The Association Between Body Composition, Overall Survival, Treatment Decisions, and Patient-Reported Outcomes in Metastatic Non-Small-Cell Lung Cancer

IF 2.9 2区医学 Q2 ONCOLOGY Cancer Medicine Pub Date : 2025-01-07 DOI:10.1002/cam4.70534

Adriana M. Coletta, Hyejung Lee, Sonam Puri, Sinead Culleton, Matthew F. Covington, Jeffrey T. Yap, Kelsey E. Maslana, Benjamin Haaland, Wallace Akerley

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Abstract

Introduction

The purpose of this study was to evaluate the association between body composition, overall survival, odds of receiving treatment, and patient-reported outcomes (PROs) in individuals living with metastatic non-small-cell lung cancer (mNSCLC).

Methods

This retrospective analysis was conducted in newly diagnosed patients with mNSCLC who had computed-tomography (CT) scans and completed PRO questionnaires close to metastatic diagnosis date. Cox proportional hazard models and logistic regression evaluated overall survival and odds of receiving treatment, respectively. Hazard ratios (HR) and odds ratios (OR) were evaluated as the interquartile range for body composition compartments. Multiple linear regression evaluated the association between PROs and body composition. Models were adjusted for gender, age at diagnosis, smoking history, and mutation status. The survival model also included adjustment for tumor histology.

Results

Our sample (n = 69) included men (52%) and women (48%), with a median age of 67.4-years, history of smoking (67%), wild-type genotype (75.4%), and a tumor histology of adenocarcinoma (68%). Greater skeletal muscle area was associated with higher physical function scores. Larger intermuscular adipose tissue area was associated with higher mortality risk (HR 2.03, 95% CI 1.32, 3.11), lower odds of receiving treatment (OR 0.76, 95% CI 0.61, 0.93), and higher fatigue. Larger subcutaneous adipose tissue area was associated with lower mortality risk (HR 0.42, 95% CI 0.22, 0.82) and higher odds of receiving treatment (OR 1.03, 95% CI 1.01, 1.06). Larger total adipose tissue area was linked with improved survival (HR 0.59, 95% CI 0.36, 0.96).

Conclusion

Findings support an association between different body composition compartments at mNSCLC diagnosis and survival, decisions to treat, and PROs. This work supports the use of data collected in routine CT scans and PROs to inform treatment decisions and supportive care options.

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转移性非小细胞肺癌的身体组成、总生存期、治疗决定和患者报告结果之间的关系

本研究的目的是评估转移性非小细胞肺癌（mNSCLC）患者的身体组成、总生存期、接受治疗的几率和患者报告的预后（PROs）之间的关系。方法：回顾性分析新诊断的小细胞肺癌患者，这些患者在转移诊断日期前进行了计算机断层扫描（CT）并完成了PRO问卷。Cox比例风险模型和logistic回归分别评估总生存率和接受治疗的几率。风险比（HR）和优势比（OR）作为身体成分区室的四分位数范围进行评估。多元线性回归评估了PROs与身体成分之间的关系。模型根据性别、诊断年龄、吸烟史和突变状态进行调整。生存模型还包括肿瘤组织学调整。结果：我们的样本（n = 69）包括男性（52%）和女性（48%），中位年龄为67.4岁，吸烟史（67%），野生型基因型（75.4%），腺癌肿瘤组织学（68%）。骨骼肌面积越大，身体机能得分越高。较大的肌间脂肪组织面积与较高的死亡风险（HR 2.03, 95% CI 1.32, 3.11）、较低的治疗几率（OR 0.76, 95% CI 0.61, 0.93）和较高的疲劳程度相关。较大的皮下脂肪组织面积与较低的死亡风险（HR 0.42, 95% CI 0.22, 0.82）和较高的接受治疗的几率相关（OR 1.03, 95% CI 1.01, 1.06）。总脂肪组织面积越大，生存率越高（HR 0.59, 95% CI 0.36, 0.96）。结论：研究结果支持在小细胞肺癌的诊断和生存、治疗决定和PROs中不同体成分间的关联。这项工作支持使用常规CT扫描和pro收集的数据来指导治疗决策和支持性护理选择。

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

Cancer Medicine ONCOLOGY-

CiteScore

5.50

自引率

2.50%

发文量

907

审稿时长

19 weeks

期刊介绍： Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas: Clinical Cancer Research Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations Cancer Biology: Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery. Cancer Prevention: Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach. Bioinformatics: Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers. Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.