, Volume 36, Issue 11, pp 2742-2743
Date: 21 Jun 2012

Defining Optimal Cut-off Values and Research Methodology for Evaluating Systemic Inflammatory Markers in Clinical Outcome Prediction

Rent the article at a discount

Rent now

* Final gross prices may vary according to local VAT.

Get Access
This is an excerpt from the content

To the Editor,

We read with interest the article by Sato et al. [1], who have elegantly demonstrated the utility of a simple measure of systemic inflammation, the neutrophil to lymphocyte ratio (NLR), in response prediction for esophageal cancer patients undergoing neoadjuvant chemotherapy. As they say, it is a readily available, non-cumbersome test that neither depends on sophisticated analytic methods nor poses an excessive burden on resources.

Despite a number of studies in esophageal cancer demonstrating the usefulness of NLR measurements, in our opinion, there remain important issues still to be addressed. One is the somewhat confusing variance in optimal NLR cut-off levels which separate favorable from poor prognostic/predictive groupings. Sato et al. [1] must be congratulated as they have performed receiver operating characteristics (ROC) curve analysis to objectively define the optimal cut-off point within their data set, producing a discriminatory NLR of 2.2. Previous studies, h