Evidence map›Paper›PMID 31992952›Full record

ArticleContemporary oncology (Poznan, Poland)2019

The roles of M30 and M65 in the assessment of treatment response and prognosis in patients with non-small cell lung cancer, who receive neoadjuvant treatment.

Belkıs Nihan Coskun, Oguzhan Sıtkı Dizdar, Seniz Korkmaz, Engin Ulukaya, Turkkan Evrensel

Open access · goldAbstract read
In one paragraph

Article in Contemporary oncology (Poznan, Poland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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 51% 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, 2 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

5 authors at 2 institutions in 1 country.

Belkıs Nihan CoskunDepartment of Internal Medicine, Uludağ University Medical School, Bursa, Turkey.
Oguzhan Sıtkı DizdarDepartment of Internal Medicine, Kayseri Training and Research Hospital, Kayseri,Turkey.
Seniz KorkmazDepartment of Clinical Biochemistry, Uludağ University Medical School, Bursa, Turkey.
Engin UlukayaDepartment of Clinical Biochemistry, Uludağ University Medical School, Bursa, Turkey.
Turkkan EvrenselDepartment of Medical Oncology, Uludağ University Medical School, Bursa, Turkey.
Bursa Uludağ Üni̇versi̇tesi̇ · TRKayseri Eğitim ve Araştırma Hastanesi · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aim of the studyTo investigate the efficacy of evaluating prognosis and response to lung cancer treatment using M30 and M65 antigens, which are indicators of necrosis. MATERIAL AND

methodsForty-eightpatients with lung cancer, who were planned to receive neoadjuvant chemotherapy, and 38 healthy volunteers were enrolled in the study. Using M30 and M65 levels, cytokeratin 18 levels were measured twice: before and 48 hours after the first chemotherapy treatment. Apoptotic and total necrosis levels were determined by measuring the M65 and M30 levels.

resultsThe M30 and M65 antigen levels in the patient group were significantly higher than in the control group (

conclusionsA significant increase was detected in serum M30 and M65 levels in patients with lung cancer. There was a greater increase in serum M30 levels in patients who did not respond to the chemotherapy. This result gives rise to the thought that evaluating apoptosis and total necrosis through M30 and M65 measurements alone only in patients receiving neoadjuvant chemotherapy would be insufficient for specifying the effectiveness of the treatment.

Indexed as

cytokeratinlung cancerneoadjuvant treatmentprognosis

Identifiers

PMID31992952
PMCPMC6978762
OpenAlexW3004099594

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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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.