Clinical Focus
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Abstract: Objective To explore risk factors of prostate biopsy and to establish scoring a system to predict prostate biopsy outcome and reduce unnecessary prostate biopsy through PIRADS v2.Methods A total of 392 patients who had accepted prostate biopsy were enrolled from August 2013 to June 2017 in Nanfang Hospital retrospectively, 267 patients in modeling group and 125 patients in authentication group. Risk factors were analyzed in diagnosis performance for prostate cancer. According to the results of Logistic regression analysis, a scoring system was developed to predict prostate cancer. The scoring system was validated using patient data from the validation group.Results According to Logistic analysis, age, prostate specific antigen density(PSAD), BMI, PIRADS, prostate volume were affecting factors for prostate cancer detection. Value of scoring system was set in accordance with regression coefficient. It ranked from -2 to 9.5 scores. Calculating overall score was used to draw receiver operating characteristic curve of modeling group and authentication group. The areas under the ROC curve were 0.923 and 0.895. Patients acquired a score ≤3 scores with low risk of prostate cancer. The patients who gained more than 3 scores met a high risk of prostate cancer. Conclusion The scoring system combined with PIRADS v2 has outstanding diagnosis performance for the risks in prostate cancer. The patients with scores lower than 3 do not recommend prostate biopsy as minimal risk of prostate cancer. In view of high risk of cancer, patients obtained 3 scores need prostate biopsy. The rational use of PIRADS v2 can help set up scoring systems.
Key words: prostatic neoplasms;punctures;magnetic resonance imaging;PI-RADS, scoring system
Yang Dashan, Peng Peidan, Pang Shiyu, Long Qicheng, Zhan Yaping, Tan Wanlong . Establishing a point-scoring system to predict prostate biopsy outcome with PI-RADS v2[J]. Clinical Focus, doi: 10.3969/j.issn.1004-583X.2017.10.015.
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URL: https://huicui.hebmu.edu.cn/EN/10.3969/j.issn.1004-583X.2017.10.015
https://huicui.hebmu.edu.cn/EN/Y2017/V32/I10/885