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首页> 外文期刊>Journal for ImmunoTherapy of Cancer >45?Body composition as a predictive and prognostic biomarker in advanced urothelial carcinoma (UC) patients treated with immune checkpoint inhibitors (ICI)
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45?Body composition as a predictive and prognostic biomarker in advanced urothelial carcinoma (UC) patients treated with immune checkpoint inhibitors (ICI)

机译:45?身体组成作为治疗免疫检查点抑制剂(ICI)治疗的晚期尿路上皮癌(UC)患者的预测和预后生物标志物

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Background Several immune checkpoint inhibitors (ICI) have been approved for the treatment of advanced urothelial carcinoma (UC). There are limited predictive biomarkers for UC patients treated with ICI. In this study, we investigated the association between body composition and clinical outcomes in ICI-treated advanced UC patients. Methods We conducted a retrospective analysis of 70 ICI-treated advanced UC patients at Winship Cancer Institute from 2015–2020. Inclusion criteria was available computed tomography (CT) scans within 2 months of ICI-initiation. Baseline CT images were collected at mid-L3 and muscle and fat compartments were segmented using SliceOMatic v5.0 (TomoVision). The density of subcutaneous fat, inter-muscular fat, visceral fat, and skeletal muscle (SM) were measured and converted to indices by dividing by height(m)2 (SFI, IFI, VFI and SMI, respectively). Attenuated SM mean (Hounsfield Units) was also collected. Myosteatosis was calculated by IFI/SMI*100%. Gender-specific optimal cuts were used to dichotomize patients as high or low for each variable using OS as the primary outcome. A prognostic body composition risk score was created based on the beta coefficient from the multivariable Cox model (MVA) following best-subset variable selection. Our body composite risk score was SMI 2*SM mean VFI and patients were categorized as high (0–1), intermediate (2–3), or low-risk (4). Comparison of OS and PFS between the risk groups was performed via Kaplan-Meier method and Log-rank test. Concordance statistics (C-statistics) were used to quantify the discriminatory magnitude of the predictive model. Results Most patients (70%) were male and more than one-quarter (26%) had an ECOG PS ≥ 2. The majority received ICI in the second (46%) or third-line (21%) setting. Body composite poor-risk patients had significantly shorter OS (HR: 6.18, p0.001), PFS (HR: 5.91, p0.001), and lower chance at CB (OR: 0.02, p=0.004) compared to low-risk group in MVA (table 1). Patients with low myosteatosis had significantly longer OS (HR: 0.35, p=0.002), PFS (HR: 0.32, p0.001), and higher chance at CB (OR: 20.47, p=0.034) compared to high myosteatosis patients in MVA. The C-statistics for our body composition risk group and myosteatosis analyses were higher than BMI for all clinical outcomes (table 2). High and intermediate-risk patients had significantly shorter OS and PFS compared to low-risk patients per Kaplan-Meier estimation (figure 1). Abstract 45 Table 1 MVA* of association between risk groups and myosteatosis with clinical outcomes Abstract 45 Table 2 Comparison of C-statistics between body composition risk groups, myosteatosis and BMI Abstract 45 Figure 1 Kaplan-Meier curves of association between body composition risk groups and overall survival (OS, top panel) and progression-free survival (PFS, bottom panel) Conclusions Body composition variables such as SMI, SM mean, VFI and myosteatosis may be predictive of clinical outcomes in ICI-treated advanced UC patients. Larger, prospective studies are warranted to validate this hypothesis-generating data. Acknowledgements Research reported in this publication was supported in part by the Biostatistics and Bioinformatics Shared Resource of Winship Cancer Institute of Emory University and NIH/NCI under award number P30CA138292. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Trial Registration Not applicable Ethics Approval This retrospective study was approved by the Emory University Institutional Review Board.
机译:背景技术几种免疫检查点抑制剂(ICI)已被批准用于治疗晚期尿路上皮癌(UC)。有限的预测生物标志物用于用ICI治疗的UC患者。在这项研究中,我们研究了ICI治疗的先进UC患者的身体成分和临床结果之间的关联。方法从2015 - 2015年开始,我们对Winship癌症研究所进行了回顾性分析了70例ICI治疗的先进UC患者。纳入标准在ICI-Insiation的2个月内扫描可用计算断层扫描(CT)扫描。基线CT图像在中间-13中收集,并且使用Sliceomatic V5.0(Tomovision)分段肌肉和脂肪室。测量皮下脂肪,肌肉间脂肪,内脏脂肪和骨骼肌(SM)的密度通过分别除以高度(M)2(SFI,IFI,VFI和SMI)来转化为索引。还收集了减毒SM平均值(Hounsfield单位)。用IFI / SMI * 100%计算肌肉病。使用操作系统作为主要结果,使用特异性特异性最佳切割对患者为每种变量而高或低。基于最佳子集变量选择之后的多变量Cox模型(MVA)的Beta系数来创建预后的身体成分风险评分。我们的身体复合风险得分为SMI 2 * SM平均VFI,患者分为高(0-1),中间体(2-3)或低风险(4)。通过Kaplan-Meier方法和日志秩测试进行风险组之间的OS和PFS的比较。协调统计(C统计)用于量化预测模型的歧视性幅度。结果大多数患者(70%)是男性,超过四分之一(26%)的ECOGPS≥2。大多数在第二(46%)或第三行(21%)设定中获得ICI。与低风险相比,身体综合患者患者(HR:6.18,P <0.001),PFS(HR:5.91,P <0.001),PFS(HR:5.91,P <0.001),以及Cb(或0.02,P = 0.004)的较低机会组在MVA中(表1)。骨髓病变低的患者具有明显更长的OS(HR:0.35,P = 0.002),PFS(HR:0.32,P <0.001),与MVA中的高骨赘病症相比,CB(或20.47,P = 0.034)的较高机会。对于所有临床结果,我们的身体成分风险组和肌室中变异分析的C统计学均高于BMI(表2)。与每kplan-meier估计的低风险患者相比,高和中性风险患者具有显着较短的OS和PFS(图1)。摘要45表1 MVA *风险群和肌室中的关联与临床结果摘要45表2身体成分风险群体,肌肉病变和BMI之间的C统计的比较45图1 Kaplan-Meier曲线在身体成分风险群体之间的关联曲线整体存活(OS,顶部面板)和无进展生存(PFS,底部面板)结论体组成变量如SMI,SM平均值,VFI和Myosteatyis,可以预测ICI治疗的先进UC患者的临床结果。较大,前瞻性研究是有必要验证此假设生成数据。本出版物报告的致谢研究是部分支持的,部分由生物统计学和生物信息学共同资源支持埃默里大学WINSHIP癌症研究所和NIH / NCI下的奖项P30CA138292。内容完全是作者的责任,不一定代表国家卫生研究院的官方意见。审判登记不适用伦理批准,这项回顾性研究得到了埃默里大学机构审查委员会的批准。
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