Evidence map›Paper›PMID 33605059›Full record

ArticleJournal of cellular and molecular medicine2021

Serum macrophage inhibitory cytokine-1 as a clinical marker for non-small cell lung cancer.

Chunhua Xu, Li Li, Wei Wang, Qian Zhang, Xiuwei Zhang, Rusong Yang

Open access · goldAbstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 25% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Review
  5. Article
  6. Article
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 at 3 institutions in 1 country.

Chunhua XuDepartment of Respiratory Medicine, Nanjing Chest Hospital, Nanjing, China.ORCID 0000-0001-8728-2183
Li LiDepartment of Respiratory Medicine, Nanjing Chest Hospital, Nanjing, China.
Wei WangDepartment of Respiratory Medicine, Nanjing Chest Hospital, Nanjing, China.
Qian ZhangDepartment of Respiratory Medicine, Nanjing Chest Hospital, Nanjing, China.
Xiuwei ZhangDepartment of Respiratory Medicine, Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, China.
Rusong YangDepartment of Thoracic Surgery, Nanjing Chest Hospital, Nanjing, China.
Nanjing Brain Hospital · CNNanjing Chest Hospital · CNNanjing Jiangning Hospital · CN

Funding

Major Program of Nanjing Medical Science and Technique Development Foundation ZKX17044
6 · The paper itself

Abstract

The aim of this study was to investigate the value of serum macrophage inhibitory factor-1 (MIC-1) level in patients with non-small cell lung cancer (NSCLC). Serum samples from 296 patients with NSCLC and 240 healthy controls were collected. The levels of serum MIC-1 were determined by ELISA. The serum MIC-1 levels in NSCLC patients were higher than that of the controls (P <.001). Univariate and multivariate Cox regression analysis showed that serum MIC-1 was an independent prognostic indicator of OS and PFS. Serum MIC-1 is a valuable biomarker for the diagnosis and prognosis of NSCLC.

Indexed as

Biomarkers, TumorAdultAgedCarcinoma, Non-Small-Cell LungCase-Control StudiesEnzyme-Linked Immunosorbent AssayFemaleGrowth Differentiation Factor 15HumansKaplan-Meier EstimateLung NeoplasmsMaleMiddle AgedNeoplasm GradingNeoplasm StagingPrognosisBiomarkers, TumorGDF15 protein, humanGrowth Differentiation Factor 15diagnosismacrophage inhibitory cytokine-1non-small cell lung cancerprognosis

Identifiers

PMID33605059
PMCPMC7957168
OpenAlexW3130501999

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.