Evidence map›Paper›PMID 36684163›Full record

ReviewFrontiers in surgery2022

Prognostic and clinicopathological value of the geriatric nutritional risk index in gastric cancer: A meta-analysis of 5,834 patients.

Liang He, Ying Li, Linlin Qu, Fan Zhang

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
2.6field-weighted citation impact, top 10% 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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 10 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Liang HeDepartment of Gastrointestinal Surgery, The First Hospital of Jilin University, Changchun, China.
Ying LiDepartment of Gastroenterology, The First Hospital of Jilin University, Changchun, China.
Linlin QuDepartment of Clinical Laboratory, The First Hospital of Jilin University, Changchun, China.
Fan ZhangDepartment of Gastroenterology, The First Hospital of Jilin University, Changchun, China.
First Hospital of Jilin University · CNJilin University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Recent studies have explored the prognostic value of the geriatric nutritional risk index (GNRI) in patients with gastric cancer (GC), but the results are controversial. We aimed to systemically identify the association between the GNRI and prognosis in GC using a meta-analysis. Methods: The databases of PubMed, Web of Science, Cochrane Library, and Embase were searched until September 25, 2022. Pooled hazard ratios and the corresponding 95% confidence intervals (CIs) were used to estimate the prognostic value of the GNRI in GC. Odds ratios (ORs) and 95% CIs were used to assess the correlation between the GNRI and clinicopathological characteristics of GC. Results: Ten studies including 5,834 patients with GC were included in this meta-analysis. The merged results indicated that a low pretreatment GNRI was associated with inferior overall survival (hazard ratio = 1.21, 95% CI = 1.12-1.30, Conclusion: Our meta-analysis identified that the pretreatment GNRI level was a significant prognostic factor for patients with GC. A low GNRI is associated with worse overall survival and inferior cancer-specific survival in patients with GC.

Indexed as

gastric cancergeriatric nutritional risk indexmeta-analysisprognosisrisk factors

Identifiers

PMID36684163
PMCPMC9852775
OpenAlexW4313641398

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.