Association between advanced lung cancer inflammation index and all-cause and cardiovascular mortality among prediabetes patients: NHANES, 1999–2018

doi:10.21203/rs.3.rs-4996903/v1

Background

Prediabetes is a significant risk factor for type 2 diabetes and cardiovascular disease, yet effective prognostic tools are lacking. The Advanced Lung Cancer Inflammation Index (ALI), an emerging inflammatory marker, has shown prognostic value in various diseases. However, the role of ALI in prediabetic patients remains understudied. This study aims to evaluate the association between ALI and all-cause and cardiovascular disease (CVD) mortality in prediabetic patients, exploring its potential as a prognostic assessment tool.

Methods

This study utilized data from the National Health and Nutrition Examination Survey (NHANES) 1999–2018. Multivariate Cox regression models were used to analyze the relationship between ALI and mortality risk. Their non-linear relationship was analyzed by restricted cubic spline analysis. Sensitivity analysis was constructed through stratified analysis and interaction analysis.

Results

The study incorporated a total of 16,670 patients. An increase in ALI was associated with a reduced risk of all-cause and CVD mortality in prediabetes patients. Compared to the lowest ALI quartile, the highest quartile showed a 30% reduction in all-cause mortality risk (HR = 0.70, 95%CI: 0.62–0.79) and a 44% reduction in CVD mortality risk (HR = 0.56, 95%CI: 0.44–0.73). In addition, there were L-shaped non-linear relationships between ALI and all-cause, CVD mortality in prediabetes patients. The inflection points were 40.50 and 37.35, respectively. For values below the inflection point, for every 10U increase in ALI, all-cause mortality risk decreased by 26%, and CVD mortality risk decreased by 32%. Beyond the inflection point, the effect weakened both all-cause and CVD mortality.

Conclusion

ALI is significantly negatively associated with all-cause and CVD mortality in prediabetic patients. ALI may serve as an effective tool for assessing long-term prognosis in prediabetic individuals.

Health sciences/Cardiology

Health sciences/Endocrinology

advanced lung cancer inflammation index

all-cause mortality

cardiovascular mortality

prediabetes

Prediabetes represents a global health challenge with increasing prevalence. The World Health Organization reports that approximately 374 million people worldwide are in a prediabetic state, projected to reach 548 million by 2045[1]. In China, the prevalence of prediabetes is particularly significant, with an estimated 169 million adults having impaired glucose tolerance in 2021[2]. This population faces a substantially increased risk of all-cause mortality and cardiovascular disease (CVD) mortality. Studies indicate that individuals with prediabetes have a 13% higher risk of CVD mortality compared to those with normal blood glucose levels[3].

The Advanced Lung Cancer Inflammation Index (ALI) is an emerging inflammatory marker calculated from body mass index (BMI), serum albumin, and neutrophil-to-lymphocyte ratio (NLR). ALI reflects the overall inflammatory state and nutritional status of the body, showing potential in the prognostic assessment of various diseases[4]. Research has found that ALI is closely associated with the prognosis of multiple cancers, including lung and colorectal cancer, with lower ALI values typically indicating poorer survival outcomes[5, 6]. Moreover, ALI has demonstrated value in cardiovascular risk assessment, offering a new perspective on cardiovascular health management[7].

In recent years, ALI has garnered significant attention in diabetes and its related complications research. A large-scale study involving 3,888 patients with type 2 diabetes demonstrated a significant inverse correlation between ALI and both all-cause and CVD mortality[8]. The study found that for every 10-unit increase in ALI, the risk of all-cause mortality decreased by 7% (HR = 0.93, 95% CI: 0.91–0.95) and CVD mortality by 6% (HR = 0.94, 95% CI: 0.91–0.97). Another study further confirmed this association and strengthened the reliability of the results through subgroup analyses and sensitivity analyses[2]. Additionally, researchers explored the relationship between ALI and mortality in stroke patients, providing new insights into the prognostic value of ALI in different disease contexts[9]. However, despite the strong evidence supporting an inverse relationship between ALI and mortality rates in existing studies, research in prediabetic populations remains relatively scarce.

