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Introduction: Specific body composition markers derived from L3 axial computed tomography (CT) images predict clinical cancer outcomes, including chemotherapy toxicity and survival. However, this method is only applicable to those undergoing lumbar (L3) CT scanning, which is not universally conducted in early breast cancer cases. This study aimed to evaluate CT analysis at T4 as a feasible alternative marker of body composition in breast cancer. Method: All patients participated in the Investigating Outcomes from Breast Cancer: Correlating Genetic, Immunological, and Nutritional (BeGIN) Predictors observational cohort study (REC reference number: 14/EE/1297). Staging chest-abdomen-pelvic CT scan images from 24 women diagnosed with early breast cancer at University Hospital Southampton were analysed. Adipose tissue, skeletal muscle, and muscle attenuation were measured from the transverse CT slices' cross-sectional area (CSA) at T4 and L3. Adipose tissue and skeletal muscle area measurements were adjusted for height. Spearman's rank correlation coefficient analysis was used to determine concordance between body composition measurements using CT analysis at L3 and T4 regions. Results: Derived estimates for total adipose tissue, subcutaneous adipose tissue, and intramuscular adipose tissue mass following adjustment for height were highly concordant when determined from CSAs of CT slices at T4 and L3 (Rs = 0.821, p < 0.001; Rs = 0.816, p < 0.001; and Rs = 0.830, p < 0.001). In this cohort, visceral adipose tissue (VAT) and skeletal muscle estimates following height adjustment were less concordant when measured by CT at T4 and L3 (Rs = 0.477, p = 0.039 and Rs = 0.578, p = 0.003). The assessment of muscle attenuation was also highly concordant when measured by CT at T4 and L3 (Rs = 0.840, p < 0.001). Discussion: These results suggest that the CT analysis at T4 and L3 provides highly concordant markers for total adipose, subcutaneous adipose, and intramuscular adipose estimation, but not VAT, in this breast cancer population. High concordance between T4 and L3 was also found when assessing skeletal muscle attenuation. Lower concordance was observed for the estimates of skeletal muscle area, potentially explained by differences in the quantity and proportions of axial and appendicular muscle between the thorax and abdomen. Future studies will determine the value of T4 metrics as predictive tools for clinical outcomes in breast cancer.
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BACKGROUND: Cancer is a leading cause of disease burden globally, with more than 19·3 million cases and 10 million deaths recorded in 2020. Research is crucial to understanding the determinants of cancer and the effects of interventions, and to improving outcomes. We aimed to analyse global patterns of public and philanthropic investment in cancer research. METHODS: In this content analysis, we searched the UberResearch Dimensions database and Cancer Research UK data for human cancer research funding awards from public and philanthropic funders between Jan 1, 2016, and Dec 31, 2020. Included award types were project and programme grants, fellowships, pump priming, and pilot projects. Awards focused on operational delivery of cancer care were excluded. Awards were categorised by cancer type, cross-cutting research theme, and research phase. Funding amount was compared with global burden of specific cancers, measured by disability-adjusted life-years, years lived with disability, and mortality using data from the Global Burden of Disease study. FINDINGS: We identified 66â388 awards with total investment of about US$24·5 billion in 2016-20. Investment decreased year-on-year, with the largest drop observed between 2019 and 2020. Pre-clinical research received 73·5% of the funding across the 5 years ($18 billion), phase 1-4 clinical trials received 7·4% ($1·8 billion), public health research received 9·4% ($2·3 billion), and cross-disciplinary research received 5·0% ($1·2 billion). General cancer research received the largest investment ($7·1 billion, 29·2% of the total funding). The most highly funded cancer types were breast cancer ($2·7 billion [11·2%]), haematological cancer ($2·3 billion [9·4%]), and brain cancer ($1·3 billion [5·5%]). Analysis by cross-cutting theme revealed that 41·2% of investment ($9·6 billion) went to cancer biology research, 19·6% ($4·6 billion) to drug treatment research, and 12·1% ($2·8 billion) to immuno-oncology. 1·4% of the total funding ($0·3 billion) was spent on surgery research, 2·8% ($0·7 billion) was spent on radiotherapy research, and 0·5% ($0·1 billion) was spent on global health studies. INTERPRETATION: Cancer research funding must be aligned with the global burden of cancer with more equitable funding for cancer research in low-income and middle-income countries (which account for 80% of cancer burden), both to support research relevant to these settings, and build research capacity within these countries. There is an urgent need to prioritise investment in surgery and radiotherapy research given their primacy in the treatment of many solid tumours. FUNDING: None.