Rutten Iris J G, Ubachs Jorne, Kruitwagen Roy F P M, Beets-Tan Regina G H, Olde Damink Steven W M, Van Gorp Toon
Department of Obstetrics and Gynaecology, Maastricht University Medical Centre, PO Box 5800, Maastricht, 6202 AZ, The Netherlands.
GROW School for Oncology and Developmental Biology, Maastricht University, PO Box 616, Maastricht, 6200 MD, The Netherlands.
J Cachexia Sarcopenia Muscle. 2017 Aug;8(4):630-638. doi: 10.1002/jcsm.12180. Epub 2017 May 16.
Computed tomography measurements of total skeletal muscle area can detect changes and predict overall survival (OS) in patients with advanced ovarian cancer. This study investigates whether assessment of psoas muscle area reflects total muscle area and can be used to assess sarcopenia in ovarian cancer patients.
Ovarian cancer patients (n = 150) treated with induction chemotherapy and interval debulking were enrolled retrospectively in this longitudinal study. Muscle was measured cross sectionally with computed tomography in three ways: (i) software quantification of total skeletal muscle area (SMA); (ii) software quantification of psoas muscle area (PA); and (iii) manual measurement of length and width of the psoas muscle to derive the psoas surface area (PLW). Pearson correlation between the different methods was studied. Patients were divided into two groups based on the extent of change in muscle area, and agreement was measured with kappa coefficients. Cox-regression was used to test predictors for OS.
Correlation between SMA and both psoas muscle area measurements was poor (r = 0.52 and 0.39 for PA and PLW, respectively). After categorizing patients into muscle loss or gain, kappa agreement was also poor for all comparisons (all κ < 0.40). In regression analysis, SMA loss was predictive of poor OS (hazard ratio 1.698 (95%CI 1.038-2.778), P = 0.035). No relationship with OS was seen for PA or PLW loss.
Change in psoas muscle area is not representative of total muscle area change and should not be used to substitute total skeletal muscle to predict survival in patients with ovarian cancer.
计算机断层扫描测量的全身骨骼肌面积可检测晚期卵巢癌患者的变化并预测总生存期(OS)。本研究调查腰大肌面积评估是否反映全身肌肉面积,以及是否可用于评估卵巢癌患者的肌肉减少症。
本纵向研究回顾性纳入了150例接受诱导化疗和间歇性肿瘤细胞减灭术治疗的卵巢癌患者。通过计算机断层扫描以三种方式进行肌肉横断面测量:(i)软件量化全身骨骼肌面积(SMA);(ii)软件量化腰大肌面积(PA);(iii)手动测量腰大肌的长度和宽度以得出腰大肌表面积(PLW)。研究不同测量方法之间的Pearson相关性。根据肌肉面积变化程度将患者分为两组,并用kappa系数测量一致性。使用Cox回归检验OS的预测因素。
SMA与两种腰大肌面积测量值之间的相关性较差(PA和PLW的r分别为0.52和0.39)。将患者分为肌肉减少或增加组后,所有比较的kappa一致性也较差(所有κ<0.40)。在回归分析中,SMA减少可预测OS较差(风险比1.698(95%CI 1.038-2.778),P=0.035)。未发现PA或PLW减少与OS有关。
腰大肌面积变化不能代表全身肌肉面积变化,不应使用其替代全身骨骼肌来预测卵巢癌患者的生存期。