Department of Urology, Ningbo Medical Center Lihuili Hospital, Ningbo, Zhejiang 315000, China.
Biomed Res Int. 2022 Aug 17;2022:7944342. doi: 10.1155/2022/7944342. eCollection 2022.
To access the incidence and predictors of Gleason grade group upgrading from cognitive MR-targeted fusion prostate biopsy to radical prostatectomy in a Chinese cohort.
We included 199 patients in our institution between January 2016 and June 2021. Multivariable logistic regression model and nomograms were utilized to analyze the collected data.
The concordance rate of biopsy Gleason grade group and radical prostatectomy was 50.3% (100 in 199). Upgrading occurred in 80 (40.2%) patients and 37 (68.5%) patients have an upgrading Gleason grade group when the biopsy Gleason grade group was 1. Multivariable logistic regression models were established to analyze the incidence and predictors of Gleason grade group upgrading from cognitive MR-targeted fusion prostate biopsy to radical prostatectomy. Biopsy Gleason grade group, prostate volume, and patient year were confirmed to be individual predictors of upgrading. Based on the logistic regression models, nomograms for predicting probability of prostate Gleason grade group upgrading were generated.
We established a logistic regression model to predict the accuracy of prostate biopsy GG and provide the probability of upgrading. Clinicians should be more cautious when deciding the treatment strategy especially for prostate cancer biopsy GG1 patients. Future studies should expand the sample size and include more variables to improve the accuracy of predicting upgrading and prostate cancer early screening program is urgently needed in our city in China.
探讨中国人群中从认知磁共振靶向融合前列腺活检到根治性前列腺切除术时,Gleason 分级分组升级的发生率和预测因素。
我们纳入了 2016 年 1 月至 2021 年 6 月在我院治疗的 199 例患者。采用多变量逻辑回归模型和列线图对收集的数据进行分析。
活检 Gleason 分级分组与根治性前列腺切除术的一致性率为 50.3%(199 例中有 100 例)。80 例(40.2%)患者发生升级,当活检 Gleason 分级分组为 1 时,37 例(68.5%)患者的 Gleason 分级分组升级。建立了多变量逻辑回归模型,以分析从认知磁共振靶向融合前列腺活检到根治性前列腺切除术时 Gleason 分级分组升级的发生率和预测因素。活检 Gleason 分级分组、前列腺体积和患者年龄被确认为升级的独立预测因素。基于逻辑回归模型,生成了预测前列腺 Gleason 分级分组升级概率的列线图。
我们建立了一个逻辑回归模型来预测前列腺活检 GG 的准确性,并提供升级的概率。临床医生在决定治疗策略时应更加谨慎,特别是对于前列腺癌活检 GG1 患者。未来的研究应扩大样本量并纳入更多变量,以提高升级和前列腺癌早期筛查计划的预测准确性,在中国的我们所在城市迫切需要开展该项目。