Evidence map›Paper›PMID 30888199›Full record

ArticleBiopreservation and biobanking2019

Utilization of Archived Plasma to Detect Epidermal Growth Factor Receptor Mutation in Non-Small Cell Lung Cancer Patients.

Ae-Chin Oh, Jin Kyung Lee, Ji-Young Kim, Hyeon-Ok Jin, Jae Won Jung, Yoon Hwan Chang, Young Jun Hong

Abstract read
In one paragraph

Article in Biopreservation and biobanking, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Ae-Chin Oh1Department of Laboratory Medicine, Korea Cancer Center Hospital, Seoul, Republic of Korea.
Jin Kyung Lee1Department of Laboratory Medicine, Korea Cancer Center Hospital, Seoul, Republic of Korea.
Ji-Young Kim2KIRAMS Radiation Biobank, Korea Institute of Radiological and Medical Sciences, Seoul, Republic of Korea.
Hyeon-Ok Jin2KIRAMS Radiation Biobank, Korea Institute of Radiological and Medical Sciences, Seoul, Republic of Korea.
Jae Won Jung1Department of Laboratory Medicine, Korea Cancer Center Hospital, Seoul, Republic of Korea.
Yoon Hwan Chang1Department of Laboratory Medicine, Korea Cancer Center Hospital, Seoul, Republic of Korea.
Young Jun Hong1Department of Laboratory Medicine, Korea Cancer Center Hospital, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precision medicine has received increased attention as an effective approach for the treatment of cancer patients. Because of challenges associated with the availability of archived tissue, liquid biopsies are often performed to detect cancer-specific mutations. One of the major advantages of the liquid biopsy is that the treatment can be monitored longitudinally, even after the tumor tissue is no longer available. In a clinical setting, one component of precision medicine is the detection of cancer-specific mutations using archived samples. In this study, we evaluated the epidermal growth factor receptor (EGFR) mutation status of samples of lung cancer patients stored before introduction of the plasma EGFR test at our institution. The aim of this study was to validate the utility of archived plasma samples for detection of the EGFR mutation in nonsmall cell lung cancer (NSCLC) patients. The Cobas

Indexed as

Biological Specimen BanksPlasmaAdultAgedAged, 80 and overCarcinoma, Non-Small-Cell LungErbB ReceptorsFemaleHumansLung NeoplasmsMaleMiddle AgedMutationPrecision MedicineEGFR protein, humanErbB Receptorsarchived plasmabiobankliquid biopsynonsmall cell lung cancerplasma EGFRprecision medicine

Identifiers

PMID30888199
PMCPMC6703236

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Registered trials

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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.