Evidence map›Paper›PMID 31636732›Full record

ReviewDisease markers2019

EpCAM

Chiara Nicolazzo, Angela Gradilone, Flavia Loreni, Cristina Raimondi, Paola Gazzaniga

Abstract readReview
In one paragraph

Review in Disease markers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Review
  2. Single-Cell RNA Sequencing of Pancreatic Circulating Tumor Cells.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  3. Article
  4. Role of circulating tumor cell clusters in breast cancer.Translational breast cancer research : a journal focusing on translational research in breast cancer · 2026
    Review
  5. Article
  6. Article
  7. Article
  8. Cancer-associated fibroblasts as a potential novel liquid biopsy marker in cancer patients.Journal of experimental & clinical cancer research : CR · 2025
    Review
  9. Review
  10. Article
  11. Review
  12. Review
  13. Review
  14. Article
  15. Review
  16. Recent Advances in Methods for Circulating Tumor Cell Detection.International journal of molecular sciences · 2023
    Review
  17. Review
  18. Review
  19. Article
  20. 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

5 authors.

Chiara NicolazzoDepartment of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy.ORCID https://orcid.org/0000-0002-2551-8979
Angela GradiloneDepartment of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy.
Flavia LoreniDepartment of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy.
Cristina RaimondiDepartment of Radiological, Oncological and Anatomopathological Sciences, Sapienza University of Rome, 00161 Rome, Italy.
Paola GazzanigaDepartment of Molecular Medicine, Sapienza University of Rome, 00161 Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The CellSearch® system which is still considered the gold standard for the enumeration of circulating tumor cells (CTC) utilizes antibodies against the epithelial cell adhesion molecule (EpCAM) for CTC enrichment. Recently, CTC discarded by the CellSearch® system due to their low EpCAM expression have been isolated and analyzed. We here sought to discuss technical and biological issues concerning the isolation and characterization of EpCAM

Indexed as

Antigens, NeoplasmBiomarkers, TumorCell MembraneEpithelial Cell Adhesion MoleculeHumansImmunomagnetic SeparationNeoplasmsNeoplastic Cells, CirculatingPrognosisReproducibility of ResultsAntigens, NeoplasmBiomarkers, TumorEpithelial Cell Adhesion Molecule

Identifiers

PMID31636732
PMCPMC6766153

What OpenQuestion holds

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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.