Evidence map›Paper›PMID 41440590›Full record

ArticleJournal of imaging2025

Applying Radiomics to Predict Outcomes in Patients with High-Grade Retroperitoneal Sarcoma Treated with Preoperative Radiotherapy.

Adel Shahnam, Nicholas Hardcastle, David E Gyorki, Katrina M Ingley, Krystel Tran, Catherine Mitchell, Sarat Chander, Julie Chu, Michael Henderson, Alan Herschtal and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Adel ShahnamDepartment of Medical Oncology, Peter MacCallum Cancer Center, Melbourne 3000, Australia.ORCID 0000-0002-0043-8374
Nicholas HardcastleDepartment of Radiation Oncology, Peter MacCallum Cancer Center, Melbourne 3000, Australia.
David E GyorkiDepartment of Surgical Oncology, Peter MacCallum Cancer Center, Melbourne 3000, Australia.
Katrina M IngleyDepartment of Medical Oncology, Peter MacCallum Cancer Center, Melbourne 3000, Australia.ORCID 0000-0002-1806-2686
Krystel TranDepartment of Radiation Oncology, Peter MacCallum Cancer Center, Melbourne 3000, Australia.ORCID 0000-0002-0411-0747
Catherine MitchellSir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne 3000, Australia.ORCID 0000-0001-5596-9511
Sarat ChanderDepartment of Radiation Oncology, Peter MacCallum Cancer Center, Melbourne 3000, Australia.
Julie ChuDepartment of Radiation Oncology, Peter MacCallum Cancer Center, Melbourne 3000, Australia.ORCID 0000-0002-5043-8508
Michael HendersonDepartment of Surgical Oncology, Peter MacCallum Cancer Center, Melbourne 3000, Australia.ORCID 0000-0002-2496-8572
Alan HerschtalCentre for Biostatistics and Clinical Trials, Peter MacCallum Cancer Center, Melbourne 3000, Australia.ORCID 0009-0004-2061-4787
Mathias BresselSir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne 3000, Australia.
Jeremy LewinDepartment of Medical Oncology, Peter MacCallum Cancer Center, Melbourne 3000, Australia.ORCID 0000-0002-4305-117X

Funding

2018 ANZSA Hannahs Chance Sarcoma Research Grant 0000000
6 · The paper itself

Abstract

Retroperitoneal sarcomas (RPS) are rare tumours, primarily treated with surgical resection. However, recurrences are frequent. Combining clinical factors with CT-derived radiomic features could enhance treatment stratification and personalization. This study aims to assess whether radiomic features provide additional prognostic value beyond clinicopathological features in patients with high-risk RPS treated with preoperative radiotherapy. This retrospective study included patients aged 18 or older with non-recurrent and non-metastatic RPS treated with preoperative radiotherapy between 2008 and 2016. Hazard ratios (HR) were calculated using Cox proportional hazards regression to assess the impact of clinical and radiomic features on time to event outcomes. Predictive accuracy was assessed with c-statistics. Radiomic analysis was performed on the high-risk group (undifferentiated pleomorphic sarcoma, well-differentiated/de-differentiated liposarcoma or grade 2/3 leiomyosarcoma). Seventy-two patients were included, with a median follow-up of 3.7 years, the 5-year overall survival (OS) was 67%. Multivariable analysis showed older age (HR: 1.3 per 5-year increase,

Indexed as

predictive modelradiomicsretroperitoneal sarcomas

Identifiers

PMID41440590
PMCPMC12733741

What OpenQuestion holds

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Registered trials

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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.