Nomograms combining computed tomography-based body composition changes with clinical prognostic factors to predict survival in locally advanced cervical cancer patients.

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Accounts of Chemical Research Pub Date : 2024-01-01 DOI:10.3233/XST-230212
Baoyue Fu, Longyu Wei, Chuanbin Wang, Baizhu Xiong, Juan Bo, Xueyan Jiang, Yu Zhang, Haodong Jia, Jiangning Dong
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Abstract

Objective: To explore the value of body composition changes (BCC) measured by quantitative computed tomography (QCT) for evaluating the survival of patients with locally advanced cervical cancer (LACC) underwent concurrent chemoradiotherapy (CCRT), nomograms combined BCC with clinical prognostic factors (CPF) were constructed to predict overall survival (OS) and progression-free survival (PFS).

Methods: Eighty-eight patients with LACC were retrospectively selected. All patients underwent QCT scans before and after CCRT, bone mineral density (BMD), subcutaneous fat area (SFA), visceral fat area (VFA), total fat area (TFA), paravertebral muscle area (PMA) were measured from two sets of computed tomography (CT) images, and change rates of these were calculated.

Results: Multivariate Cox regression analysis showed ΔBMD, ΔSFA, SCC-Ag, LNM were independent factors for OS (HR = 3.560, 5.870, 2.702, 2.499, respectively, all P < 0.05); ΔPMA, SCC-Ag, LNM were independent factors for PFS (HR = 2.915, 4.291, 2.902, respectively, all P < 0.05). Prognostic models of BCC combined with CPF had the highest predictive performance, and the area under the curve (AUC) for OS and PFS were 0.837, 0.846, respectively. The concordance index (C-index) of nomograms for OS and PFS were 0.834, 0.799, respectively. Calibration curves showed good agreement between the nomograms' predictive and actual OS and PFS, decision curve analysis (DCA) showed good clinical benefit of nomograms.

Conclusion: CT-based body composition changes and CPF (SCC-Ag, LNM) were associated with survival in patients with LACC. The prognostic nomograms combined BCC with CPF were able to predict the OS and PFS in patients with LACC reliably.

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将基于计算机断层扫描的身体成分变化与临床预后因素相结合的提名图,用于预测局部晚期宫颈癌患者的生存期。
目的为了探讨通过定量计算机断层扫描(QCT)测量的身体成分变化(BCC)在评估接受同步放化疗(CCRT)的局部晚期宫颈癌(LACC)患者生存率方面的价值,我们构建了将BCC与临床预后因素(CPF)相结合的提名图,以预测总生存率(OS)和无进展生存率(PFS):方法:回顾性筛选出88例LACC患者。所有患者在接受 CCRT 治疗前后均接受了 QCT 扫描,通过两组计算机断层扫描(CT)图像测量了骨矿密度(BMD)、皮下脂肪面积(SFA)、内脏脂肪面积(VFA)、总脂肪面积(TFA)和椎旁肌肉面积(PMA),并计算了这些指标的变化率:多变量Cox回归分析显示,ΔBMD、ΔSFA、SCC-Ag、LNM是影响OS的独立因素(HR=3.560、5.870、2.702、2.499,均P<0.05);ΔPMA、SCC-Ag、LNM是影响PFS的独立因素(HR=2.915、4.291、2.902,均P<0.05)。BCC结合CPF的预后模型具有最高的预测性能,OS和PFS的曲线下面积(AUC)分别为0.837和0.846。OS和PFS提名图的一致性指数(C-index)分别为0.834和0.799。校准曲线显示,提名图的预测OS和PFS与实际OS和PFS之间具有良好的一致性,决策曲线分析(DCA)显示提名图具有良好的临床效益:结论:基于 CT 的身体成分变化和 CPF(SCC-Ag、LNM)与 LACC 患者的生存率相关。结合 BCC 和 CPF 的预后提名图能够可靠地预测 LACC 患者的 OS 和 PFS。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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