Could Inflammatory Indices and Metabolic Syndrome Predict the Risk of Cancer Development? Analysis from the Bagnacavallo Population Study

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 popul...
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Autor*in:	Margherita Rimini [verfasserIn] Andrea Casadei-Gardini [verfasserIn] Alessandra Ravaioli [verfasserIn] Giulia Rovesti [verfasserIn] Fabio Conti [verfasserIn] Alberto Borghi [verfasserIn] Anna Chiara Dall’Aglio [verfasserIn] Giorgio Bedogni [verfasserIn] Marco Domenicali [verfasserIn] Pierluigi Giacomoni [verfasserIn] Claudio Tiribelli [verfasserIn] Lauro Bucchi [verfasserIn] Fabio Falcini [verfasserIn] Francesco Giuseppe Foschi [verfasserIn] Bagnacavallo Study Group [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Inflammatory indices NLR SII PLR cancer incidence breast cancer

Übergeordnetes Werk:	In: Journal of Clinical Medicine - MDPI AG, 2013, 9(2020), 4, p 1177
Übergeordnetes Werk:	volume:9 ; year:2020 ; number:4, p 1177

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/jcm9041177

Katalog-ID:	DOAJ010262970

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245	1	0	\|a Could Inflammatory Indices and Metabolic Syndrome Predict the Risk of Cancer Development? Analysis from the Bagnacavallo Population Study
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520			\|a 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; <i<p</i< = 0.155). High glucose (HR 1.49; <i<p</i< = 0.0.16), NLR HR 1.54, <i<p</i< = 0.002), PLR (HR 1.58, <i<p</i< = 0.001), and SII (HR 1.47, <i<p</i< = 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.
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allfields	10.3390/jcm9041177 doi (DE-627)DOAJ010262970 (DE-599)DOAJa1725b3061264a06bb1354e67c936f04 DE-627 ger DE-627 rakwb eng Margherita Rimini verfasserin aut Could Inflammatory Indices and Metabolic Syndrome Predict the Risk of Cancer Development? Analysis from the Bagnacavallo Population Study 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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; <i<p</i< = 0.155). High glucose (HR 1.49; <i<p</i< = 0.0.16), NLR HR 1.54, <i<p</i< = 0.002), PLR (HR 1.58, <i<p</i< = 0.001), and SII (HR 1.47, <i<p</i< = 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. Inflammatory indices NLR SII PLR cancer incidence breast cancer Medicine R Andrea Casadei-Gardini verfasserin aut Alessandra Ravaioli verfasserin aut Giulia Rovesti verfasserin aut Fabio Conti verfasserin aut Alberto Borghi verfasserin aut Anna Chiara Dall’Aglio verfasserin aut Giorgio Bedogni verfasserin aut Marco Domenicali verfasserin aut Pierluigi Giacomoni verfasserin aut Claudio Tiribelli verfasserin aut Lauro Bucchi verfasserin aut Fabio Falcini verfasserin aut Francesco Giuseppe Foschi verfasserin aut Bagnacavallo Study Group verfasserin aut In Journal of Clinical Medicine MDPI AG, 2013 9(2020), 4, p 1177 (DE-627)718632478 (DE-600)2662592-1 20770383 nnns volume:9 year:2020 number:4, p 1177 https://doi.org/10.3390/jcm9041177 kostenfrei https://doaj.org/article/a1725b3061264a06bb1354e67c936f04 kostenfrei https://www.mdpi.com/2077-0383/9/4/1177 kostenfrei https://doaj.org/toc/2077-0383 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2020 4, p 1177
spelling	10.3390/jcm9041177 doi (DE-627)DOAJ010262970 (DE-599)DOAJa1725b3061264a06bb1354e67c936f04 DE-627 ger DE-627 rakwb eng Margherita Rimini verfasserin aut Could Inflammatory Indices and Metabolic Syndrome Predict the Risk of Cancer Development? Analysis from the Bagnacavallo Population Study 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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; <i<p</i< = 0.155). High glucose (HR 1.49; <i<p</i< = 0.0.16), NLR HR 1.54, <i<p</i< = 0.002), PLR (HR 1.58, <i<p</i< = 0.001), and SII (HR 1.47, <i<p</i< = 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. Inflammatory indices NLR SII PLR cancer incidence breast cancer Medicine R Andrea Casadei-Gardini verfasserin aut Alessandra Ravaioli verfasserin aut Giulia Rovesti verfasserin aut Fabio Conti verfasserin aut Alberto Borghi verfasserin aut Anna Chiara Dall’Aglio verfasserin aut Giorgio Bedogni verfasserin aut Marco Domenicali verfasserin aut Pierluigi Giacomoni verfasserin aut Claudio Tiribelli verfasserin aut Lauro Bucchi verfasserin aut Fabio Falcini verfasserin aut Francesco Giuseppe Foschi verfasserin aut Bagnacavallo Study Group verfasserin aut In Journal of Clinical Medicine MDPI AG, 2013 9(2020), 4, p 1177 (DE-627)718632478 (DE-600)2662592-1 20770383 nnns volume:9 year:2020 number:4, p 1177 https://doi.org/10.3390/jcm9041177 kostenfrei https://doaj.org/article/a1725b3061264a06bb1354e67c936f04 kostenfrei https://www.mdpi.com/2077-0383/9/4/1177 kostenfrei https://doaj.org/toc/2077-0383 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2020 4, p 1177