Furthermore, as a composite indicator, the components of ALI (BMI, albumin, and NLR) are each closely related to the development and prognosis of diabetes and its complications. For example, BMI shows a J-shaped curve relationship with diabetes risk[10], albumin levels are associated with the progression of diabetic nephropathy[11, 12], and NLR is considered a potential predictor of diabetic vascular complications[13]. Given this context, we have designed a retrospective cohort study to evaluate the association between ALI and both all-cause and cardiovascular mortality among prediabetic patients. This study not only aims to provide crucial insights into the prognostic value of ALI in prediabetic patients but may also inform the development of early intervention strategies to improve long-term health outcomes in this high-risk population.

Study design and participants

The current study was conducted from 1999 to 2018. The National Health and Nutrition Examination Survey (NHANES) is a complex, multistage, continuous nationwide survey program conducted by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). The purpose of NHANES is to evaluate the health and nutritional status of adults and children in the United States. This study was approved by the Research Ethics Review Board of the National Center for Health Statistics (NCHS), and informed consent was obtained from all adult participants[14]. The study design and implementation complied with the ethical principles of the Declaration of Helsinki. For more comprehensive information, please visit the website: www.cdc.gov/nchs/nhanes/irba98.htm.

The study population comprised prediabetic individuals from the NHANES database. Inclusion criteria were: 1) diagnosed with prediabetes; 2) age ≥20 years. Exclusion criteria included: 1) missing data on albumin, lymphocytes, neutrophils, or BMI; 2) extreme ALI values (below the 1st percentile and above the 99th percentile); 3) missing information on other covariates. After screening, 16,670 eligible participants were included (Figure 1). The following index was used to diagnose prediabetes: One of four criteria must be met: (1) a diagnosis made by medical specialists; (2) a hemoglobin A1c (HbA1c) level falling between 5.7% and less than 6.5%; (3) a fasting plasma glucose (FPG) level between 5.6 mmol/L and 7.0 mmol/L; or (4) a 2-hour FPG value between 7.8 mmol/L and 11.0 mmol/L during an oral glucose tolerance test (OGTT).

Measurement of ALI

ALI was measured using BMI, albumin, and NLR, which was defined as BMI (kg/m2) * albumin level (g/dL)/NLR[4]. NLR was computed as neutrophil counts divided by lymphocyte counts. According to the ALI levels, patients were grouped into four quartile groups based on ALI levels: Quantile1 group, Quantile2 group, Quantile3 group, and Quantile4 group.

Mortality

All-cause and CVD mortality were determined based on data released by the NCHS, with a cutoff date of December 31, 2019. The definition of CVD mortality was based on ICD-10 codes (I00–I078).

Covariates definitions

Covariates included age, sex, race, education level, poverty income ratio (PIR), BMI, smoking and alcohol status, liver and kidney function indicators, inflammatory markers, and history of hypertension and cardiovascular diseases. The present analysis removed the factors for which there were missing data. The comprehensive description and classification of the aforementioned covariates are presented in the Supplementary material.

Statistical analysis

The mean and standard deviation (SD) were used to describe continuous variables, and proportions were used to express categorical variables. The Student's t-test or the chi-square test were used for variables that followed a normal distribution. For variables with non-normal distributions, we used Fisher's exact probability tests or non-parametric tests. The preliminary relationship between ALI levels and all-cause and CVD mortality in patients with prediabetes was determined using Kaplan–Meier analysis. After correcting for numerous factors, multivariate Cox analysis was used to investigate the impact of ALI levels on all-cause and CVD mortality in patients with prediabetes. The results are shown as a Hazard Ratio (HR) and 95% Confidence Interval (CI). In total, the following 4 models were used in this study: The Crude model is referred to as the unadjusted model. Model 1 took into account demographic variables

such as age, sex, race, education level, and PIR. Model 2 considered demographics, BMI, smoking status, alcohol consumption, and a history of hypertension and cardiovascular disease. In addition to the covariates found in Model 2, Model 3 also includes BUN, Cr, eGFR, HbA1c, ALT, and AST. We used restricted cubic spline (RCS) analysis to elucidate the non-linear connection between ALI levels and all-cause and CVD mortality in patients with prediabetes. Once a non-linear relationship was discovered, a recursive algorithm was used to calculate its inflection point. To further investigate threshold effects, we used piecewise Cox regression models for evaluation. Additionally, we divided each participant's ALI level by ten and then included the results as continuous factors into a multivariable Cox regression analysis with the goal of determining the effect of each 10-unit change in ALI on all-cause and CVD mortality in patients with prediabetes. To enhance the robustness of the current study, we conducted sensitivity analyses. For example, we used stratified analyses in conjunction with interaction analyses to investigate potential interactions between ALI levels and stratified factors. R software (version 4.3.1) was used for all analyses. Two-sided P less than 0.05 was used to establish statistical significance.

