Evidence map›Paper›PMID 27785450›Full record

ReviewJournal of hepatocellular carcinoma2016

Minimally invasive image-guided therapies for hepatocellular carcinoma.

Mohamed E Abdelsalam, Ravi Murthy, Rony Avritscher, Armeen Mahvash, Michael J Wallace, Ahmed O Kaseb, Bruno C Odisio

Open access · goldAbstract readReview
In one paragraph

Review in Journal of hepatocellular carcinoma, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.4field-weighted citation impact, top 34% 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

6 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. Local-Regional Treatment of Hepatocellular Carcinoma: A Primer for Radiologists.Radiographics : a review publication of the Radiological Society of North America, Inc · 2022
    Article
  4. Review
  5. Article
  6. 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

7 authors at 2 institutions in 1 country.

Mohamed E AbdelsalamDepartment of Interventional Radiology.
Ravi MurthyDepartment of Interventional Radiology.
Rony AvritscherDepartment of Interventional Radiology.
Armeen MahvashDepartment of Interventional Radiology.
Michael J WallaceDepartment of Interventional Radiology.
Ahmed O KasebDepartment of Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Bruno C OdisioDepartment of Interventional Radiology.
Society of Interventional Radiology · USThe University of Texas MD Anderson Cancer Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is the fifth most frequently occurring cancer globally and predominantly develops in the setting of various grades of underlying chronic liver disease, which affects management decisions. Image-guided percutaneous ablative or transarterial therapies have acquired wide acceptance in HCC management as a single treatment modality or combined with other treatment options in patients who are not amenable for surgery. Recently, such treatment modalities have also been used for bridging or downsizing before definitive treatment (ie, surgical resection or liver transplantation). This review focuses on the use of minimally invasive image-guided locoregional therapies for HCC. Additionally, it highlights recent advancements in imaging and catheter technology, embolic materials, chemotherapeutic agents, and delivery techniques; all lead to improved patient outcomes, thereby increasing the interest in these invasive techniques.

Indexed as

90Yablationhepatocelleular carcinomalocoregional therapyTACE

Identifiers

PMID27785450
PMCPMC5067062
OpenAlexW2530067681

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.