BackgroundThis meta-analysis was updated with results from a new trial and final data to reassess the efficacy and safety of bevacizumab combined with chemotherapy in ovarian cancer (OC).MethodsRandomized controlled trials (RCTs) were searched in PubMed, EMBASE, Cochrane clinical trials, Web of Science and clinicaltrial.gov databases. Outcomes included the progression-free survival (PFS), overall survival (OS), objective response rate (ORR) and common adverse events. The hazard ratio (HR), risk ratio (RR) and odds ratio (OR) were pooled when the meta-analysis was performed.ResultsFive RCTs with 4994 patients were included. In overall newly diagnosed OC, bevacizumab combined with chemotherapy did not significantly improve PFS (HR 0.85, 95%CI 0.70-1.02) or OS (HR 0.94, 95%CI 0.84-1.05). In the high-risk progression subgroup, the addition of bevacizumab significantly improved PFS (HR 0.76, 95%CI 0.68-0.84) and OS (HR 0.85, 95%CI 0.74-0.96). In recurrent OC, the addition of bevacizumab to chemotherapy significantly extended PFS (HR 0.53, 95%CI 0.45-0.63) and OS (HR 0.87, 95%CI 0.77-0.99). The ORR was improved (OR 2.37, 95%CI 1.99-2.82) in the overall population. Bevacizumab increased the incidence of hypertension (RR 21.27, 95%CI 9.42-48.02), proteinuria (RR 4.77, 95%CI 2.15-10.61), bleeding (RR 3.16, 95%CI 1.59-6.30), GI perforations (RR 2.76, 95%CI 1.51-5.03), arterial thrombosis events (RR 2.39, 95%CI 1.39-4.10) and venous thrombosis events (RR 1.43, 95%CI 1.04-1.96).ConclusionsBevacizumab combined with chemotherapy significantly improved PFS and OS in both patients with high-risk of progression and patients with recurrent OC, with an increased incidence of common adverse events. However, no statistically significant survival benefit was identified in the front-line settings.

Background/Aims: Conversion therapy can convert unresectable metastatic colorectal cancer (mCRC) into resectable. However, the optimal conversion regimen was not yet defined. This meta-analysis aimed to compare the efficacy and safety of the triplet chemotherapy (FOLFOXIRI) plus bevacizumab (Bev) with doublet chemotherapy (FOLFOX/FOLFIRI) plus Bev in conversion therapy. Methods: Randomized controlled trials (RCTs) from databases, including Pubmed, EMBASE, Cochrane clinical trials, clinicaltrial.gov and some conferences, were searched from the inception to November 2017. The R0 resection, objective response rate (ORR), progression-free survival (PFS), overall survival (OS) and the incidence of adverse events were pooled with the use of hazard ratio (HR) or risk ratio (RR). Results: Four RCTs with 1013 patients were included. FOLFOXIRI plus Bev regimen significantly improved the overall R0 resection rate (RR 1.41, 95% confidence interval (CI) 1.07-1.85, I²=37%), liver R0 resection rate (RR 2.28, 95% CI 1.34-3.89, I²=0%), ORR (RR 1.20, 95% CI 1.09-1.32, I²=0%), PFS (HR 0.72, 95% CI 0.62-0.84, I²=36%) and OS (HR 0.80, 95% CI 0.66-0.97, I²=0%). There was no significant difference in any Grade≥3 adverse event (RR 1.08, 95% CI 0.99-1.17, I²=0%) between two regimens. FOLFOXIRI-Bev was associated with a higher risk of neutropenia (RR 1.77, 95% CI 1.13-2.79, I²=68%) and diarrhea (RR 1.65, 95% CI 1.17-2.32, I²=0%). Conclusions: Triplet chemotherapy plus Bev significantly improved the R0 resection rates, ORR, PFS and OS in comparison with doublet chemotherapy plus Bev in conversion therapy for mCRC patients, with a higher risk of neutropenia and diarrhea.

Despite significant improvements in transcatheter aortic valve implantation (TAVI) outcomes, periprocedural conduction disturbances, such as new-onset left bundle branch block (LBBB) and new pacemaker implantation (PMI), remain relatively frequent concerns. The development of periprocedural conduction disturbances can be explained by the proximity between the aortic valve and the conduction system. Although prior studies reported heterogeneity in PMI rates after TAVI, current evidence supports the potentially deleterious consequence of LBBB and PMI, and several predisposing factors have been reported. Therefore, new strategies to avoid conduction disturbances and to improve their management are required, particularly with the current trend to expand TAVI to a low-risk population.

State of charge (SOC) is very important parameter for monitoring the battery charge and discharge operation and estimating the drive distance of electric vehicle. Especially, with the cycle number increasing, the precision estimation of SOC for battery management system is still not well resolved. Therefore, in this study, aim at accurate sampling of voltage, current and temperature signals based on LTC6803-3 chip, the paper proposed a support vector machine (SVM) optimized by particle swarm optimization (PSO) to improve SOC estimation accuracy. The results demonstrate that the proposed PSO-SVM model has good forecasting performance.