Prediction of whole body composition utilizing cross-sectional abdominal imaging in pediatrics.

BACKGROUND: Although body composition is an important determinant of pediatric health outcomes, we lack tools to routinely assess it in clinical practice. We define models to predict whole-body skeletal muscle and fat composition, as measured by dual X-ray absorptiometry (DXA) or whole-body magnetic resonance imaging (MRI), in pediatric oncology and healthy pediatric cohorts, respectively. METHODS: Pediatric oncology patients (≥5 to ≤18 years) undergoing an abdominal CT were prospectively recruited for a concurrent study DXA scan. Cross-sectional areas of skeletal muscle and total adipose tissue at each lumbar vertebral level (L1-L5) were quantified and optimal linear regression models were defined. Whole body and cross-sectional MRI data from a previously recruited cohort of healthy children (≥5 to ≤18 years) was analyzed separately. RESULTS: Eighty pediatric oncology patients (57% male; age range 5.1-18.4 y) were included. Cross-sectional areas of skeletal muscle and total adipose tissue at lumbar vertebral levels (L1-L5) were correlated with whole-body lean soft tissue mass (LSTM) (R2 = 0.896-0.940) and fat mass (FM) (R2 = 0.874-0.936) (p < 0.001). Linear regression models were improved by the addition of height for prediction of LSTM (adjusted R2 = 0.946-0.971; p < 0.001) and by the addition of height and sex (adjusted R2 = 0.930-0.953) (p < 0.001)) for prediction of whole body FM. High correlation between lumbar cross-sectional tissue areas and whole-body volumes of skeletal muscle and fat, as measured by whole-body MRI, was confirmed in an independent cohort of 73 healthy children. CONCLUSION: Regression models can predict whole-body skeletal muscle and fat in pediatric patients utilizing cross-sectional abdominal images.

Rapid atrophy of cardiac left ventricular mass in patients with non-small cell carcinoma of the lung.

BACKGROUND: Cancer is a systemic catabolic condition affecting skeletal muscle and fat. We aimed to determine whether cardiac atrophy occurs in this condition and assess its association with cardiac function, symptoms, and clinical outcomes. METHODS: Treatment naïve metastatic non-small cell lung cancer patients (n = 50) were assessed prior to and 4 months after commencement of carboplatin-based palliative chemotherapy. Methods included echocardiography for left ventricular mass (LVM) and LV function [LV ejection fraction, global longitudinal strain (GLS), diastolic function], computed tomography to quantify skeletal muscle and total adipose tissue, Eastern Cooperative Oncology Group Performance Status (ECOG-PS), validated questionnaires for dyspnoea and fatigue, plasma biomarkers, tumour response to therapy, and overall survival. RESULTS: During 112 ± 6 days, the median change in LVM was -8.9% [95% confidence interval (95% CI) -10.8 to -4.8, P < 0.001]. Quartiles of LVM loss were -20.1%, -12.9%, -4.8%, and +5.5%. Losses of muscle, adipose tissue, and LVM were frequently concurrent; LVM loss > median value was associated with loss of skeletal muscle [odds ratio (OR) = 4.5, 95% CI: 1.4-14.8, P=0.01] and loss of total adipose tissue (OR = 10.0, 95% CI: 2.7-36.7, P < 0.001). LVM loss was associated with decreased GLS (OR = 6.6, 95% CI: 1.9-22.7, P=0.003) but not with LV ejection fraction or diastolic function. In the population overall, plasma levels of C-reactive protein (P=0.008), high sensitivity troponin T (hs-TnT) (P=0.03), and galectin-3 (P=0.02) increased over time, while N-terminal pro B-type natriuretic peptide and hs-cTnI did not change over time. C-reactive protein was the only biomarker associated with LVM loss but at the univariate level only. Independent predictors of LVM loss were prior weight loss (adjusted OR = 10.2, 95% CI: 2.2-46.9, P=0.003) and tumour progression (adjusted OR = 14.6, 95% CI: 1.4-153.9, P=0.02). LVM loss was associated with exacerbations of fatigue (OR = 6.6, 95% CI: 1.9-22.7, P=0.003), dyspnoea (OR = 9.3, 95% CI: 2.4-35.8, P<0.001), and deterioration of performance status (OR = 4.8, 95% CI: 1.3-18.3,P=0.02). Patients with concurrent loss of LVM, skeletal muscle, and fat were more likely to deteriorate in all three symptom domains and to have reduced survival (P=0.05). CONCLUSIONS: Intense LVM atrophy is associated with non-small cell lung cancer-induced cachexia. Loss of LVM was associated with emerging alterations of GLS, indicating subtle changes in left ventricular function. Longer term studies are needed to assess the full scope of cardiac atrophy and its impact. LVM atrophy arises in conjunction with losses of fat and skeletal muscle and is temporally associated with meaningful declines in performance status, worsening of fatigue, and dyspnoea, as well as poorer tumour response and decreased survival. The specific contribution of LVM atrophy to these outcomes requires further study.

