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PHI density prospectively improves prostate cancer detection
PURPOSE: To evaluate the Prostate Health Index (PHI) density (PHID) in direct comparison with PHI in a prospective large cohort. METHODS: PHID values were calculated from prostate-specific antigen (PSA), free PSA and [− 2]proPSA and prostate volume. The 1057 patients included 552 men with prostate c...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8510982/ https://www.ncbi.nlm.nih.gov/pubmed/33471165 http://dx.doi.org/10.1007/s00345-020-03585-2 |
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author | Stephan, Carsten Jung, Klaus Lein, Michael Rochow, Hannah Friedersdorff, Frank Maxeiner, Andreas |
author_facet | Stephan, Carsten Jung, Klaus Lein, Michael Rochow, Hannah Friedersdorff, Frank Maxeiner, Andreas |
author_sort | Stephan, Carsten |
collection | PubMed |
description | PURPOSE: To evaluate the Prostate Health Index (PHI) density (PHID) in direct comparison with PHI in a prospective large cohort. METHODS: PHID values were calculated from prostate-specific antigen (PSA), free PSA and [− 2]proPSA and prostate volume. The 1057 patients included 552 men with prostate cancer (PCa) and 505 with no evidence of malignancy (NEM). In detail, 562 patients were biopsied at the Charité Hospital Berlin and 495 patients at the Sana Hospital Offenbach. All patients received systematic or magnetic resonance imaging (MRI)/ultrasound fusion-guided biopsies. The diagnostic accuracy was evaluated by receiver operating characteristic (ROC) curves comparing areas under the ROC-curves (AUC). The decision curve analysis (DCA) was performed with the MATLAB Neural Network Toolbox. RESULTS: PHID provided a significant larger AUC than PHI (0.835 vs. 0.801; p = 0.0013) in our prospective cohort of 1057 men from 2 centers. The DCA had a maximum net benefit of ~ 5% for PHID vs. PHI between 35 and 65% threshold probability. In those 698 men within the WHO-calibrated PSA grey-zone up to 8 ng/ml, PHID was also significantly better than PHI (AUC 0.819 vs. 0.789; p = 0.0219). But PHID was not different from PHI in the detection of significant PCa. CONCLUSIONS: Based on ROC analysis and DCA, PHID had an advantage in comparison with PHI alone to detect any PCa but PHI and PHID performed equal in detecting significant PCa. |
format | Online Article Text |
id | pubmed-8510982 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-85109822021-10-27 PHI density prospectively improves prostate cancer detection Stephan, Carsten Jung, Klaus Lein, Michael Rochow, Hannah Friedersdorff, Frank Maxeiner, Andreas World J Urol Original Article PURPOSE: To evaluate the Prostate Health Index (PHI) density (PHID) in direct comparison with PHI in a prospective large cohort. METHODS: PHID values were calculated from prostate-specific antigen (PSA), free PSA and [− 2]proPSA and prostate volume. The 1057 patients included 552 men with prostate cancer (PCa) and 505 with no evidence of malignancy (NEM). In detail, 562 patients were biopsied at the Charité Hospital Berlin and 495 patients at the Sana Hospital Offenbach. All patients received systematic or magnetic resonance imaging (MRI)/ultrasound fusion-guided biopsies. The diagnostic accuracy was evaluated by receiver operating characteristic (ROC) curves comparing areas under the ROC-curves (AUC). The decision curve analysis (DCA) was performed with the MATLAB Neural Network Toolbox. RESULTS: PHID provided a significant larger AUC than PHI (0.835 vs. 0.801; p = 0.0013) in our prospective cohort of 1057 men from 2 centers. The DCA had a maximum net benefit of ~ 5% for PHID vs. PHI between 35 and 65% threshold probability. In those 698 men within the WHO-calibrated PSA grey-zone up to 8 ng/ml, PHID was also significantly better than PHI (AUC 0.819 vs. 0.789; p = 0.0219). But PHID was not different from PHI in the detection of significant PCa. CONCLUSIONS: Based on ROC analysis and DCA, PHID had an advantage in comparison with PHI alone to detect any PCa but PHI and PHID performed equal in detecting significant PCa. Springer Berlin Heidelberg 2021-01-20 2021 /pmc/articles/PMC8510982/ /pubmed/33471165 http://dx.doi.org/10.1007/s00345-020-03585-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 | Original Article Stephan, Carsten Jung, Klaus Lein, Michael Rochow, Hannah Friedersdorff, Frank Maxeiner, Andreas PHI density prospectively improves prostate cancer detection |
title | PHI density prospectively improves prostate cancer detection |
title_full | PHI density prospectively improves prostate cancer detection |
title_fullStr | PHI density prospectively improves prostate cancer detection |
title_full_unstemmed | PHI density prospectively improves prostate cancer detection |
title_short | PHI density prospectively improves prostate cancer detection |
title_sort | phi density prospectively improves prostate cancer detection |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8510982/ https://www.ncbi.nlm.nih.gov/pubmed/33471165 http://dx.doi.org/10.1007/s00345-020-03585-2 |
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