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A preoperative magnetic resonance imaging-based model to predict biochemical failure after radical prostatectomy
To investigate if a magnetic resonance imaging (MRI)-based model reduced postoperative biochemical failure (BF) incidence in patients with prostate cancer (PCa). From June 2018 to January 2020, we retrospectively analyzed 967 patients who underwent prostate bi-parametric MRI and radical prostatectom...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9829893/ https://www.ncbi.nlm.nih.gov/pubmed/36624154 http://dx.doi.org/10.1038/s41598-022-26920-6 |
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author | Pan, Minjie Li, Shouchun Liu, Fade Liang, Linghui Shang, Jinwei Xia, Wei Cheng, Gong Hua, Lixin |
author_facet | Pan, Minjie Li, Shouchun Liu, Fade Liang, Linghui Shang, Jinwei Xia, Wei Cheng, Gong Hua, Lixin |
author_sort | Pan, Minjie |
collection | PubMed |
description | To investigate if a magnetic resonance imaging (MRI)-based model reduced postoperative biochemical failure (BF) incidence in patients with prostate cancer (PCa). From June 2018 to January 2020, we retrospectively analyzed 967 patients who underwent prostate bi-parametric MRI and radical prostatectomy (RP). After inclusion criteria were applied, 446 patients were randomized into research (n = 335) and validation cohorts (n = 111) at a 3:1 ratio. In addition to clinical variables, MRI models also included MRI parameters. The area under the curve (AUC) of receiver operating characteristic and decision curves were analyzed. The risk of postoperative BF, defined as persistently high or re-elevated prostate serum antigen (PSA) levels in patients with PCa with no clinical recurrence. In the research (age 69 [63–74] years) and validation cohorts (age 69 [64–74] years), the postoperative BF incidence was 22.39% and 27.02%, respectively. In the research cohort, the AUC of baseline and MRI models was 0.780 and 0.857, respectively, with a significant difference (P < 0.05). Validation cohort results were consistent (0.753 vs. 0.865, P < 0.05). At a 20% risk threshold, the false positive rate in the MRI model was lower when compared with the baseline model (31% [95% confidence interval (CI): 9–39%] vs. 44% [95% CI: 15–64%]), with the true positive rate only decreasing by a little (83% [95% CI: 63–94%] vs. 87% [95% CI: 75–100%]). 32 of 100 RPs can been performed, with no raise in quantity of patients with missed BF. We developed and verified a MRI-based model to predict BF incidence in patients after RP using preoperative clinical and MRI-related variables. This model could be used in clinical settings. |
format | Online Article Text |
id | pubmed-9829893 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-98298932023-01-11 A preoperative magnetic resonance imaging-based model to predict biochemical failure after radical prostatectomy Pan, Minjie Li, Shouchun Liu, Fade Liang, Linghui Shang, Jinwei Xia, Wei Cheng, Gong Hua, Lixin Sci Rep Article To investigate if a magnetic resonance imaging (MRI)-based model reduced postoperative biochemical failure (BF) incidence in patients with prostate cancer (PCa). From June 2018 to January 2020, we retrospectively analyzed 967 patients who underwent prostate bi-parametric MRI and radical prostatectomy (RP). After inclusion criteria were applied, 446 patients were randomized into research (n = 335) and validation cohorts (n = 111) at a 3:1 ratio. In addition to clinical variables, MRI models also included MRI parameters. The area under the curve (AUC) of receiver operating characteristic and decision curves were analyzed. The risk of postoperative BF, defined as persistently high or re-elevated prostate serum antigen (PSA) levels in patients with PCa with no clinical recurrence. In the research (age 69 [63–74] years) and validation cohorts (age 69 [64–74] years), the postoperative BF incidence was 22.39% and 27.02%, respectively. In the research cohort, the AUC of baseline and MRI models was 0.780 and 0.857, respectively, with a significant difference (P < 0.05). Validation cohort results were consistent (0.753 vs. 0.865, P < 0.05). At a 20% risk threshold, the false positive rate in the MRI model was lower when compared with the baseline model (31% [95% confidence interval (CI): 9–39%] vs. 44% [95% CI: 15–64%]), with the true positive rate only decreasing by a little (83% [95% CI: 63–94%] vs. 87% [95% CI: 75–100%]). 32 of 100 RPs can been performed, with no raise in quantity of patients with missed BF. We developed and verified a MRI-based model to predict BF incidence in patients after RP using preoperative clinical and MRI-related variables. This model could be used in clinical settings. Nature Publishing Group UK 2023-01-09 /pmc/articles/PMC9829893/ /pubmed/36624154 http://dx.doi.org/10.1038/s41598-022-26920-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Pan, Minjie Li, Shouchun Liu, Fade Liang, Linghui Shang, Jinwei Xia, Wei Cheng, Gong Hua, Lixin A preoperative magnetic resonance imaging-based model to predict biochemical failure after radical prostatectomy |
title | A preoperative magnetic resonance imaging-based model to predict biochemical failure after radical prostatectomy |
title_full | A preoperative magnetic resonance imaging-based model to predict biochemical failure after radical prostatectomy |
title_fullStr | A preoperative magnetic resonance imaging-based model to predict biochemical failure after radical prostatectomy |
title_full_unstemmed | A preoperative magnetic resonance imaging-based model to predict biochemical failure after radical prostatectomy |
title_short | A preoperative magnetic resonance imaging-based model to predict biochemical failure after radical prostatectomy |
title_sort | preoperative magnetic resonance imaging-based model to predict biochemical failure after radical prostatectomy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9829893/ https://www.ncbi.nlm.nih.gov/pubmed/36624154 http://dx.doi.org/10.1038/s41598-022-26920-6 |
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