Combining the Fibrinogen/Albumin Ratio and Systemic Inflammation Response Index Predicts Survival in Resectable Gastric Cancer
Junbin Zhang, Yongfeng Ding, Weibin Wang, Yimin Lu, Haiyong Wang, Haohao Wang, Lisong Teng
Abstract
Aims . Predicting the prognosis of gastric cancer using tumour-node-metastasis (TNM) staging is difficult as patients with the same TNM stage exhibit different prognoses. Methods . This study investigated the prognostic value of the preoperative fibrinogen/albumin ratio (FAR)-systemic inflammation response index (SIRI) score in resectable gastric cancer (rGC). Results . Clinicopathological features of 231 rGC patients were analysed retrospectively. Patients were divided into three groups: FAR-SIRI score 2 (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mtext>FAR</mml:mtext><mml:mo>≥</mml:mo><mml:mn>0.071</mml:mn></mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mtext>SIRI</mml:mtext><mml:mo>≥</mml:mo><mml:mn>0.84</mml:mn></mml:math>), 1 (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mtext>FAR</mml:mtext><mml:mo><</mml:mo><mml:mn>0.071</mml:mn></mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M4"><mml:mtext>SIRI</mml:mtext><mml:mo>≥</mml:mo><mml:mn>0.84</mml:mn></mml:math>), and 0 (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M5"><mml:mtext>SIRI</mml:mtext><mml:mo><</mml:mo><mml:mn>0.84</mml:mn></mml:math>). Higher FAR-SIRI scores were associated with larger tumours, poorer differentiation, and advanced TNM stage (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M6"><mml:mi>P</mml:mi><mml:mo><</mml:mo><mml:mn>0.05</mml:mn></mml:math>). Compared to those with FAR-SIRI scores of 0, patients with scores of 2 had poorer overall survival (OS). The FAR-SIRI score was an independent prognostic factor for OS in rGC. Conclusion . The present data demonstrated that FAR-SIRI scores predicted radical gastric cancer surgical outcomes and may serve as a blood marker for identifying high-risk patients.