering the climatic characteristics of North China, the winter days are divided into three classifications. A forecasting model based on random forest algorithm is then designed for each classification. To evaluate its performance, the proposed model and three other methods are separately used to forecast the daily power generation at the Zhonghe PV station, which is located in the center of North China. Empirical results show that, because of its ability to reduce the risk of overfitting by balancing decision trees, the proposed model obtains mean absolute percentage errors as low as 2.83% and 3.89% for clear and cloudy days, respectively. For days in which weather conditions are unusual, forecasting errors are relatively large. On these days, enlarging training samples, performing subdivision, and imposing manual intervention can improve the forecasting precision. Generally, the proposed model is better than the other three methods for nearly all error evaluation indicators in each classification.