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全脑低剂量放疗联合ICI及鞘内化疗治疗非小细胞肺癌脑膜转移的安全性与疗效分析
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作者 向丽莎 张轩薇 +7 位作者 余敏 修为刚 邹炳文 徐泳 刘咏梅 周麟 薛建新 卢铀 《中国肿瘤临床》 CAS CSCD 北大核心 2024年第18期943-949,共7页
目的:探索经全脑低剂量放疗(whole-brain low-dose radiotherapy,WB-LDRT)联合程序性死亡受体-1(programmed cell death protein-1,PD-1)抑制剂信迪利单抗及培美曲塞鞘内化疗(intrathecal pemetrexed,IP)的联合治疗方案治疗难治性非小... 目的:探索经全脑低剂量放疗(whole-brain low-dose radiotherapy,WB-LDRT)联合程序性死亡受体-1(programmed cell death protein-1,PD-1)抑制剂信迪利单抗及培美曲塞鞘内化疗(intrathecal pemetrexed,IP)的联合治疗方案治疗难治性非小细胞肺癌(non-small cell lung cancer,NSCLC)伴脑膜转移(leptomeningeal metastases,LM)的疗效和安全性。方法:回顾性分析2022年12月至2024年5月于四川大学华西医院收治的8例NSCLC伴LM患者的临床资料。患者男性4例,女性4例,年龄34~58岁,中位年龄49岁。所有患者均接受WB-LDRT联合免疫检查点抑制剂(immune checkpoint inhibitor,ICI)及鞘内化疗方案治疗,根据神经肿瘤评估标准(RANO)进行疗效评价;以及卡氏体力状态评分标准(KPS)体力状态评分,评估患者生命质量;根据常见不良事件评价标准(CTCAE)5.0版评估不良反应。生存分析采用Kaplan-Meier法;通过单细胞测序分析患者治疗前后脑脊液细胞亚群分类占比,并行细胞基因表达差异分析。结果:接受治疗8例患者RANO标准评估最佳临床疗效,5例(62.5%)评价为好转,3例(37.5%)评价为稳定;8例患者治疗前中位KPS评分为30(20~50)分,治疗后中位KPS评分明显提高,为60(40~90)分(P=0.000 9);8例患者观察到神经症状的缓解率为100%(8/8);中位神经系统无进展生存期(neurological progression-free survival,NPFS)为12个月。P1患者脑脊液单细胞测序结果提示,WB-LDRT治疗后患者脑脊液细胞分群中T细胞比率较治疗前明显上升(治疗前vs.治疗后:6.08%vs. 68.87%),肿瘤细胞比率明显下降(治疗前vs.治疗后:12.92%vs.0.60%);WB-LDRT治疗后脑脊液T细胞显著上调基因包括CCL5及CXCL13等。结论:采用WB-LDRT联合方案(WBLDRT+IP+ICI)治疗NSCLC伴LM可明显缓解患者神经症状、改善患者生存质量及延长颅内无进展生存生存时间,是一种安全有效的治疗措施。 展开更多
关键词 非小细胞肺癌 脑膜转移 全脑低剂量放疗 免疫治疗 鞘内注射治疗 培美曲塞
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A More Effective Method of Extracting the Characteristic Value of Pulse Wave Signal Based on Wavelet Transform 被引量:1
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作者 xuanwei zhang Yazhou Shang +3 位作者 Daoxin Guo Tianxia Zhao Qiuping Li Xin’an Wang 《Journal of Biomedical Science and Engineering》 2016年第10期9-19,共11页
Pulse wave contains human physiological and pathological information. Different people will exhibit different characteristics, and hence determining the characteristic points of the pulse wave of human physiological h... Pulse wave contains human physiological and pathological information. Different people will exhibit different characteristics, and hence determining the characteristic points of the pulse wave of human physiological health makes sense. It is common that we extract the characteristic value of pulse wave signal with the method based on wavelet transform on a small scale, and then determine the locations of the characteristic points by modulus maxima and modulus minima. Before determining characteristic value by detecting modulus maxima and modulus minima, we need to determine every period of the pulse wave. This paper presents a new kind of adaptive threshold determination method which is more effective. It can accurately determine every period of the pulse wave, and then extract characteristic values by modulus maxima and modulus minima in every period of the pulse wave. The method presented in this paper promotes the research utilizing pulse wave on health life. 展开更多
关键词 Pulse Wave Wavelet Transform Adaptive Threshold Characteristic Values
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