Evidence map›Paper›PMID 40558116›Full record

ReviewAdvances in respiratory medicine2025

Clinical Utility of ctDNA Analysis in Lung Cancer-A Review.

Kamil Makar, Agata Wróbel, Adam Antczak, Damian Tworek

Abstract readReview
In one paragraph

Review in Advances in respiratory medicine, 2025. 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
–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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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

4 authors.

Kamil MakarDepartment of General and Oncological Pulmonology, Medical University of Lodz, Stefana Zeromskiego 113, 90-549 Lodz, Poland.ORCID 0009-0000-6413-708X
Agata WróbelFaculty of Medicine, Medical University of Lodz, Pomorska 251, 92-213 Lodz, Poland.
Adam AntczakDepartment of General and Oncological Pulmonology, Medical University of Lodz, Stefana Zeromskiego 113, 90-549 Lodz, Poland.
Damian TworekDepartment of General and Oncological Pulmonology, Medical University of Lodz, Stefana Zeromskiego 113, 90-549 Lodz, Poland.ORCID 0000-0001-9862-6703

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Circulating free DNA (cfDNA) is genetic material released from various cells into bodily fluids. Among its fractions, circulating tumor DNA (ctDNA) originates from tumor cells and reflects their genetic material, including mutations and epigenetic changes. Methods commonly employed for detecting ctDNA in blood include next-generation sequencing (NGS) and various types of PCR. The presence of ctDNA can be utilized in liquid biopsies for many diagnostic purposes related to various cancers. It is a minimally invasive method of sampling molecular compounds from tumor cells. In this paper, we focus on current knowledge regarding the liquid biopsy of blood ctDNA in the context of lung cancer, one of the leading causes of cancer-related mortality. Currently, as a clinically approved method, liquid biopsy serves as a complementary technique in NSCLC diagnostic and genetic profiling. Other applications of liquid biopsy that are still being investigated include the detection of minimal residual disease (MRD) after curative treatment and response monitoring to systemic treatment. This review discusses current and future potential directions for the development and implementation of ctDNA for patients with NSCLC.

Indexed as

Carcinoma, Non-Small-Cell LungCirculating Tumor DNALung NeoplasmsBiomarkers, TumorHigh-Throughput Nucleotide SequencingHumansLiquid BiopsyBiomarkers, TumorCirculating Tumor DNAcancer diagnosticscfDNActDNAliquid biopsylung cancerNSCLC

Identifiers

PMID40558116
PMCPMC12189613

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.