Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.] · 2026
Longitudinal body composition changes distinguish pancreatic ductal adenocarcinoma from controls in a pre-diagnostic CT cohort.
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Bogdanski Aleksander M, Klatte Derk C F, van Hooft Jeanin E, Patel Shrinath, van Leerdam Monique E, Ngufor Che G, Kuanar Shiba P, Weston Alex D, Wallace Michael B, Bi Yan
Аннотация
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is often diagnosed at an advanced stage, limiting curative treatment options. Although prior studies have characterized longitudinal body composition changes in PDAC, it remains unclear whether these pre-diagnostic trajectories differ from matched controls or distinguish PDAC cases from non-PDAC individuals.
METHODS: In this retrospective, multicenter case-control study, adults diagnosed with PDAC between 2002 and 2020 with abdominal CT imaging within 36 months before diagnosis were identified. Controls were selected from CT-imaged individuals and matched 2:1 to cases on age, sex, and diabetes status. Deep learning-based segmentation quantified skeletal muscle index (SMI), visceral fat index (VFI), and subcutaneous fat index (SFI). Cohort-level trajectories were evaluated using locally estimated scatterplot smoothing and linear mixed-effects models. For individual-level analyses, body composition rates of change were estimated and evaluated for discrimination.
RESULTS: Cohort-level analyses included 1825 cases and 3650 controls. Compared with controls, PDAC cases exhibited steeper declines in SFI (-0.53 cm2/m2/month, p < 0.001) and VFI (-0.37 cm2/m2/month, p < 0.001) over 36 months preceding diagnosis, whereas SMI differences emerged within the final 12 months (-0.28 cm2/m2/month, p = 0.01). Individual-level analyses (581 cases, 581 controls) showed longitudinal changes in SMI, SFI, and VFI moderately discriminated cases from controls (AUC 0.76; 95% CI, 0.73-0.78), with performance driven largely by changes occurring closer to diagnosis.
CONCLUSIONS: In a CT-imaged cohort, PDAC is associated with measurable longitudinal body composition changes prior to diagnosis that differ from matched controls. These changes demonstrate moderate discrimination to distinguish cases from controls but appear to reflect processes occurring closer to clinical diagnosis.
METHODS: In this retrospective, multicenter case-control study, adults diagnosed with PDAC between 2002 and 2020 with abdominal CT imaging within 36 months before diagnosis were identified. Controls were selected from CT-imaged individuals and matched 2:1 to cases on age, sex, and diabetes status. Deep learning-based segmentation quantified skeletal muscle index (SMI), visceral fat index (VFI), and subcutaneous fat index (SFI). Cohort-level trajectories were evaluated using locally estimated scatterplot smoothing and linear mixed-effects models. For individual-level analyses, body composition rates of change were estimated and evaluated for discrimination.
RESULTS: Cohort-level analyses included 1825 cases and 3650 controls. Compared with controls, PDAC cases exhibited steeper declines in SFI (-0.53 cm2/m2/month, p < 0.001) and VFI (-0.37 cm2/m2/month, p < 0.001) over 36 months preceding diagnosis, whereas SMI differences emerged within the final 12 months (-0.28 cm2/m2/month, p = 0.01). Individual-level analyses (581 cases, 581 controls) showed longitudinal changes in SMI, SFI, and VFI moderately discriminated cases from controls (AUC 0.76; 95% CI, 0.73-0.78), with performance driven largely by changes occurring closer to diagnosis.
CONCLUSIONS: In a CT-imaged cohort, PDAC is associated with measurable longitudinal body composition changes prior to diagnosis that differ from matched controls. These changes demonstrate moderate discrimination to distinguish cases from controls but appear to reflect processes occurring closer to clinical diagnosis.