Evidence map›Paper›PMID 28271361›Full record

ReviewLa Radiologia medica2017

Prognosis of local recurrence in giant cell tumour of bone: what can we do?

Yifeng He, Ji Zhang, Xiaoyi Ding

Abstract readReview
PubMed Publisher
In one paragraph

Review in La Radiologia medica, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

17 citing papers in PubMed, 19 citations in OpenAlex.

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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 2 institutions in 1 country.

Yifeng HeDepartment of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ji ZhangDepartment of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xiaoyi DingDepartment of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. dingxiaoyi@hotmail.com.
Shanghai Jiao Tong University · CNRuijin Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Giant cell tumour of bone (GCTB) is classified as an intermediate tumour with rare metastasis, but is challenged by local recurrence. This review focuses on the role of radiological evaluation in terms of prognosis of local recurrence in GCTB. We hope to highlight the value of radiological evaluation by integrating studies on the impact of surgical treatments and non-surgical factors on local recurrence of GCTB and the current statuses of genetic and molecular prognostic factors of GCTB. Radiological evaluation can provide diverse information on tumours. As a non-invasive method, magnetic resonance imaging (MRI) is especially valuable for the diagnosis and evaluation of bone tumours due to its heightened sensitivity to soft tissue disease and multiplanar image acquisition. Imaging findings should be integrated with clinical characteristics, pathology and genetic and molecular prognostic factors to direct clinical approach and reduce the local recurrence of GCTB. Therefore, it is necessary to establish a multi-perspective evaluation system by which prognostic factors can be reliably determined. We further advocate more large-scale prospective studies. With the help of radiological evaluation, the clinic treatment of GCTB can be guided and local recurrence might be reduced; additionally, MR imaging can identify local recurrence of GCTB after surgical treatment in the early stage.

Indexed as

Giant Cell Tumor of BoneHumansMagnetic Resonance ImagingNeoplasm Recurrence, LocalPrognosisGiant cell tumour of boneLocal recurrenceMagnetic resonancePrognosisRadiological evaluation

Identifiers

PMID28271361
OpenAlexW2592700578

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.