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Background: Several studies have systematically assessed the efficacy and safety of progressive or recurrent glioblastoma multiforme (GBM). However, the discernible limitations of efficacy and the elevated costs of interventions instigate an investigation into the cost-effectiveness of these treatments. Objectives: This study aimed to evaluate cost-effectivenesses of 11 pharmacotherapeutic interventions for recurrent GBM from the perspective of healthcare payers in the United States (US) and China. Design: A model-based pharmacoeconomic evaluation. Methods: A partitioned survival model was employed to evaluate the cost-effectiveness of 11 distinct drug-based treatments. The clinical efficacy and safety data were obtained from a network meta-analysis, while the medical expenditure and health utility were primarily derived from published literature. One-way sensitivity analyses, scenario analyses, and probabilistic sensitivity analyses (PSA) were performed to scrutinize the impact of potential uncertainties to ensure the robustness of the model. The primary endpoint was the incremental cost-effectiveness ratio. Results: Among the therapeutic interventions evaluated, lomustine emerged as the cheapest option, with costs amounting to $78,998 in the United States and $30,231 in China, respectively. Regorafenib displayed the highest quality-adjusted life years at 0.475 in the United States and 0.465 in China. The one-way sensitivity analyses underscored that drug price was a key factor influencing cost-effectiveness. Both scenario and PSA consistently demonstrated that, considering the willingness-to-pay thresholds, lomustine was a cost-effective treatment with probability of more than 94%. Conclusion: In comparison to the alternative antitumor agents, lomustine was likely to be a cost-effective option for relapsed GBM patients from the perspective of healthcare payers in both the United States and China. [ABSTRACT FROM AUTHOR]

The antagonistic behavior in the crowd usually exacerbates the seriousness of the situation in sudden riots, where the antagonistic emotional contagion and behavioral decision making play very important roles. However, the complex mechanism of antagonistic emotion influencing decision making, especially in the environment of sudden confrontation, has not yet been explored very clearly. In this paper, we propose an Emotional contagion-aware Deep reinforcement learning model for Antagonistic Crowd Simulation (ACSED). First, we build a group emotional contagion module based on the improved Susceptible Infected Susceptible (SIS) infection disease model, and estimate the emotional state of the group at each time step during the simulation. Then, the tendency of crowd antagonistic action is estimated based on Deep Q Network (DQN), where the agent learns the action autonomously, and leverages the mean field theory to quickly calculate the influence of other surrounding individuals on the central one. Finally, the rationality of the predicted actions by DQN is further analyzed in combination with group emotion, and the final action of the agent is determined. The proposed method in this paper is verified through several experiments with different settings. We can conclude antagonistic emotions play a critical role in the decision making of the crowd through influencing the individual behavior in the riot scenario, where individual behaviors are primarily driven by emotions and goals, rather than common rules. The experiment results also prove that the antagonistic emotion has a vital impact on the group combat, and positive emotional states are more conducive to combat. Moreover, by comparing the simulation results with real scenes, the feasibility of our method is further confirmed, which can provide good reference to formulate battle plans and improve the win rate of righteous groups in a variety of situations. [ABSTRACT FROM AUTHOR]

Background: Aneurysm inflow angle has been shown to be associated with hemodynamic changes by computational fluid dynamics. However, these studies were based on single aneurysm model and were limited to side‐wall aneurysms. Purpose: To investigate the association between inflow angle and morphology, hemodynamic, and inflammation of intracranial side‐wall and bifurcation aneurysms. Study type: Prospective. Population: A total of 62 patients (aged 58.34 ± 12.39, 44 female) with 59 unruptured side‐wall aneurysms and 17 unruptured bifurcation aneurysms were included. Field strength/sequence: A 3.0 T; 3D fast field echo sequence (TOF‐MRA); free‐breathing, 3D radio‐frequency‐spoiled, multi‐shot turbo field echo sequence (4D‐flow MRI); 3D black‐blood T1‐weighted volumetric turbo spin echo acquisition sequence (T1‐VISTA) Assessment: Two neuroradiologists assessed the inflow angle and size for intracranial aneurysms in 3D space with TOF‐MRA images. The average and maximum inflow velocity (Vavg‐IA, Vmax‐IA), blood flow (Flowavg‐IA, Flowmax‐IA), and average wall shear stress (WSSavg‐IA) for aneurysms were assessed from 4D‐flow MRI in regions of interest drawn by two neuroradiologists. The aneurysmal wall enhancement (AWE) grades between precontrast and postcontrast T1‐VISTA images were evaluated by three neuroradiologists. Statistical tests: Kruskal–Wallis H test, χ2 test, Pearson's correlation coefficient, scatter plots and regression lines, multivariate logistic regression analysis (partial correlation r) were performed. A P < 0.05 was considered statistically significant. Results: The WSSavg‐IA (0.52 ± 0.34 vs. 0.27 ± 0.22) and AWE grades (1.38 ± 1.04 vs. 2.02 ± 0.68) between the two inflow angle subgroups of side‐wall aneurysms were significantly different. The aneurysm size (rs = 0.31), WSSavg‐IA (rs = −0.45), and AWE grades (rs = 0.45) were significantly correlated with inflow angle in side‐wall aneurysms. While in bifurcation aneurysms, there were no significant associations between inflow angle and size (P = 0.901), Vavg‐IA (P = 0.699), Vmax‐IA (P = 0.482), Flowavg‐IA (P = 0.550), Flowmax‐IA (P = 0.689), WSSavg‐IA (P = 0.573), and AWE grades (P = 0.872). Data conclusion: A larger aneurysm size, a lower WSS and a higher AWE grade were correlated with a larger inflow angle in side‐wall aneurysms. Evidence Level: 3 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]