Novel inflammation-based prognostic index for predicting survival outcomes in patients with gastric cancer

Author:

Hirahara Noriyuki1,Matsubara Takeshi1,Kaji Shunsuke2,Hayashi Hikota1,Sasaki Yohei3,Kawakami Koki2,Hyakudomi Ryoji1,Yamamoto Tetsu1,Tanaka Wataru2,Tajima Yoshitsugu1

Affiliation:

1. Shimane University Faculty of Medicine

2. Matsue Red Cross Hospital

3. Masuda Red Cross Hospital

Abstract

Abstract Background We focused on the lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) and devised an inflammation-based prognostic index (IBPI) as a prognostic marker of cancer-specific survival (CSS).MethodsWe reviewed the clinicopathological data of 480 patients with gastric cancer undergoing curative laparoscopic gastrectomy between January 2009 and December 2019. This study examined the significance of LMR, NLR, PLR, and IBPI as cancer-specific prognostic markers.ResultsIn univariate analysis, tumor diameter, histological differentiation, pathological tumor-node-metastasis (pTNM) stage, LMR, NLR, PLR, C-reactive protein (CRP) level, carcinoembryonic antigen (CEA), and postoperative chemotherapy were significantly associated with CSS. In multivariate analysis, pTNM stage and CEA were the independent risk factors for CSS, although LMR, NLR, and PLR were not the independent risk factors for CSS. The IBPI formula was constructed using hazard ratios for three inflammation-based biomarkers with worse prognosis identified in the univariate analysis: LMR < 4.315, NLR ≥ 2.344, and PLR ≥ 212.01, which were each pointed as 1, with all remaining values pointed at 0. IBPI was calculated as follows: IBPI = 2.9 × LMR + 2.8 × NLR + 2.8 × PLR. The optimal cutoff value of IBPII was 2.9. On multivariate analysis, pTNM stage, CEA, and IBPI were independent prognostic factors for CSS. In the Kaplan–Meier survival analysis, CSS in the high IBPI group was significantly worse than that in the low IBPI group.ConclusionIBPI was devised as a novel predictive index for prognosis, and its usefulness was clarified.

Publisher

Research Square Platform LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3