在前列腺针切病理活检中测量癌症负担:简化评估在评估结果方面优于复杂的测量结果:证据有助于病理学家效率和最小化数据集。
Measuring Cancer burden in prostatic needle core biopsies: Simplified assessments outperform complex measurements in assessing outcome: evidence to assist pathologist efficiency and minimise datasets.
发表日期:2023 Feb 13
作者:
Daniel M Berney, Kier Finnegan, Kim Chu, Samson W Fine, Murali Varma, Jack Cuzick, Luis Beltran,
来源:
HISTOPATHOLOGY
摘要:
前列腺癌(PCa)活检中测量癌细胞范围的最佳方法尚不清楚。方法和结果:回顾管理保守的981名临床局部PCa患者并进行随访。计算阳性穿刺针的数量(NPC),穿刺针中最大癌细胞长度(MCL),总癌细胞长度(TCL)和阳性穿刺针的百分比(%+cores),并使用血清前列腺特异性抗原(PSA),T分期和Gleason评分进行单变量和多变量分析。记录间质缺口(SG)。在MCL受到SG影响的单变量模型有显著差异。在单变量模型中,所有变量都与PCa死亡有显著关联。在多变量模型中,仅有%+cores是预测结果的显著预测因子,每增加10%的%+cores结果为危险率(HR)1.07(LRT p > Χ2 = 0.01)。有120名患者MCL受到SG影响,该组共有20起事件。在包括SG的单变量分析中,中位数MCL为10毫米,HR为1.16(p = 0.007),未包括SG,中位数MCL为6毫米,HR为1.23(p = 6.3x10-4)。包括或不包括SG不会对TCL作为预测结果产生显著差异。癌细胞范围是PCa死亡的强预测因子,但只有%+cores对多元模型有贡献。作为NPC /总穿刺针数的分数表示,这是我们在非靶向活检中偏爱的最简单的评估方法。本文受版权保护。保留所有权利。
The Optimal method of measuring cancer extent in prostate cancer (PCa) biopsies is unknown METHODS AND RESULTS: 981 men with clinically localized PCa managed conservatively were reviewed with follow up. The number of positive cores (NPC), the Maximum Cancer Length in a core (MCL), Total Cancer Length (TCL) and percentage of positive cores (%+cores) was calculated and univariate and multivariate analysis performed using PSA, T-stage and Gleason score. The presence of stromal gaps (SG) was recorded. Univariate models were run where SG made a difference to the MCL. All variables showed significant association with PCa death in univariate models. In multivariate models, incorporating PSA, T-stage and Gleason score, only %+cores was a significant predictor of outcome with a 10% increase in %+cores resulting in a hazard ratio (HR) of 1.07 (LRT p > Χ2 = 0.01). There were 120 patients where SG made a difference to the MCL and a total of 20 events in this group. Including SG, on univariate analysis the median MCL was 10 mm and HR was 1.16 (p=0.007), not including SG the median MCL was 6 mm and HR was 1.23 (p=6.3x10-4). Inclusion or exclusion of SG made no significant difference to TCL as a predictor of outcome.Cancer extent is a strong predictor of PCa death but only %+cores adds to the multivariate model. Expressed as a fraction of NPC/total number of cores, this is the simplest method of assessment which we favour over more complicated methods in non-targeted biopsies.This article is protected by copyright. All rights reserved.