Evidence map›Paper›PMID 37342198›Full record

SynthesisFrontiers in oncology2023

Prognostic significance of systemic immune-inflammation index in patients with ovarian cancer: a meta-analysis.

Huaying Mao, Fan Yang

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 pooled it
5.7field-weighted citation impact, top 4% 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

20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 21 citations in OpenAlex.

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  20. Systemic Immune-Inflammatory Index as a Prognostic Biomarker in Patients with Heart Failure: A Comprehensive Analysis.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
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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

2 authors at 2 institutions in 1 country.

Huaying MaoClinical Laboratory, Huzhou Central Hospital, Affiliated Central Hospital of Huzhou University, Huzhou, Zhejiang, China.
Fan YangClinical Laboratory, Huzhou Maternity and Child Health Care Hospital, Huzhou, Zhejiang, China.
Huzhou Central Hospital · CNHuzhou Women and Children's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The prognosis of several malignancies has been influenced by the systemic immune-inflammation index (SII); however, its association with the prognostic outcome of ovarian cancer (OC) remains controversial. The present meta-analysis focused on the systemic and comprehensive identification of the role of SII in predicting OC prognosis. Methods: We searched the Web of Science, PubMed, Cochrane Library, Embase, and China National Knowledge Infrastructure (CNKI) from inception until March 6, 2023. To predict the prognostic value of SII for overall survival (OS) and progression-free survival (PFS) in patients with OC, we calculated pooled hazard ratios (HRs) and corresponding 95% confidence intervals (CIs). Results: The meta-analysis included six studies involving 1546 patients. The combined results showed that a high SII was significantly associated with poor OS (HR=2.70, 95% CI=1.98-3.67, p<0.001) and poor PFS (HR=2.71, 95% CI=1.78-4.12, p<0.001) in OC patients. These results were confirmed using subgroup and sensitivity analyses. Conclusion: Our results concluded that a high SII significantly predicted poor OS and PFS in patients with OC. Therefore, it can be speculated that the SII may have an independent effect on the prognosis of OC.

Indexed as

meta-analysisovarian cancerprognosisSIIsurvival

Identifiers

PMID37342198
PMCPMC10277625
OpenAlexW4379470720

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.