Laura Birdsell

PURPOSE: Emerging evidence suggests muscle depletion predicts survival of patients with cancer. PATIENTS AND METHODS: At a cancer center in Alberta, Canada, consecutive patients with cancer (lung or GI; N = 1,473) were assessed at presentation for weight loss history, lumbar skeletal muscle index, and mean muscle attenuation (Hounsfield units) by computed tomography (CT). Univariate and multivariate analyses were conducted. Concordance (c) statistics were used to test predictive accuracy of survival models. RESULTS: Body mass index (BMI) distribution was 17% obese, 35% overweight, 36% normal weight, and 12% underweight. Patients in all BMI categories varied widely in weight loss, muscle index, and muscle attenuation. Thresholds defining associations between these three variables and survival were determined using optimal stratification. High weight loss, low muscle index, and low muscle attenuation were independently prognostic of survival. A survival model containing conventional covariates (cancer diagnosis, stage, age, performance status) gave a c statistic of 0.73 (95% CI, 0.67 to 0.79), whereas a model ignoring conventional variables and including only BMI, weight loss, muscle index, and muscle attenuation gave a c statistic of 0.92 (95% CI, 0.88 to 0.95; P < .001). Patients who possessed all three of these poor prognostic variables survived 8.4 months (95% CI, 6.5 to 10.3), regardless of whether they presented as obese, overweight, normal weight, or underweight, in contrast to patients who had none of these features, who survived 28.4 months (95% CI, 24.2 to 32.6; P < .001). CONCLUSION: CT images reveal otherwise occult muscle depletion. Patients with cancer who are cachexic by the conventional criterion (involuntary weight loss) and by two additional criteria (muscle depletion and low muscle attenuation) share a poor prognosis, regardless of overall body weight.

PURPOSE: The average weight-losing pancreatic cancer patient undergoing palliative therapy is frequently overweight rather than underweight, and this can confound conventional measures used for risk stratification. The aim of this study was to evaluate if weight and body composition, specifically sarcopenia, assessed from diagnostic computed tomography (CT) scans, is of prognostic value in patients with pancreatic cancer. The nature and extent of tissue loss over subsequent months was also evaluated. EXPERIMENTAL DESIGN: A total of 111 patients entering a palliative therapy program, who had CT images and had undergone nutritional screening, were studied. In patients for whom follow-up scans were available (n = 44), longitudinal changes in body composition were studied at a mean of 230 +/- 62 and 95 +/- 60 days prior to demise. RESULTS: Sixty-two patients (55.9%) were sarcopenic, 44 (39.6%) were overweight/obese, and 18 (16.2%) were both. Age > or =59 years (hazard ratio, 1.71; 95% confidence interval, 1.10-2.66; P = 0.018), and overweight/obese sarcopenia (hazard ratio, 2.07; 95% confidence interval, 1.23-3.50; P = 0.006) were identified as independent predictors of survival on multivariate analysis. Longitudinal analysis revealed that total fat-free mass index decreased from 15.5 +/- 2.5 kg/m(2) to 14.5 +/- 2.0 kg/m2 (P = 0.002), and total fat mass index decreased from 7.5 +/- 2.0kg/m2 to 6.0 +/- 1.5kg/m2 (P < 0.0001) over 135 days. CONCLUSIONS: Sarcopenia in overweight/obese patients with advanced pancreatic cancer is an occult condition but can be identified using CT scans. This condition is an independent adverse prognostic indicator that should be considered for stratification of patients' entering clinical trials, systemic therapy, or support care programs.

Purpose Effects of specific antineoplastic therapies on progression of cancer-associated wasting remain uncharacterized. We selected a targeted therapy, sorafenib, because of its reported association with weight loss. Patients and Methods Patients with metastatic renal cell cancer (RCC) who were resistant to standard therapy (N = 80) received sorafenib 400 mg twice daily or placebo in a randomized, double-blinded clinical trial. Computed tomography image analysis, which has high precision and specificity for evaluation of specific muscles and adipose tissues, was used to define change in total skeletal muscle and adipose tissue. Results At inclusion, 51% of patients were overweight or obese (ie, body mass index [BMI] &gt; 25 kg/m 2 ). Only 5% were underweight. Advanced muscle wasting (ie, sarcopenia) was present in 72% of patients with BMI less than 25 and in 34% of those with a BMI greater than 25. Patients received placebo for an average of 6 months and received sorafenib for 1 year. Patients in the placebo group had stable body weight during 6 months (0.8 kg ± 0.7 kg), with no significant alteration of muscle or fat. Patients who received sorafenib lost 2.1 kg ± 0.6 kg (P &lt; .01) in 6 months and lost 4.2 kg ± 0.7 kg (P &lt; .01) by 1 year. Sorafenib-treated patients lost skeletal muscle progressively at 6 months (decrease of 4.9%; P &lt; .01) and 12 months (decrease of 8.0%; P &lt; .01). Conclusion Sarcopenia is prevalent in patients with metastatic RCC and is an occult condition in patients with normal or high BMI. Muscle loss is specifically exacerbated by sorafenib, consistent with the evidence for a role of kinases in regulating muscle mass. Muscle loss is a sorafenib adverse effect that may relate to asthenia, fatigue, and physical disability.

PURPOSE OF REVIEW: The present review represents an overview of the potential opportunistic use of computerized tomography (CT) to enhance our understanding of abnormal body composition, specifically lean and adipose tissue changes in cancer cachexia. RECENT FINDINGS: One of the characteristics of cancer cachexia is the depletion of muscle with or without adipose tissue loss. Therefore, a body composition tool that specifically distinguishes between these tissues is essential in assessing this syndrome. Cancer patients are routinely evaluated by high resolution imaging such as CT for the purpose of diagnosis and follow-up. Recent work exploiting CT images for body composition analysis has revealed the natural history of cancer cachexia, including progressive alterations in skeletal muscle, adipose tissue, organs, and tumor mass. CT-based quantification of skeletal muscle has permitted identification of individuals with sarcopenia, and links between sarcopenia and functional status, chemotherapy toxicity, time to tumor progression, and mortality. SUMMARY: CT images routinely acquired from health records of cancer patients can be used to quantify specific lean and adipose tissues, to interpret body composition in population-based studies, and to evaluate individual patients in a clinical and therapeutic decision-making setting.