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Updated: Sep 5, 2025

Assessment of the Metabolic Profile of Primary Leukemia Cells
Published on: November 21, 2018
Assessment of peripheral blood cells parameters as a valuable tool in patients with neuroendocrine neoplasms
Ioana Maria Lambrescu1, Ioana Maria Lambrescu2, Sorina Martin3
1Cell Biology, Neurosciences and Experimental Myology Laboratory, Victor Babes Institute of Pathology, 050096 Bucharest, Romania.
Objectives:
Neuroendocrine neoplasms (NENs) are an extremely heterogeneous medical entity, representing a diagnostic and therapeutic challenge. Chronic inflammation, as is the case with other malignancies, plays a crucial role in NEN carcinogenesis.
Design:
The complete blood count (CBC) is a reliable tool for monitoring patients with cancer. Quantifying the absolute count of neutrophils (N), lymphocytes (L), platelets (P), and the ratios that derive from these parameters (neutrophil-to-lymphocyte ratio - NLR, platelet-to-lymphocyte ratio - PLR, and inflammatory systemic index - SII calculated as N×P/L) proved their prognostic and predictive value in numerous malignancies.
Materials And Methods:
We aimed to investigate the utility of these hematological parameters in 31 patients with NENs of various locations. Our study included the comparative analysis of pre-treatment hematological markers in NEN patients versus 21 age and gender matched healthy individuals. Additionally, for 26 out of the 31 patients included we analyzed and compared the inflammatory markers before and after treatment initiation.
Results:
The results revealed a statistically significant higher median value of N, NLR, PLR and SII in the NENs group in comparison with the values obtained in the control group and higher values of N, NLR and SII in the pretreatment group. Furthermore, we observed a higher mean value of the post-treatment P in the pancreatic NENs as opposed to the values obtained for other tumor locations.
Conclusions:
The current study emphasizes the importance of the evaluation of CBC in the NENs setting thus adding value to prognostic models that can be useful for risk stratification and medical decision-making.
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