Evidence map›Paper›PMID 33348683›Full record

ArticleCancers2020

Pediatric Rhabdomyosarcomas: Three-Dimensional Radiological Assessments after Induction Chemotherapy Predict Survival Better than One-Dimensional and Two-Dimensional Measurements.

Giovanna Orsatti, Carlo Morosi, Chiara Giraudo, Alessia Varotto, Filippo Crimì, Miriam Bonzini, Marta Minotti, Anna Chiara Frigo, Ilaria Zanetti, Stefano Chiaravalli and 4 more

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-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

8 citing papers in PubMed, 14 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

14 authors at 2 institutions in 1 country.

Giovanna OrsattiRadiology Institute, Department of Medicine, University of Padova, 35121 Padova, Italy.
Carlo MorosiDepartment of Radiology, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori, 20133 Milan, Italy.
Chiara GiraudoRadiology Institute, Department of Medicine, University of Padova, 35121 Padova, Italy.ORCID 0000-0003-0924-5883
Alessia VarottoRadiology Institute, Department of Medicine, University of Padova, 35121 Padova, Italy.ORCID 0000-0002-1486-8009
Filippo CrimìRadiology Institute, Department of Medicine, University of Padova, 35121 Padova, Italy.ORCID 0000-0001-6822-1430
Miriam BonziniDepartment of Radiology, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori, 20133 Milan, Italy.
Marta MinottiDepartment of Radiology, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori, 20133 Milan, Italy.
Anna Chiara FrigoUnit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, 35121 Padova, Italy.
Ilaria ZanettiHaematology Oncology Division, Department of Women's and Children's Health, University of Padova, 35121 Padova, Italy.
Stefano ChiaravalliPediatric Oncology Unit, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori, 20133 Milan, Italy.
Michela CasanovaPediatric Oncology Unit, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori, 20133 Milan, Italy.
Andrea FerrariPediatric Oncology Unit, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale dei Tumori, 20133 Milan, Italy.ORCID 0000-0002-4724-0517
Gianni BisognoHaematology Oncology Division, Department of Women's and Children's Health, University of Padova, 35121 Padova, Italy.ORCID 0000-0003-4462-5523
Roberto StramareRadiology Institute, Department of Medicine, University of Padova, 35121 Padova, Italy.
University of Padua · ITFondazione IRCCS Istituto Nazionale dei Tumori · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radiological response to neoadjuvant chemotherapy is currently used to assess the efficacy of treatment in pediatric patients with rhabdomyosarcoma (RMS), but the association between early tumor response on imaging and survival is still controversial. The aim of this study was to investigate the prognostic value of assessing radiological response after induction therapy in pediatric RMS, comparing four different methods. This retrospective, two-center study was conducted on 66 non-metastatic RMS patients. Two radiologists measured tumor size on pre- and post-treatment magnetic resonance (MR) or computed tomography (CT) images using four methods: considering maximal diameter with the 1D-RECIST (Response Evaluation Criteria in Solid Tumors); multiplying the two maximal diameters with the 2D-WHO (World Health Organization); multiplying the three maximal diameters with the 3D-EpSSG (European pediatric Soft tissue sarcoma Study Group); obtaining a software-assisted volume assessment with the 3D-Osirix. Each patient was classified as a responder or non-responder based on the proposed thresholds for each method. Tumor response was compared with survival using Kaplan-Meier plots, the log-rank test, and Cox's regression. Agreement between methods and observers (weighted-κ) was also calculated. The 5-year event-free survival (5yr-EFS) calculated with the Kaplan-Meier plots was significantly longer for responders than for non-responders with all the methods, but the 3D assessments differentiated between the two groups better than the 1D-RECIST or 2D-WHO (

Indexed as

imagingpediatricresponse assessmentrhabdomyosarcoma

Identifiers

PMID33348683
PMCPMC7766999
OpenAlexW3112570279

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.