Baseline characteristics

After extracting 101, 316 participants from the NHANES 1999-2018 cohorts, we applied inclusion and exclusion criteria, and 16, 670 participants were found to be eligible. A thorough flow diagram was shown in Figure 1. The participants were divided into quartiles based on their ALI levels. The average ALI values for Quantile1 group, Quantile2 group, Quantile3 group, and Quantile4 group were 34.16, 53.60, 72.29, and 112.75, respectively. The average age of these 16, 670 participants was 55.73 years and a mean ALI value of 69.93.

As ALI increased, age, neutrophil count, and neutrophil-to-lymphocyte ratio (NLR) decreased, while body mass index (BMI) and lymphocyte count increased. Higher ALI quartiles showed a greater proportion of females, Non-Hispanic Blacks, and never-smokers. Notably, cardiovascular disease prevalence, all-cause mortality, and cardiovascular disease mortality rates significantly decreased with increasing ALI. Detailed results were displayed in Table 1.

Table 1. Baseline characteristics of the study population by ALI quartiles

Characteristic	Overall	Q1	Q2	Q3	Q4	P-value
N	16670	3792	4001	4181	4696
ALI	69.93 ± 34.75	34.16 ± 7.53	53.60 ± 4.90	72.29 ± 6.34	112.75 ± 25.19	<0.001
Age (years)	55.73 ± 16.55	61.65 ± 16.85	56.23 ± 16.55	53.80 ± 16.05	52.26 ± 15.37	<0.001
BMI (kg/m²)	30.14 ± 6.85	26.89 ± 5.25	29.19 ± 5.86	30.74 ± 6.53	33.04 ± 7.68	<0.001
ALT (U/L)	26.20 ± 28.15	23.56 ± 47.75	25.65 ± 18.43	26.86 ± 19.25	28.19 ± 18.60	<0.001
AST (U/L)	25.88 ± 21.15	25.47 ± 35.88	25.43 ± 14.48	25.82 ± 14.28	26.64 ± 13.70	0.024
BUN (mmol/L)	5.16 ± 2.15	5.64 ± 2.67	5.15 ± 2.10	5.05 ± 1.93	4.87 ± 1.81	<0.001
Creatinine (μmol/L)	81.05 ± 34.37	87.09 ± 50.77	79.74 ± 28.23	79.28 ± 26.81	78.85 ± 27.47	<0.001
eGFR	89.73 ± 22.08	84.02 ± 24.06	90.26 ± 21.74	91.67 ± 21.40	92.17 ± 20.42	<0.001
Neutrophils (10³ cells/μL)	4.21 ± 1.60	5.35 ± 1.77	4.49 ± 1.39	3.97 ± 1.28	3.26 ± 1.15	<0.001
Lymphocytes (10³ cells/μL)	2.13 ± 0.71	1.62 ± 0.50	1.98 ± 0.54	2.22 ± 0.60	2.58 ± 0.76	<0.001
NLR	2.14 ± 0.98	3.43 ± 1.01	2.30 ± 0.45	1.80 ± 0.37	1.28 ± 0.34	<0.001
HbA1c (%)	5.77 ± 0.41	5.75 ± 0.41	5.75 ± 0.41	5.76 ± 0.41	5.82 ± 0.42	<0.001
Sex, n (%)						<0.001
Male	8793 (52.75)	2162 (57.01)	2128 (53.19)	2189 (52.36)	2314 (49.28)
Female	7877 (47.25)	1630 (42.99)	1873 (46.81)	1992 (47.64)	2382 (50.72)
Race, n (%)						<0.001
Non-Hispanic White	6998 (41.98)	2118 (55.85)	1837 (45.91)	1646 (39.37)	1397 (29.75)
Non-Hispanic Black	3619 (21.71)	504 (13.29)	647 (16.17)	842 (20.14)	1626 (34.63)
Mexican American	2897 (17.38)	503 (13.26)	725 (18.12)	849 (20.31)	820 (17.46)
Other	3156 (18.93)	667 (17.59)	792 (19.80)	844 (20.19)	853 (18.16)
Education level, n (%)						0.270
Less than high school	4947 (29.72)	1151 (30.43)	1236 (30.95)	1198 (28.70)	1362 (29.02)
High school or equivalent	3972 (23.86)	910 (24.05)	935 (23.41)	1000 (23.96)	1127 (24.01)
College or above	7725 (46.41)	1722 (45.52)	1823 (45.64)	1976 (47.34)	2204 (46.96)
PIR, n (%)						0.061
<1.3	4686 (30.95)	1049 (30.63)	1107 (30.36)	1180 (31.00)	1350 (31.66)
1.3-3.5	5900 (38.97)	1383 (40.38)	1439 (39.47)	1416 (37.20)	1662 (38.98)
≥3.5	4555 (30.08)	993 (28.99)	1100 (30.17)	1210 (31.79)	1252 (29.36)
Smoking status, n (%)						<0.001
Never	8595 (51.61)	1672 (44.12)	1982 (49.57)	2250 (53.88)	2691 (57.38)
Former	4712 (28.29)	1220 (32.19)	1161 (29.04)	1145 (27.42)	1186 (25.29)
Current	3347 (20.10)	898 (23.69)	855 (21.39)	781 (18.70)	813 (17.33)
Alcohol consumption, n (%)	10661 (68.42)	2425 (68.33)	2655 (71.10)	2667 (68.04)	2914 (66.56)	<0.001
Hypertension, n (%)	10799 (64.78)	2528 (66.67)	2539 (63.46)	2669 (63.84)	3063 (65.23)	0.012
CVD, n (%)	2277 (13.66)	794 (20.94)	531 (13.27)	497 (11.89)	455 (9.69)	<0.001
All-cause mortality, n (%)	2884 (17.33)	1126 (29.76)	708 (17.73)	549 (13.15)	501 (10.68)	<0.001
CVD mortality, n (%)	758 (4.55)	323 (8.52)	173 (4.32)	143 (3.42)	119 (2.53)	<0.001

