Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, Hawaii, USA.
Department of Kinesiology & Health Sciences, University of Waterloo, Waterloo, Ontario, Canada.
Nutrition. 2024 Sep;125:112494. doi: 10.1016/j.nut.2024.112494. Epub 2024 May 6.
Measurement of body composition using computed tomography (CT) scans may be a viable clinical tool for low muscle mass assessment in oncology. However, longitudinal assessments are often infeasible with CT. Clinically accessible body composition technologies can be used to track changes in fat-free mass (FFM) or muscle, though their accuracy may be impacted by cancer-related physiological changes. The purpose of this study was to examine the agreement among accessible body composition method with criterion methods for measures of whole-body FFM measurements and, when possible, muscle mass for the classification of low muscle in patients with cancer.
Patients with colorectal cancer were recruited to complete measures of whole-body DXA, air displacement plethysmography (ADP), and bioelectrical impedance analysis (BIA). These measures were used alone, or in combination to construct the criterion multicompartment (4C) mode for estimating FFM. Patients also underwent abdominal CT scans as part of routine clinical assessment. Agreement of each method with 4C model was analyzed using mean constant error (CE = criterion - alternative), linear regression including root mean square error (RMSE), Bland-Altman limits of agreement (LoA) and mean percentage difference (MPD). Additionally, appendicular lean soft tissue index (ALSTI) measured by DXA and predicted by CT were compared for the absolute agreement, while the ALSTI values and skeletal muscle index by CT were assessed for agreement on the classification of low muscle mass.
Forty-five patients received all measures for the 4C model and 25 had measures within proximity of clinical CT measures. Compared to 4C, DXA outperformed ADP and BIA by showing the strongest overall agreement (CE = 1.96 kg, RMSE = 2.45 kg, MPD = 98.15 ± 2.38%), supporting its use for body composition assessment in patients with cancer. However, CT cutoffs for skeletal muscle index or CT-estimated ALSTI were lower than DXA ALSTI (average 1.0 ± 1.2 kg/m) with 24.0% to 32.0% of patients having a different low muscle classification by CT when compared to DXA.
Despite discrepancies between clinical body composition assessment and the criterion multicompartment model, DXA demonstrates the strongest agreement with 4C. Disagreement between DXA and CT for low muscle mass classification prompts further evaluation of the measures and cutoffs used with each technique. Multicompartment models may enhance our understanding of body composition variations at the individual patient level and improve the applicability of clinically accessible technologies for classification and monitoring change over time.
使用计算机断层扫描（CT）测量身体成分可能是评估肿瘤患者低肌肉量的一种可行的临床工具。然而，CT 进行纵向评估通常不可行。临床可用的身体成分技术可用于跟踪去脂体重（FFM）或肌肉的变化，尽管它们的准确性可能受到癌症相关生理变化的影响。本研究的目的是检查临床可用的身体成分方法与用于测量全身 FFM 的标准方法之间的一致性，并且在可能的情况下，用于对癌症患者的低肌肉量进行分类的肌肉量。
招募结直肠癌患者完成全身 DXA、空气置换体描记术（ADP）和生物电阻抗分析（BIA）的测量。这些方法单独使用，或组合使用以构建用于估计 FFM 的多区（4C）模型的标准方法。患者还接受腹部 CT 扫描作为常规临床评估的一部分。使用平均恒误差（CE=标准值-替代值）、包括均方根误差（RMSE）的线性回归、Bland-Altman 一致性界限（LoA）和平均百分比差异（MPD）分析每种方法与 4C 模型的一致性。此外，还比较了 DXA 测量的四肢瘦软组织指数（ALSTI）和 CT 预测的 ALSTI 的绝对一致性，而 CT 测量的骨骼肌指数和分类的低肌肉量的骨骼肌肉指数的一致性进行评估。
45 名患者接受了用于 4C 模型的所有测量，25 名患者的测量值接近临床 CT 测量值。与 4C 相比，DXA 通过显示出最强的总体一致性（CE=1.96kg，RMSE=2.45kg，MPD=98.15±2.38%），在癌症患者的身体成分评估中表现优于 ADP 和 BIA，支持其用于身体成分评估。然而，与 DXA ALSTI 相比，骨骼肌指数或 CT 估计的 ALSTI 的 CT 截断值更低（平均 1.0±1.2kg/m），与 DXA 相比，24.0%至 32.0%的患者的低肌肉分类不同。
尽管临床身体成分评估与多区模型之间存在差异，但 DXA 与 4C 显示出最强的一致性。DXA 和 CT 用于低肌肉量分类的不一致促使进一步评估每种技术使用的测量值和截断值。多区模型可以提高我们对个体患者身体成分变化的理解，并提高临床可用技术的适用性，以分类和随时间监测变化。
