Evidence map›Paper›PMID 38400801›Full record

ArticleThoracic cancer2024

Distinction of ALK fusion gene- and EGFR mutation-positive lung cancer with tumor markers.

Takahiro Akita, Ryo Ariyasu, Sho Kakuto, Keiki Miyadera, Ayu Kiritani, Ryosuke Tsugitomi, Yoshiaki Amino, Ken Uchibori, Satoru Kitazono, Noriko Yanagitani and 2 more

Open access · goldAbstract read
In one paragraph

Article in Thoracic cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.4field-weighted citation impact, top 17% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Integrating ctDNA testing forAdvances in laboratory medicine · 2025
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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

12 authors at 2 institutions in 1 country.

Takahiro AkitaDepartment of Thoracic Medical Oncology, The Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.
Ryo AriyasuDepartment of Thoracic Medical Oncology, The Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.ORCID 0000-0003-4393-9176
Sho KakutoDepartment of Thoracic Medical Oncology, The Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.
Keiki MiyaderaDepartment of Thoracic Medical Oncology, The Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.
Ayu KiritaniDepartment of Thoracic Medical Oncology, The Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.
Ryosuke TsugitomiDepartment of Thoracic Medical Oncology, The Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.
Yoshiaki AminoDepartment of Thoracic Medical Oncology, The Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.ORCID 0000-0002-3242-0662
Ken UchiboriDepartment of Thoracic Medical Oncology, The Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.ORCID 0000-0003-1491-923X
Satoru KitazonoDepartment of Thoracic Medical Oncology, The Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.
Noriko YanagitaniDepartment of Thoracic Medical Oncology, The Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.
Sadatomo TasakaDepartment of Respiratory Medicine, Hirosaki University Graduate School of Medicine, Hirosaki, Japan.
Makoto NishioDepartment of Thoracic Medical Oncology, The Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan.ORCID 0000-0003-4969-4165
The Cancer Institute Hospital · JPHirosaki University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIt is difficult to predict gene mutations individually based on clinical background alone. Tumor markers may help to predict each gene mutation. Identifying tumor markers that can predict gene mutation will facilitate timely genetic testing and intervention.

methodsWe selected 134 cases of advanced or recurrent ALK-positive and 172 cases of advanced or recurrent EGFR-positive lung cancer from our clinical database. The cutoff values for the tumor markers were defined as 5.0 ng/mL or higher for carcinoembryonic antigen (CEA) and 3.5 ng/mL or higher for soluble fragment of cytokeratin 19 (CYFRA21-1) in accordance with the institutional standards. A positive CYFRA21-1:CEA ratio was defined as 0.7 or higher.

resultsThe CEA-positivity rate was 49% for ALK-positive lung cancers and 73% for EGFR-positive lung cancers, which was significantly different (p < 0.001). The CYFRA21-1 positivity rate was significantly higher in ALK-positive lung cancer (36%) compared with EGFR-positive lung cancer (23%) (p = 0.034). The median CYFRA21-1:CEA ratio was 0.395 for the ALK group, which was significantly higher compared with 0.098 for the EGFR group (p < 0.001). These trends were similar when excluding histology other than adenocarcinoma. The median time-to-treatment failure (TTF) for initial tyrosine kinase inhibitor (TKI) therapy was 308 days for the high CYFRA21-1:CEA ratio group and 617 days for the low CYFRA21-1:CEA ratio group for ALK-positive lung cancer (p = 0.100).

conclusionsA higher proportion of patients with ALK-positive lung cancer were CYFRA21-1 positive and had higher CYFRA21-1:CEA ratios compared with EGFR-positive lung cancer patients.

Indexed as

Antigens, NeoplasmCarcinoma, Non-Small-Cell LungKeratin-19Lung NeoplasmsBiomarkers, TumorCarcinoembryonic AntigenErbB ReceptorsHumansMutationNeoplasm Recurrence, Localantigen CYFRA21.1Antigens, NeoplasmBiomarkers, TumorCarcinoembryonic AntigenEGFR protein, humanErbB ReceptorsKeratin-19ALK‐positive lung cancerCEACYFRA21‐1EGFR‐positive lung cancertumor marker

Identifiers

PMID38400801
PMCPMC10995710
OpenAlexW4392131371

What OpenQuestion holds

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LicenceCC BY
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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.