Development of a novel nomogram for predicting clinically significant prostate cancer with the prostate health index and multiparametric MRI
IntroductionOn prostate biopsy, multiparametric magnetic resonance imaging (mpMRI) and the Prostate Health Index (PHI) have allowed prediction of clinically significant prostate cancer (csPCa).MethodsTo predict the likelihood of csPCa, we created a nomogram based on a multivariate model that include...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-11-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.1068893/full |
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| author | Li-Cai Mo Xian-Jun Zhang Hai-Hong Zheng Xiao-peng Huang Lin Zheng Zhi-Rui Zhou Jia-Jia Wang |
| author_facet | Li-Cai Mo Xian-Jun Zhang Hai-Hong Zheng Xiao-peng Huang Lin Zheng Zhi-Rui Zhou Jia-Jia Wang |
| author_sort | Li-Cai Mo |
| collection | DOAJ |
| description | IntroductionOn prostate biopsy, multiparametric magnetic resonance imaging (mpMRI) and the Prostate Health Index (PHI) have allowed prediction of clinically significant prostate cancer (csPCa).MethodsTo predict the likelihood of csPCa, we created a nomogram based on a multivariate model that included PHI and mpMRI. We assessed 315 males who were scheduled for prostate biopsies.ResultsWe used the Prostate Imaging Reporting and Data System version 2 (PI-RADS V2) to assess mpMRI and optimize PHI testing prior to biopsy. Univariate analysis showed that csPCa may be identified by PHI with a cut-off value of 77.77, PHID with 2.36, and PI-RADS with 3 as the best threshold. Multivariable logistic models for predicting csPCa were developed using PI-RADS, free PSA (fPSA), PHI, and prostate volume. A multivariate model that included PI-RADS, fPSA, PHI, and prostate volume had the best accuracy (AUC: 0.882). Decision curve analysis (DCA), which was carried out to verify the nomogram’s clinical applicability, showed an ideal advantage (13.35% higher than the model that include PI-RADS only).DiscussionIn conclusion, the nomogram based on PHI and mpMRI is a valuable tool for predicting csPCa while avoiding unnecessary biopsy as much as possible. |
| first_indexed | 2024-04-13T13:32:13Z |
| format | Article |
| id | doaj.art-1760daf740f543809951cac98a411281 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-04-13T13:32:13Z |
| publishDate | 2022-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-1760daf740f543809951cac98a4112812022-12-22T02:44:54ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-11-011210.3389/fonc.2022.10688931068893Development of a novel nomogram for predicting clinically significant prostate cancer with the prostate health index and multiparametric MRILi-Cai Mo0Xian-Jun Zhang1Hai-Hong Zheng2Xiao-peng Huang3Lin Zheng4Zhi-Rui Zhou5Jia-Jia Wang6Department of Urology, Taizhou Hospital of Zhejiang Province affiliated with Wenzhou Medical University, Linhai, Taizhou, Zhejiang, ChinaDepartment of Urology, Taizhou Hospital of Zhejiang Province affiliated with Wenzhou Medical University, Linhai, Taizhou, Zhejiang, ChinaDepartment of Pathology, Taizhou Hospital of Zhejiang Province affiliated with Wenzhou Medical University, Linhai, Taizhou, Zhejiang, ChinaDepartment of Urology, Taizhou Cancer Hospital, Wenling, Taizhou, Zhejiang, ChinaDepartment of Radiation Oncology Center, Taizhou Cancer Hospital, Wenling, Taizhou, Zhejiang, ChinaDepartment of Radiation Oncology Center, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, ChinaDepartment of Traditional Chinese Medicine, Taizhou Hospital of Zhejiang Province affiliated with Wenzhou Medical University, Linhai, Taizhou, Zhejiang, ChinaIntroductionOn prostate biopsy, multiparametric magnetic resonance imaging (mpMRI) and the Prostate Health Index (PHI) have allowed prediction of clinically significant prostate cancer (csPCa).MethodsTo predict the likelihood of csPCa, we created a nomogram based on a multivariate model that included PHI and mpMRI. We assessed 315 males who were scheduled for prostate biopsies.ResultsWe used the Prostate Imaging Reporting and Data System version 2 (PI-RADS V2) to assess mpMRI and optimize PHI testing prior to biopsy. Univariate analysis showed that csPCa may be identified by PHI with a cut-off value of 77.77, PHID with 2.36, and PI-RADS with 3 as the best threshold. Multivariable logistic models for predicting csPCa were developed using PI-RADS, free PSA (fPSA), PHI, and prostate volume. A multivariate model that included PI-RADS, fPSA, PHI, and prostate volume had the best accuracy (AUC: 0.882). Decision curve analysis (DCA), which was carried out to verify the nomogram’s clinical applicability, showed an ideal advantage (13.35% higher than the model that include PI-RADS only).DiscussionIn conclusion, the nomogram based on PHI and mpMRI is a valuable tool for predicting csPCa while avoiding unnecessary biopsy as much as possible.https://www.frontiersin.org/articles/10.3389/fonc.2022.1068893/fullprostate cancernomogrammultiparametric magnetic resonance imaging (mpMRI)prostate health indexpredicting |
| spellingShingle | Li-Cai Mo Xian-Jun Zhang Hai-Hong Zheng Xiao-peng Huang Lin Zheng Zhi-Rui Zhou Jia-Jia Wang Development of a novel nomogram for predicting clinically significant prostate cancer with the prostate health index and multiparametric MRI Frontiers in Oncology prostate cancer nomogram multiparametric magnetic resonance imaging (mpMRI) prostate health index predicting |
| title | Development of a novel nomogram for predicting clinically significant prostate cancer with the prostate health index and multiparametric MRI |
| title_full | Development of a novel nomogram for predicting clinically significant prostate cancer with the prostate health index and multiparametric MRI |
| title_fullStr | Development of a novel nomogram for predicting clinically significant prostate cancer with the prostate health index and multiparametric MRI |
| title_full_unstemmed | Development of a novel nomogram for predicting clinically significant prostate cancer with the prostate health index and multiparametric MRI |
| title_short | Development of a novel nomogram for predicting clinically significant prostate cancer with the prostate health index and multiparametric MRI |
| title_sort | development of a novel nomogram for predicting clinically significant prostate cancer with the prostate health index and multiparametric mri |
| topic | prostate cancer nomogram multiparametric magnetic resonance imaging (mpMRI) prostate health index predicting |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2022.1068893/full |
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