Background: Despite the robust data available on inflammatory indices (neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), and systemic immune-inflammation index (SII)) and clinical outcome in oncological patients, their utility as a predictor of cancer incidence in the general population has not been reported in literature. Methods: The Bagnacavallo study was performed between October 2005 and March 2009. All citizens of Bagnacavallo (Ravenna, Emilia-Romagna, Italy) aged 30-60 years as of January 2005 were eligible and were invited by written letter to participate to the study. All participants underwent a detailed clinical history and physical examination following the model of the Dionysos Study. All blood values included in the analysis were obtained the day of physical examination. Cancer incidence data were obtained from the population-based Romagna Cancer Registry, which operates according to standard methods. The aim of this analysis was to examine the association between metabolic syndrome and baseline SII, NLR, and PLR levels, and the diagnosis of an invasive cancer in the Bagnacavallo study cohort. Results: At univariate analysis, metabolic syndrome was not associated with an increase of cancer incidence (HR 1.30; p = 0.155). High glucose (HR 1.49; p = 0.0.16),NLRHR 1.54, p = 0.002), PLR (HR 1.58, p = 0.001), and SII (HR 1.47, p = 0.006) were associated with an increase of cancer incidence. After adjusting for clinical covariates (smoking, physical activity, education, age, and gender) SII, PLR, and NLR remained independent prognostic factors for the prediction of cancer incidence. Conclusions: Inflammatory indices are promising, easy to perform, and inexpensive tools for identifying patients with higher risk of cancer in cancer-free population.
CITATION STYLE
Rimini, M., Casadei-Gardini, A., Ravaioli, A., Rovesti, G., Conti, F., Borghi, A., … Stefanini, G. F. (2020). Could inflammatory indices and metabolic syndrome predict the risk of cancer development? Analysis from the bagnacavallo population study. Journal of Clinical Medicine, 9(4). https://doi.org/10.3390/jcm9041177
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