Evidence map›Paper›PMID 27666661›Full record

ReviewMolecular medicine reports2016

Molecular screening strategies for NF1-like syndromes with café-au-lait macules (Review).

Jia Zhang, Ming Li, Zhirong Yao

Open access · hybridAbstract readReview
In one paragraph

Review in Molecular medicine reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 21% 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

8 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Biomarker Landscape in RASopathies.International journal of molecular sciences · 2024
    Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. [Pigmented macules as possible early signs of genetic syndromes].Der Hautarzt; Zeitschrift fur Dermatologie, Venerologie, und verwandte Gebiete · 2019
    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

3 authors at 1 institution in 1 country.

Jia ZhangDepartment of Dermatology, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, P.R. China.
Ming LiDepartment of Dermatology, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, P.R. China.
Zhirong YaoDepartment of Dermatology, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, P.R. China.
XinHua Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple café-au-lait macules (CALM) are usually associated with neurofibromatosis type 1 (NF1), one of the most common hereditary disorders. However, a group of genetic disorders presenting with CALM have mutations that are involved in human skin pigmentation regulation signaling pathways, including KIT ligand/KIT proto‑oncogene receptor tyrosine kinase and Ras/mitogen‑activated protein kinase. These disorders, which include Legius syndrome, Noonan syndrome with multiple lentigines or LEOPARD syndrome, and familial progressive hyperpigmentation) are difficult to distinguish from NF1 at early stages, using skin appearance alone. Furthermore, certain syndromes are clinically overlapping and molecular testing is a vital diagnostic method. The present review aims to provide an overview of these 'NF1‑like' inherited diseases and recommend a cost‑effective strategy for making a clear diagnosis among these diseases with an ambiguous borderline.

Indexed as

Cafe-au-Lait SpotsDiagnosis, DifferentialHumansLEOPARD SyndromeMutationNeurofibromatosis 1Noonan SyndromePathology, MolecularSignal TransductionSkin Pigmentation

Identifiers

PMID27666661
PMCPMC5112360
OpenAlexW2521425287

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.