Evidence map›Paper›PMID 24396506›Full record

ReviewTheranostics2013

Can microRNAs improve the management of lung cancer patients? A clinician's perspective.

Amanda Tufman, Fei Tian, Rudolf Maria Huber

Abstract readReview
In one paragraph

Review in Theranostics, 2013. 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. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Clinical Aspect of MicroRNA in Lung Cancer.Tuberculosis and respiratory diseases · 2014
    Review
  7. Article
  8. Article
  9. 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

3 authors.

Amanda Tufman1. Division of Respiratory Medicine and Thoracic Oncology, Department of Internal Medicine V, Thoracic Oncology Centre Munich, Ludwig-Maximilians Universität München, Germany; ; 2. Member of the German Center for Lung Research (DZL CPC-M).
Fei Tian1. Division of Respiratory Medicine and Thoracic Oncology, Department of Internal Medicine V, Thoracic Oncology Centre Munich, Ludwig-Maximilians Universität München, Germany; ; 2. Member of the German Center for Lung Research (DZL CPC-M).
Rudolf Maria Huber1. Division of Respiratory Medicine and Thoracic Oncology, Department of Internal Medicine V, Thoracic Oncology Centre Munich, Ludwig-Maximilians Universität München, Germany; ; 2. Member of the German Center for Lung Research (DZL CPC-M).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The treatment of patients with lung cancer is increasingly individualised. Rather than treating lung cancer as a single disease, clinicians are often called upon to consider the precise histology and molecular biology of each tumour in addition to the individual characteristics of each patient. Paralleling advances in lung cancer management, advances in the detection of lung cancer are changing practice. Lung cancer screening promises to find disease at a curable stage; however, the high false positive rate in screening trials has clinical and fiscal ramifications which demand attention. Biomarkers able to stratify for the risk of cancer, prognosticate the course of disease, or predict the response to treatment are in increasing demand. This paper summarizes some of the clinical problems faced by those treating lung cancer patients, and examines how knowledge about the role of microRNAs in lung cancer biology may change patient management.

Indexed as

HumansLung NeoplasmsMicroRNAsMolecular ImagingMolecular Targeted TherapyMicroRNAsbiomarkerearly detectionlung cancermicroRNApredictive marker.prognostic markerscreeningthoracic oncologytumor biology

Identifiers

PMID24396506
PMCPMC3881097

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.