Peripheral platelet/lymphocyte ratio predicts lymph node metastasis and acts as a superior prognostic factor for cervical cancer when combined with neutrophil: Lymphocyte.

Inflammation-based indicators such as neutrophil/lymphocyte ratio (NLR), derived NLR (dNLR), and platelet/lymphocyte ratio (PLR) have been reported to possess significant predictive value for several types of cancer. We investigated the predictive value of these 3 biomarkers on lymph node metastasis (LNM) and clinical outcome in patients with stage Ib1-IIa cervical cancer undergoing radical surgery.A total of 407 patients with FIGO stage Ib1-IIa cervical cancer, who underwent radical surgery between January 2006 and December 2009 at the Department of Gynecological and Oncology of Shandong Cancer Hospital Affiliated to Shandong University were recruited. Binary logistic regression analysis was performed to determine the relationship between PLR, NLR, dNLR, and LNM. Multivariate Cox regression analysis was performed to determine the association between the 3 indices and recurrence-free survival (RFS) and overall survival (OS).Optimal cut-off values for the 3 indices were determined by applying receiver operating curve (ROC) analysis. Univariate and binary logistic regression analyses both indicate that PLR was significantly associated with increased LNM (P < 0.05). In the multivariate survival analysis, increased preoperative PLR and NLR were significantly associated with reduced RFS (P = 0.001 and P = 0.002, respectively), whereas a combination of both PLR and NLR revealed a more significant association with reduced RFS (P < 0.001). Furthermore, increased preoperative PLR and NLR were significantly associated with reduced OS (P = 0.007 and P = 0.009, respectively), whereas the combined use of PLR and NLR revealed a more significant association with reduced OS (P = 0.003).PLR is an independent risk factor for increased LNM and clinical outcome in patients with stage Ib1-IIa cervical cancer. A combination of PLR and NLR may enable better risk stratification for predicting survival.