Comprehensive Analysis of the Neutrophil-to-Lymphocyte Ratio for Preoperative Prognostic Prediction Nomogram in Gastric Cancer.
retrospective_cohort · Level III
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- Record sourced from PubMed, PMID 29392430.
- Also identified by DOI 10.1007/s00268-018-4510-4.
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Abstract
The role of neutrophil-to-lymphocyte ratio (NLR) and preoperative prediction model in gastric cancer is controversial, while postoperative prognostic models are available. This study investigated NLR as a preoperative prognostic indicator in gastric cancer. We reviewed patients with primary gastric cancer who underwent surgery during 2007-2010. Preoperative clinicopathologic factors were analyzed with their interaction and used to develop a prognosis prediction nomogram. That preoperative prediction nomogram was compared to a nomogram using pTNM or a historical postoperative prediction nomogram. The contribution of NLR to a preoperative nomogram was evaluated with integrated discrimination improvement (IDI). Using 2539 records, multivariable analysis revealed that NLR was one of the independent prognostic factors and had a significant interaction with only age among other preoperative factors (especially significant in patients < 50 years old). NLR was constantly significant between 1.1 and 3.1 without any distinctive cutoff value. Preoperative prediction nomogram using NLR showed a Harrell's C-index of 0.79 and an R<sup>2</sup> of 25.2%, which was comparable to the C-index of 0.78 and 0.82 and R<sup>2</sup> of 26.6 and 25.8% from nomogram using pTNM and a historical postoperative prediction nomogram, respectively. IDI of NLR to nomogram in the overall population was 0.65%, and that of patients < 50 years old was 2.72%. NLR is an independent prognostic factor for gastric cancer, especially in patients < 50 years old. A preoperative prediction nomogram using NLR can predict prognosis of gastric cancer as effectively as pTNM and a historical postoperative prediction nomogram.
Medical subject headings
- Lymphocytes
- Neutrophils
- Nomograms
- Stomach Neoplasms