Abbreviations: ALI, Advanced lung cancer inflammation index; BMI, Body Mass Index; ALT, Alanine Aminotransferase; AST, Aspartate Aminotransferase; BUN, Blood Urea Nitrogen; eGFR, estimated Glomerular Filtration Rate; NLR, Neutrophil-to-Lymphocyte Ratio; HbA1c, Glycated Hemoglobin; PIR, Poverty Income Ratio; CVD, Cardiovascular Disease.

Data are presented as mean ± standard deviation for continuous variables and n (%) for categorical variables. P-values were calculated using one-way ANOVA for continuous variables and chi-square test for categorical variables.

Kaplan–Meier analysis

The Kaplan-Meier analysis was used to initially differentiate the connection between all-cause mortality and CVD mortality in ALI and prediabetes individuals. A total of 2,884 fatalities from all causes were reported among the 16, 670 prediabetes patients, with 758 deaths being linked to CVD. The Kaplan-Meier survival curve analysis revealed substantial disparities in survival rates between the ALI quartile groups. As seen in Figure 2, patients with prediabetes who had greater ALI levels had lower all-cause and CVD mortality (P <0.0001, P <0.0001, respectively).

ALI and mortality

Table 2 shows the logistic regression model results, which show the relationship between the ALI and all-cause and CVD mortality in prediabetes patients. Regardless of whether variables were corrected, there was a significant negative relationship between ALI and all-cause and CVD mortality in patients with prediabetes. In the adjusted III model, compared to the lowest ALI quartile (Q1), higher ALI levels were associated with decreased all-cause mortality in prediabetes patients, The HR (95% CI) for the Quantile2, Quantile3, and Quantile4 groups were 0.78 (0.70-0.86), 0.73 (0.65-0.81), 0.70 (0.62-0.79), respectively (P_trend < 0.001). A similar trend was also seen in CVD mortality, wherein patients with prediabetes who have greater levels of ALI also have lower CVD mortality. The HR (95% CI) for the Quantile2, Quantile3, and Quantile4 groups were 0.66 (0.54-0.81), 0.68 (0.55-0.85), 0.56 (0.44-0.73), respectively (P_trend < 0.001).

