Chinese Herbal Medicine for Chemotherapy-Induced Leukopenia: A Systematic Review and Meta-Analysis of High-Quality Randomized Controlled Trials.

Aim: We conducted a systematic review of high-quality randomized controlled trials (RCTs) to assess the efficacy and safety of Chinese herbal medicine (CHM) for the treatment of chemotherapy-induced leukopenia (CIL). Methods: Eight electronic databases were searched from the date of inception to November 4, 2020 for high-quality RCTs that met the requirements of at least four key domains of the Cochrane risk of bias (RoB) tool. RevMan 5.3 was applied for the meta-analysis. Results: Fourteen RCTs involving 1,053 patients were included. The pooled results showed that CHM + chemotherapy exerted greater beneficial effects on white blood cell (WBC), neutrophil (NEU), hemoglobin (Hb), and platelet (PLT) counts in addition to the Karnofsky performance scale (KPS) score, but showed no significant difference on granulocyte colony-stimulating factor (G-CSF) dosage compared with chemotherapy alone. Placebo (PBO) + chemotherapy and CHM + chemotherapy groups showed no significant differences in terms of reduction of the incidence of neutropenia. CHM + chemotherapy was superior to Western medicine (WM) + chemotherapy in improving the WBC count, KPS, infection amount, G-CSF use rate, and incidence of leukopenia. In addition, no severe adverse events were observed in the 14 RCTs. Conclusion: CHM in combination with chemotherapy could effectively improve the clinical symptoms of CIL when compared with chemotherapy alone or Western medicine + chemotherapy, except when comparing with PBO + chemotherapy. While CHMs were generally safe for clinical use and exerted no severe side effects in the 14 RCTs, high-quality RCTs with larger sample sizes are essential to reduce study heterogeneity.

Effects of meteorological factors on the incidence of mumps and models for prediction, China.

BACKGROUND: Mumps is an acute respiratory infectious disease with obvious regional and seasonal differences. Exploring the impact of climate factors on the incidence of mumps and predicting its incidence trend on this basis could effectively control the outbreak and epidemic of mumps. METHODS: Considering the great differences of climate in the vast territory of China, this study divided the Chinese mainland into seven regions according to the administrative planning criteria, data of Mumps were collected from the China Disease Prevention and Control Information System, ARIMA model and ARIMAX model with meteorological factors were established to predict the incidence of mumps. RESULTS: In this study, we found that precipitation, air pressure, temperature, and wind speed had an impact on the incidence of mumps in most regions of China and the incidence of mumps in the north and southwest China was more susceptible to climate factors. Considering meteorological factors, the average relative error of ARIMAX model was 10.87%, which was lower than ARIMA model (15.57%). CONCLUSIONS: Meteorology factors were the important factors which can affect the incidence of mumps, ARIMAX model with meteorological factors could better simulate and predict the incidence of mumps in China, which has certain reference value for the prevention and control of mumps.

Spatial-temporal analysis and visualization of scarlet fever in mainland China from 2004 to 2017.

This study retrospectively analyzed the spatio-temporal distribution and spatial clustering of scarlet fever in mainland China from 2004 to 2017. In recent years, the incidence of scarlet fever is increasing. Previous studies on the spatial distribution of scarlet fever in China are mainly focused at the provincial and municipal levels, and there is few systematic report on the spatial and temporal distribution characteristics of scarlet fever on the national level. Based on the incidence information of scarlet fever in mainland China between 2004 and 2017 collected from the China Center for Disease Control, this paper systematically explored the Spatio-temporal distribution of scarlet fever by three methods, contains spatial autocorrelation analysis, Spatio-temporal scanning analysis, and trend surface analysis. The results demonstrate that the incidence of scarlet fever varies by seasons, which is in line with double-peak distribution.The first peak generally occurs from May to June and the second one from November to December, while February and August is the lowest period of incidence. Trend surface analysis indicates that the incidence of scarlet fever in northern China is higher than the south, slightly higher in western compared to the east, and lower in the central part. Additionally, the results show that the clustering regions of scarlet fever centrally distributed in the northeast, northwest, north china and some provinces in the east, such as Zhejiang, Shanghai, Shandong, and Jiangsu.