1.Sorafenib in the treatment of advanced renal cell carcinoma (analysis of 33 cases)
Lanting HU ; Qifu ZHANG ; Youtao JIANG ; Zecheng NI ; Yu ZHANG ; Shengjun WANG ; Qing WANG
Chinese Journal of Urology 2011;32(7):494-496
Objective To investigate the efficacy and toxicity of sorafenib in the treatment of advanced renal cell carcinoma. Methods From May 2007 to JUN 2009, 33 patients with advanced renal cell carcinoma were given oral sorafenib 400-600 mg twice daily. There were 23 males and 10 females in the study group. The pathological diagnosis of the primary tumors was clear cell carcinoma in 29 patients, papillary renal cell carcinoma in 2 patients, chromophobe renal cell carcinoma in 1 patient and chromophobe renal cell carcinoma mixed with clear renal cell carcinoma in 1 patient. Fifteen patients had multiple organ metastases and 18 patients had single organ metastasis. The median follow-up time was 29 weeks. Results Four (12%) patients achieved partial remission, 2 (6%) patients achieved progression disease, the remaining 27 (82%) patients achieved stable disease. Complete remission was not observed in the group. Two of the partial remission patients benefited on bone metastases. Common toxicities were skin reaction (85%), diarrhea (46%), erythra (42%), alopecia (36%), oral ulcer (18%) and hypertension (9%). Conclusions Sorafenib could be effective in controlling tumor growth. The overall effectiveness was 12%, the disease control proportion was 94% in this group and its toxicity was relatively minor and well tolerated.
2.Retrospective analysis of the predictive value of immunoglobulin and complement combined leukocyte levels on the outcome of severe COVID-19
Yong ZHAO ; Weirong ZENG ; Fuan YU ; Youtao HU ; Li XU ; Junfeng ZENG ; Kunyun JIA ; Jianbin SUN ; Jiancheng TU
Chinese Journal of Experimental and Clinical Virology 2021;35(1):1-6
Objective:To retrospectively analyze the blood leukocytes (WBC), lymphocytes (LYM), lymphocyte% (LYM%), and serum total immunoglobulin (IGA, IGG, IGM) and complement (C3, C4) index levels to explore its predictive value for the outcome of COVID-19 severe pneumonia.Methods:Eighty-five COVID-19 patients with severe pneumonia diagnosed in our hospital were randomly selected and were divided into good outcome group (50 cases) and poor outcome group (35 cases). WBC, LYM, LYM%, IGA, IGG, IGM, and C3, C4 level data, and analyze the differences between the two groups, the correlation of each indicator, and ROC curves of single and joint detection to explore relationship between indicators and outcomes, and the predictive efficacy of indicators on outcomes.Results:Differences in WBC, LYM, LYM%, IGG, and IGA levels were significant between the two groups ( P=0.000, 0.015, 0.000, 0.000, 0.001), among them with significant differences, LYM and LYM% were significantly positively correlated ( r=0.669, P=0.000), while WBC and LYM% levels were significantly negatively correlated ( r=-0.600, P=0.000), WBC and IGA levels were significantly positively correlated ( r=0.283, P=0.009) and IGG and IGA levels were also significantly positively correlated ( r=0.0.442, P=0.000); After logistic regression analysis, WBC, LYM, LYM%, IGG, and IGA are all important influencing factors ( P=0.001, 0.022, 0.000, 0.000, 0.003); but only the levels of WBC, IGG, and LYM% are Independent risk factors ( P=0.034, 0.004, 0.001), the ROC curve of the single detection and joint detection of their predicted outcome performance, respectively, and the max AUC (AUC=0.890, P=0.000) at the time of joint testing of WBC, LYM% and IGG, index YI=0.657, it has the greatest predictive power for adverse outcomes, with a sensitivity of 77.10% and a specificity of 88.00%. IGM, C3, C4, IGG/IGM, and C3/C4 levels were not significantly different( P=0.066, 0.204, 0.076, 0.310, 0.156). Conclusions:The levels of WBC, LYM, LYM%, IGG, and IGA in the early admission of COVID-19 infected patients with severe pneumonia have important predictive value for the outcome of them. WBC, LYM% and IGG levels are independent risks and joint detection of the three indexes have the best predictive performance.