Assessing the dynamic alterations in ALI was vital to the prognosis of individuals with prediabetes patients. The multivariable-adjusted HR for all-cause mortality was 0.95 (0.94-0.97) and for CVD mortality was 0.93 (0.90-0.96) for every 10U increment in ALI.

Table 2. Association between ALI and mortality outcomes in NHANES participants.

Exposure	Non-adjusted	Adjust I	Adjust II	Adjust III
All-cause mortality
ALI quartile
Q1	Reference	Reference	Reference	Reference
Q2	0.54 (0.49, 0.59)	0.74 (0.67, 0.81)	0.76 (0.68, 0.84)	0.78 (0.70, 0.86)
Q3	0.40 (0.36, 0.44)	0.70 (0.63, 0.78)	0.72 (0.64, 0.80)	0.73 (0.65, 0.81)
Q4	0.32 (0.29, 0.36)	0.64 (0.57, 0.72)	0.68 (0.60, 0.77)	0.70 (0.62, 0.79)
ALI (per 10 U increment)	0.86 (0.84, 0.87)	0.94 (0.93, 0.96)	0.95 (0.93, 0.96)	0.95 (0.94, 0.97)
P for trend	<0.001	<0.001	<0.001	<0.001
Cardiovascular mortality
ALI quartile
Q1	Reference	Reference	Reference	Reference
Q2	0.46 (0.38, 0.55)	0.66 (0.54, 0.80)	0.64 (0.53, 0.79)	0.66 (0.54, 0.81)
Q3	0.36 (0.30, 0.44)	0.72 (0.58, 0.88)	0.67 (0.54, 0.83)	0.68 (0.55, 0.85)
Q4	0.27 (0.22, 0.33)	0.58 (0.46, 0.73)	0.53 (0.42, 0.69)	0.56 (0.44, 0.73)
ALI (per 10 U increment)	0.84 (0.81, 0.86)	0.94 (0.91, 0.97)	0.93 (0.90, 0.96)	0.93 (0.90, 0.96)
P for trend	<0.001	<0.001	<0.001	<0.001

Data are presented as HR (95% CI). P<0.001
Abbreviations: ALI, Advanced lung cancer inflammation index; HR, hazard ratio; CI, confidence interval.

Non-adjusted model: unadjusted.
Adjust I model: adjusted for age, sex, race, education level, and poverty income ratio.
Adjust II model: adjusted for variables in Adjust I plus body mass index, smoking status, alcohol consumption, hypertension, and cardiovascular disease.
Adjust III model: adjusted for variables in Adjust II plus alanine aminotransferase, aspartate aminotransferase, blood urea nitrogen, creatinine, estimated glomerular filtration rate, and glycated hemoglobin.

All models used Cox proportional hazards regression with follow-up time as the time variable.

Non-linear relationships

The non-linear connection between ALI levels and prediabetes patients' long-term prognosis was depicted in Figure 3. An L-shaped non-linear connection was seen between prediabetes patients' all-cause and CVD mortality (all p < 0.001). The study identified that the inflection points for all-cause mortality and CVD mortality were 40.50 and 37.35, respectively. For ALI values below 40.50, an increase of 10 U ALI corresponded to a 26% reduction in the all-cause mortality risk (HR: 0.74, 95% CI: 0.69-0.80, P_trend <0.0001). Yet, when ALI>40.50, the effect weakened (HR: 0.98, 95% CI: 0.96-1.00, P_trend =0.0149). CVD mortality showed a similar trend, for ALI values below 37.35, an increase of 10 U ALI corresponded to a 32% reduction in the CVD mortality risk (HR: 0.68, 95% CI:0.57-0.80, P_trend <0.0001). However, when ALI exceeded 37.35, every 10 U ALI increase led to a 4% decrease in CVD mortality risk (HR: 0.96, 95% CI:0.93-1.00, P_trend =0.0248). The details were presented in Table 3.

