Evidence map›Paper›PMID 34593492›Full record

SynthesisBMJ open2021

Inflammation and nutrition-based biomarkers in the prognosis of oesophageal cancer: a systematic review and meta-analysis.

Yan Jiang, Dian Xu, Huan Song, Beibei Qiu, Dan Tian, Zhongqi Li, Ye Ji, Jianming Wang

Open access · goldAbstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 101 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
101citing papers in PubMed, 8 pooled it
8.9field-weighted citation impact, top 1% of its field
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

101 citing papers in PubMed, 8 syntheses or guidelines pooled it, 129 citations in OpenAlex.

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  14. Influence of dietary intake and eating patterns on reactive hypoglycemic events in patients postesophagectomy: A prospective observational study using continuous glucose monitoring.Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition · 2026
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41 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

8 authors at 2 institutions in 1 country.

Yan Jiang *Department of Epidemiology, Nanjing Medical University, Nanjing, China.ORCID 0000-0001-7312-8708
Dian Xu *Department of Epidemiology, Nanjing Medical University, Nanjing, China.
Huan Song *Department of Epidemiology, Nanjing Medical University, Nanjing, China.
Beibei QiuDepartment of Epidemiology, Nanjing Medical University, Nanjing, China.ORCID 0000-0002-7053-7503
Dan TianDepartment of Epidemiology, Nanjing Medical University, Nanjing, China.
Zhongqi LiDepartment of Epidemiology, Nanjing Medical University, Nanjing, China.
Ye JiDepartment of Epidemiology, Nanjing Medical University, Nanjing, China.
Jianming WangDepartment of Epidemiology, Nanjing Medical University, Nanjing, China jmwang@njmu.edu.cn.ORCID 0000-0002-9151-284X
Nanjing Medical University · CNNingbo Center for Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccumulating literature has shown the predictive values of inflammation and nutrition-based biomarkers in the prognosis of oesophageal cancer but with inconsistent findings.

methodWe performed a meta-analysis to systematically evaluate the predictive value of the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), C reactive protein-to-albumin ratio (CAR), systemic inflammation index (SII), prognostic nutritional index (PNI), Glasgow Prognostic Score (GPS) and modified Glasgow Prognostic Score (mGPS) in oesophageal cancer. The outcome indicators include the overall survival (OS), disease-free survival (DFS) and cancer-specific survival (CSS). We applied pooled HR, sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the curve together with 95% CI to estimate the predictive accuracy.

resultsA total of 72 studies, including 22 260 patients, were included in the meta-analysis. Elevated NLR, PLR CAR, SII, GPS, mGPS and decreased LMR and PNI were associated with poor OS of oesophageal cancer. A high level of NLR, PLR and GPS was related to poor DFS. A high level of NLR and GPS was related to poor CSS. The summarised AUC of CAR (0.72, 95% CI: 0.68 to 0.75) and mGPS (0.75, 95% CI: 0.71 to 0.78) surpassed any other indicators.

conclusionsClinical indicators such as NLR, PLR, LMR, PNI, SII, CAR, GPS and mGPS have the moderate predictive ability in OS, DFS and CSS of oesophageal cancer. The pretreatment level of CAR and mGPS showed an outstanding prediction value in 5-year OS for oesophageal cancer.

Indexed as

Esophageal NeoplasmsInflammationBiomarkersHumansLymphocytesNeutrophilsPrognosisRetrospective StudiesBiomarkersgastrointestinal tumoursinflammatory bowel diseasenutritional support

Identifiers

PMID34593492
PMCPMC8487212
OpenAlexW3204083801

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.