Evidence map›Paper›PMID 36884163›Full record

ReviewCurrent treatment options in oncology2023

Not All Leiomyosarcomas Are the Same: How to Best Classify LMS.

Ashley Hickman, Brittany L Siontis

Open access · greenAbstract readReview
In one paragraph

Review in Current treatment options in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. 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 1 institution in 1 country.

Ashley HickmanDivision of Medical Oncology, Mayo Clinic, 200 1St Street SW, Rochester, MN, 55902, USA.
Brittany L SiontisDivision of Medical Oncology, Mayo Clinic, 200 1St Street SW, Rochester, MN, 55902, USA. Siontis.Brittany@mayo.edu.ORCID 0000-0002-9471-6792
Mayo Clinic · US

Funding

PROJECT 3: Applying Liquid Biopsy Technologies to Detect Clinical Response and Mechanisms of Resistance in the Treatment of LMSP50CA272170 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI JUDY E. GARBER · 2022 to 2026
$13.3M
NCI NIH HHS P50 CA272170
6 · The paper itself

Abstract

opinion statementLeiomyosarcoma arises from smooth muscle and represents one of the most common soft tissue sarcomas. Despite aggressive multimodality care, over half of the patients will ultimately develop metastatic and incurable disease with a median survival of 12-18 months. At present, there is no standard system to classify leiomyosarcoma, which itself is a heterogeneous disease. Classification by tumor location is the most simplistic approach and is most frequently utilized in clinical practice. Tumor location impacts diagnosis (recognition pre-operatively versus at the time of surgery) as well as treatment (ability to completely resect with clear margins with minimal morbidity). While tumor location can impact prognosis, for example, extremity tumors would generally be considered as lower risk than inferior vena cava tumors, leiomyosarcoma can exhibit a heterogeneous behavior irrespective of tumor location. Specifically, some patients have rapidly progressing disease despite aggressive chemotherapy, while others display a more indolent course even in the metastatic setting. The pathogenic drivers of the heterogeneity observed in tumor behavior are not well understood. As we learn more about the molecular composition of leiomyosarcoma, various classification groups have been proposed as discussed here. Ultimately, it is unlikely that one variable will be adequate for tumor classification, and a combination of location and molecular composition will be necessary to develop appropriate risk stratification nomograms and treatment strategies.

Indexed as

LeiomyosarcomaSarcomaSoft Tissue NeoplasmsHumansPrognosisVena Cava, InferiorLeiomyosarcomaMolecular classificationSarcomaTumor classification

Identifiers

PMID36884163
PMCPMC11869319
OpenAlexW4323530921

What OpenQuestion holds

Textmetadata
LicenceTDM
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.