Evidence map›Paper›PMID 35320997›Full record

ArticleJournal of healthcare engineering2022

Expression Level and Clinical Significance of AK021443 in Non-Small-Cell Lung Carcinoma.

Xiyong Wang, Yu Dai, Hongming Zhang, Honglin Xia, Qingsheng Kan

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 59% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Xiyong WangDepartment of Oncology, Suzhou Hospital Affiliated to Anhui Medical University (Suzhou Municipal Hospital), Suzhou, China.
Yu DaiDepartment of Oncology, Suzhou Hospital Affiliated to Anhui Medical University (Suzhou Municipal Hospital), Suzhou, China.
Hongming ZhangDepartment of Respiratory Medicine, Yancheng Third People's Hospital, The Affiliated Yancheng Hospital of Southeast University, Yancheng, China.
Honglin XiaClinical Laboratory, Suzhou Hospital Affiliated to Anhui Medical University (Suzhou Municipal Hospital), Suzhou, China.
Qingsheng KanDepartment of Oncology, Suzhou Hospital Affiliated to Anhui Medical University (Suzhou Municipal Hospital), Suzhou, China.ORCID 0000-0003-0424-4347
Anhui Medical University · CNYancheng Third People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To explore the prognostic potential of AK021443 in non-small-cell lung carcinoma (NSCLC), AK021443 levels in NSCLC specimens were determined by quantitative real-time polymerase chain reaction (qRT-PCR). The correlation between the AK021443 level and pathological factors in NSCLC patients was analyzed. Kaplan-Meier curves were plotted for assessing the prognostic value of AK021443 in NSCLC patients. Potential factors influencing NSCLC prognosis were analyzed by multivariable Cox regression test. AK021443 was upregulated in NSCLC specimens than normal ones. Its level was correlated to histological type, tumor differentiation, TNM staging, and lymphatic metastasis in NSCLC patients. AK021443 was the independent risk factor for the overall survival of NSCLC. AK021443 is highly expressed in NSCLC specimens, which is correlated to histological type, tumor differentiation, TNM staging, and lymphatic metastasis in NSCLC patients. It is the independent prognostic factor for NSCLC.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsBiomarkers, TumorHumansKaplan-Meier EstimateLymphatic MetastasisBiomarkers, Tumor

Identifiers

PMID35320997
PMCPMC8938069
OpenAlexW4221071240

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.