Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Jan 20;25(1):227.
doi: 10.1186/s12889-025-21423-1.

Association between systemic immune-inflammation index and the risk of all-cause, cancer and non-cancer mortality in the general population: results from national health and nutrition examination survey 2005-2018

Siyu Wu  1   2 , Zhao Liu  1 , Xing Li  1 , Shan Gao  1 , Peng Xia  3
Affiliations

Association between systemic immune-inflammation index and the risk of all-cause, cancer and non-cancer mortality in the general population: results from national health and nutrition examination survey 2005-2018

Siyu Wu et al. BMC Public Health. .

Abstract

Background: Inflammation plays an important role in the progression of cancer and other diseases, such as diabetes and cardiovascular and cerebrovascular diseases. The systemic immune-inflammation index (SII) was recognized as an objective biomarker reflecting immunoinflammatory status. This study aimed to identify the association between SII with all-cause, cancer and non-cancer mortality among general population in the United States.

Methods: 25,955 participants (≥ 20 years) were included from 2005 to 2018 National Health and Nutrition Examination Survey (NHANES) and were divided into four groups according to the SII quartiles. Weighted multivariate Cox regression was used to assess the correlation between SII and mortality. Subgroup analyses were conducted to identify the effects of other covariates on the relationship between SII and mortality. A restricted cubic spline (RCS) model was subsequently used to explore the dose-response relationship between SII and mortality. Survival analysis was assessed using Kaplan-Meier method.

Results: In fully adjusted model, the adjusted hazard ratio (aHR) and 95% confidence intervals (CIs) of individuals in Q4 were 1.24 (1.09, 1.41) for all-cause mortality and 1.41 (1.23, 1.63) for non-cancer mortality compared with Q1. Besides, the aHR and 95% CIs in Q2 of SII were 0.70 (0.50, 0.99) and in Q3 were 0.68 (0.52, 0.87) compared with Q1 for cancer mortality. In RCS analysis, non-linear relationships of J-shaped curves were observed in the association between SII with all-cause and non-cancer mortality. Additionally, a U-shaped curve was identified between SII and cancer mortality with a threshold value of 445.22.

Conclusion: Our findings imply that SII can serve as a potential prognosis indicator among general population. Elevated SII is associated with higher all-cause and non-cancer mortality. Furthermore, both the lowest and highest quartiles of the SII exhibit a correlation with heightened cancer mortality.

Keywords: Mortality; NHANES; Non-linear relationship; Prospective cohort study; Systemic immune-inflammation index.

PubMed Disclaimer

Conflict of interest statement

Declarations. Ethics approval and consent to participate: The research was carried out following the Declaration of Helsinki and received approval from the NCHS Ethics Review Board. The NCHS IRB/ERB Protocol Number or Description of NHANES 2005–2006, NHANES 2007–2008, NHANES 2009–2010, NHANES 2011–2012, NHANES 2013–2014 and NHANES 2015–2016 were Protocol #2005-06, Continuation of Protocol #2005-06, Continuation of Protocol #2005-06, Protocol #2011-17, Continuation of Protocol #2011-17 and Continuation of Protocol #2011-17. Besides, the NCHS IRB/ERB Protocol Number or Description of NHANES 2017–2018 were Continuation of Protocol #2011-17 (Effective through October 26, 2017) and Protocol #2018-01 (Effective beginning October 26, 2017). The participants provided their written informed consent to participate in this study. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Flowchart of included participants
Fig. 2
Fig. 2
Associations of SII with all-cause, cancer and non-cancer mortality Model 1: Age was adjusted Model 2: Age, gender, race, education attainment, marital status, family poverty income ratio, body mass index, smoking status, alcohol drinking status were adjusted Model 3: Based on model 2, the status of hypertension, diabetes and dyslipidemia were further adjusted
Fig. 3
Fig. 3
Subgroup analysis of the association between SII with all-cause, cancer and non-cancer mortality. Each stratum was adjusted for age, gender, race, education attainment, marital status, family poverty income ratio, body mass index, smoking status, alcohol drinking status, hypertension, diabetes and dyslipidemia
Fig. 4
Fig. 4
Non-linear relationships between SII with all-cause, cancer and non-cancer mortality. (A) all-cause mortality, (B) cancer mortality, (C) non-cancer mortality HR, hazard ratio; CI confidence interval. HRs (solid lines) and 95% CIs (shaded areas) were adjusted for age, gender, race, education attainment, marital status, family poverty income ratio, body mass index, smoking status, alcohol drinking status, hypertension, diabetes and dyslipidemia. Vertical dotted lines suggested the minimal threshold for the beneficial association with estimated HR = 1
Fig. 5
Fig. 5
Kaplan-Meier analysis estimates all-cause, cancer and non-cancer mortality according to SII levels. (A) All-cause mortality according to Q1-Q4 of four SII levels. (B) Cancer mortality according to Q1-Q4 of four SII levels. (C) Non-cancer mortality according to Q1-Q4 of four SII levels. (D) Cancer mortality according to Q1 or Q4, and Q2 + Q3 of three SII levels
See this image and copyright information in PMC

References

    1. Bruni D, Angell HK, Galon J. The immune contexture and immunoscore in cancer prognosis and therapeutic efficacy. Nat Rev Cancer. 2020;20(11):662–80. - PubMed
    1. Ridker PM, MacFadyen JG, Thuren T, Everett BM, Libby P, Glynn RJ. Effect of interleukin-1β inhibition with canakinumab on incident lung cancer in patients with atherosclerosis: exploratory results from a randomised, double-blind, placebo-controlled trial. Lancet (London England). 2017;390(10105):1833–42. - PubMed
    1. Rohm TV, Meier DT, Olefsky JM, Donath MY. Inflammation in obesity, diabetes, and related disorders. Immunity. 2022;55(1):31–55. - PMC - PubMed
    1. Liberale L, Badimon L, Montecucco F, Lüscher TF, Libby P, Camici GG. Inflammation, aging, and Cardiovascular Disease: JACC Review topic of the Week. J Am Coll Cardiol. 2022;79(8):837–47. - PMC - PubMed
    1. Willerson JT, Ridker PM. Inflammation as a cardiovascular risk factor. Circulation. 2004;109(21 Suppl 1):Ii2–10. - PubMed

LinkOut - more resources