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Background <p>Prostate cancer (PCa), a significant health concern among middle-aged and elderly men globally, has increasingly been associated with metabolic and inflammatory processes. The advanced lung cancer inflammation index (ALI), a novel marker reflecting nutritional and inflammatory status, has not yet been thoroughly investigated in the context of PCa. This study investigated the potential link between ALI and PCa.</p> Methods <p>We first conducted a cross-sectional study utilizing data from the National Health and Nutrition Examination Survey (NHANES). The relationship between ALI and PCa was examined by NHANES-provided survey weights. Smoothed curve fitting and threshold effect analyses were conducted to evaluate possible nonlinear associations. Then we analyzed the correlation between the prognosis of PCa patients and ALI.</p> Results <p>Out of 15,042 adult participants, 683 (4.54%) were diagnosed with PCa. The risk of PCa decreased across increasing quartiles of ALI. Multivariate logistic regression analysis revealed that compared to participants in the lowest ALI quartile (Q1: 2.89–41.94), those in higher quartiles (Q2: 41.94–59.08, Q3: 59.08–80.88, and Q4: ≥80.88) had progressively lower odds of developing PCa in both unadjusted and adjusted models. Smoothed curve fitting indicated a U-shaped relationship between ALI and PCa. Longitudinal follow-up data indicated that lower ALI values were positively correlated with a poor survival in cancer patients.</p> Conclusion <p>Our study revealed a non-linear relationship between ALI and the risk of PCa development. Specifically, there was a negative correlation between ALI and PCa risk when the ALI value was &lt; 100. Furthermore, we found that lower ALI levels are strongly associated with a poor survival in cancer patients. Additional large-scale prospective studies are needed to confirm these findings and investigate the underlying mechanisms.</p>

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A cross-sectional study examining the relationship between the advanced lung cancer inflammation index and prostate cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月29日

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  • Mengjun Huang,
  • Qiliang Teng,
  • Dong Ning,
  • Tongyu Tong,
  • Fei Cao,
  • Yiting Wang,
  • Hanqi Lei,
  • Jun Pang

摘要

Background

Prostate cancer (PCa), a significant health concern among middle-aged and elderly men globally, has increasingly been associated with metabolic and inflammatory processes. The advanced lung cancer inflammation index (ALI), a novel marker reflecting nutritional and inflammatory status, has not yet been thoroughly investigated in the context of PCa. This study investigated the potential link between ALI and PCa.

Methods

We first conducted a cross-sectional study utilizing data from the National Health and Nutrition Examination Survey (NHANES). The relationship between ALI and PCa was examined by NHANES-provided survey weights. Smoothed curve fitting and threshold effect analyses were conducted to evaluate possible nonlinear associations. Then we analyzed the correlation between the prognosis of PCa patients and ALI.

Results

Out of 15,042 adult participants, 683 (4.54%) were diagnosed with PCa. The risk of PCa decreased across increasing quartiles of ALI. Multivariate logistic regression analysis revealed that compared to participants in the lowest ALI quartile (Q1: 2.89–41.94), those in higher quartiles (Q2: 41.94–59.08, Q3: 59.08–80.88, and Q4: ≥80.88) had progressively lower odds of developing PCa in both unadjusted and adjusted models. Smoothed curve fitting indicated a U-shaped relationship between ALI and PCa. Longitudinal follow-up data indicated that lower ALI values were positively correlated with a poor survival in cancer patients.

Conclusion

Our study revealed a non-linear relationship between ALI and the risk of PCa development. Specifically, there was a negative correlation between ALI and PCa risk when the ALI value was < 100. Furthermore, we found that lower ALI levels are strongly associated with a poor survival in cancer patients. Additional large-scale prospective studies are needed to confirm these findings and investigate the underlying mechanisms.