Background and objective: Cancer is a life-threatening disease worldwide and current standard therapy cannot fulfill all clinical needs. Chinese herbal injections have been widely used for cancer in Chinese and Western hospitals in China. This study aimed to apply evidence mapping in order to provide an overview of the clinical application of Chinese herbal injections in cancer care based on randomized controlled trials, systematic reviews, and meta-analyses.Methods and results: Seven databases were systematically searched for eligible randomized controlled trials, systematic reviews, and meta-analyses for ten Chinese herbal injections used in cancer treatment and covered in the Chinese national essential health insurance program. Excel 2016 and RStudio were used to integrate and process the data.In total 366 randomized controlled trials and 48 systematic reviews and meta-analyses were included in the evidence mapping of herbal medicines including; Compound Kushen, Shenqi Fuzheng, Aidi, Kangai, Kanglaite, Xiaoaiping, Cinobufacin, Brucea javanica oil emulsion, Polyporus polysaccharide injection, and Astragalus polysaccharide for injection. Health insurance restricts the scope of clinical application for these herbal injections. The numbers of studies published increased, especially around 2013–2015. The most studied cancer types were lung cancer (118, 32.2%), colorectal cancer (39, 10.7%), and gastric cancer (39, 10.7%), and the most used injections were Compound Kushen (78, 21.3%), Shenqi Fuzheng (76, 20.8%), and Aidi (63, 17.2%). The most consistently reported benefits were observed for Compound Kushen, Shenqi Fuzheng, Aidi, and Kangai for tumor response, quality of life, myelosuppression, and enhancing immunity.Conclusion: The current evidence mapping provides an overview of the outcomes and effects of Chinese herbal injections used in cancer care, and offers information on their clinical application which warrants further evidence-based research in order to inform clinical and policy decision-making.

BackgroundThe relationship between sleep and migraine is well known to be bidirectional. However, few studies have systematically assessed the association between sleep quality and the risk of developing migraine, and its gender and age differences are unclear. And there is currently limited evidence on the associations between sleep quality and migraine-related burdens.ObjectiveThe objectives of this study were to: (1) explore the association between sleep quality and the risk of developing migraine, and its gender and age differences; (2) investigate the associations between sleep quality and the total pain burden, severity, disability, headache impact, quality of life, anxiety, and depression of migraine patients.MethodsThis study consecutively enrolled 134 migraine patients and 70 sex- and age-matched healthy control subjects. Sleep quality was assessed through the Pittsburgh Sleep Quality Index (PSQI). Logistic regression and linear regression analyses were used to explore the associations between sleep quality with the risk of developing migraine and the migraine-related burdens.ResultsThe prevalence of poor sleep quality in migraine patients was significantly higher than that in subjects without migraine (P < 0.001). After adjusting for various confounding factors, the risk of migraine with poor sleep quality remained 3.981 times that of those with good sleep quality. The subgroup analysis showed that there were significant additive interactions between poor sleep quality and the risk of migraine in gender, age, and education level (P for interaction < 0.05), and the stronger correlations were found in females, populations with ages more than 35 years old, and with lower education levels. In addition, multivariate linear regression analysis showed that poor sleep quality was significantly and independently associated with the total pain burden, severity, headache impact, quality of life, anxiety, and depression in migraine patients (P trend < 0.05).ConclusionPoor sleep quality was significantly independently associated with an increased risk of developing migraine and the migraine-related burdens. Strengthening PSQI assessment is valuable for the early prevention and treatment of migraine patients.

BackgroundAnxiety and depression are the most common psychiatric comorbidities in migraine, but their impact on the risk of developing migraine and their gender and age differences are unclear, and research on their associations with migraine-related burdens are limited.ObjectiveTo systematically explore the association between anxiety and depression with migraine and migraine-related burdens, including the risk of developing migraine, as well as migraine frequency, severity, disability, headache impact, quality of life and sleep quality.MethodsA total of 170 migraineurs and 85 sex-and age-matched healthy control subjects were recruited consecutively for this study. Anxiety and depression were assessed using Zung’s Self-rating Anxiety Scale (SAS) and Self-rating Depression Scale (SDS), respectively. Logistic regression and linear regression analyses were used to explore the associations between anxiety and depression with migraine and its burdens. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of SAS score and SDS score on migraine and its severe burdens.ResultsAfter adjusting for confounders, anxiety and depression remained significantly associated with an increased risk of developing migraine, with odds ratios of 5.186 (95% CI:1.755–15.322) and 3.147 (95% CI:1.387–7.141), respectively. Meanwhile, there were significant additive interactions between the association of anxiety and depression with the risk of developing migraine in gender and age (P for interaction <0.05), and the stronger correlations were found in participants with an age ≤ 36 years old and females. In addition, anxiety and depression were significantly independently associated with the migraine frequency, severity, disability, headache impact, quality of life, and sleep quality in migraine patients (P trend <0.05). The area under the ROC curve (AUC) of SAS score in predicting developing migraine was significantly higher than that of SDS score [0.749 (95% CI: 0.691–0.801) vs. 0.633 (95% CI: 0.571–0.692), p < 0.0001].ConclusionAnxiety and depression were significantly independently associated with the increased risk of migraine and migraine-related burdens. Enhanced assessment of SAS score and SDS score is of great clinical value for the early prevention and treatment of migraine and its burdens.