Evidence map›Paper›PMID 34764670›Full record

ArticleJournal of inflammation research2021

The Efficacy of Different Inflammatory Markers for the Prognosis of Patients with Malignant Tumors.

Kaiwen Zheng, Xiangliang Liu, Wei Ji, Jin Lu, Jiuwei Cui, Wei Li

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Article in Journal of inflammation research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 6 pooled it
–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

24 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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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

6 authors.

Kaiwen Zheng *Cancer Center, the First Hospital of JiLin University, Changchun, Jilin, People's Republic of China.ORCID 0000-0001-9801-4897
Xiangliang Liu *Cancer Center, the First Hospital of JiLin University, Changchun, Jilin, People's Republic of China.
Wei Ji *Cancer Center, the First Hospital of JiLin University, Changchun, Jilin, People's Republic of China.
Jin LuCancer Center, the First Hospital of JiLin University, Changchun, Jilin, People's Republic of China.
Jiuwei CuiCancer Center, the First Hospital of JiLin University, Changchun, Jilin, People's Republic of China.
Wei LiCancer Center, the First Hospital of JiLin University, Changchun, Jilin, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInflammation is considered essential in cancer progression, as it affects the nutritional status and prognosis of patients. In this study, we aim to analyze the efficacy of various inflammatory markers in predicting prognosis in cancer patients.

methodsPatients with malignant tumor were included as primary and validation cohort. Basic clinical information, anthropometric indicators, body composition analysis, and serological indicators were recorded. After proposing the optimal thresholds by time-dependent receiver operating characteristic (ROC), univariate and multivariate Cox regression analyses were performed to analyze the association between inflammatory markers and overall survival (OS). A nomogram was established to develop a scored-inflammatory marker system. Eight inflammatory models based on combinations of inflammatory markers were assessed. Cox regression analysis was used to analyze the relationship of each inflammatory model and mortality of participants. Then, subanalysis of specific tumor types was conducted by Cox regression. Logistic regression models were used to analyze the relationship between different inflammatory models and malnutrition.

resultsUnivariate and multivariate Cox regression analyses indicated that pack-years of cigarette smoking, C-reactive protein (CRP), and systemic immune-inflammation index (SII) were related to the OS of cancer patients. A nomogram was constructed to develop a scored-inflammatory marker system. Among the eight inflammatory models, patients in model A had worst prognosis compared with patients in other models. Subanalysis next showed lung cancer, breast cancer and digestive system neoplasms patients in model A suffered the worst prognosis. Logistic regression indicated that model A was also with predictive value for malnutrition.

conclusionA scored-inflammatory marker system was established to predict the OS of cancer patients. The inflammatory models established in this study can be used to predict prognosis, as well as cancer-related malnutrition. Inflammatory model A suffered the worst OS and was with the predictive efficacy for malnutrition.

Indexed as

cancerinflammatory markersnutritional statusoverall survival

Identifiers

PMID34764670
PMCPMC8573157

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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.