目的:研究可预测PD-1/PD-L1抑制剂治疗恶性肿瘤临床疗效的潜在生物标志物。方法:检索PubMed、Web of Science、CNKI、万方和维普数据库,检索时限为各数据库建库至2022年9月20日。由2名评价员独立筛选文献、提取资料并评价纳入研究的偏...目的:研究可预测PD-1/PD-L1抑制剂治疗恶性肿瘤临床疗效的潜在生物标志物。方法:检索PubMed、Web of Science、CNKI、万方和维普数据库,检索时限为各数据库建库至2022年9月20日。由2名评价员独立筛选文献、提取资料并评价纳入研究的偏倚风险后,采用RevMan5.4和STATA16.0软件进行Meta分析。结果:共纳入18项研究,共计4018例患者。在随访的1年和2年内,发现高水平肿瘤突变负担(TMB)的肿瘤患者使用PD-1/PD-L1抑制剂的总生存率(OS)(P=0.003,P=0.01)和无进展生存率(PFS)(P=0.0002,P=0.04)更高。在不同的随访时间内,以1%为临界值,PD-L1表达高低作为预测PD-1/PD-L1抑制剂OS和PFS的生物标志物差异无统计学意义(P>0.05)。结论:TMB可以作为预测PD-1/PD-L1抑制剂治疗恶性肿瘤患者后2年内临床疗效的生物学指标,但其效用能否持续更长时间有待进一步研究;PD-L1单项检测目前不能成为预测应用PD-1/PD-L1抑制剂受益与否的生物学标志物。展开更多
转移性肺癌指任何部位的恶性肿瘤通过各种转移方式转移至肺部的肿瘤,在经历多线化疗、放疗、免疫及靶向治疗后,患者往往存在着心理上负担,从而患上抑郁症,导致肿瘤的治疗效果不尽人意。本文针对转移性肺癌与抑郁之间的影响因素进行综述...转移性肺癌指任何部位的恶性肿瘤通过各种转移方式转移至肺部的肿瘤,在经历多线化疗、放疗、免疫及靶向治疗后,患者往往存在着心理上负担,从而患上抑郁症,导致肿瘤的治疗效果不尽人意。本文针对转移性肺癌与抑郁之间的影响因素进行综述,探求原因,以期为临床转移性肺癌患者抑郁症的治疗提供相关思路。Metastatic lung cancer refers to tumors that have metastasized to the lungs through various metastatic modalities from malignant tumors in any part of the body. After undergoing multiple lines of chemotherapy, radiotherapy, immunotherapy and targeted therapy, patients are often psychologically burdened, and thus suffer from depression, which leads to unsatisfactory treatment results of the tumors. This paper reviews the influencing factors between metastatic lung cancer and depression and explores the causes, with a view to providing relevant ideas for the treatment of depression in clinical metastatic lung cancer patients.展开更多
We propose a new and efficient algorithm to detect, identify, and correct measurement errors and branch parameter errors of power systems. A dynamic state estimation algorithm is used based on the Kalman filter theory...We propose a new and efficient algorithm to detect, identify, and correct measurement errors and branch parameter errors of power systems. A dynamic state estimation algorithm is used based on the Kalman filter theory. The proposed algorithm also successfully detects and identifies sudden load changes in power systems. The method uses three normalized vectors to process errors at each sampling time: normalized measurement residual, normalized Lagrange multiplier, and normalized innovation vector. An IEEE 14-bus test system was used to verify and demonstrate the effectiveness of the proposed method. Numerical results are presented and discussed to show the accuracy of the method.展开更多
文摘目的:研究可预测PD-1/PD-L1抑制剂治疗恶性肿瘤临床疗效的潜在生物标志物。方法:检索PubMed、Web of Science、CNKI、万方和维普数据库,检索时限为各数据库建库至2022年9月20日。由2名评价员独立筛选文献、提取资料并评价纳入研究的偏倚风险后,采用RevMan5.4和STATA16.0软件进行Meta分析。结果:共纳入18项研究,共计4018例患者。在随访的1年和2年内,发现高水平肿瘤突变负担(TMB)的肿瘤患者使用PD-1/PD-L1抑制剂的总生存率(OS)(P=0.003,P=0.01)和无进展生存率(PFS)(P=0.0002,P=0.04)更高。在不同的随访时间内,以1%为临界值,PD-L1表达高低作为预测PD-1/PD-L1抑制剂OS和PFS的生物标志物差异无统计学意义(P>0.05)。结论:TMB可以作为预测PD-1/PD-L1抑制剂治疗恶性肿瘤患者后2年内临床疗效的生物学指标,但其效用能否持续更长时间有待进一步研究;PD-L1单项检测目前不能成为预测应用PD-1/PD-L1抑制剂受益与否的生物学标志物。
文摘转移性肺癌指任何部位的恶性肿瘤通过各种转移方式转移至肺部的肿瘤,在经历多线化疗、放疗、免疫及靶向治疗后,患者往往存在着心理上负担,从而患上抑郁症,导致肿瘤的治疗效果不尽人意。本文针对转移性肺癌与抑郁之间的影响因素进行综述,探求原因,以期为临床转移性肺癌患者抑郁症的治疗提供相关思路。Metastatic lung cancer refers to tumors that have metastasized to the lungs through various metastatic modalities from malignant tumors in any part of the body. After undergoing multiple lines of chemotherapy, radiotherapy, immunotherapy and targeted therapy, patients are often psychologically burdened, and thus suffer from depression, which leads to unsatisfactory treatment results of the tumors. This paper reviews the influencing factors between metastatic lung cancer and depression and explores the causes, with a view to providing relevant ideas for the treatment of depression in clinical metastatic lung cancer patients.
文摘We propose a new and efficient algorithm to detect, identify, and correct measurement errors and branch parameter errors of power systems. A dynamic state estimation algorithm is used based on the Kalman filter theory. The proposed algorithm also successfully detects and identifies sudden load changes in power systems. The method uses three normalized vectors to process errors at each sampling time: normalized measurement residual, normalized Lagrange multiplier, and normalized innovation vector. An IEEE 14-bus test system was used to verify and demonstrate the effectiveness of the proposed method. Numerical results are presented and discussed to show the accuracy of the method.
