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A new systemic nutrition-inflammation index predicted perioperative non-small cell lung cancer outcomes better than current nutrition and inflammation markers.

A novel tool called the systemic nutrition-inflammation index (SNII) predicted perioperative outcomes in patients with non-small cell lung cancer (NSCLC) better than existing nutrition and inflammation indicators, according to a study published online in BMC Medicine.

“This study introduces the SNII tool for assessing systemic nutrition/inflammation risk in [patients with NSCLC] and validated its predictive power for postoperative complications and recovery,” researchers wrote. “The SNII is recommended for preoperative nutrition/inflammation assessment and subsequent integration into perioperative management strategies.”

The SNII was developed using data from 1,497 patients who underwent video-assisted thoracoscopic lobectomy at two hospitals. Associations between patient outcomes and nutrition and inflammation measures from routine blood tests taken 1 week before surgery informed the tool’s development.

SNI Superiority in Development & Validation Cohorts

“In the development cohort, the SNII tool, calculated as the product of total cholesterol and total lymphocytes divided by total monocytes, demonstrated a stronger correlation with perioperative outcomes compared to 11 existing nutrition/inflammation indicators,” investigators wrote.

The tool classifies nutrition/inflammation risk into tertiles, with higher risk reflected in lower scores. In analyses, a low SNII score independently predicted the occurrence and severity of perioperative complications, prolonged chest tube duration, and hospital stay.

Researchers confirmed the findings in an external validation cohort that included 505 patients with NSCLC. When the study team combined the development and validation cohorts, they further confirmed the superiority of the SNII over other nutrition/inflammation indicators for predicting perioperative outcomes.

Using the SNI in Clinical Settings

Comprehensive subgroup analyses corroborated the SNII’s predictive performance and revealed heterogeneity across patient populations. For example, the tool’s correlation with perioperative outcomes was lower in patients with a history of smoking, a Charlson Comorbidity Index of 3 or higher, and squamous cell carcinoma. Its performance also weakened with increasing BMI. Researchers noted that the findings suggest a need to tailor the SNII to better accommodate the subpopulations.

Nevertheless, they recommended using the SNII in clinical practice to assess a patient’s surgical risk and, when indicated, prepare management strategies.

“High-risk patients may require more rigorous treatment strategies, including meticulous surgical techniques, optimal medical resources, early antimicrobial therapy, and aggressive nutritional support,” they wrote. “A preoperative intervention targeting poor nutrition and inflammation status over 2 weeks could be beneficial.”