Objective: To systematically evaluate the efficacy of Xihuang pill (XHP) in breast cancer patients receiving chemotherapy.
Methods: Three English and four Chinese databases were searched. Literature was screened using EndNote X7 and data were analyzed by Review Manager.
Results: This review included 13 randomized clinical studies of 1272 patients. The results showed that XHP increased the tumor response [risk ratio (RR) = 2.91; 95% confidence interval (CI): 1.98-4.26] and improved Karnofsky performance score (KPS) for breast cancer patients receiving chemotherapy [RR = 4.96; 95% CI = 2.07-11.86]. In addition, XHP treatment significantly reduced chemotherapy-induced adverse events, including nausea and vomiting [RR = 0.50; 95% CI = 0.33-0.74], WBC reduction [RR = 0.71; 95% CI = 0.47-1.06], platelet reduction [RR = 0.53; 95% CI = 0.19-1.44], hemoglobin reduction [RR = 0.31; 95% CI = 0.19-0.52], and hepatic function damage [RR = 0.63; 95% CI = 0.35-1.11].
Conclusion: XHP combined with chemotherapy in comparison with chemotherapy alone could significantly enhance the tumor response, improve KPS, and alleviate toxicity induced by chemotherapy in breast cancer patients.
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http://dx.doi.org/10.1155/2019/3502460 | DOI Listing |
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Department of Ultrasound, Chongqing General Hospital, Chongqing University, Chongqing, 401147, China.
Gas therapy represents a promising strategy for cancer treatment, with nitric oxide (NO) therapy showing particular potential in tumor therapy. However, ensuring sufficient production of NO remains a significant challenge. Leveraging ultrasound-responsive nanoparticles to promote the release of NO is an emerging way to solve this challenge.
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Cancer Signaling and Microenvironment Program, Fox Chase Cancer Center, Philadelphia, PA, USA. Electronic address:
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Breast Cancer Center, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, China. Electronic address:
Am J Pathol
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Department of Computer Science, Faculty of Engineering Sciences, University College London, Gower Street, London, WC1E 6BT, United Kingdom.
Understanding the tumor hypoxic microenvironment is crucial for grasping tumor biology, clinical progression, and treatment responses. This study presents a novel application of AI in computational histopathology to evaluate hypoxia in breast cancer. Weakly Supervised Deep Learning (WSDL) models can accurately detect morphological changes associated with hypoxia in routine Hematoxylin and Eosin (H&E) whole slide images (WSI).
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