Evidence map›Paper›PMID 32481437›Full record

ArticleMedicine2020

Evaluation of predictive role of carcinoembryonic antigen and salivary mRNA biomarkers in gastric cancer detection.

Fei Xu, Meiquan Jiang

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 33% 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

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

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Review
  6. Review
  7. Review
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 1 institution in 1 country.

Fei XuDepartment of Digestive Medicine.
Meiquan JiangDepartment of General Surgery, PKUCare Luzhong Hospital, Zibo, Shandong, China.
Endangered Language Fund · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We explored the potential of combining carcinoembryonic antigen (CEA) and salivary mRNAs for gastric cancer (GC) detection.This study included 2 phases of study: a biomarker discovery phase and an independent validation phase. In the discovery phase, we measured CEA levels in blood samples and expression level of messenger RNAs (SPINK7, PPL, SEMA4B, SMAD4) in saliva samples of 140 GC patients and 140 healthy controls. We evaluated the clinical performance of each biomarker and developed a predictive model using machine-learning algorithm to differentiate GC patients and healthy controls.Our biomarker panel successfully discriminated GC patients from healthy controls with both high sensitivity (0.94) and high specificity (0.91). We next applied our biomarker panel in the independent validation phase, in which we recruited a new patient cohort of 60 GC patients and 60 healthy controls. Using our biomarker panel, the GC patients were discriminated from healthy controls in the validation phase, with sensitivity of 0.92 and specificity of 0.87.A combination of blood CEA and salivary messenger RNA could be a promising approach to detect GC.

Indexed as

Biomarkers, TumorCarcinoembryonic AntigenCohort StudiesDiagnosis, Computer-AssistedFemaleHumansMachine LearningMaleMiddle AgedPlakinsProof of Concept StudyRNA, MessengerSalivaSemaphorinsSensitivity and SpecificitySerine Peptidase Inhibitors, Kazal TypeBiomarkers, TumorCarcinoembryonic AntigenPlakinsPPL protein, humanRNA, Messengersemaphorin 4B, humanSemaphorinsSerine Peptidase Inhibitors, Kazal TypeSmad4 ProteinSMAD4 protein, humanSPINK7 protein, human

Identifiers

PMID32481437
PMCPMC12245265
OpenAlexW3032763657

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.