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Temporal Trends in Body Composition and Metabolic Markers Prior to Diagnosis of Pancreatic Ductal Adenocarcinoma.
Clinical Gastroenterology and Hepatology 2024 May 3
BACKGROUND AND AIMS: Changes in body composition and metabolic factors may serve as biomarkers for the early detection of pancreatic ductal adenocarcinoma (PDAC). The aim of this study was to capture the longitudinal changes in body composition and metabolic factors prior to diagnosis of PDAC.
METHODS: We performed a retrospective cohort study in which all patients (≥18 years) diagnosed with PDAC from 2002 to 2021 were identified. We collected all abdominal CT scans and 10 different blood-based biomarkers up to 36 months prior to diagnosis. We applied a fully automated abdominal segmentation algorithm previously developed by our group for three-dimensional quantification of body composition on CT scans. Longitudinal trends of body composition and blood-based biomarkers prior to PDAC diagnosis were estimated using linear mixed models, compared across different time windows, and visualized using spline regression.
RESULTS: We included 1,690 patients in body composition analysis, of whom 516 (30.5%) had ≥ 2 prediagnostic CT scans. For analysis of longitudinal trends of blood-based biomarkers, 3,332 individuals were included. As an early manifestation of PDAC, we observed a significant decrease in visceral and subcutaneous adipose tissue (β =-1.94 (95% CI, -2.39, -1.48) and β = -2.59 (95% CI, -3.17, -2.02 in area (cm2 )/height (m2 ) per 6 months closer to diagnosis, accompanied by a decrease in serum lipids (e.g., LDL; β = -2.83; 95% CI, -3.31, -2.34, total cholesterol; β = -2.69; 95% CI, -3.18, -2.20, and triglycerides; β = -1.86; 95% CI, -2.61, -1.11), and an increase in blood glucose levels. Loss of muscle tissue and bone volume was predominantly observed in the last 6 months prior to diagnosis.
CONCLUSION: This study identified significant alterations in a variety of soft tissue and metabolic markers that occur in the development of PDAC. Early recognition of these metabolic changes may provide an opportunity for early detection.
METHODS: We performed a retrospective cohort study in which all patients (≥18 years) diagnosed with PDAC from 2002 to 2021 were identified. We collected all abdominal CT scans and 10 different blood-based biomarkers up to 36 months prior to diagnosis. We applied a fully automated abdominal segmentation algorithm previously developed by our group for three-dimensional quantification of body composition on CT scans. Longitudinal trends of body composition and blood-based biomarkers prior to PDAC diagnosis were estimated using linear mixed models, compared across different time windows, and visualized using spline regression.
RESULTS: We included 1,690 patients in body composition analysis, of whom 516 (30.5%) had ≥ 2 prediagnostic CT scans. For analysis of longitudinal trends of blood-based biomarkers, 3,332 individuals were included. As an early manifestation of PDAC, we observed a significant decrease in visceral and subcutaneous adipose tissue (β =-1.94 (95% CI, -2.39, -1.48) and β = -2.59 (95% CI, -3.17, -2.02 in area (cm2 )/height (m2 ) per 6 months closer to diagnosis, accompanied by a decrease in serum lipids (e.g., LDL; β = -2.83; 95% CI, -3.31, -2.34, total cholesterol; β = -2.69; 95% CI, -3.18, -2.20, and triglycerides; β = -1.86; 95% CI, -2.61, -1.11), and an increase in blood glucose levels. Loss of muscle tissue and bone volume was predominantly observed in the last 6 months prior to diagnosis.
CONCLUSION: This study identified significant alterations in a variety of soft tissue and metabolic markers that occur in the development of PDAC. Early recognition of these metabolic changes may provide an opportunity for early detection.
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