Comparison of clinical utilities of the platelet count and platelet-lymphocyte ratio for predicting survival in patients with cervical cancer: a single institutional study and literature review

OBJECTIVE To compare the clinical utilities of the platelet count and platelet-lymphocyte ratio (PLR) for predicting survival in patients with cervical cancer. RESULTS Multivariate analyses demonstrated that thrombocytosis and elevated PLR were found to be independent prognostic factors for progression-free survival (PFS, P = 0.0077, P = 0.044) and overall survival (OS, P = 0.025, P = 0.019) in separate Multivariate analyses. In the ROC analysis, the platelet count showed a significantly greater area under the ROC curve (AUC) value than that of PLR for predicting patient recurrence (0.5941 versus 0.5331, p = 0.018) and survival (0.6139 versus 0.5468, p = 0.029). In patients without thrombocytosis, elevated PLR correlated with shorter survival (PFS, P = 0.041; OS, P = 0.017). In contrast, PLR in patients with thrombocytosis did not provide prognostic information. We divided patients into 3 prognostic groups using platelet counts and PLR: high-risk (thrombocytosis with any PLR); intermediate-risk (elevated PLR without thrombocytosis); low-risk (none of the above), which allowed for individualized and accurate survival estimates. MATERIALS AND METHODS The baseline characteristics and clinical outcomes of cervical cancer patients were identified. Patients were grouped according to their pretreatment platelet counts or PLR, and clinicopathological characteristics and patient survival were then compared between these groups. The clinical utilities of the platelet count and PLR were compared using a time-dependent receiver operating characteristic (ROC) analysis. CONCLUSIONS Pretreatment thrombocytosis and elevated PLR were identified as independent predictors in cervical cancer patients. Platelet counts were superior to PLR for predicting the prognosis of uterine cervical cancer patients. Our prognostic model consisting of platelet counts and PLR offers individualized survival estimates.