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.
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.
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