Cargando…
A novel model to predict positive prostate biopsy based on serum androgen level
Circulating levels of prostate-specific antigen (PSA) and testosterone are widely used for the detection of prostate cancer prior to prostate biopsy; however, both remain controversial. Effective screening strategies based on quantitative factors could help avoid unnecessary biopsies. Here, we sough...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Bioscientifica Ltd
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5744473/ https://www.ncbi.nlm.nih.gov/pubmed/29046289 http://dx.doi.org/10.1530/ERC-17-0134 |
_version_ | 1783288753140269056 |
---|---|
author | Ujike, Takeshi Uemura, Motohide Kawashima, Atsunari Nagahara, Akira Fujita, Kazutoshi Miyagawa, Yasushi Nonomura, Norio |
author_facet | Ujike, Takeshi Uemura, Motohide Kawashima, Atsunari Nagahara, Akira Fujita, Kazutoshi Miyagawa, Yasushi Nonomura, Norio |
author_sort | Ujike, Takeshi |
collection | PubMed |
description | Circulating levels of prostate-specific antigen (PSA) and testosterone are widely used for the detection of prostate cancer prior to prostate biopsy; however, both remain controversial. Effective screening strategies based on quantitative factors could help avoid unnecessary biopsies. Here, we sought to clarify the predictive value of free testosterone (FT) vs total testosterone (TT) in identifying patients likely to have positive biopsies. This study aims to develop a novel model for predicting positive prostate biopsy based on serum androgen levels. This study included 253 Japanese patients who underwent prostate biopsy at our institution. TT and FT, %FT (=FT/TT), age, PSA, prostate volume (PV) and PSA density (PSAD = PSA/PV) were assessed for association with prostate biopsy findings. The following results were obtained. Of 253 patients, 145 (57.3%) had positive biopsies. Compared to the negative biopsy group, the positive biopsy group demonstrated higher age, PSA and PSAD but lower PV, FT and %FT by univariate analysis. Multivariate logistic regression analysis indicated PSA, PSAD and %FT were independent predictors of cancer detection. We developed a predictive model based on PSAD and %FT, for which the area under the curve was significantly greater than that of PSA (0.82 vs 0.66), a well-known predictor. Applying this analysis to the subset of patients with PSA <10 ng/mL yielded similar results. We confirmed the utility of this model in another independent cohort of 88 patients. In conclusion, lower %FT predicted a positive prostate biopsy. We constructed a predictive model based on %FT and PSAD, which are easily obtained prior to biopsy. |
format | Online Article Text |
id | pubmed-5744473 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Bioscientifica Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-57444732018-01-04 A novel model to predict positive prostate biopsy based on serum androgen level Ujike, Takeshi Uemura, Motohide Kawashima, Atsunari Nagahara, Akira Fujita, Kazutoshi Miyagawa, Yasushi Nonomura, Norio Endocr Relat Cancer Research Circulating levels of prostate-specific antigen (PSA) and testosterone are widely used for the detection of prostate cancer prior to prostate biopsy; however, both remain controversial. Effective screening strategies based on quantitative factors could help avoid unnecessary biopsies. Here, we sought to clarify the predictive value of free testosterone (FT) vs total testosterone (TT) in identifying patients likely to have positive biopsies. This study aims to develop a novel model for predicting positive prostate biopsy based on serum androgen levels. This study included 253 Japanese patients who underwent prostate biopsy at our institution. TT and FT, %FT (=FT/TT), age, PSA, prostate volume (PV) and PSA density (PSAD = PSA/PV) were assessed for association with prostate biopsy findings. The following results were obtained. Of 253 patients, 145 (57.3%) had positive biopsies. Compared to the negative biopsy group, the positive biopsy group demonstrated higher age, PSA and PSAD but lower PV, FT and %FT by univariate analysis. Multivariate logistic regression analysis indicated PSA, PSAD and %FT were independent predictors of cancer detection. We developed a predictive model based on PSAD and %FT, for which the area under the curve was significantly greater than that of PSA (0.82 vs 0.66), a well-known predictor. Applying this analysis to the subset of patients with PSA <10 ng/mL yielded similar results. We confirmed the utility of this model in another independent cohort of 88 patients. In conclusion, lower %FT predicted a positive prostate biopsy. We constructed a predictive model based on %FT and PSAD, which are easily obtained prior to biopsy. Bioscientifica Ltd 2017-10-18 /pmc/articles/PMC5744473/ /pubmed/29046289 http://dx.doi.org/10.1530/ERC-17-0134 Text en © 2018 The authors http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Ujike, Takeshi Uemura, Motohide Kawashima, Atsunari Nagahara, Akira Fujita, Kazutoshi Miyagawa, Yasushi Nonomura, Norio A novel model to predict positive prostate biopsy based on serum androgen level |
title | A novel model to predict positive prostate biopsy based on serum androgen level |
title_full | A novel model to predict positive prostate biopsy based on serum androgen level |
title_fullStr | A novel model to predict positive prostate biopsy based on serum androgen level |
title_full_unstemmed | A novel model to predict positive prostate biopsy based on serum androgen level |
title_short | A novel model to predict positive prostate biopsy based on serum androgen level |
title_sort | novel model to predict positive prostate biopsy based on serum androgen level |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5744473/ https://www.ncbi.nlm.nih.gov/pubmed/29046289 http://dx.doi.org/10.1530/ERC-17-0134 |
work_keys_str_mv | AT ujiketakeshi anovelmodeltopredictpositiveprostatebiopsybasedonserumandrogenlevel AT uemuramotohide anovelmodeltopredictpositiveprostatebiopsybasedonserumandrogenlevel AT kawashimaatsunari anovelmodeltopredictpositiveprostatebiopsybasedonserumandrogenlevel AT nagaharaakira anovelmodeltopredictpositiveprostatebiopsybasedonserumandrogenlevel AT fujitakazutoshi anovelmodeltopredictpositiveprostatebiopsybasedonserumandrogenlevel AT miyagawayasushi anovelmodeltopredictpositiveprostatebiopsybasedonserumandrogenlevel AT nonomuranorio anovelmodeltopredictpositiveprostatebiopsybasedonserumandrogenlevel AT ujiketakeshi novelmodeltopredictpositiveprostatebiopsybasedonserumandrogenlevel AT uemuramotohide novelmodeltopredictpositiveprostatebiopsybasedonserumandrogenlevel AT kawashimaatsunari novelmodeltopredictpositiveprostatebiopsybasedonserumandrogenlevel AT nagaharaakira novelmodeltopredictpositiveprostatebiopsybasedonserumandrogenlevel AT fujitakazutoshi novelmodeltopredictpositiveprostatebiopsybasedonserumandrogenlevel AT miyagawayasushi novelmodeltopredictpositiveprostatebiopsybasedonserumandrogenlevel AT nonomuranorio novelmodeltopredictpositiveprostatebiopsybasedonserumandrogenlevel |