Undiagnosed cardiac deficits in non-small cell carcinoma patients in the candidate population for anti-cachexia clinical trials.

PURPOSE: Currently, there is no approved therapy for cancer cachexia. According to European and American regulatory agencies, physical function improvements would be approvable co-primary endpoints of new anti-cachexia medications. As physical functioning is in part dependent on cardiac functioning, we aimed to explore the cardiac status of a group of patients meeting current criteria for inclusion in cachexia clinical trials. METHODS: Seventy treatment-naive patients with metastatic NSCLC [36 (51.4%) male; 96% ECOG 0-1; eligible for carboplatin-based therapy and meeting eligibility criteria for cachexia clinical trials] were recruited before the start of first-line carboplatin-based chemotherapy. Patients were evaluated by echocardiography, electrocardiography, and scales for fatigue and dyspnea. Computed tomography cross-sectional images were utilized for body composition analysis. RESULTS: In 9/70 patients (12.8%), echocardiography allowed discovery of clinically relevant cardiac disorders [seven patients with left ventricular ejection fraction (LVEF) 32%-47%; one patient with severe right ventricular dilation and severe pulmonary hypertension and one patient with severe pericardial effusion warranted hospitalization and drainage]. Another 10/70 (14.3%) patients had diastolic dysfunction with preserved LVEF. The cardiac conditions were associated with aggravated fatigue (p < 0.05), dyspnea (p < 0.05), and anemia (p = 0.06). Five out of seven patients with LVEF < 50% were sarcopenic and one was borderline sarcopenic. CONCLUSION: Baseline cardiac status of the metastatic NSCLC patients adds potential heterogeneity for anti-cachexia clinical trials. Detailed cardiac screening data might be useful for inclusion/exclusion criteria, randomization, and post hoc analysis.

Weight loss versus muscle loss: re-evaluating inclusion criteria for future cancer cachexia interventional trials.

PURPOSE: Participation in cancer cachexia clinical trials requires a defined weight loss (WL) over time. A loss in skeletal muscle mass, measured by cross-sectional computed tomography (CT) image analysis, represents a possible alternative. Our aim was to compare WL versus muscle loss in patients who were screened to participate in a cancer cachexia clinical trial. METHODS: This was a single-center, retrospective analysis in metastatic colorectal cancer patients screened for an interventional cancer cachexia trial requiring a ≥5 % WL over the preceding 6 months. Concurrent CT images obtained as part of standard oncology care were analyzed for changes in total muscle and fat (visceral, subcutaneous, and total). RESULTS: Of patients screened (n = 36), 3 (8 %) enrolled in the trial, 17 (47 %) were excluded due to insufficient WL (<5 %), 3 (8 %) were excluded due to excessive WL (>20 %), and 16 (44 %) met inclusion criteria for WL. Patients who met screening criteria for WL (5-20 %) had a mean ± SD of 7.7 ± 8.7 % muscle loss, 24.4 ± 37.5 % visceral adipose loss, 21.6 ± 22.3 % subcutaneous adipose loss, and 22.1 ± 24.7 % total adipose loss. Patients excluded due to insufficient WL had 2 ± 6.4 % muscle loss, but a gain of 8.5 ± 39.8 % visceral adipose, and 4.2 ± 28.2 % subcutaneous adipose loss and 0.8 ± 28.4 % total adipose loss. Of the patients excluded due to WL <5 % (n = 17), 7 (41 %) had a skeletal muscle loss >5 %. CONCLUSIONS: Defining cancer cachexia by WL over time may be limited as it does not capture skeletal muscle loss. Cross-sectional CT body composition analysis may improve early detection of muscle loss and patient participation in future cancer cachexia clinical trials.