Evidence map›Paper›PMID 31192960›Full record

ArticleMedicine2019

Pattern identification of lung cancer patients based on body constitution questionnaires (BCQ) and glycoproteomics for precision medicine.

Wonryeon Cho, Ji Hye Kim, Miseon Jeong, Myeong-Sun Kim, Jinwook Lee, Hyoungwoo Son, Chunhoo Cheon, Sunju Park, Seong-Gyu Ko

Registry-linked trialOpen access · goldAbstract readClinical Trial Protocol
In one paragraph

Article in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03384680 (A Study on Symptom Collection of Patients With Lung Cancer.), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 93% 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.

NCT03384680 unknown statusnot on this map

A Study on Symptom Collection of Patients With Lung Cancer.

TypeobservationalSponsorSeong-Gyu KoRan2015 to 2018Enrolled100ConditionsLung Cancer
3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. 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

9 authors at 4 institutions in 1 country.

Wonryeon ChoDepartment of Chemistry, Wonkwang University, Iksan, Jeonbuk.
Ji Hye KimLaboratory of Clinical Biology and Pharmacogenomics, Department of Preventive Medicine, College of Korean Medicine.
Miseon JeongDepartment of Chemistry, Wonkwang University, Iksan, Jeonbuk.
Myeong-Sun KimDepartment of Cancer Preventive Material Development, Graduate School, Kyung Hee University.
Jinwook LeeDepartment of Chemistry, Wonkwang University, Iksan, Jeonbuk.
Hyoungwoo SonDepartment of Korean Medicine, Graduate School of Kyung Hee University.
Chunhoo CheonDepartment of Preventive Medicine, College of Korean Medicine, Kyung Hee University Dongdaemun-gu, Seoul.
Sunju ParkDepartment of Preventive Medicine, College of Korean Medicine, Daejeon University, Dong-gu, Daejeon, Republic of Korea.
Seong-Gyu KoLaboratory of Clinical Biology and Pharmacogenomics, Department of Preventive Medicine, College of Korean Medicine.
Kyung Hee University · KRWonkwang University · KRDaejeon University · KRDunsan Korean Medicine Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe patient's pattern identification has been used for personalized medicine in traditional Korean medicine (TKM) and aims for patient-specific therapy by Korean medical doctors. The pattern identification in this trial will be diagnosed from body constitution questionnaire (BCQ) with a more objective diagnosis of it but this method still needs a more concrete scientific basis. Glycoproteins are well-known to be associated with diseases (especially cancers) so glycoproteomics can be applied to differentiate pattern identification types of lung cancer patients. Thus, for the first time proteomics approach will be applied to the pattern identification by comparing BCQ assessment in order to establish a scientific basis with clinical proteomics for precision medicine.

methodsThis observational trial will at first diagnose the pattern identification types of lung cancer patients with BCQ assessment and then elucidate their relationships with proteomics. Blood samples will be collected before surgery along with clinical information of participants. The patients' pattern identification in TKM will be diagnosed from BCQ assessment. Then, lung cancer patients will be divided and pooled into 3 lung cancer entire (LCE) groups according to their pattern identification types (Xu, Stasis, or Gentleness). Three lung cancer representative (LCR) groups will be selected and pooled from each LCE group by selecting those with the same control factors. The 3 LCE groups and the 3 LCR groups from lung cancer patients will be independently analyzed through the glycoproteomics approach based on the patients' pattern identification. Glycoproteins from the 6 groups will be identified through proteomics approach and then categorized for analysis. DISCUSSION: This study intends to diagnose pattern identification of patients in TKM with BCQ assessment and proteomics approach. The identification of the glycoproteins in each group will lead to the scientific foundation of personalized medicine in TKM according to patients' pattern identification for lung cancer therapy. We intend to(1) diagnose the pattern identification types of lung cancer patients with BCQ under the framework of TKM;(2) evaluate BCQ assessment with glycoproteomics approach for precision medicine.

trial registrationClinicalTrials.gov NCT03384680. Registered 27 December 2017. Retrospectively registered.

Indexed as

Body ConstitutionClinical Trials as TopicObservational Studies as TopicPrecision MedicineBiomarkers, TumorGlycoproteinsHumansLung NeoplasmsMedicine, Korean TraditionalPatient SelectionProteomeProteomicsSurveys and QuestionnairesBiomarkers, TumorGlycoproteinsProteome

Identifiers

PMID31192960
PMCPMC6587619
OpenAlexW2952860594

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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 Socratic graph.