Evidence map›Paper›PMID 30643553›Full record

ReviewLung cancer management2016

Liquid biopsy and NSCLC.

Domenico Trombetta, Angelo Sparaneo, Federico Pio Fabrizio, Lucia Anna Muscarella

Abstract readReview
In one paragraph

Review in Lung cancer management, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. [Advances of Exosomes Extraction and Its Mechanism in Early Diagnosis of Lung Cancer].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2020
    Review
  9. Foreword: message from the Editor.Lung cancer management · 2016
    Article
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.

Domenico TrombettaLaboratory of Oncology, IRCCS "Casa Sollievo della Sofferenza" Hospital, San Giovanni Rotondo (FG), Italy.
Angelo SparaneoLaboratory of Oncology, IRCCS "Casa Sollievo della Sofferenza" Hospital, San Giovanni Rotondo (FG), Italy.
Federico Pio FabrizioLaboratory of Oncology, IRCCS "Casa Sollievo della Sofferenza" Hospital, San Giovanni Rotondo (FG), Italy.
Lucia Anna MuscarellaLaboratory of Oncology, IRCCS "Casa Sollievo della Sofferenza" Hospital, San Giovanni Rotondo (FG), Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the era of high-throughput molecular screening and personalized medicine, difficulty in determining whether cancer mutations are truly 'actionable' remains a gray zone in NSCLC. The most important prerequisite to perform such investigations is the tumor tissue retrieval via biopsy at diagnosis and after occurrence of resistance. Blood-based liquid biopsy as circulating tumor cells, circulating tumor DNA and exosomes can offer a fast and non-invasive method to elucidate the genetic heterogeneity of patients, the screening and patient stratification and give a dynamic surveillance for tumor progression and monitor treatments response. Here we prospectively discuss the three main approaches in the blood-biopsy field of lung cancer patients and its clinical applications in patient management. We also outline some of the analytical challenges that remain for liquid biopsy techniques in demonstrating that it could represent a true and actionable picture in lung cancer management for the implementation into clinical routine.

Indexed as

CTCsctDNAearly detectionexosomesliquid biopsyminimal residual diseaseNSCLCpersonalized medicineresistance monitoringtherapy optionstumor burdentumor evolution

Identifiers

PMID30643553
PMCPMC6310318

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.