Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition · 2025
Systematic inflammation burdens improve the survival prediction value of nutrition assessment in postoperative patients with recurrent or metastatic cancer: A retrospective observational study.
СтатьяНаблюдательное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Song Ge, Dai Tingting, Min Yu, Liu Xiaoxia, Yang Qiwei, Li Xuemei, Liu Zheran, Yang Qian, Jia Rong, Zhou Jitao, Peng Xingchen
Аннотация
BACKGROUND: The prognostic value of nutrition status assessed by the Patient-Generated Subjective Global Assessment (PG-SGA) in postoperative patients with recurrent or metastatic (R/M) cancer remains unclear. This study assessed whether combining PG-SGA-defined malnutrition with systemic inflammation indices improves mortality prediction accuracy.
METHODS: Nutrition status was evaluated via PG-SGA, with systemic inflammation assessed by systemic immune-related inflammation index (SII), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and monocyte to lymphocyte ratio (MLR). Kaplan-Meier and Cox regression analyses examined associations (individual/combined) of PG-SGA-defined malnutrition and systemic inflammation with all-cause mortality. Receiver operating characteristic curves and concordance index (C index) evaluated accuracy.
RESULTS: Among 537 postoperative patients with R/M cancer, multivariable Cox regression analysis showed malnutrition significantly increased mortality risk (malnourished: hazard ratio [HR] = 1.82 [95% CI, 1.23-2.72; P < 0.001]; severely malnourished: HR = 2.46 [95% CI, 1.67-3.62; P < 0.001]). In joint analysis, severely malnourished patients with high systemic inflammation burden had the highest overall mortality risks. The C index was 0.626 for PG-SGA-SII, 0.630 for PG-SGA-NLR, 0.618 for PG-SGA-PLR, and 0.630 for PG-SGA-MLR. Subgroup analyses revealed amplified composite risks in women, older adults, and those with chemotherapy history.
CONCLUSION: This study highlights the synergistic prognostic impact of PG-SGA-assessed malnutrition and systemic inflammation in postoperative R/M cancer, identifying a high-risk subgroup requiring prioritized nutrition and immunomodulatory interventions. Prospective multi-center validition is warranted.
METHODS: Nutrition status was evaluated via PG-SGA, with systemic inflammation assessed by systemic immune-related inflammation index (SII), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and monocyte to lymphocyte ratio (MLR). Kaplan-Meier and Cox regression analyses examined associations (individual/combined) of PG-SGA-defined malnutrition and systemic inflammation with all-cause mortality. Receiver operating characteristic curves and concordance index (C index) evaluated accuracy.
RESULTS: Among 537 postoperative patients with R/M cancer, multivariable Cox regression analysis showed malnutrition significantly increased mortality risk (malnourished: hazard ratio [HR] = 1.82 [95% CI, 1.23-2.72; P < 0.001]; severely malnourished: HR = 2.46 [95% CI, 1.67-3.62; P < 0.001]). In joint analysis, severely malnourished patients with high systemic inflammation burden had the highest overall mortality risks. The C index was 0.626 for PG-SGA-SII, 0.630 for PG-SGA-NLR, 0.618 for PG-SGA-PLR, and 0.630 for PG-SGA-MLR. Subgroup analyses revealed amplified composite risks in women, older adults, and those with chemotherapy history.
CONCLUSION: This study highlights the synergistic prognostic impact of PG-SGA-assessed malnutrition and systemic inflammation in postoperative R/M cancer, identifying a high-risk subgroup requiring prioritized nutrition and immunomodulatory interventions. Prospective multi-center validition is warranted.
Предметные рубрики MeSH
HumansNutrition AssessmentFemaleMaleRetrospective StudiesMiddle AgedInflammationAgedMalnutritionNutritional StatusNeoplasmsPrognosisPostoperative ComplicationsNeoplasm Recurrence, LocalPostoperative PeriodPredictive Value of TestsProportional Hazards ModelsNeoplasm MetastasisKaplan-Meier EstimateROC Curve