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局限性前列腺癌根治性前列腺切除术后的肿瘤学结局:按磁共振成像和风险分类分层

Oncological outcomes after radical prostatectomy of localized prostate cancer: stratified by magnetic resonance imaging and risk classification.

作者信息

Jung Gyoohwan, Song Byeongdo, Ahn Hyungwoo, Hwang Sung Il, Lee Hak Jong, Huh Ki Young, Song Sang Hun, Lee Sangchul, Byun Seok-Soo, Hong Sung Kyu

机构信息

Department of Urology, Hanyang University College of Medicine, Seoul, Korea.

Department of Urology, Hanyang University Guri Hospital, Guri, Kyunggi-Do, Korea.

出版信息

Prostate Int. 2024 Dec;12(4):224-230. doi: 10.1016/j.prnil.2024.09.003. Epub 2024 Sep 28.

DOI:10.1016/j.prnil.2024.09.003
PMID:39735202
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11681324/
Abstract

BACKGROUND

We investigated whether combining T2-weighted magnetic resonance imaging (MRI) findings and clinical risk categories improves upon established prognostic indicators of oncological outcomes in prostate cancer.

METHODS

Patients who underwent radical prostatectomy, but not preoperative hormone therapy, radiotherapy, or chemotherapy, for localized prostate cancer at Seoul National University Bundang Hospital from October 2007 to April 2016 were included. MRIs were classified according to the Prostate Imaging-Reporting and Data System (PI-RADS). Patients were divided into the following five groups: 1, no focal suspicious lesion; 2, organ-confined suspicious lesion PI-RADS ≤3; 3, organ-confined suspicious lesion PI-RADS 4 or 5; 4, suspicious lesion with extraprostatic extension (EPE), no seminal vesicle invasion (SVI); 5, suspicious lesion with EPE and SVI. Risk classified according to the National Comprehensive Cancer Network (NCCN) and MRI findings were combined to analyze survival curves for biochemical recurrence (BCR)-free and metastasis-free survival. The area under a time-dependent receiver operating characteristic was analyzed for event prediction after 5 years.

RESULTS

We analyzed 1,290 patients. In multivariate Cox regression models, PI-RADS ≥4 (hazard ratio [HR] 2.33,  < 0.001), EPE (HR 1.46,  = 0.027), SVI (HR 5.03,  < 0.001) and NCCN high-risk (HR 2.33, 95% CI 1.66-3.26,  < 0.001) were associated with BCR. For metastasis, EPE (HR 2.33,  = 0.047), SVI (HR 13.08,  < 0.001) and NCCN high-risk (HR 2.78,  = 0.026) were independent risk factors. Depending on MRI group, BCR-free survival significantly decreased in NCCN intermediate-risk ( = 0.001) and high-risk ( < 0.001) groups, and metastasis-free survival decreased in the intermediate-risk group ( = 0.39) and significantly decreased in the high-risk ( < 0.001) group. Adding MRI group to NCCN risk classification significantly improved the predictive accuracy for BCR in comparison with NCCN risk classification alone ( = 0.042), but not for metastasis ( = 0.012).

CONCLUSION

Combining prostate MRI with NCCN risk classification improves the prediction value of BCR following radical prostatectomy for localized prostate cancer.

摘要

背景

我们研究了将T2加权磁共振成像(MRI)结果与临床风险类别相结合是否能改善前列腺癌肿瘤学结局的既定预后指标。

方法

纳入2007年10月至2016年4月在首尔国立大学盆唐医院接受局限性前列腺癌根治性前列腺切除术,但未接受术前激素治疗、放疗或化疗的患者。MRI根据前列腺影像报告和数据系统(PI-RADS)进行分类。患者分为以下五组:1,无局灶性可疑病变;2,器官局限性可疑病变,PI-RADS≤3;3,器官局限性可疑病变,PI-RADS 4或5;4,有前列腺外侵犯(EPE)的可疑病变,无精囊侵犯(SVI);5,有EPE和SVI的可疑病变。根据美国国立综合癌症网络(NCCN)分类的风险与MRI结果相结合,分析无生化复发(BCR)和无转移生存的生存曲线。分析时间依赖性受试者工作特征曲线下面积,以预测5年后的事件。

结果

我们分析了1290例患者。在多变量Cox回归模型中,PI-RADS≥4(风险比[HR]2.33,P<0.001)、EPE(HR 1.46,P = 0.027)、SVI(HR 5.03,P<0.001)和NCCN高风险(HR 2.33,95%CI 1.66 - 3.26,P<0.001)与BCR相关。对于转移,EPE(HR 2.33,P = 0.047)、SVI(HR 13.08,P<0.001)和NCCN高风险(HR 2.78,P = 0.026)是独立危险因素。根据MRI分组,NCCN中风险(P = 0.001)和高风险(P<0.001)组的无BCR生存率显著降低,中风险组的无转移生存率降低(P = 0.39),高风险组显著降低(P<0.001)。与单独的NCCN风险分类相比,将MRI分组添加到NCCN风险分类中显著提高了BCR的预测准确性(P = 0.042),但对转移的预测准确性没有提高(P = 0.012)。

结论

前列腺MRI与NCCN风险分类相结合可提高局限性前列腺癌根治性前列腺切除术后BCR的预测价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d0a/11681324/2fa09538e957/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d0a/11681324/27e19a71a7cc/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d0a/11681324/8eb9092190ee/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d0a/11681324/2fa09538e957/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d0a/11681324/27e19a71a7cc/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d0a/11681324/8eb9092190ee/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4d0a/11681324/2fa09538e957/gr3.jpg

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