Evidence map›Paper›PMID 32977421›Full record

ArticleDiagnostics (Basel, Switzerland)2020

Developing a Preoperative Algorithm for the Diagnosis of Uterine Leiomyosarcoma.

Hannah Lawlor, Alexandra Ward, Alison Maclean, Steven Lane, Meera Adishesh, Sian Taylor, Shandya Bridget DeCruze, Dharani Kosala Hapangama

Open access · goldAbstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.1field-weighted citation impact, top 17% 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

11 citing papers in PubMed, 22 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

8 authors at 1 institution in 1 country.

Hannah LawlorDepartment of Women's and Children's Health, Institute of Life Course and Medical Sciences, University of Liverpool Member of Liverpool Health Partners, Liverpool L8 7SS, UK.ORCID 0000-0003-4365-9473
Alexandra WardDepartment of Women's and Children's Health, Institute of Life Course and Medical Sciences, University of Liverpool Member of Liverpool Health Partners, Liverpool L8 7SS, UK.ORCID 0000-0002-1505-3223
Alison MacleanDepartment of Women's and Children's Health, Institute of Life Course and Medical Sciences, University of Liverpool Member of Liverpool Health Partners, Liverpool L8 7SS, UK.ORCID 0000-0002-5713-6959
Steven LaneDepartment of Biostatistics, University of Liverpool Member of Liverpool Health Partners, Liverpool L69 3BX, UK.
Meera AdisheshDepartment of Women's and Children's Health, Institute of Life Course and Medical Sciences, University of Liverpool Member of Liverpool Health Partners, Liverpool L8 7SS, UK.
Sian TaylorLiverpool Women's NHS Foundation Trust Member of Liverpool Health Partners, Liverpool L8 7SS, UK.
Shandya Bridget DeCruzeLiverpool Women's NHS Foundation Trust Member of Liverpool Health Partners, Liverpool L8 7SS, UK.
Dharani Kosala HapangamaDepartment of Women's and Children's Health, Institute of Life Course and Medical Sciences, University of Liverpool Member of Liverpool Health Partners, Liverpool L8 7SS, UK.
University of Liverpool · GB

Funding

Liverpool Women's NHS Foundation Trust cancer charityNIHR ACF ACF MacleanUniversity of Liverpool RS2Wellbeing of Women RG1487 and RG2137
6 · The paper itself

Abstract

Early diagnosis of the rare and life-threatening uterine leiomyosarcoma (LMS) is essential for prompt treatment, to improve survival. Preoperative distinction of LMS from benign leiomyoma remains a challenge, and thus LMS is often diagnosed post-operatively. This retrospective observational study evaluated the predictive diagnostic utility of 32 preoperative variables in 190 women who underwent a hysterectomy, with a postoperative diagnosis of leiomyoma (

Indexed as

diagnosisfibroidleiomyomauterine leiomyosarcomauterine neoplasm

Identifiers

PMID32977421
PMCPMC7598216
OpenAlexW3087878118

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.