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体脂成分在接受酪氨酸激酶抑制剂治疗的转移性肾细胞癌患者中的预后价值

The Prognostic Value of Body Fat Components in Metastasis Renal Cell Carcinoma Patients Treated with TKIs.

作者信息

Dai Jindong, Zhang Xingming, Liu Zhenhua, Song Tingni, Zhu Xudong, Zhang Haoran, Wu Mingpeng, Li Xiang, Zeng Hao, Shen Pengfei

机构信息

Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu 610041, People's Republic of China.

Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, People's Republic of China.

出版信息

Cancer Manag Res. 2020 Feb 7;12:891-903. doi: 10.2147/CMAR.S230973. eCollection 2020.

DOI:10.2147/CMAR.S230973
PMID:32104071
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7012252/
Abstract

PURPOSE

To assess the association between body fat components and survival status and tumor response for metastatic renal cell carcinoma (mRCC) patients treated with tyrosine kinase inhibitors (TKIs).

PATIENTS AND METHODS

Patients with pathologically diagnosed and radiologically indicated mRCC were enrolled into the retrospective study. Three body fat components: total fat accumulation (TFA), visceral fat accumulation (VFA) and subcutaneous fat accumulation (SFA) were measured using standard CT scans. The clinical outcomes included progression-free survival (PFS), overall survival (OS), and tumor response rates. Univariate analysis and multivariate Cox proportion hazard regression models were used to find associated parameters and to calculate the adjusted hazard ratio (HR).

RESULTS

A total of 146 patients were enrolled and the average age of patients was 56.5 years old. According to the univariate analysis, patients with an increased SFA and TFA had a longer PFS and OS. A similar phenomenon was observed among patients with ≥2 increasing body fat components about PFS and OS. As for multivariate analysis, SFA change (p=0.014) or the number of increasing body fat components (p=0.040) were independent indicators to predict PFS. In addition, SFA change (p=0.022) or the number of increasing body fat components (p=0.008) could independently predict OS. Moreover, a better disease control rate (p=0.028) was founded in patients with ≥2 increasing components. In the subgroup of patients with ≥2 metastasis sites, improved OS (p=0.017) and PFS (p=0.027) were found compared to those with <2 increasing components. Further multivariate analysis identified the number of increasing body fat components was an independent factor in predicting PFS (p=0.018) and OS (p=0.029).

CONCLUSION

Body fat accumulation, such as high SFA or TFA at progression, could improve the survival of patients with mRCC treated with TKIs, especially patients with higher tumor burden. It should be considered as an important parameter to predict the survival status of patients with mRCC.

摘要

目的

评估接受酪氨酸激酶抑制剂(TKIs)治疗的转移性肾细胞癌(mRCC)患者的体脂成分与生存状况及肿瘤反应之间的关联。

患者与方法

将经病理诊断和影像学检查确诊为mRCC的患者纳入这项回顾性研究。使用标准CT扫描测量三种体脂成分:总脂肪蓄积(TFA)、内脏脂肪蓄积(VFA)和皮下脂肪蓄积(SFA)。临床结局包括无进展生存期(PFS)、总生存期(OS)和肿瘤反应率。采用单因素分析和多因素Cox比例风险回归模型来寻找相关参数并计算调整后的风险比(HR)。

结果

共纳入146例患者,患者的平均年龄为56.5岁。根据单因素分析,SFA和TFA增加的患者具有更长的PFS和OS。在体脂成分增加≥2种的患者中,观察到关于PFS和OS的类似现象。至于多因素分析,SFA变化(p = 0.014)或体脂成分增加的数量(p = 0.040)是预测PFS的独立指标。此外,SFA变化(p = 0.022)或体脂成分增加的数量(p = 0.008)可独立预测OS。此外,在体脂成分增加≥2种的患者中发现了更好的疾病控制率(p = 0.028)。在转移部位≥2个的患者亚组中,与体脂成分增加<2种的患者相比,OS(p = 0.017)和PFS(p = 0.027)有所改善。进一步的多因素分析确定体脂成分增加的数量是预测PFS(p = 0.018)和OS(p = 0.029)的独立因素。

结论

体脂蓄积,如病情进展时高SFA或TFA,可改善接受TKIs治疗的mRCC患者的生存,尤其是肿瘤负荷较高的患者。它应被视为预测mRCC患者生存状况的重要参数。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e659/7012252/901eef3e1c8e/CMAR-12-891-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e659/7012252/73a9d5d3c73e/CMAR-12-891-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e659/7012252/5a25b2e21cd3/CMAR-12-891-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e659/7012252/90500fa336a0/CMAR-12-891-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e659/7012252/901eef3e1c8e/CMAR-12-891-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e659/7012252/73a9d5d3c73e/CMAR-12-891-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e659/7012252/5a25b2e21cd3/CMAR-12-891-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e659/7012252/90500fa336a0/CMAR-12-891-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e659/7012252/901eef3e1c8e/CMAR-12-891-g0004.jpg

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