Evidence map›Paper›PMID 34522127›Full record

ArticleInternational journal of general medicine2021

The Prognostic Value of Biomarkers on Detecting Non-Small Cell Lung Cancer in a Chinese Elderly Population.

Lianghua Guo, Bin Song, Jianhong Xiao, Hui Lin, Junhua Chen, Xianghua Su

Open access · goldAbstract read
In one paragraph

Article in International journal of general medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 34% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Lung Cancer: New Directions in Senior Patients Assessment.Geriatrics (Basel, Switzerland) · 2024
    Review
  2. 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 1 institution in 1 country.

Lianghua GuoDepartment of Respiratory Medicine, Mindong Hospital of Fujian Medical University, Fuan City, 355000, People's Republic of China.
Bin SongDepartment of Respiratory Medicine, Mindong Hospital of Fujian Medical University, Fuan City, 355000, People's Republic of China.
Jianhong XiaoDepartment of Respiratory Medicine, Mindong Hospital of Fujian Medical University, Fuan City, 355000, People's Republic of China.
Hui LinDepartment of Respiratory Medicine, Mindong Hospital of Fujian Medical University, Fuan City, 355000, People's Republic of China.
Junhua ChenDepartment of Respiratory Medicine, Mindong Hospital of Fujian Medical University, Fuan City, 355000, People's Republic of China.
Xianghua SuDepartment of Neurosurgery, Mindong Hospital of Fujian Medical University, Fuan City, 355000, People's Republic of China.
Fujian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSurvival in non-small cell lung cancer (NSCLC) remains poor. Early detection of NSCLC is of great significance to provide a chance to improve survival.

aimWe constructed predictive models to evaluate the predictive value of four tumor biomarkers by including serum human epididymis protein 4 (HE4), carcinoembryonic antigen (CEA), squamous cell carcinoma antigen (SCCA), and cytokeratin 19 fragment (CY21-1) on detecting NSCLC in a Chinese elderly population.

methodsA total of 363 patients with NSCLC and 433 subjects without cancer (healthy control group) were admitted to the respiratory department in our hospital. We assessed serum levels of these four tumor biomarkers in the two groups and then the predictive value of predictive models was evaluated.

resultsSerum median values of HE4 (143.3 pmol/L), CEA (4.60 ng/mL), SCCA (1.52 ng/mL), and CY21-1 (5.36 ng/mL) in patients with NSCLC were significantly higher than the healthy control group, respectively (all

conclusionOur study showed that several lung cancer-related biomarkers were used to build prediction models, which has good value for early prediction of NSCLC.

Indexed as

CEAChinese elderly populationCY21-1HE4NSCLCpredictive valueSCCA

Identifiers

PMID34522127
PMCPMC8434877
OpenAlexW3198084009

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.