Imaging · dataset · 2019
Development and validation of a prediction model for identifying men with intermediate- or high-risk prostate cancer for whom bone imaging is unnecessary: a nation-wide population-based study
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<p><b>Objective:</b> To develop and validate a nomogram that identifies men for whom bone scan is unnecessary.</p> <p><b>Material and methods:</b> The study datasets were derived from the National Prostate Cancer Register (NPCR) of Sweden.
Description
All men in the NPCR ≤80 years of age who were diagnosed with intermediate- or high-risk prostate cancer and who had pretreatment bone imaging (<sup>99m</sup>Tc MDP scintigraphy, plain x-ray, computed tomography, magnetic resonance imaging, and/or positron emission tomography fused with computed tomography) were included.
Men diagnosed from 2015–2016 formed a development dataset and men diagnosed in 2017 formed a validation dataset. Outcome was metastasis on bone imaging as registered in NPCR. Multivariable logistic regression was used to develop a nomogram.</p> <p><b>Results:</b> In the development dataset 482/5084 men (10%) had bone metastasis, the corresponding percentage in the validation dataset was 282/2554 (11%).
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Gleason grade group, clinical T stage, and prostate-specific antigen were included in the final model. Discrimination and calibration were satisfactory in both the development (AUC 0.80, 95% CI 0.78–0.82) and validation dataset (AUC 0.80, 95% CI, 0.77–0.82). Compared with using the EAU guidelines’ recommendation for selecting men for imaging, using the nomogram with a cut-off at 4% chance of bone metastasis, would have avoided imaging in 519/2068 men (25%) and miss bone metastasis in 10/519 (2%) men in the validation dataset.</p> <p><b>Conclusion:</b> By use of our nomogram, bone scans of men with prostate cancer can be avoided in a large proportion of men.</p>
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Where it is published
- DOI doi.org/10.6084/m9.figshare.11328605.v2 ↗
DOI / persistent id · from figshare com
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from figshare com
Topics
- From keywords
- Astronomy & Astrophysics · Cancer · Chemistry · Computer Science & AI · Earth & Environmental Science · Economics & Finance · Engineering · Genetics · Humanities · Imaging · Life Sciences · Medicine & Health · Ocean & Atmospheric Science · Plant biology · Social Science
- Inferred from text
- Computed tomography 75% · Magnetic resonance imaging 75%
Provenance · 1 source records, 22 field assertions
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