Evidence map›Paper›PMID 31005205›Full record

ArticleRadiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology2019

MRI heterogeneity analysis for prediction of recurrence and disease free survival in anal cancer.

Kasia Owczarczyk, Davide Prezzi, Matthew Cascino, Robert Kozarski, Andrew Gaya, Muhammad Siddique, Gary J Cook, Rob Glynne-Jones, Vicky Goh

Open access · hybridAbstract read
In one paragraph

Article in Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.1field-weighted citation impact, top 9% 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

14 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Factors Influencing Outcomes and Survival in Anal Cancer.Current oncology (Toronto, Ont.) · 2024
    Article
  7. Article
  8. Magnetic resonance imaging of anal cancer: tumor characteristics and early prediction of treatment outcome.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2024
    Article
  9. A common [18F]-FDG PET radiomic signature to predict survival in patients with HPV-induced cancers.European journal of nuclear medicine and molecular imaging · 2023
    Article
  10. Estimating Risk of Locoregional Failure and Overall Survival in Anal Cancer Following Chemoradiation: A Machine Learning Approach.Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract · 2023
    Article
  11. Review
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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

9 authors at 3 institutions in 1 country.

Kasia OwczarczykCancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom. Electronic address: kasia.owczarczyk@kcl.ac.uk.
Davide PrezziCancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Matthew CascinoGenentech, South San Francisco, United States.
Robert KozarskiCancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Andrew GayaDepartment of Oncology, Guy's and St Thomas' Hospital NHS Foundation Trust, London, United Kingdom.
Muhammad SiddiqueCancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Gary J CookCancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Rob Glynne-JonesCancer Centre, Mount Vernon Hospital, Northwood, United Kingdom.
Vicky GohCancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
King's College London · GBMount Vernon Hospital · GBSt Thomas' Hospital · GB

Funding

Cancer Research UK 16463Cancer Research UK 19121Department of HealthMedical Research CouncilWellcome Trust 203148Wellcome Trust WT 203148/Z/16/Z
6 · The paper itself

Abstract

backgroundThe aim of this study was to evaluate the role of image heterogeneity analysis of standard care magnetic resonance imaging (MRI) in patients with anal squamous cell carcinoma (ASCC) to predict chemoradiotherapy (CRT) outcome. The ability to predict disease recurrence following CRT has the potential to inform personalized radiotherapy approaches currently being explored in novel clinical trials.

methodsAn IRB waiver was obtained for retrospective analysis of standard care MRIs from ASCC patients presenting between 2010 and 2014. Whole tumor 3D volume-of-interest (VOI) was outlined on T2-weighted (T2w) and diffusion weighted imaging (DWI) of the pre- and post-treatment scans. Independent imaging features most predictive of disease recurrence were added to the baseline clinico-pathological model and the predictive value of respective extended models was calculated using net reclassification improvement (NRI) algorithm. Cross-validation analysis was carried out to determine percentage error reduction with inclusion of imaging features to the baseline model for both endpoints.

resultsForty patients who underwent 1.5 T pelvic MRI at baseline and following completion of CRT were included. A combination of two baseline MR heterogeneity features (baseline T2w energy and DWI coefficient of variation) was most predictive of disease recurrence resulting in significant NRI (p = 0 < 0.001). This was confirmed in cross-validation analysis with 34.8% percentage error reduction for the primary endpoint and 18.1% reduction for the secondary endpoint with addition of imaging variables to baseline model.

conclusionMRI heterogeneity analysis offers complementary information, in addition to clinical staging, in predicting outcome of CRT in anal SCC, warranting validation in larger datasets.

Indexed as

ChemoradiotherapyNeoplasm Recurrence, LocalAdultAgedAged, 80 and overAnus NeoplasmsCarcinoma, Squamous CellDiffusion Magnetic Resonance ImagingDisease-Free SurvivalFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedRetrospective StudiesAnal cancerBiomarkersImagingMRI

Identifiers

PMID31005205
PMCPMC7617040
OpenAlexW2914820491

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.