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首页> 外文期刊>World Journal of Surgery: Official Journal of the Societe Internationale de Chirurgie, Collegium Internationale Chirurgiae Digestivae, and of the International Association of Endocrine Surgeons >Worsening central sarcopenia and increasing intra-abdominal fat correlate with decreased survival in patients with adrenocortical carcinoma
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Worsening central sarcopenia and increasing intra-abdominal fat correlate with decreased survival in patients with adrenocortical carcinoma

机译:肾上腺皮质癌患者的中央肌肉减少症恶化和腹内脂肪增加与存活率降低相关

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Background Accurate prediction of survival from adrenocortical carcinoma (ACC) is difficult and current staging models are unreliable. Central sarcopenia as part of the cachexia syndrome is a marker of frailty and predicts mortality. This study seeks to confirm that psoas muscle density (PMD), lean psoas muscle area (LPMA), lumbar skeletal muscle index (LSMI), and intra-abdominal (IA) or subcutaneous fat (SC) can be used in combination to more accurately predict survival in ACC patients. Methods PMD, LPMA, IA, and SC fat were measured on serial CT scans of patients with ACC. Clinical outcome was correlated with quantitative data from patients with ACC and analyzed. A linear regression model was used to describe the relationship between PMD, LPMA, LSMI, IA, and SC fat, time to recurrence, and length of survival according to tumor stage. Results One hundred twenty-five ACC patients (94 females) were treated from 2005 to 2011. Significant morphometric predictors of survival include PMD, LPMA, and IA fat (p ≤ 0.0001, ≤ 0.0024, ≤ 0.0001, respectively) and improve prediction of survival compared to using stage alone. A 100-mm 2 increase in LPMA confers an 8 % lower hazard of death. LSMI does not change significantly between stages (p = 0.3196). Conclusion Decreased PMD, LPMA, and increased IA fat suggest decreased survival in ACC patients and correlate with traditional staging systems. A more precise prediction of survival may be achieved when staging systems and morphometric measures are used in combination. Serial measurements of morphometric data are possible. The rate of change of these variables over time may be more important than the absolute value.
机译:背景技术准确预测肾上腺皮质癌(ACC)的生存是困难的,目前的分期模型也不可靠。中枢肌肉减少症是恶病质综合征的一部分,是体弱的标志,可预测死亡率。这项研究旨在确认腰肌密度(PMD),瘦腰肌面积(LPMA),腰椎骨骼肌指数(LSMI)和腹腔内(IA)或皮下脂肪(SC)可以结合使用,以更准确地进行预测ACC患者的生存率。方法对ACC患者进行连续CT扫描,测量PMD,LPMA,IA和SC脂肪。将临床结果与ACC患者的定量数据进行关联并进行分析。使用线性回归模型描述PMD,LPMA,LSMI,IA和SC脂肪之间的关系,复发时间以及根据肿瘤分期的生存时间。结果2005年至2011年共治疗了125例ACC患者(94名女性)。显着的生存形态预测指标包括PMD,LPMA和IA脂肪(分别为p≤0.0001,≤0.0024,≤0.0001),并改善了生存预测与单独使用舞台相比。 LPMA增加100 mm 2可使死亡危险降低8%。 LSMI在两个阶段之间没有显着变化(p = 0.3196)。结论PMD,LPMA的减少和IA脂肪的增加表明ACC患者的生存率降低,并且与传统的分期系统相关。结合使用分期系统和形态计量指标,可以实现更精确的生存预测。形态计量数据的串行测量是可能的。这些变量随时间的变化率可能比绝对值更重要。

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