Table 3. Threshold effect analysis of ALI on all-cause, CVD mortality in NHANES participants.

Model	All-cause mortality	P-Value	CVD mortality	P-Value
Model I
Linear effect	0.95 (0.94, 0.97)	<0.0001	0.93 (0.90, 0.96)	<0.0001
Model II
Knot (K)	4.050		3.735
Effect for ALI < K	0.74 (0.69, 0.80)	<0.0001	0.68 (0.57, 0.80)	<0.0001
Effect for ALI > K	0.98 (0.96, 1.00)	0.0149	0.96 (0.93, 1.00)	0.0248
Difference in effects	1.31 (1.21, 1.42)	<0.0001	1.42 (1.19, 1.70)	<0.0001
LR test p-value	<0.001		<0.001

Data are presented as HR (95% CI) for each 10 U increase in ALI.
CVD: Cardiovascular disease; LR: Likelihood ratio
Models were adjusted for age, sex, race/ethnicity, education level, poverty income ratio, body mass index, smoking status, alcohol consumption, hypertension, alanine aminotransferase, aspartate aminotransferase, blood urea nitrogen, creatinine, estimated glomerular filtration rate, glycated hemoglobin, and history of cardiovascular disease.

Sensitivity analysis

Sensitivity analysis was carried out using stratified analysis and interaction analysis. In order to evaluate possible interactions between stratified factors and ALI, stratified analyses for all-cause and CVD mortality among patients with prediabetes were shown in Tables S1 and S2. There were no significant interactions seen in either all-cause or CVD mortality. Furthermore, Tables S3 and S4 showed a stratified study of all-cause and CVD mortality in prediabetes patients, grouped by inflection points, to investigate potential interactions between stratified factors and ALI. There were no significant interactions observed. Given that interaction analyses revealed no statistically significant differences across all subgroups (all P for interaction >0.05), indicating the consistency and robustness of the inverse relationship between ALI and mortality risk across diverse demographic and clinical subgroups.

This was the first study to employ a large cohort to investigate the relationships between ALI levels and all-cause and CVD mortality among prediabetic patients. After multivariate adjustments, an increase in ALI was significantly linked with lower all-cause and CVD mortality. This study discovered an L-shaped non-linear relationship between ALI and all-cause and CVD mortality, with inflection points of 40.50 and 37.35, respectively. All-cause mortality risk dropped by 26% and CVD mortality risk decreased by 32% for values below the inflection point for every 10U increase in ALI. The influence weakened both all-cause and CVD mortality beyond the inflection point. Sensitivity analysis revealed that there was no meaningful interaction between ALI and the stratification factors.

Prediabetes research has gained significant attention due to its role as a critical stage in the progression of type 2 diabetes. Current studies focus on early detection, risk factors, and intervention strategies. Research has shown that lifestyle modifications, including diet and exercise, can effectively prevent or delay the onset of diabetes in prediabetic individuals[15]. Genetic factors and their interaction with environmental influences are also under scrutiny[16]. Additionally, there's growing interest in the role of inflammation and oxidative stress in prediabetes progression[17]. Novel biomarkers, such as the Advanced Lung Cancer Inflammation Index (ALI), are being investigated for their potential in risk stratification and prognosis[8, 18]. Zhang et al.[8] in a large-scale prospective cohort study involving 3,888 patients with type 2 diabetes, found that for every 10-unit increase in ALI, the risk of all-cause mortality decreased by 7% (HR = 0.93, 95% CI: 0.91-0.95) and cardiovascular disease mortality by 6% (HR = 0.94, 95% CI: 0.91-0.97). Consistent with previous studies, our research further confirms the inverse relationship between ALI and both all-cause and cardiovascular disease mortality in prediabetic patients. However, our study extends this finding, demonstrating that ALI has similar predictive value in prediabetic populations. Moreover, we explored the non-linear relationship between ALI and mortality rates, identifying inflection points, which provide new perspectives on the predictive value of ALI at different levels.

