BackgroundImmune checkpoint inhibitors (ICIs) combined with chemotherapy have been widely employed to improve the outcome of gastric cancer patients. In the present study, the impact of posttreatment growth hormone (GH) levels on the treatment efficacy of ICIs for advanced gastric cancer (AGC) patients was assessed.MethodsSeventy-five AGC patients treated with anti-PD-1 antibodies at The Fourth Hospital of Hebei Medical University were involved. We divided AGC patients into two groups as high-GH group and low-GH group based on the GH level. Immunotherapy efficacy was assessed in terms of objective response rate, disease control rate (DCR), progression-free survival (PFS), and overall survival (OS) based on the National Comprehensive Cancer Network Guidelines. The enumeration data were compared by χ2 test or Fisher’s exact test. Survival curves were drawn by the Kaplan–Meier method, and comparisons between the curves were made using the log-rank test. Multivariate survival analysis was performed using a Cox proportional hazards model.ResultsThe higher GH levels were associated with a lower DCR of ICIs with a DCR of 30.0% in the high-GH group and 53.3% in the low-GH group (P = 0.046). The subsequent univariate analysis showed that a high GH level was associated with both shorter PFS (P = 0.016) and shorter OS at the borderline statistical level (P = 0.052) in AGC patients treated with ICIs. Cox model analysis also proved that the GH level was an independent risk factor for the outcome of AGC patients (PFS: P = 0.013, HR, 2.424, 95% CI, 1.202–4.890; OS: P = 0.014, HR, 3.301, 95% CI, 1.279–8.519).ConclusionsThe post-treatment GH level might be a predictor for ICIs treatment in AGC patients.
In the network geographic information system, through voice interaction, the operation can be made simple, convenient and effective. To this end, this paper studies the GIS map component technology to support voice interaction. Build the overall design of GIS map components, which includes three layers: function layer, data layer and map UI layer. The functional layer is the main layer for realizing voice interaction. After audio enters the functional layer, voice recognition must be performed first. After understanding the semantics, the mapping feedback is completed, and voice interaction is realized and supported. Experiments show that the recognition speed of the content designed in this paper is relatively fast, and the highest recognition rate is 98.5%, which provides functional component support for the information processing of geospatial information.
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