allfields_unstemmed	10.3390/jcm9041177 doi (DE-627)DOAJ010262970 (DE-599)DOAJa1725b3061264a06bb1354e67c936f04 DE-627 ger DE-627 rakwb eng Margherita Rimini verfasserin aut Could Inflammatory Indices and Metabolic Syndrome Predict the Risk of Cancer Development? Analysis from the Bagnacavallo Population Study 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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; <i<p</i< = 0.155). High glucose (HR 1.49; <i<p</i< = 0.0.16), NLR HR 1.54, <i<p</i< = 0.002), PLR (HR 1.58, <i<p</i< = 0.001), and SII (HR 1.47, <i<p</i< = 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. Inflammatory indices NLR SII PLR cancer incidence breast cancer Medicine R Andrea Casadei-Gardini verfasserin aut Alessandra Ravaioli verfasserin aut Giulia Rovesti verfasserin aut Fabio Conti verfasserin aut Alberto Borghi verfasserin aut Anna Chiara Dall’Aglio verfasserin aut Giorgio Bedogni verfasserin aut Marco Domenicali verfasserin aut Pierluigi Giacomoni verfasserin aut Claudio Tiribelli verfasserin aut Lauro Bucchi verfasserin aut Fabio Falcini verfasserin aut Francesco Giuseppe Foschi verfasserin aut Bagnacavallo Study Group verfasserin aut In Journal of Clinical Medicine MDPI AG, 2013 9(2020), 4, p 1177 (DE-627)718632478 (DE-600)2662592-1 20770383 nnns volume:9 year:2020 number:4, p 1177 https://doi.org/10.3390/jcm9041177 kostenfrei https://doaj.org/article/a1725b3061264a06bb1354e67c936f04 kostenfrei https://www.mdpi.com/2077-0383/9/4/1177 kostenfrei https://doaj.org/toc/2077-0383 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2020 4, p 1177
allfieldsGer	10.3390/jcm9041177 doi (DE-627)DOAJ010262970 (DE-599)DOAJa1725b3061264a06bb1354e67c936f04 DE-627 ger DE-627 rakwb eng Margherita Rimini verfasserin aut Could Inflammatory Indices and Metabolic Syndrome Predict the Risk of Cancer Development? Analysis from the Bagnacavallo Population Study 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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; <i<p</i< = 0.155). High glucose (HR 1.49; <i<p</i< = 0.0.16), NLR HR 1.54, <i<p</i< = 0.002), PLR (HR 1.58, <i<p</i< = 0.001), and SII (HR 1.47, <i<p</i< = 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. Inflammatory indices NLR SII PLR cancer incidence breast cancer Medicine R Andrea Casadei-Gardini verfasserin aut Alessandra Ravaioli verfasserin aut Giulia Rovesti verfasserin aut Fabio Conti verfasserin aut Alberto Borghi verfasserin aut Anna Chiara Dall’Aglio verfasserin aut Giorgio Bedogni verfasserin aut Marco Domenicali verfasserin aut Pierluigi Giacomoni verfasserin aut Claudio Tiribelli verfasserin aut Lauro Bucchi verfasserin aut Fabio Falcini verfasserin aut Francesco Giuseppe Foschi verfasserin aut Bagnacavallo Study Group verfasserin aut In Journal of Clinical Medicine MDPI AG, 2013 9(2020), 4, p 1177 (DE-627)718632478 (DE-600)2662592-1 20770383 nnns volume:9 year:2020 number:4, p 1177 https://doi.org/10.3390/jcm9041177 kostenfrei https://doaj.org/article/a1725b3061264a06bb1354e67c936f04 kostenfrei https://www.mdpi.com/2077-0383/9/4/1177 kostenfrei https://doaj.org/toc/2077-0383 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2020 4, p 1177
allfieldsSound	10.3390/jcm9041177 doi (DE-627)DOAJ010262970 (DE-599)DOAJa1725b3061264a06bb1354e67c936f04 DE-627 ger DE-627 rakwb eng Margherita Rimini verfasserin aut Could Inflammatory Indices and Metabolic Syndrome Predict the Risk of Cancer Development? Analysis from the Bagnacavallo Population Study 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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; <i<p</i< = 0.155). High glucose (HR 1.49; <i<p</i< = 0.0.16), NLR HR 1.54, <i<p</i< = 0.002), PLR (HR 1.58, <i<p</i< = 0.001), and SII (HR 1.47, <i<p</i< = 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. Inflammatory indices NLR SII PLR cancer incidence breast cancer Medicine R Andrea Casadei-Gardini verfasserin aut Alessandra Ravaioli verfasserin aut Giulia Rovesti verfasserin aut Fabio Conti verfasserin aut Alberto Borghi verfasserin aut Anna Chiara Dall’Aglio verfasserin aut Giorgio Bedogni verfasserin aut Marco Domenicali verfasserin aut Pierluigi Giacomoni verfasserin aut Claudio Tiribelli verfasserin aut Lauro Bucchi verfasserin aut Fabio Falcini verfasserin aut Francesco Giuseppe Foschi verfasserin aut Bagnacavallo Study Group verfasserin aut In Journal of Clinical Medicine MDPI AG, 2013 9(2020), 4, p 1177 (DE-627)718632478 (DE-600)2662592-1 20770383 nnns volume:9 year:2020 number:4, p 1177 https://doi.org/10.3390/jcm9041177 kostenfrei https://doaj.org/article/a1725b3061264a06bb1354e67c936f04 kostenfrei https://www.mdpi.com/2077-0383/9/4/1177 kostenfrei https://doaj.org/toc/2077-0383 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2020 4, p 1177
