Evidence map›Paper›PMID 39806614›Full record

ArticleBMJ open2024

Development and internal validation of prognostic models for event-free survival in newly diagnosed Ewing sarcoma patients based on routinely collected clinical characteristics from the European randomised controlled trial, EE2012.

Laura Kirton, Richard Riley, Piers Gaunt, Bernadette Brennan, Kym Snell

Abstract readClinical Trial Protocol
In one paragraph

Article in BMJ open, 2024. 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

5 authors.

Laura KirtonCancer Research UK Clinical Trials Unit, School of Medical Sciences, College of Medicine and Health, University of Birmingham, Birmingham, UK l.kirton@bham.ac.uk.ORCID http://orcid.org/0000-0002-6255-6552
Richard RileyDepartment of Applied Health Sciences, School of Health Sciences, College of Medicine and Health, University of Birmingham, Birmingham, UK.ORCID http://orcid.org/0000-0001-8699-0735
Piers GauntCancer Research UK Clinical Trials Unit, School of Medical Sciences, College of Medicine and Health, University of Birmingham, Birmingham, UK.ORCID http://orcid.org/0000-0001-8665-300X
Bernadette BrennanRoyal Manchester Children's Hospital, Manchester, UK.
Kym SnellDepartment of Applied Health Sciences, School of Health Sciences, College of Medicine and Health, University of Birmingham, Birmingham, UK.ORCID http://orcid.org/0000-0001-9373-6591

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionEwing sarcoma is a rare paediatric cancer. Currently, there is no way of accurately predicting these patients' survival at diagnosis. Disease type (ie, localised disease, lung/pleuropulmonary metastases and other metastases) is used to guide treatment decisions, with metastatic patients generally having worse outcomes than localised disease patients. However, not all patients fit this trend. An accurate prognostic model could be used to guide treatment decisions in clinical practice to avoid patients being incorrectly under or overtreated. METHODS AND ANALYSIS: This study aims to develop and internally validate prognostic models in newly diagnosed Ewing sarcoma patients, using the EE2012 clinical trial data set. The models will incorporate prognostic factors, identified from a literature review, to predict patients' probability of event-free survival at clinically important time points. Three models will be developed, for comparison of their performance and stability, using different methods of model selection and penalisation for overfitting (full model or backwards selection applying uniform shrinkage; and lasso variable selection). The models will be internally validated using bootstrapping to give optimism-adjusted performance statistics (calibration and discrimination) and model stability results. Patient and clinical user groups will be asked to determine risk thresholds to guide treatment decisions in clinical practice based on the model. Decision curve analyses will examine clinical utility at these thresholds. ETHICS AND DISSEMINATION: This study is a secondary analysis of EE2012 clinical trial data. The EE2012 trial received ethical approval from the competent authorities (UK ethics reference approval number 12/NW/0827). This study is covered by the trial ethics in place. The results from this study will be published in peer-reviewed journals to act as a benchmark for future studies. TRIAL REGISTRATION NUMBER: EudraCT number 2012-002107-17. ISRCTN number 92192408.

Indexed as

Bone NeoplasmsModels, StatisticalSarcoma, EwingAdolescentChildDisease-Free SurvivalEuropeFemaleHumansMalePrognosisRandomized Controlled Trials as TopicPaediatric oncologyPrognosisSarcomaSTATISTICS & RESEARCH METHODS

Identifiers

PMID39806614
PMCPMC11667367

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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.