Optimal Predictors on Repeat Prostate Biopsy : A Retrospective Analysis
碩士 === 中山醫學大學 === 醫學研究所 === 98 === Purpose: The aim of our study was to identify the optimal predictor of prostate cancer among several prostate-specific antigen (PSA) derivatives in repeat prostate biopsy. Methods: We retrospectively assessed the repeat prostate biopsy specimens, obtained between 1...
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ndltd-TW-098CSMU55340062015-10-28T04:07:06Z http://ndltd.ncl.edu.tw/handle/42154860189296333359 Optimal Predictors on Repeat Prostate Biopsy : A Retrospective Analysis 利用血清PSA及其衍生數據預測再次攝護腺切片結果之研究 Chuan-Shu 陳卷書 碩士 中山醫學大學 醫學研究所 98 Purpose: The aim of our study was to identify the optimal predictor of prostate cancer among several prostate-specific antigen (PSA) derivatives in repeat prostate biopsy. Methods: We retrospectively assessed the repeat prostate biopsy specimens, obtained between 1999 and 2008, of 212 patients with total PSA (tPSA) of 4-10 ng/ml and normal digital rectal examination (DRE). Using receiver operating characteristic (ROC) analysis, we assessed the predictive power of tPSA, percent free PSA (f/t PSA), PSA density (PSAD), and PSA velocity (PSAV) for detection of prostate cancer. Results: Repeat prostate biopsy specimens were positive for prostate cancer in the case of 26 patients and negative in the case of 186 patients. The areas under the ROC curve for tPSA, f/tPSA, PSAD, and PSAV were 72.7%, 57.9%, 74.4%, and 64.8%, respectively. The ROC curve analysis revealed that PSAD was a better predictor of prostate cancer than f/t PSA. Moreover, when PSAD at an optimal cutoff of 0.18 ng/ml/cc was considered as the predictor, the detection of prostate cancer was found to have a high sensitivity and specificity ( 77% and 69%, respectively). Conclusions: In repeat prostate biopsy, PSAD is superior to f/t PSA as a predictor of prostate cancer and by assessing this predictor, unnecessary repeat biopsy of patients with tPSA of 4-10 ng/ml can be avoided. Ming-Chih Chou 周明智 2010 學位論文 ; thesis 25 zh-TW |
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碩士 === 中山醫學大學 === 醫學研究所 === 98 === Purpose: The aim of our study was to identify the optimal predictor of prostate cancer among several prostate-specific antigen (PSA) derivatives in repeat prostate biopsy.
Methods: We retrospectively assessed the repeat prostate biopsy specimens, obtained between 1999 and 2008, of 212 patients with total PSA (tPSA) of 4-10 ng/ml and normal digital rectal examination (DRE). Using receiver operating characteristic (ROC) analysis, we assessed the predictive power of tPSA, percent free PSA (f/t PSA), PSA density (PSAD), and PSA velocity (PSAV) for detection of prostate cancer.
Results: Repeat prostate biopsy specimens were positive for prostate cancer in the case of 26 patients and negative in the case of 186 patients. The areas under the ROC curve for tPSA, f/tPSA, PSAD, and PSAV were 72.7%, 57.9%, 74.4%, and 64.8%, respectively. The ROC curve analysis revealed that PSAD was a better predictor of prostate cancer than f/t PSA. Moreover, when PSAD at an optimal cutoff of 0.18 ng/ml/cc was considered as the predictor, the detection of prostate cancer was found to have a high sensitivity and specificity ( 77% and 69%, respectively).
Conclusions: In repeat prostate biopsy, PSAD is superior to f/t PSA as a predictor of prostate cancer and by assessing this predictor, unnecessary repeat biopsy of patients with tPSA of 4-10 ng/ml can be avoided.
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Ming-Chih Chou |
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Ming-Chih Chou Chuan-Shu 陳卷書 |
author |
Chuan-Shu 陳卷書 |
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Chuan-Shu 陳卷書 Optimal Predictors on Repeat Prostate Biopsy : A Retrospective Analysis |
author_sort |
Chuan-Shu |
title |
Optimal Predictors on Repeat Prostate Biopsy : A Retrospective Analysis |
title_short |
Optimal Predictors on Repeat Prostate Biopsy : A Retrospective Analysis |
title_full |
Optimal Predictors on Repeat Prostate Biopsy : A Retrospective Analysis |
title_fullStr |
Optimal Predictors on Repeat Prostate Biopsy : A Retrospective Analysis |
title_full_unstemmed |
Optimal Predictors on Repeat Prostate Biopsy : A Retrospective Analysis |
title_sort |
optimal predictors on repeat prostate biopsy : a retrospective analysis |
publishDate |
2010 |
url |
http://ndltd.ncl.edu.tw/handle/42154860189296333359 |
work_keys_str_mv |
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