ABSTRACT
BACKGROUND: Coronavirus disease 2019 (COVID-19) is an infectious disease that has been spreading very fast worldwide. Up to now, there is scarce information regarding the clinical features and short-term outcomes of infected patients with cancer. METHODS: We performed a retrospective study in Wuhan Union Hospital from Feb 14, 2020, to Mar 15, 2020, China. Data were retrieved including demographic and clinical features, laboratory findings, and outcome data. Patients were classified into the discharged group and undischarged group by the 4-week outcomes from admission. Difference analysis and correlation analysis were performed between the two groups. RESULTS: A total of 37 patients were enrolled in the study, including 27 cancer survivors in routine follow-up. Breast cancer (18.9%) was the most frequent cancer type, and common symptoms included cough (54.1%), fever (48.6%), and fatigue (27%). Lymphocytopenia and hypoproteinemia were much frequent in patients who had received chemotherapy, radiotherapy, or surgery within the past month. However, the concentration of D-dimer (median: 3.75 vs 0.43, P =0.010) and fibrin degradation products (median: 23.60 vs 1.80, P =0.002) were evidently increased in this population compared with cancer survivors. At the end of follow-up, 83.8% of the enrolled patients were discharged. Among the discharged, women (48.6%) and cancer survivors (67.6%) showed better short-term outcomes. The elevated level of FDP was significantly higher in the undischarged group (median: 21.85 vs 2.00, P =0.049). The proportion of CD3-positive lymphocyte cells and CD4-positive lymphocytes was correlated with short-term outcomes. CONCLUSION: Peripheral lymphocyte subset (CD3-positive and CD4-positive) on admission as a novel biomarker had a potential association with early efficacy. Cancer survivors in routine follow-up would achieve better short-term outcomes. COVID-19 patients with cancer should gain more attention and close monitoring.
ABSTRACT
BACKGROUND: Neoadjuvant chemotherapy (NAC) has become the best comprehensive treatment choice for breast cancer. Epirubicin is a crucial drug widely used in breast cancer chemotherapy, but it is often used with a reduced dosage in NAC for Chinese patients for its notable cardiotoxicity and frequent adverse events. This study aimed to investigate the efficacy and safety of standard-dose epirubicin in NAC for Chinese breast cancer patients retrospectively. METHODS: We retrospectively collected clinicopathological parameters of breast cancer patients who underwent epirubicin-based NAC and a later surgery from three separate medical centers. Patients were divided into standard-dose and low-dose groups according to the epirubicin dose. The pathological complete response (pCR) rate, as the main therapeutic outcomes, and the incidence of adverse events were recorded and compared. RESULTS: The pCR rate of the standard-dose group was 41.2%, while the low-dose group was 10.1% (P<0.001). The univariate analysis showed that ER status (HR, 2.519; 95% CI, 1.057-5.988, P=0.037) and epirubicin dose (HR, 6.200; 95% CI, 2.374-16.193, P<0.001) were associated with pCR rates. The multivariate analysis showed that patients receiving standard-dose epirubicin chemotherapy (HR, 6.925; 95% CI, 2.537-18.902, P<0.001) showed more possibility to achieve pCR after NAC. There was no significant difference in the incidence rates of grade III/IV adverse events between these two different dose groups. CONCLUSIONS: Standard-dose epirubicin increases the pCR rate in breast cancer patients treated with NAC, and no other toxicity is noted.
ABSTRACT
BACKGROUND: Small cell lung cancer (SCLC) is a special type of lung cancer and it is responsive to chemotherapy. Blood parameters have been proved to be associated with survival for many types of malignancies. This study aimed to investigate the prognostic significance of platelet-to-lymphocyte ratio (PLR) and mean platelet volume (MPV) for SCLC patients with etoposide-based first-line treatment. METHODS: We retrospectively identified 138 patients diagnosed as SCLC who underwent etoposide-based first-line chemotherapy. The patients' baseline clinical characteristics and blood parameters were collected. Kaplan-Meier analysis and Cox regression methods were used to determine the factors associated with progression-free survival (PFS). RESULTS: The optimal cut-off value of diagnosis was depended on the ROC curve, the cut-off value of pretreatment PLR was 190 (sensitivity 39.0%, specificity 88.5%), and the cut-off value of pretreatment MPV was 10.0 (sensitivity 60.7%, specificity 61%). Kaplan-Meier analysis showed patients with high PLR levels in baseline had worse PFS than those with low PLR levels (P <0.001). Multivariate analysis revealed pretreatment MPV was an independent prognostic factor for PFS (HR: 0.815, 95% CI: 0.711-0.933, P =0.003). Further research suggested continuous high PLR indicated a poor therapy outcome (P =0.002). CONCLUSION: Pretreatment MPV can be an independent predictor for first-line treatment outcome and a continuously high level of PLR suggested inferior PFS in etoposide-treated SCLC patients.
ABSTRACT
Gastric cancer (GC) is a common gastrointestinal tumor with poor prognosis. However, conventional prognostic factors cannot accurately predict the outcomes of GC patients. Therefore, there remains a need to identify novel predictive markers to improve prognosis. In this study, we obtained microRNA expression profiles of 385 GC patients from The Cancer Genome Atlas. We performed Cox regression analysis to identify overall survival-related microRNA and then constructed a microRNA signature-based prognostic model. The accuracy of the model was evaluated and validated through Kaplan-Meier survival analysis and time-dependent receiver operating characteristic (ROC) curve analysis. The independent prognostic value of the model was assessed by multivariate Cox regression analysis. Enrichment analysis was performed to explore potential functions of the prognostic microRNA. Finally, a prognostic model based on a six-microRNA (miRNA-100, miRNA-374a, miRNA-509-3, miRNA-668, miRNA-549, and miRNA-653) signature was developed. Further analysis in the training, test, and complete The Cancer Genome Atlas set showed the model can distinguish between high-risk and low-risk patients and predict 3-year and 5-year survival. The six-microRNA signature was also an independent prognostic marker, and enrichment analysis suggested that the microRNA may be involved in cell cycle and mitosis. These results demonstrated that the model based on the six-microRNA signature can be used to accurately predict the prognosis of GC patients.
