Evidence map›Paper›PMID 14760775›Full record

ArticleWorld journal of gastroenterology2004

Multiple biomarkers of colorectal tumor in a differential diagnosis model: a quantitative study.

Wen Jin, Mei-Qin Gao, Zhi-Wu Lin, Dai-Xing Yang

Open access · hybridAbstract read
In one paragraph

Article in World journal of gastroenterology, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 29% 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, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Journal of Cancer · 2018
    Article
  4. Quantitative assessment model for gastric cancer screening.World journal of gastroenterology · 2005
    Article
  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

4 authors at 2 institutions in 1 country.

Wen JinDepartment of Pathology, Fujian Medical University, Fuzhou 350004, Fujian Province, China. jinwen9484@sina.com
Mei-Qin Gao
Zhi-Wu Lin
Dai-Xing Yang
Fujian Medical University · CNFujian Provincial Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo evaluate the multiple biomarkers of colorectal tumor and their potential usage in early diagnosis of colorectal cancers.

methodsMultiple biomarkers (DNA contents, AgNOR, PCNA, p53, c-erbB-2) in 10 normal colorectal mucosae, 37 colorectal adenomas and 55 colorectal cancers were analyzed quantitatively in the computed processing imaging system. Discrimination patterns were employed to evaluate the significance of single and multiple indices in diagnosis of colorectal cancers.

resultsThe mean values of the analyzed parameters increased in order of the normal mucosa, adenoma and adenocarcinoma, and this tendency reflected the progression of colorectal malignancy. The parameters including DNA index, positive rates, densities of AgNOR, c-erbB-2, and p53, shape and density of nucleus were relatively valuable for diagnoses. Then a diagnostic discrimination model was established. The samples were confirmed with the model, the sensitivity rates in cancer group and adenoma group were 96.36% and 89.19%, respectively. The value of proliferating cell nuclear antigen (PCNA) in early diagnosis of colorectal cancers was uncertain.

conclusionThe quantitative evaluation of some parameters for colorectal tumor can provide reproducible data for differential diagnosis. The established diagnostic discrimination model may be of clinicopathological value, and can make the early diagnosis of colorectal cancer possible.

Indexed as

AdenomaAdultAgedAged, 80 and overBiomarkers, TumorCarcinomaColorectal NeoplasmsDiagnosis, DifferentialFemaleHumansMaleMiddle AgedBiomarkers, Tumor

Identifiers

PMID14760775
PMCPMC4724933
OpenAlexW2189378498

What OpenQuestion holds

Textmetadata
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.