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Published on: January 3, 2013
Inflammation-Based Hematological Indices (NLR, PLR, LMR) in Pancreatic Cancer: Implications for Laboratory
Iwona Zawistowska1, Blanka Wolszczak-Biedrzycka2, Tomasz Kukliński3
1Medical Laboratory Diagnostic, Polish Red Cross Memorial Municipal Hospital, Henryka Sienkiewicza 79 St., 15-003 Bialystok, Poland.
Abstract:
Objectives: Pancreatic cancer remains one of the most aggressive malignancies, characterized by late diagnosis, limited therapeutic options, and poor survival outcomes. Increasing evidence indicates that systemic inflammation and tumor microenvironment interactions play a crucial role in disease progression and patient prognosis. This review aims to summarize current evidence on the clinical utility of inflammation-based hematological indices derived from complete blood count (CBC), including the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR), in pancreatic cancer. Content: Available data consistently demonstrate that elevated NLR and PLR, as well as decreased LMR, are associated with poorer overall survival, more aggressive disease phenotype, and reduced response to therapy. Among these indices, NLR appears to be the most robust and widely validated prognostic marker. Its clinical value is enhanced when combined with markers such as CA 19-9. LMR reflects the balance between host immune response and monocyte-derived tumor-promoting activity, while PLR highlights the role of platelets in tumor progression, angiogenesis, and immune evasion. Despite their potential, the routine clinical implementation of these indices is limited by the lack of standardized cut-off values, variability between patient populations, and susceptibility to confounding factors such as inflammatory conditions. Summary and outlook: In this article we show that inflammation-based hematological indices represent inexpensive, accessible, and promising tools for laboratory diagnostics and prognostic assessment in pancreatic cancer. Their integration with clinical, biochemical, and molecular data may improve risk stratification and support personalized therapeutic strategies; however, further large-scale prospective studies are required to establish their standardized clinical use.