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建立预测前列腺癌Gleason分级组升级的模型。

Establishing a model predicting Gleason grade group upgrading in prostate cancer.

作者信息

Chen Jian, Chen Qiming, Wang Ze, Yan Xuzhi, Wang Yapeng, Zhang Yao, Zhang Jun, Xu Jing, Ma Qiang, Zhong Peng, Zhang Dianzheng, Liu Qiuli, Lan Weihua, Jiang Jun

机构信息

Department of Urology, Institute of Surgery Research, Daping Hospital, Army Medical University, Chongqing, China.

Department of Pathology, Institute of Surgery Research, Daping Hospital, Army Medical University, Chongqing, China.

出版信息

Transl Androl Urol. 2024 Aug 31;13(8):1378-1387. doi: 10.21037/tau-24-155. Epub 2024 Aug 22.

Abstract

BACKGROUND

Gleason grade group (GG) upgrading is associated with increased biochemical recurrence (BCR), local progression, and decreased cancer-specific survival (CSS) in prostate cancer (PCa). However, descriptions of the risk factors of GG upgrading are scarce. The objective of this study was to identify risk factors and establish a model to predict GG upgrading.

METHODS

There were 361 patients with PCa who underwent radical prostatectomy between May 2011 and February 2022 enrolled. Univariate and multivariate logistic regression analyses were identified and nomogram further narrowed down the contributing factors in GG upgrading. The correction curve and decision curve were used to assess the model.

RESULTS

In the overall cohort, 141 patients had GG upgrading. But the subgroup cohort (GG ≤2) showed that 68 patients had GG upgrading. Multivariate logistic regression analysis showed that in the overall cohort, total prostate-specific antigen (tPSA) ≥10 ng/mL, systemic immune-inflammation index (SII) >379.50, neutrophil-lymphocyte ratio (NLR) >2.13, the GG of biopsy ≥3, the number of positive cores >3 were independent risk factors in GG upgrading. In the cohort of biopsy GG ≤2, multivariate logistic regression showed that the tPSA ≥10 ng/mL, SII >379.50 and the number of positive cores >3 were independent risk factors in GG upgrading. A novel model predicting GG upgrading was established based on these three parameters. The area under the curve (AUC) of the prediction model was 0.759. The C-index of the nomogram was 0.768. The calibration curves of the model showed good predictive performance. Clinical decision curves indicated clinical benefit in the interval of 20% to 90% of threshold probability and good clinical utility.

CONCLUSIONS

Combined levels of tPSA, SII and the positive biopsy cores distinguish patients with high-risk GG upgrading in the group of biopsy GG ≤2 and are helpful in the decision of treatment plans.

摘要

背景

在前列腺癌(PCa)中,Gleason分级组(GG)升级与生化复发(BCR)增加、局部进展以及癌症特异性生存(CSS)降低相关。然而,关于GG升级的危险因素的描述却很少。本研究的目的是确定危险因素并建立一个预测GG升级的模型。

方法

纳入2011年5月至2022年2月期间接受根治性前列腺切除术的361例PCa患者。进行单因素和多因素逻辑回归分析,列线图进一步缩小了GG升级的影响因素。采用校正曲线和决策曲线评估该模型。

结果

在整个队列中,141例患者出现GG升级。但亚组队列(GG≤2)显示有68例患者出现GG升级。多因素逻辑回归分析显示,在整个队列中,总前列腺特异性抗原(tPSA)≥10 ng/mL、全身免疫炎症指数(SII)>379.50、中性粒细胞与淋巴细胞比值(NLR)>2.13、活检GG≥3、阳性核心数>3是GG升级的独立危险因素。在活检GG≤2的队列中,多因素逻辑回归显示tPSA≥10 ng/mL、SII>379.50和阳性核心数>3是GG升级的独立危险因素。基于这三个参数建立了一个预测GG升级的新模型。预测模型的曲线下面积(AUC)为0.759。列线图的C指数为0.768。该模型的校准曲线显示出良好的预测性能。临床决策曲线表明在阈值概率的20%至90%区间内有临床益处且临床实用性良好。

结论

tPSA、SII和阳性活检核心的综合水平可区分活检GG≤2组中GG升级高危患者,并有助于治疗方案的决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42d4/11399042/3a0418f3b96d/tau-13-08-1378-f1.jpg

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