Evidence map›Paper›PMID 37185297›Full record

ArticleScientific reports2023

CEA dynamics for predicting response after anti-EGFR monoclonal antibody treatment in metastatic colorectal cancer.

Sora Kang, Sun Young Kim, Yong Sang Hong, Tae Won Kim, Ki Eun Choi, Min Jung Kim, Jeong Eun Kim

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. The effectiveness of three months EGFR-CTH therapy in palliative colorectal cancer.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 2025
    Article
  5. Review
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 at 1 institution in 1 country.

Sora KangDepartment of Medical Oncology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea.
Sun Young KimDepartment of Medical Oncology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea.
Yong Sang HongDepartment of Medical Oncology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea.
Tae Won KimDepartment of Medical Oncology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea.
Ki Eun ChoiDepartment of Medical Oncology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea.
Min Jung KimDepartment of Medical Oncology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea.
Jeong Eun KimDepartment of Medical Oncology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea. jeongeunkim@amc.seoul.kr.
Ulsan College · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Carcinoembryonic antigen (CEA) is the most widely used tumor marker in metastatic colorectal cancer (mCRC). However, its potential as a predictive marker of progression in mCRC during systemic chemotherapy, particularly in patients receiving monoclonal antibodies as a combination therapy, has remained of interest. Herein, we investigated whether CEA changes could predict disease progression and clinical outcomes in patients with mCRC cotreated with systemic chemotherapy and/or biologic agents. A total of 1261 patients with mCRC undergoing a first-line systemic treatment were included in this retrospective study. We analyzed the optimal cut-off value for CEA changes to predict progression at the first response evaluation by the treatment arm (chemotherapy alone, chemotherapy plus anti-vascular endothelial growth factor (VEGF) monoclonal antibody [mAb], and chemotherapy plus anti-epidermal growth factor receptor [EGFR] mAb). These cut-off values were then used to predict overall survival (OS) and progression-free survival (PFS). When stratified by their treatment arm, 891 (70.6%), 266 (21.0%), and 104 (8.2%) of the study patients were included in the chemotherapy alone-, anti-VEGF mAb, and anti-EGFR mAb groups, respectively. The optimal CEA cut-off values were 16.5% and 38.9% increase in the whole cohort and anti-EGFR mAb group, respectively, and these values showed high sensitivity and specificity for predicting disease progression. The patients in the entire population and anti-EGFR mAb group with CEA changes below these cut-off values showed significantly better OS and PFS outcomes compared those whose changes were above cut-off values. Among the patients with mCRC treated with anti-VEGF mAb, no associations were found between OS or PFS outcomes and CEA changes. CEA is potentially a good surrogate marker for predicting disease progression and survival outcomes in patients with mCRC receiving first-line systemic chemotherapy alone or chemotherapy with anti-EGFR mAb, whereas it is less effective in those treated with anti-VEGF mAb.

Indexed as

Antineoplastic AgentsColonic NeoplasmsColorectal NeoplasmsRectal NeoplasmsAntibodies, MonoclonalAntineoplastic Combined Chemotherapy ProtocolsCarcinoembryonic AntigenDisease ProgressionErbB ReceptorsHumansRetrospective StudiesAntibodies, MonoclonalAntineoplastic AgentsCarcinoembryonic AntigenErbB Receptors

Identifiers

PMID37185297
PMCPMC10130020
OpenAlexW4366987009

What OpenQuestion holds

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LicenceCC BY
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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.