Evidence map›Paper›PMID 32241019›Full record

SynthesisPloS one2020

The clinicopathological and prognostic value of the pretreatment neutrophil-to-lymphocyte ratio in small cell lung cancer: A meta-analysis.

Yan Lu, JinWen Jiang, ChaoXiang Ren

Abstract readMeta-Analysis
In one paragraph

Synthesis in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 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

22 citing papers in PubMed, 2 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

3 authors.

Yan LuClinical Laboratory, DongYang People's Hospital, Dongyang, Zhejiang, China.ORCID 0000-0001-8153-7149
JinWen JiangClinical Laboratory, DongYang People's Hospital, Dongyang, Zhejiang, China.
ChaoXiang RenClinical Laboratory, DongYang People's Hospital, Dongyang, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although many scholars have recently studied the relationships between the pretreatment neutrophil-to-lymphocyte ratio (NLR) and prognosis in patients with small cell lung cancer (SCLC), the conclusions have been inconsistent. Accordingly, in this meta-analysis, we attempted to assess the clinicopathological and prognostic value of the pretreatment NLR in SCLC. Related literature was searched using PubMed, Embase, Cochrane Library, Web of Science, Chinese Biomedical Literature, China National Knowledge Infrastructure (CNKI), and Wanfang databases. Each eligible study was extracted, and a meta-analysis was performed using hazard ratios (HRs) and 95% confidence intervals (95% CIs) to assess the prognostic value of NLR. Evaluation of the clinicopathological significance of NLR in SCLC used odds ratios (ORs) and 95% confidence intervals (95% CIs). We included a total of 20 studies with 21 outcomes (5141 patients) in this meta-analysis. The results showed that high pretreatment NLR was closely related to poorer progression free survival (PFS) and overall survival (OS) (PFS, HR = 1.55, 95% CI = 1.27-1.88, P < 0.0001; I2 = 0%; OS, HR = 1.40, 95% CI = 1.26-1.55, P < 0.00001; I2 = 64%). In addition, pretreatment NLR was significantly associated with clinical stage of SCLC (OR = 2.14, 95% CI = 1.35-3.39, P = 0.001). Our meta-analysis showed that high levels of pretreatment NLR were significantly associated with a more serious clinical stage and poorer PFS and OS in SCLC.

Indexed as

AdolescentAdultAgedAged, 80 and overChinaDisease-Free SurvivalFemaleHumansLeukocyte CountLung NeoplasmsLymphocyte CountLymphocytesMaleMiddle AgedNeutrophilsOdds Ratio

Identifiers

PMID32241019
PMCPMC7117946

What OpenQuestion holds

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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.