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Original Article
- Clinical Implications of the Cut-off Value of the Preoperative Prognostic Nutritional Index in Patients with Early Stage Gastric Cancer
- Ji Hye Jung, Ji Yeong An, You Na Kim, Min Gew Choi, Jun Ho Lee, Tae Sung Sohn, Jae Moon Bae, Sung Kim
- Surg Metab Nutr 2019;10(2):59-65. Published online December 30, 2019
- DOI: https://doi.org/10.18858/smn.2019.10.2.59
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Abstract
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ePub Purpose:
The perioperative nutritional status is a potential prognostic factor in gastric cancer patients. This study assessed the optimal cut-off value of the prognostic nutritional index (PNI) for predicting the survival of patients with early stage gastric cancer and evaluated its power for predicting the survival after gastric cancer surgery.
Materials and Methods:
This study reviewed the data of 8,014 patients with stage T1N0~1M0 and T2~3N0M0 gastric cancer who underwent a curative gastrectomy without adjuvant chemotherapy between January 2006 and December 2015. The log-rank test on SAS was conducted to determine the preoperative PNI cut-off value that indicated the most significant difference in survival, and the clinical features and oncological outcomes were analyzed according to the cut-off value of the preoperative PNI.
Results:
The preoperative PNI cut-off value that indicated the most significant difference in survival was 43.7. Using this cut-off value, patients were classified into high PNI and low PNI groups. The five-year overall survival rate was 96.9% and 81.5% for the high and low PNI group, respectively (P<0.001). Considering each stage (Ia, Ib, and IIa), the overall survival rates were significantly higher for the high PNI group than the low PNI group. Multivariable analysis revealed the cut-off value of the preoperative PNI to be among the independent risk factors for survival.
Conclusions:
The cut-off value of the preoperative PNI that could be used to determine the significant differences in the survival of patients with early stage gastric cancer was identified and proven to have a significant impact on predicting survival.
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