ALI, as a composite indicator, reflects the overall inflammatory state and nutritional status of the body[4]. Its inverse relationship with mortality can be explained through multiple mechanisms. Firstly, chronic low-grade inflammation is considered a key factor in the development of prediabetes and type 2 diabetes[19]. Higher ALI values typically indicate lower inflammation levels, which may help slow disease progression and the onset of complications. The review by Donath and Shoelson[20] emphasizes the central role of inflammation in the pathogenesis of type 2 diabetes, supporting our perspective. Secondly, the albumin level included in ALI reflects liver function and overall nutritional status, factors closely related to long-term survival[21]. The study by Levitt and Levitt[21] elaborates on the crucial role of serum albumin in human homeostasis, providing a theoretical foundation for our findings. Furthermore, BMI, as a component of ALI, shows a J-shaped curve relationship with diabetes risk[22], which may partly explain the non-linear relationship we observed. The research by Bhupathiraju and Hu[22] delves into the complex relationship between BMI and diabetes risk, offering additional support for our results.

Our study's identification of inflection points in the ALI-mortality relationship is a novel finding. This suggests that different intervention strategies may be needed based on ALI levels, with more aggressive approaches potentially necessary for patients with ALI below the inflection point. This concept of tailored interventions based on inflammatory markers is supported by the work of Ridker et al. on targeted anti-inflammatory therapy in cardiovascular disease[23].

It's worth noting that our results differ from some other studies. For example, Gong et al. found a lower ALI may serve as an independent predictor of increased 30-day all-cause mortality and MACEs[24]. Additionally, Xiao et al. discovered that in senior heart failure patients, increased ALI was substantially linked with decreased all-cause and cardiovascular mortalities[7]. These discrepancies might be due to differences in study populations, designs, and outcome measures. The heterogeneity of results across different populations underscores the importance of population-specific validation of biomarkers, as emphasized by the Emerging Risk Factors Collaboration[25].

The prognostic value of ALI extends beyond diabetes and cardiovascular disease. Studies have demonstrated its utility in various cancers, including lung cancer[26], esophageal squamous cell carcinoma[27], colorectal cancer[28], and hepatocellular carcinoma[29]. This broad applicability suggests that ALI captures fundamental aspects of health status that are relevant across multiple disease states.

In summary, our study not only validates the prognostic value of ALI in prediabetic patients but also provides new insights into its predictive capabilities. These findings offer important evidence for using ALI to assess risk in prediabetic patients in clinical practice, while also opening new avenues for further exploration of the role of inflammatory markers in metabolic diseases. Future research should focus on the predictive value of ALI in different populations and disease stages, as well as the development of personalized intervention strategies based on ALI levels. For example, the large-scale meta-analysis by the Emerging Risk Factors Collaboration highlights the importance of validating novel biomarkers across different populations, guiding our future research directions[25]. Moreover, considering the heterogeneity of prediabetic patients, future studies should explore the predictive value of ALI in different subgroups. Lastly, given that the components of ALI (BMI, albumin, and NLR) are each associated with diabetes and its complications[30, 31], future research should delve into the relative contributions of these factors to ALI's predictive power, as well as potential interactions between them.

The findings of this study have significant implications for the clinical management of prediabetic patients. By revealing the association between ALI and both all-cause and cardiovascular disease mortality, we provide clinicians with a potential new tool for assessing long-term prognosis in prediabetic individuals. As a composite index, ALI may offer a more comprehensive reflection of overall health status compared to traditional single indicators. This discovery could shift clinical practice towards greater attention to patients' nutritional status and chronic inflammation levels, beyond mere glycemic control. We suggest incorporating ALI into routine assessments for prediabetic patients, with particular attention to those with ALI below 40.5, who may require closer monitoring and more aggressive intervention. However, prospective studies are needed to validate the predictive value of ALI before its widespread adoption in clinical practice. Future research directions may include exploring the relationship between ALI and the effectiveness of specific interventions, as well as investigating the applicability of ALI across different ethnic and geographic populations. Moreover, developing intervention strategies aimed at improving ALI, such as enhancing nutritional status and reducing chronic inflammation, could provide new approaches to managing prediabetic patients. Overall, this study offers a fresh perspective on risk stratification and personalized management for prediabetic individuals, potentially improving long-term health outcomes for this growing high-risk population.

