File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Prostate volume does not provide additional predictive value to prostate health index for prostate cancer or clinically significant prostate cancer: Results from a multicenter study in China

TitleProstate volume does not provide additional predictive value to prostate health index for prostate cancer or clinically significant prostate cancer: Results from a multicenter study in China
Authors
KeywordsChina; prostate cancer; prostate health index; prostate volume
Issue Date2020
Citation
Asian Journal of Andrology, 2020, v. 22, n. 5, p. 539-543 How to Cite?
AbstractTo evaluate whether prostate volume (PV) would provide additional predictive utility to the prostate health index (phi) for predicting prostate cancer (PCa) or clinically significant prostate cancer, we designed a prospective, observational multicenter study in two prostate biopsy cohorts. Cohort 1 included 595 patients from three medical centers from 2012 to 2013, and Cohort 2 included 1025 patients from four medical centers from 2013 to 2014. Area under the receiver operating characteristic curves (AUC) and logistic regression models were used to evaluate the predictive performance of PV-based derivatives and models. Linear regression analysis showed that both total prostate-specific antigen (tPSA) and free PSA (fPSA) were significantly correlated with PV (all P < 0.05). [-2]proPSA (p2PSA) was significantly correlated with PV in Cohort 2 (P< 0.001) but not in Cohort 1 (P= 0.309), while no significant association was observed between phi and PV. When combining phi with PV, phi density (PHID) and another phi derivative (PHIV, calculated as phi/PV0.5) did not outperform phi for predicting PCa or clinically significant PCa in either Cohort 1 or Cohort 2. Logistic regression analysis also showed that phi and PV were independent predictors for both PCa and clinically significant PCa (all P < 0.05); however, PV did not provide additional predictive value to phi when combining these derivatives in a regression model (all models vs phi were not statistically significant, all P > 0.05). In conclusion, PV-based derivatives (both PHIV and PHID) and models incorporating PV did not improve the predictive abilities of phi for either PCa or clinically significant PCa.
Persistent Identifierhttp://hdl.handle.net/10722/314369
ISSN
2023 Impact Factor: 3.0
2023 SCImago Journal Rankings: 0.689
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHuang, Da-
dc.contributor.authorWu, Yi Shuo-
dc.contributor.authorYe, DIng Wei-
dc.contributor.authorQi, Jun-
dc.contributor.authorLiu, Fang-
dc.contributor.authorHelfand, Brian-
dc.contributor.authorZheng, Siqun-
dc.contributor.authorDIng, Qiang-
dc.contributor.authorXu, Dan Feng-
dc.contributor.authorNa, Rong-
dc.contributor.authorXu, Jian Feng-
dc.contributor.authorSun, Ying Hao-
dc.date.accessioned2022-07-20T12:03:47Z-
dc.date.available2022-07-20T12:03:47Z-
dc.date.issued2020-
dc.identifier.citationAsian Journal of Andrology, 2020, v. 22, n. 5, p. 539-543-
dc.identifier.issn1008-682X-
dc.identifier.urihttp://hdl.handle.net/10722/314369-
dc.description.abstractTo evaluate whether prostate volume (PV) would provide additional predictive utility to the prostate health index (phi) for predicting prostate cancer (PCa) or clinically significant prostate cancer, we designed a prospective, observational multicenter study in two prostate biopsy cohorts. Cohort 1 included 595 patients from three medical centers from 2012 to 2013, and Cohort 2 included 1025 patients from four medical centers from 2013 to 2014. Area under the receiver operating characteristic curves (AUC) and logistic regression models were used to evaluate the predictive performance of PV-based derivatives and models. Linear regression analysis showed that both total prostate-specific antigen (tPSA) and free PSA (fPSA) were significantly correlated with PV (all P < 0.05). [-2]proPSA (p2PSA) was significantly correlated with PV in Cohort 2 (P< 0.001) but not in Cohort 1 (P= 0.309), while no significant association was observed between phi and PV. When combining phi with PV, phi density (PHID) and another phi derivative (PHIV, calculated as phi/PV0.5) did not outperform phi for predicting PCa or clinically significant PCa in either Cohort 1 or Cohort 2. Logistic regression analysis also showed that phi and PV were independent predictors for both PCa and clinically significant PCa (all P < 0.05); however, PV did not provide additional predictive value to phi when combining these derivatives in a regression model (all models vs phi were not statistically significant, all P > 0.05). In conclusion, PV-based derivatives (both PHIV and PHID) and models incorporating PV did not improve the predictive abilities of phi for either PCa or clinically significant PCa.-
dc.languageeng-
dc.relation.ispartofAsian Journal of Andrology-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectChina; prostate cancer; prostate health index; prostate volume-
dc.titleProstate volume does not provide additional predictive value to prostate health index for prostate cancer or clinically significant prostate cancer: Results from a multicenter study in China-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.4103/aja.aja_136_19-
dc.identifier.pmid31929198-
dc.identifier.pmcidPMC7523603-
dc.identifier.scopuseid_2-s2.0-85090054120-
dc.identifier.volume22-
dc.identifier.issue5-
dc.identifier.spage539-
dc.identifier.epage543-
dc.identifier.eissn1745-7262-
dc.identifier.isiWOS:000569872800016-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats