Evidence map›Paper›PMID 35651679›Full record

ReviewFrontiers in surgery2022

Application of Non-Blood-Derived Fluid Biopsy in Monitoring Minimal Residual Diseases of Lung Cancer.

Xing Yan, Changhong Liu

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 31% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Review
  6. Review
  7. 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

2 authors at 2 institutions in 1 country.

Xing YanThoracic Surgery Department, The Second Affiliated Hospital of Dalian Medical University Thoracic surgery, DaLian, China.
Changhong LiuThoracic Surgery Department, The Second Affiliated Hospital of Dalian Medical University Thoracic surgery, DaLian, China.
Dalian Medical University · CNSecond Affiliated Hospital of Dalian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is one of the most fatal malignant tumors in the world. Overcoming this disease is difficult due to its late diagnosis and relapse after treatment. Minimal residual disease (MRD) is described as the presence of free circulating tumor cells or other tumor cell derivatives in the biological fluid of patients without any clinical symptoms of cancer and negative imaging examination after the treatment of primary tumors. It has been widely discussed in the medical community as a bridge to solid tumor recurrence. Radiology, serology (carcinoembryonic antigen), and other clinical diagnosis and treatment methods widely used to monitor the progression of disease recurrence have obvious time-limited and -specific defects. Furthermore, as most samples of traditional liquid biopsies come from patients' blood (including plasma and serum), the low concentration of tumor markers in blood samples limits the ability of these liquid biopsies in the early detection of cancer recurrence. The use of non-blood-derived fluid biopsy in monitoring the status of MRD and further improving the postoperative individualized treatment of patients with lung cancer is gradually ushering in the dawn of hope. This paper reviews the progress of several non-blood-derived fluid samples (urine, saliva, sputum, and pleural effusion) in detecting MRD in lung cancer as well as selecting the accurate treatment for it.

Indexed as

liquid biopsylung cancerminimal residual diseasenon-bloodtumor

Identifiers

PMID35651679
PMCPMC9149287
OpenAlexW4280601951

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.