Evidence map›Paper›PMID 27893656›Full record

SynthesisMedicine2016

Is it feasible to detect epidermal growth factor receptor mutations in circulating tumor cells in nonsmall cell lung cancer?: A meta-analysis.

Yafang Liu, Ze Xing, Ping Zhan, Hongbing Liu, Wei Ye, Tangfeng Lv, Yong Song

Abstract readMeta-Analysis
In one paragraph

Synthesis in Medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

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

Yafang LiuDepartment of Respiratory Medicine, Jinling Hospital, Southern Medical University Department of Orthopedics Medicine, Jinling Hospital, Southern Medical University, Nanjing, China.
Ze Xing
Ping Zhan
Hongbing Liu
Wei Ye
Tangfeng Lv
Yong Song

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe value of circulating tumor cells (CTCs) in detecting epidermal growth factor receptor (EGFR) mutations in patients with nonsmall cell lung cancer (NSCLC) is controversial. We performed a meta-analysis to investigate the diagnostic significance of CTCs with tumor tissues as the standard control.

methodsA systematic literature search, including papers published until November 26, 2015, was performed using PubMed, Medline, Embase, Web of Science, and the China National Knowledge Infrastructure, and the references of retrieved articles were screened. The pooled sensitivity, specificity, and diagnostic odds ratio (DOR) were calculated according to the data selection from the included studies. The evaluation indexes of the diagnostic performance were the summary receiver operating characteristic curve (SROC) and area under the SROC (AUSROC).

resultsEight eligible articles with a total of 170 participants were identified in our meta-analysis. The pooled sensitivity and specificity were 0.91 [95% CI: 0.55-0.99] and 0.99 [95% CI: 0.59-1.00]. The positive likelihood ratio and negative likelihood ratio were 68 [95% CI: 1.4-3364] and 0.09 [95% CI: 0.01-0.64], respectively. The DOR was 788 [95% CI: 9-71884]. The high diagnostic performance of CTCs in detecting EGFR mutations was indicated by the AUSROC of 0.99 [95% CI: 0.98-1.00].

conclusionsCTCs are a feasible and highly specific biomarker for detecting the EGFR mutation status in NSCLC patients.

Indexed as

MutationNeoplastic Cells, CirculatingBiomarkers, TumorCarcinoma, Non-Small-Cell LungErbB ReceptorsLung NeoplasmsBiomarkers, TumorErbB Receptors

Identifiers

PMID27893656
PMCPMC5134849

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.