This study has several notable strengths. Firstly, we utilized the National Health and Nutrition Examination Survey (NHANES) database, a large-scale, representative population sample, enhancing the external validity of our findings. Secondly, in terms of data analysis, we employed multivariate Cox regression models and conducted extensive subgroup and sensitivity analyses to ensure the robustness of our results. Notably, we used restricted cubic spline analysis to explore the non-linear relationship between ALI and mortality risk, revealing potential threshold effects. Furthermore, we accounted for multiple potential confounding factors, including demographic characteristics, lifestyle factors, and comorbidities, thereby increasing the reliability of our findings. Lastly, our study's focus on the specific population of prediabetic individuals addresses a gap in existing research, providing valuable insights for the management of this growing high-risk group.

Despite its strengths, this study has several limitations. Firstly, because this study was observational research, it was not possible to definitively establish a causal relationship between ALI and mortality in patients with prediabetes; further research with larger sample sizes and a prospective design was required to clarify their causality. Secondly, even though we controlled for several known confounders, we cannot completely rule out the influence of unmeasured or unknown confounding factors.

Overall, our study found a significant relationship between increasing ALI levels and lower all-cause and CVD mortality in prediabetes individuals. The study demonstrated that ALI has an L-shaped non-linear relationship with all-cause mortality and CVD mortality, with inflection points at 40.50 and 37.35, respectively. These findings highlighted the necessity of keeping ALI within a reasonable range in clinical settings for improving all-cause and CVD mortality in prediabetes patients.

ALI: Advanced Lung Cancer Inflammation Index

CVD: Cardiovascular Disease

NHANES: National Health and Nutrition Examination Survey

HbA1c: Hemoglobin A1c

FPG: Fasting Plasma Glucose

OGTT: Oral Glucose Tolerance Test

BMI: Body Mass Index

NLR: Neutrophil-to-Lymphocyte Ratio

NCHS: National Center for Health Statistics

CDC: Centers for Disease Control and Prevention

ICD-10: International Classification of Diseases, 10th Revision

PIR: Poverty Income Ratio

BUN: Blood Urea Nitrogen

Cr: Creatinine

eGFR: Estimated Glomerular Filtration Rate

ALT: Alanine Aminotransferase

AST: Aspartate Aminotransferase

RCS: Restricted Cubic Spline

HR: Hazard Ratio

CI: Confidence Interval

SD: Standard Deviation

MACEs: Major Adverse Cardiovascular Events

Ethical approval

The protocols of NHANES were approved by the institutional review board of the National Center for Health Statistics, CDC (https://www.cdc.gov/nchs/nhanes/irba98.htm).

Consent for publication

Not applicable.

Data availability

The datasets generated and analyzed in the current study are available at NHANES website: https://www.cdc.gov/nchs/nhanes/index.htm.

Acknowledgements

The authors thank the participants of the NHANES databases.

Competing interests

The authors declare that they have no competing interests.

Funding

This work was supported by the Natural Science Foundation of Ningxia Province [grant numbers 2018AAC02015]; Natural Science Foundation of Ningxia Province [grant number 2022AAC03479]; Natural Science Foundation of Ningxia Province [grant number 2023AAC02071]; National Natural Science Foundation of China [grant number 82260086:82060057]; and the Central Government Guided Local Science and Technology Project [grant number 2022FRD05046].

Authors' contributions

Rui Yan: Conceptualization, Formal analysis, Investigation, Methodology, Writing – original draft. Xueping Ma: Conceptualization, Investigation, Methodology, Writing – original draft. Bo Shi: Data curation, Formal analysis, Writing – original draft. Congyan Ye: Investigation, Formal analysis, Writing – original draft. Shizhe Fu: Data curation, Investigation, Writing – original draft. Kairu Wang: Investigation, Formal analysis, Writing – original draft. Ru Yan: Visualization, Writing – review & editing, Validation. Shaobin Jia: Project administration, Resources, Supervision, Writing – review & editing, Validation. Guangzhi Cong: Data curation, Project administration, Resources, Supervision, Writing – review & editing, Validation.

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No competing interests reported.

SupplementaryMaterial.docx

Association between advanced lung cancer inflammation index and all-cause and cardiovascular mortality among prediabetes patients: NHANES, 1999–2018

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Abstract

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Supplementary Files

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