Sir Run Run Shaw Hospital

About: Sir Run Run Shaw Hospital is a healthcare organization based out in Hangzhou, China. It is known for research contribution in the topics: Cancer & Population. The organization has 5123 authors who have published 3957 publications receiving 70489 citations. The organization is also known as: Shao Yifu Hospital & Shào Yìfū Yīyuàn.

Efficacy and safety of sorafenib in patients in the Asia-Pacific region with advanced hepatocellular carcinoma: a phase III randomised, double-blind, placebo-controlled trial.

Abstract: Summary Background Most cases of hepatocellular carcinoma occur in the Asia-Pacific region, where chronic hepatitis B infection is an important aetiological factor. Assessing the efficacy and safety of new therapeutic options in an Asia-Pacific population is thus important. We did a multinational phase III, randomised, double-blind, placebo-controlled trial to assess the efficacy and safety of sorafenib in patients from the Asia-Pacific region with advanced (unresectable or metastatic) hepatocellular carcinoma. Methods Between Sept 20, 2005, and Jan 31, 2007, patients with hepatocellular carcinoma who had not received previous systemic therapy and had Child-Pugh liver function class A, were randomly assigned to receive either oral sorafenib (400 mg) or placebo twice daily in 6-week cycles, with efficacy measured at the end of each 6-week period. Eligible patients were stratified by the presence or absence of macroscopic vascular invasion or extrahepatic spread (or both), Eastern Cooperative Oncology Group performance status, and geographical region. Randomisation was done centrally and in a 2:1 ratio by means of an interactive voice-response system. There was no predefined primary endpoint; overall survival, time to progression (TTP), time to symptomatic progression (TTSP), disease control rate (DCR), and safety were assessed. Efficacy analyses were done by intention to treat. This trial is registered with ClinicalTrials.gov, number NCT00492752. Findings 271 patients from 23 centres in China, South Korea, and Taiwan were enrolled in the study. Of these, 226 patients were randomly assigned to the experimental group (n=150) or to the placebo group (n=76). Median overall survival was 6·5 months (95% CI 5·56–7·56) in patients treated with sorafenib, compared with 4·2 months (3·75–5·46) in those who received placebo (hazard ratio [HR] 0·68 [95% CI 0·50–0·93]; p=0·014). Median TTP was 2·8 months (2·63–3·58) in the sorafenib group compared with 1·4 months (1·35–1·55) in the placebo group (HR 0·57 [0·42–0·79]; p=0·0005). The most frequently reported grade 3/4 drug-related adverse events in the 149 assessable patients treated with sorafenib were hand-foot skin reaction (HFSR; 16 patients [10·7%]), diarrhoea (nine patients [6·0%]), and fatigue (five patients [3·4%]). The most common adverse events resulting in dose reductions were HFSR (17 patients [11·4%]) and diarrhoea (11 patients [7·4%]); these adverse events rarely led to discontinuation. Interpretation Sorafenib is effective for the treatment of advanced hepatocellular carcinoma in patients from the Asia-Pacific region, and is well tolerated. Taken together with data from the Sorafenib Hepatocellular Carcinoma Assessment Randomised Protocol (SHARP) trial, sorafenib seems to be an appropriate option for the treatment of advanced hepatocellular carcinoma. Funding Bayer HealthCare Pharmaceuticals and Onyx Pharmaceuticals, Inc.

Approaches to Catheter Ablation for Persistent Atrial Fibrillation

Abstract: BackgroundCatheter ablation is less successful for persistent atrial fibrillation than for paroxysmal atrial fibrillation. Guidelines suggest that adjuvant substrate modification in addition to pulmonary-vein isolation is required in persistent atrial fibrillation. MethodsWe randomly assigned 589 patients with persistent atrial fibrillation in a 1:4:4 ratio to ablation with pulmonary-vein isolation alone (67 patients), pulmonary-vein isolation plus ablation of electrograms showing complex fractionated activity (263 patients), or pulmonary-vein isolation plus additional linear ablation across the left atrial roof and mitral valve isthmus (259 patients). The duration of follow-up was 18 months. The primary end point was freedom from any documented recurrence of atrial fibrillation lasting longer than 30 seconds after a single ablation procedure. ResultsProcedure time was significantly shorter for pulmonary-vein isolation alone than for the other two procedures (P<0.001). After 18 months, 59% of patients ass...

Autophagy and chemotherapy resistance: a promising therapeutic target for cancer treatment

Abstract: Induction of cell death and inhibition of cell survival are the main principles of cancer therapy. Resistance to chemotherapeutic agents is a major problem in oncology, which limits the effectiveness of anticancer drugs. A variety of factors contribute to drug resistance, including host factors, specific genetic or epigenetic alterations in the cancer cells and so on. Although various mechanisms by which cancer cells become resistant to anticancer drugs in the microenvironment have been well elucidated, how to circumvent this resistance to improve anticancer efficacy remains to be defined. Autophagy, an important homeostatic cellular recycling mechanism, is now emerging as a crucial player in response to metabolic and therapeutic stresses, which attempts to maintain/restore metabolic homeostasis through the catabolic lysis of excessive or unnecessary proteins and injured or aged organelles. Recently, several studies have shown that autophagy constitutes a potential target for cancer therapy and the induction of autophagy in response to therapeutics can be viewed as having a prodeath or a prosurvival role, which contributes to the anticancer efficacy of these drugs as well as drug resistance. Thus, understanding the novel function of autophagy may allow us to develop a promising therapeutic strategy to enhance the effects of chemotherapy and improve clinical outcomes in the treatment of cancer patients.

UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation

Abstract: Recently, a growing interest has been seen in deep learning-based semantic segmentation. UNet, which is one of deep learning networks with an encoder-decoder architecture, is widely used in medical image segmentation. Combining multi-scale features is one of important factors for accurate segmentation. UNet++ was developed as a modified Unet by designing an architecture with nested and dense skip connections. However, it does not explore sufficient information from full scales and there is still a large room for improvement. In this paper, we propose a novel UNet 3+, which takes advantage of full-scale skip connections and deep supervisions. The full-scale skip connections incorporate low-level details with high-level semantics from feature maps in different scales; while the deep supervision learns hierarchical representations from the full-scale aggregated feature maps. The proposed method is especially benefiting for organs that appear at varying scales. In addition to accuracy improvements, the proposed UNet 3+ can reduce the network parameters to improve the computation efficiency. We further propose a hybrid loss function and devise a classification-guided module to enhance the organ boundary and reduce the over-segmentation in a non-organ image, yielding more accurate segmentation results. The effectiveness of the proposed method is demonstrated on two datasets. The code is available at: github.com/ZJUGiveLab/UNet-Version