Nutritional status in retroperitoneal sarcoma: Implication of prognostic Nutritional Index (PNI) and skeletal muscle index (SMI) on postoperative and oncological outcomes.

BACKGROUND AND AIMS: Nutritional status is a critical yet underexplored factor in retroperitoneal sarcoma (RPS) care. Traditional anthropometric indicators such as BMI are unreliable in this setting due to tumor-related weight masking. This study aimed to assess the prognostic impact of preoperative nutritional status in RPS patients using the Prognostic Nutritional Index (PNI) and Skeletal Muscle Index (SMI).

METHODS

A retrospective cohort study was conducted on 250 RPS patients treated at a high-volume sarcoma centre between 2010 and 2023. Nutritional status was assessed preoperatively via PNI (malnutrition) and CT-derived SMI (sarcopenia). Associations with postoperative complications and oncological outcomes were analysed using logistic and Cox regression models.

RESULTS

Malnutrition and sarcopenia were observed in 50.2 % and 53.2 % of patients, respectively. BMI did not correlate with either PNI or SMI. Malnutrition, but not sarcopenia, was independently associated with increased severe postoperative complications (OR 2.128, p = 0.021). On survival analysis, malnutrition was significantly associated with reduced overall survival (OS) in both primary (HR 1.762, p = 0.043) and recurrent (HR 4.000, p = 0.001) tumors. Among patients with favorable Sarculator-derived prognosis (5-year OS ≥ 60 %), malnutrition stratified survival outcomes (log-rank p = 0.044). Conversely, in poor-prognosis patients (Sarculator <60 %), the impact of malnutrition was not statistically significant. SMI correlated with OS as a continuous variable (p = 0.043), but predefined sarcopenia thresholds failed to predict outcomes.

CONCLUSION

PNI is a reliable and accessible tool for identifying malnutrition and predicting outcomes in RPS patients. Integration of nutritional assessment into preoperative pathways and the development of RPS-specific SMI cut-offs may improve risk stratification and patient management.