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Background <p>A tight association between systemic inflammation and nutritional status has been established. We aim to evaluate the prognostic role of systemic inflammation-modified Patient-Generated Subjective Global Assessment (PG-SGA) criteria in advanced cancers.</p> Method <p>In this retrospective study, patients with advanced cancers were included from the West China Hospital between Nov 2019 and Sep 2023. Five systemic inflammatory indicators were selected, including the systemic inflammatory index (SII), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR), and advanced lung cancer inflammation index (ALI). Nutritional status was evaluated by the PG-SGA criteria. Kaplan–Meier curves, restricted cubic splines (RCS), and Cox regression analyses were used to estimate the effects of inflammation-modified PG-SGA index on the survival of cancer patients.</p> Results <p>In total, there were 1,065 patients with advanced cancers included in our study. The ALI showed better predictive power in predicting the all-cause mortality of patients with advanced cancers when compared with other systemic inflammation indicators (4th quartile: hazard ratio (HR) = 0.38, 95% confidence interval (CI): 0.29, 0.50, P &lt; 0.001). The ALI-modified PG-SGA index showed the best survival prediction value in patients with advanced cancers, with an AUC of ROC of 0.68 for 365-day mortality, 0.65 for 730-day mortality, and 0.64 for 1,300-day survival prediction, respectively. The C-index (0.626), calibration curves, and decision curve analysis validated the promising predictive accuracy of the PG-SGA/ALI index in predicting the all-cause mortality of patients with advanced cancers. The sensitive analyses also supported the consistent findings as we determined in the main regression.</p> Conclusions <p>The findings highlight that considering the host systemic inflammation status during the nutrition assessment would bring additional benefits to the survival prediction of advanced cancers. The PG-SGA/ALI index has moderate predictive value compared to the original PG-SGA criteria in the survival prediction of patients with advanced cancers. The PG-SGA/ALI index would be an optimal biomarker for precise survival prediction in cancer patients in clinical practice.</p>

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Prognostic value of systemic inflammation-modified Patient-Generated Subjective Global Assessment in advanced cancers: A large-scale retrospective cohort study

  • 期刊论文

  • 发表日期：

    2025年10月13日

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  • Ge Song,
  • Tingting Dai,
  • Yu Min,
  • Haohan Fan,
  • Xuemei Li,
  • Zheran Liu,
  • Qian Yang,
  • Rong Jia,
  • Qiwei Yang,
  • Xiaolin Hu,
  • Yonglin Su,
  • Jitao Zhou

摘要

Background

A tight association between systemic inflammation and nutritional status has been established. We aim to evaluate the prognostic role of systemic inflammation-modified Patient-Generated Subjective Global Assessment (PG-SGA) criteria in advanced cancers.

Method

In this retrospective study, patients with advanced cancers were included from the West China Hospital between Nov 2019 and Sep 2023. Five systemic inflammatory indicators were selected, including the systemic inflammatory index (SII), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR), and advanced lung cancer inflammation index (ALI). Nutritional status was evaluated by the PG-SGA criteria. Kaplan–Meier curves, restricted cubic splines (RCS), and Cox regression analyses were used to estimate the effects of inflammation-modified PG-SGA index on the survival of cancer patients.

Results

In total, there were 1,065 patients with advanced cancers included in our study. The ALI showed better predictive power in predicting the all-cause mortality of patients with advanced cancers when compared with other systemic inflammation indicators (4th quartile: hazard ratio (HR) = 0.38, 95% confidence interval (CI): 0.29, 0.50, P < 0.001). The ALI-modified PG-SGA index showed the best survival prediction value in patients with advanced cancers, with an AUC of ROC of 0.68 for 365-day mortality, 0.65 for 730-day mortality, and 0.64 for 1,300-day survival prediction, respectively. The C-index (0.626), calibration curves, and decision curve analysis validated the promising predictive accuracy of the PG-SGA/ALI index in predicting the all-cause mortality of patients with advanced cancers. The sensitive analyses also supported the consistent findings as we determined in the main regression.

Conclusions

The findings highlight that considering the host systemic inflammation status during the nutrition assessment would bring additional benefits to the survival prediction of advanced cancers. The PG-SGA/ALI index has moderate predictive value compared to the original PG-SGA criteria in the survival prediction of patients with advanced cancers. The PG-SGA/ALI index would be an optimal biomarker for precise survival prediction in cancer patients in clinical practice.