The impact of Red Cell Distribution Width and Neutrophil/Lymphocyte Ratio on Long-term Survival after Pulmonary Resection for Non-Small Cell Lung Cancer


Uysal S., Sahinoglu T., KUMBASAR U. , DEMİRCİN M. , PAŞAOĞLU İ. , DOĞAN R.

UHOD-ULUSLARARASI HEMATOLOJI-ONKOLOJI DERGISI, vol.26, no.2, pp.69-74, 2016 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 26 Issue: 2
  • Publication Date: 2016
  • Doi Number: 10.4999/uhod.161246
  • Title of Journal : UHOD-ULUSLARARASI HEMATOLOJI-ONKOLOJI DERGISI
  • Page Numbers: pp.69-74

Abstract

Red cell distribution width (RDW) and Neutrophil/Lymphocyte Ratio (NLR) are widely available blood tests which can be used to reflect patients' inflammatory status. We investigated the effects of RDW and NLR levels on long-term survival after pulmonary resection for non-small cell lung cancers. Data were compiled retrospectively from 249 patients. We found a significant correlation between higher RDW and NLR levels and poorer prognosis. Overall survival rates of patients with high and normal RDW levels were 42 +/- 7 and 84 +/- 12 months, respectively (p= 0.019). In addition, disease free survival rates of patients with high and normal RDW levels were 62 +/- 6 and 76 +/- 4 months (p= 0.047), respectively. When NLR levels were divided into tertiles we observed significantly poorer overall and disease free survival in ascending tertiles. The overall and disease free survival rates in the lower through upper tertiles were; 88 +/- 6, 80 +/- 6, 50 +/- 5 months for overall and 87 +/- 6, 77 +/- 6, 47 +/- 5 months for disease free survival (p< 0.001). In conclusion, the ability to accurately predict sub-sets with poorer outcomes among patients who had undergone pulmonary resection for non-small cell lung cancers is important. RDW and NLR are biomarkers which could influence patients categorization in this regard. Preoperative measurement of these potential markers are simple, adds no additional cost to routine preoperative workup and can be used to identify patients with poorer prognosis.