Evidence map›Paper›PMID 37970608›Full record

ReviewAnnals of translational medicine2023

Narrative review-diagnosing and managing malignant epidural spinal cord compression: an evidence-based approach.

Zarique Z Akanda, Michael J McKay

Open access · diamondAbstract readReview
In one paragraph

Review in Annals of translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

3 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Review
  3. 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

2 authors at 2 institutions in 1 country.

Zarique Z AkandaDepartment of Radiation Oncology, Alfred Health, Melbourne, Victoria, Australia.
Michael J McKayNorthwest Regional Hospital, Rural Clinical School, The University of Tasmania, Burnie, Tasmania, Australia.
Alfred Health · AUUniversity of Tasmania · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objective: Malignant spinal cord compression (MSCC) is a medical emergency. Clinical deterioration can occur quickly and irreversibly. MSCC is caused predominantly by metastatic cancer spread to the epidural space by epithelial or haematological malignancies. The primary diagnostic test is full-spine magnetic resonance imaging (MRI) since it has excellent soft tissue spatial resolution, and MSCC is multi-level in around one-third of cases. The modalities of therapy for MSCC are steroids, radiotherapy, and surgery. Radiotherapy is a mainstay of treatment since indications for surgery are limited. Recently randomised clinical trials exploring long course Methods: Multiple medical databases were searched through January 7 Key Content and Findings: In addition to a detailed overview of the pathophysiology and diagnosis of cord compression, we also examine all recent phase III clinical trials to date on the use of conventional radiotherapy in managing MSCC. Our review also provides a comprehensive summary and discussion of the novel approaches to the management of cord compression, including the role of SABR and a non-traditional surgical approach as well. Conclusions: Shorter courses of radiotherapy can be considered for poor prognosis patients. For favourable prognosis patients, longer courses of treatment provide more durable local control. An emerging treatment paradigm is a hybrid approach of surgery and SABR, however this has not been studied prospectively.

Indexed as

compressionepiduralmalignantRadiotherapyspinal cord

Identifiers

PMID37970608
PMCPMC10632584
OpenAlexW4387856542

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.