Evidence map›Paper›PMID 26714494›Full record

ReviewCurrent treatment options in oncology2016

Molecular Predictors of Radiotherapy Response in Sarcoma.

Carlos H F Chan, Philip Wong

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current treatment options in oncology, 2016. 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
0.2field-weighted citation impact, top 36% 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, 6 citations in OpenAlex.

  1. Article
  2. Article
  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 2 countries.

Carlos H F ChanDepartment of Surgery, University of Iowa Carver College of Medicine, 200 Hawkins Drive, Iowa City, IA, 52242, USA.
Philip WongDepartment of Radiation Oncology, Centre Hospitalier de L'Université de Montréal, 1560 Sherbrooke Street East, Montreal, QC, Canada, H2L 4M1. philip.wong.chum@ssss.gouv.qc.ca.
Centre Hospitalier de l’Université de Montréal · CAUniversity of Iowa · US

Funding

Viral VectorP30CA086862 · NCI · UNIVERSITY OF IOWA · PI Christopher K Laubenthal · 2000 to 2026
$70.0M
6 · The paper itself

Abstract

opinion statementSoft-tissue sarcoma is one of the few clinical cancer models in which pre-operative radiotherapy is commonly utilized and in which tumor response to radiotherapy could be assessed. However, clinical and histopathological features of soft-tissue sarcomas are not useful in predicting tumor radiotherapy response. Exploration of predictive markers of sarcoma response to radiotherapy is further confounded by discordance between radiological tumor size reduction, pathological changes, and clinical local recurrence rates. The diversity of disease histology and anatomical origin further influences which type of radiotherapy response (volumetric vs. cytotoxic) would best relate to patient outcome. Advances in molecular biology and understanding of sarcoma biology have recently resulted in the identification of several molecular and imaging predictive markers of radiotherapy response. As the underlying mechanism of radiation-induced cell killing involves the production of DNA damage through the production of oxygen radicals, the most promising biomarkers and imaging markers are related to DNA damage repair genes, hypoxia, and tumor vasculature. As bone and cartilaginous sarcomas are less often treated with radiotherapy, biomarkers of response in these diseases are less examined.

Indexed as

Biomarkers, TumorDNA DamageDNA RepairDose-Response Relationship, RadiationHumansNeoplasm Recurrence, LocalRadiotherapy, AdjuvantRadiotherapy DosageSarcomaSoft Tissue NeoplasmsTreatment OutcomeBiomarkers, TumorBiomarkerImagingMolecularRadiationResponseSarcoma

Identifiers

PMID26714494
OpenAlexW2277678255

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.