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At present, treatment options for osimertinib resistance are very limited. Dual inhibition of the vascular endothelial growth factor (VEGF) and epidermal growth factor receptor (EGFR) significantly improved the progression-free survival (PFS) of advanced EGFR-mutant non–small cell lung cancer (NSCLC). After EGFR-tyrosine kinase inhibitor (TKI) resistance, EGFR-TKI continuation combined with VEGF inhibitors still had clinical benefits. It is unclear whether the addition of bevacizumab after osimertinib progresses will prolong the duration of the osimertinib benefit. We screened 1289 patients with NSCLC and finally included 96 patients to evaluate osimertinib combined with bevacizumab (osi + bev) versus chemotherapy combined with bevacizumab (che + bev) for patients with acquired resistance to osimertinib. The overall response rate (ORR) for osi + bev and chem + bev was 15.8% (6 of 38) and 20.7% (12 of 58), respectively. The median PFS for osi + bev and che + bev was 7.0 and 4.9 months (HR 0.415 95%CI: 0.252–0.687 p = 0.001). The median OS for osi + bev and che + bev was 12.6 and 7.1 months (HR 0.430 95%CI: 0.266–0.696 p = 0.001). Multivariate analyses showed that no brain metastases and osi + bev treatment after osimertinib resistance correlated with longer PFS (p = 0.044, p = 0.001), while the median PFS of osimertinib less than 6 months (p = 0.021) had a detrimental effect on sequent treatment. Only osi + bev treatment was identified as an independent predictor of OS (p = 0.001). The most common adverse events (AEs) of grade ≥3 were hypertension (13.2%) and diarrhea (10.5%) in the osi + bevacizumab group. Neutropenia (24.1%) and thrombocytopenia (19%) were the most common grade ≥3 AEs in the che + bev group. The overall incidence of serious AEs (grade ≥3) was significantly higher in the chemotherapy plus bevacizumab group. Our study has shown the superiority of osi + bev compared to che + bev after the failure of osimertinib, making it a preferred option for patients with acquired resistance to osimertinib.

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This paper proposes a PCA and ANN based approach to identify significant influential quality factors and modeling customer satisfaction for complex service processes. Firstly, the performance evaluation index system includes initial factors and customer satisfaction degree is proposed, and then the measurement data are collected by questionnaires. Secondly, by using PCA, several preceding principal components (PCs) are extracted, which present about 90% contributions of the whole variations of initial factors. Thirdly, the extracted PCs are converted to new significant factors according to the corresponding coefficients of initial factors in each PC. Finally, BP network is applied to modeling the nonlinear relationship between the significant factors and customer satisfaction degree. The case study of the maintenance service process of an automobile 4S store shows that, the proposed approach can extracted the significant factors from lots of initial factors, and can exactly modeling the complex nonlinear relationship between influential factors and customer satisfaction as well. 1 Keywords -customer satisfaction modeling; complex service process; artificial neural networks; principal component analysis Along with market developing, the auto 4S shops, as a representative of modern service industry are able to birth and development. 4S mode is actually the inevitable product under the fierce competition in the car market. Therefore, it becomes very important to the development of service sector of how to improve the customer satisfaction and trust under the new features. How to make model in the study of customer satisfaction for the characteristics of strong nonlinear, and how to identify the key service quality factors becomes an important topic worthy of further study.The existing research of customer satisfaction modeling is multi-purpose structure equation model (SEM) [1] [2], for example: Peters and Enders [3] use SEM to study the impact of the biggest drivers of customer satisfaction; Sheng Lin, Jinlan Liu, Wenxiu Han [4] analysis PLS path modeling algorithm with multiple latent variables, using the method to discuss the correlation between each latent variable relations in customer satisfaction in a commercial real estate in Tianjin. But relation between the customer satisfaction and each Fund projects: 1. The national social science fund projects: Rapid rescue management system construction of the major emergency disasters in coal mine in China: 10GBL087; 2. The natural science research project of Henan province department of education: The key technology development of coal logistics network modeling and optimization under work well production conditions. Project numbers: 2011A410003 structure variables has strong nonlinear. Due to structural equation has certain inadaptability for processing nonlinear problem, It would affect the precision of the research on customer satisfaction by using the structural equation model. Thus the conclusion can't be convincingly. In order to solve this strong nonlinear pro...