Evidence map›Paper›PMID 36852672›Full record

ArticleJournal of cachexia, sarcopenia and muscle2023

The inflammatory burden index is a superior systemic inflammation biomarker for the prognosis of non-small cell lung cancer.

Hailun Xie, Guotian Ruan, Lishuang Wei, Li Deng, Qi Zhang, Yizhong Ge, Mengmeng Song, Xi Zhang, Shiqi Lin, Xiaoyue Liu and 4 more

Abstract read
In one paragraph

Article in Journal of cachexia, sarcopenia and muscle, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers.

0numbers the graph read from it
0cells of the map it votes in
78citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

78 citing papers in PubMed.

  1. Article
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  3. ALNCR.TNM as a Novel Prognostic Tool for Cancer Survival.Journal of cachexia, sarcopenia and muscle · 2026
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18 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Hailun XieDepartment of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Guotian RuanDepartment of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Lishuang WeiDepartment of Geriatric Respiratory Disease Ward, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, China.
Li DengDepartment of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Qi ZhangDepartment of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Yizhong GeDepartment of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Mengmeng SongDepartment of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Xi ZhangDepartment of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Shiqi LinDepartment of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Xiaoyue LiuDepartment of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Ming YangDepartment of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Chunhua SongDepartment of Epidemiology, College of Public Health, Zhengzhou University, Zhenzhou, China.
Xiaowei ZhangDepartment of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Hanping ShiDepartment of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0003-4514-8693

Funding

Beijing Municipal Science and Technology Commission SCW2018-06National Key Research and Development Program 2022YFC2009600
6 · The paper itself

Abstract

backgroundSystemic inflammation, the most representative tumour-host interaction, plays a crucial role in disease progression and prognosis in patients with non-small cell lung cancer (NSCLC). Few studies have compared the performance of existing haematological systemic inflammation biomarkers in predicting the prognosis of NSCLC patients. The purpose of this study was to compare the prognostic value of existing systemic inflammation biomarkers and determine the optimal systemic inflammation biomarker in patients with NSCLC through a multicentre prospective study.

methodsThe predictive accuracy of systemic inflammation biomarkers for prognostic assessment in NSCLC was assessed using C-statistics. Inter-group differences in survival were assessed using the log-rank test and visualized using the Kaplan-Meier method. A restricted cubic spline (RCS) curve was used to explore the association between the biomarkers and survival. Independent prognostic biomarkers for overall survival were determined using multivariable Cox proportional hazards regression analysis. Logistic regression analysis was used to determine independent predictors of 90-day outcomes, length of hospitalization, hospitalization expenses and cachexia.

resultsThe inflammatory burden index (IBI) had the highest C-statistic for predicting the prognosis of patients with NSCLC, reaching 0.640 (0.617, 0.663). Patients with a high IBI had significantly worse outcomes than those with a low IBI (35.46% vs. 57.22%; log-rank P < 0.001). The IBI was also able to differentiate the prognosis of patients with NSCLC with the same pathological stage. The RCS curve showed an inverted L-shaped dose-response relationship between the IBI and survival of patients with NSCLC. Multivariable Cox proportional hazards regression analysis showed that a high IBI was an independent risk factor for death of patients with NSCLC (hazard ratio = 1.229, 95% confidence interval [CI]: 1.131-1.335, P < 0.001). A high IBI was an independent predictor of 90-day outcomes (odds ratio [OR] = 1.789, 95% CI: 1.489-2.151, P < 0.001), prolonged hospital stays (OR = 1.560, 95% CI: 1.256-1.938, P < 0.001), high hospitalization expenses (OR = 1.476, 95% CI: 1.195-1.822, P < 0.001) and cachexia (OR = 1.741, 95%CI = 1.374-2.207, P < 0.001) in patients with NSCLC.

conclusionsThe IBI was independently associated with overall survival, 90-day outcomes, length of hospitalization, hospitalization expenses and cachexia in NSCLC patients. As an optimal systemic inflammation biomarker, the IBI has broad clinical application prospects in predicting the prognosis of patients with NSCLC.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsBiomarkersCachexiaHumansInflammationPrognosisProspective StudiesBiomarkersBiomarkerCachexiaExpensesNon-small cell lung cancerPrognosisSystemic inflammation

Identifiers

PMID36852672
PMCPMC10067487

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.