language	English
source	In Journal of Clinical Medicine 9(2020), 4, p 1177 volume:9 year:2020 number:4, p 1177
sourceStr	In Journal of Clinical Medicine 9(2020), 4, p 1177 volume:9 year:2020 number:4, p 1177
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Inflammatory indices NLR SII PLR cancer incidence breast cancer Medicine R
isfreeaccess_bool	true
container_title	Journal of Clinical Medicine
authorswithroles_txt_mv	Margherita Rimini @@aut@@ Andrea Casadei-Gardini @@aut@@ Alessandra Ravaioli @@aut@@ Giulia Rovesti @@aut@@ Fabio Conti @@aut@@ Alberto Borghi @@aut@@ Anna Chiara Dall’Aglio @@aut@@ Giorgio Bedogni @@aut@@ Marco Domenicali @@aut@@ Pierluigi Giacomoni @@aut@@ Claudio Tiribelli @@aut@@ Lauro Bucchi @@aut@@ Fabio Falcini @@aut@@ Francesco Giuseppe Foschi @@aut@@ Bagnacavallo Study Group @@aut@@
publishDateDaySort_date	2020-01-01T00:00:00Z
hierarchy_top_id	718632478
id	DOAJ010262970
language_de	englisch
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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; <i<p</i< = 0.155). High glucose (HR 1.49; <i<p</i< = 0.0.16), NLR HR 1.54, <i<p</i< = 0.002), PLR (HR 1.58, <i<p</i< = 0.001), and SII (HR 1.47, <i<p</i< = 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. 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author	Margherita Rimini
spellingShingle	Margherita Rimini misc Inflammatory indices misc NLR misc SII misc PLR misc cancer incidence misc breast cancer misc Medicine misc R Could Inflammatory Indices and Metabolic Syndrome Predict the Risk of Cancer Development? Analysis from the Bagnacavallo Population Study
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topic_title	Could Inflammatory Indices and Metabolic Syndrome Predict the Risk of Cancer Development? Analysis from the Bagnacavallo Population Study Inflammatory indices NLR SII PLR cancer incidence breast cancer
topic	misc Inflammatory indices misc NLR misc SII misc PLR misc cancer incidence misc breast cancer misc Medicine misc R
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title	Could Inflammatory Indices and Metabolic Syndrome Predict the Risk of Cancer Development? Analysis from the Bagnacavallo Population Study
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title_full	Could Inflammatory Indices and Metabolic Syndrome Predict the Risk of Cancer Development? Analysis from the Bagnacavallo Population Study
author_sort	Margherita Rimini
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author_browse	Margherita Rimini Andrea Casadei-Gardini Alessandra Ravaioli Giulia Rovesti Fabio Conti Alberto Borghi Anna Chiara Dall’Aglio Giorgio Bedogni Marco Domenicali Pierluigi Giacomoni Claudio Tiribelli Lauro Bucchi Fabio Falcini Francesco Giuseppe Foschi Bagnacavallo Study Group
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author-letter	Margherita Rimini
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title_sort	could inflammatory indices and metabolic syndrome predict the risk of cancer development? analysis from the bagnacavallo population study
title_auth	Could Inflammatory Indices and Metabolic Syndrome Predict the Risk of Cancer Development? Analysis from the Bagnacavallo Population Study
abstract	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; <i<p</i< = 0.155). High glucose (HR 1.49; <i<p</i< = 0.0.16), NLR HR 1.54, <i<p</i< = 0.002), PLR (HR 1.58, <i<p</i< = 0.001), and SII (HR 1.47, <i<p</i< = 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.
abstractGer	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; <i<p</i< = 0.155). High glucose (HR 1.49; <i<p</i< = 0.0.16), NLR HR 1.54, <i<p</i< = 0.002), PLR (HR 1.58, <i<p</i< = 0.001), and SII (HR 1.47, <i<p</i< = 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.
abstract_unstemmed	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; <i<p</i< = 0.155). High glucose (HR 1.49; <i<p</i< = 0.0.16), NLR HR 1.54, <i<p</i< = 0.002), PLR (HR 1.58, <i<p</i< = 0.001), and SII (HR 1.47, <i<p</i< = 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.
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title_short	Could Inflammatory Indices and Metabolic Syndrome Predict the Risk of Cancer Development? Analysis from the Bagnacavallo Population Study
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