Nuclear magnetic
resonance (NMR) metabolomics was used for identification of metabolic changes in pancreatic cancer (PC) blood
plasma samples when compared to healthy controls or diabetes mellitus
patients. An increased number of PC samples enabled a subdivision
of the group according to individual PC stages and the construction
of predictive models for finer classification of at-risk individuals
recruited from patients with recently diagnosed diabetes mellitus.
High-performance values of orthogonal partial least squares (OPLS)
discriminant analysis were found for discrimination between individual
PC stages and both control groups. The discrimination between early
and metastatic stages was achieved with only 71.5% accuracy. A predictive
model based on discriminant analyses between individual PC stages
and the diabetes mellitus group identified 12 individuals out of 59
as at-risk of development of pathological changes in the pancreas,
and four of them were classified as at moderate risk.