Nonlinear association between advanced lung cancer inflammation index and latent tuberculosis infection risk: threshold effects and predictive value of a novel biomarker.

BACKGROUND: Nutritional and inflammatory status influence latent tuberculosis infection (LTBI) susceptibility, but the role of composite biomarkers like advanced lung cancer inflammation index (ALI) is unclear. This study aimed to explore the association of the ALI with LTBI.

METHODS: This cross-sectional study analyzed the National Health and Nutrition Examination Survey (NHANES) data of 3,010 adult participants in the USA from 2011 to 2012, of whom 382 were diagnosed with LTBI. Multivariate logistic regression, subgroup analysis, and interaction assessment were performed to investigate the association between ALI and LTBI. Restricted cubic spline (RCS) and threshold effect analysis were employed to examine the non-linear relationship. Mediation analysis was conducted to assess the mediating role of ALI. The adjusted receiver operating characteristic (ROC) curve was utilized to evaluate the prognostic value of ALI.

RESULTS: After adjusting for all covariates, we found a significant inverse relationship between ALI and LTBI [odds ratio (OR) =0.765, 95% confidence interval (CI): 0.601-0.973], which persisted among men, participants without diabetes, and those with hypertension. The risk of LTBI tended to decrease with increasing tertiles of ALI (P for trend =0.002). The RCS curve revealed a non-linear relationship between log-ALI and LTBI (P for nonlinear =0.04), which was further confirmed by threshold effect analysis. ALI partially mediated the associations of smoking and poverty income ratio with LTBI (P=0.02). Compared with other indicators, although ALI had a slightly higher area under the curve (AUC) (0.7809, 95% CI: 0.7575-0.8044) in predicting LTBI, the difference was not statistically significant (all DeLong test P>0.05).

CONCLUSIONS: This study identified a significant non-linear association between ALI and LTBI risk. These preliminary findings highlight ALI as a potential integrated biomarker, but require validation in prospective studies.