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Platelet to lymphocyte ratio and red cell distribution width as prognostic factors for survival and recurrence in patients with oral cancer.

Manupol TangthongkumSireethorn TiyanuchitVirat KirtsreesakulPasawat SupanimitjaroenpornWattana Sinkitjaroenchai
Published in: European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery (2017)
Although platelet to lymphocyte ratio (PLR) and red cell distribution width (RDW) have been reported as good predictors for survival outcomes in various cancers, there is limited data supporting these as reliable predictors in oral cancer. This study thus aimed to assess the prognostic value of PLR and RDW markers in predicting survival and recurrence rates in patients with oral cancer. The records of 374 oral cancer patients treated with curative intent over a 7-year period (2009-2015) were reviewed. Survival and recurrence outcomes were compared between those with low and high PLR (≤135 vs. >135) and those with low and high RDW (≤14.05 vs. >14.05) using hazard ratios (HR). The 5-year disease-specific survival was significantly higher and recurrence rate significantly lower among the low PLR group compared to the high PLR group (65.7 vs. 37.6%; p < 0.001 and 34.4 and 57.5%; p < 0.001), respectively. There were no significant differences between the low and high RDW groups for disease-specific survival (53.6 vs. 54.7%, p = 0.408) and recurrence (40.0% vs. 53.8%, p = 0.079). Multivariate analysis showed that PLR was associated with disease-specific survival (HR = 2.05, p < 0.001) and recurrence (HR = 1.69, p < 0.005) after adjusting for other factors, but not RDW. High PLR shows promise as a prognostic predictor for poor survival and recurrence in patients with oral cancer, but further studies are required. RDW has no prognostic value on any outcome.
Keyphrases
  • free survival
  • prognostic factors
  • single cell
  • type diabetes
  • adipose tissue
  • skeletal muscle
  • rectal cancer
  • bone marrow
  • artificial intelligence
  • insulin resistance
  • glycemic control