Clinical Usefulness of Prostate and Tumor Volume Related Parameters following Radical Prostatectomy for Localized Prostate Cancer.

Clinical Usefulness of Prostate and Tumor Volume Related Parameters following Radical Prostatectomy for Localized Prostate Cancer.
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DOI:
10.1016/j.juro.2018.09.060
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发表时间:
2019-03
期刊:
The Journal of urology
影响因子:
--
通讯作者:
Fine SW
Fine SW
中科院分区:
其他
文献类型:
--
作者:
Ito Y;Udo K;Vertosick EA;Sjoberg DD;Vickers AJ;Al-Ahmadie HA;Chen YB;Gopalan A;Sirintrapun SJ;Tickoo SK;Scardino PT;Eastham JA;Reuter VE;Fine SW

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评价6个参数中的任一个是否能增强根治性前列腺切除术(RP)后生化复发(BCR)的预测:前列腺体积、肿瘤总体积(TV)、高级别TV、高级别TV与TV的比值、TV与前列腺体积的比值和/或高级别TV与前列腺体积的比值。1261例在3年内接受RP的患者具有用Gleason模式构建的肿瘤图,表示为低(3)或高(4或5),以及使用市售软件生成的体积数据。单变量考克斯回归模型用于评估每个体积相关参数是否与RP后的BCR相关。将多变量考克斯回归“基础模型”(年龄、PSA、Gleason评分/分级组、病理分期和切缘状态)与6个额外模型(基础模型+每个体积相关参数)进行比较,以评估预测准确性的增强。进行决策曲线分析,以确定提高预测准确性的参数的临床效用。在单变量分析中,除前列腺体积外,其他参数均与BCR显著相关。多变量基础模型的预测准确性较高(c指数=0.861)。添加与体积相关的参数略微增强了辨别力。即使对于高等级TV/TV(具有最高辨别性改进的参数),决策曲线分析也未能显示出附加益处。肿瘤体积相关参数与BCR显著相关,但不会增加BCR预测的标准临床病理学变量的重要区分,也不会在一系列临床相关决策阈值中提供获益。在常规病理学评价和报告中不需要进行体积相关测量。
To evaluate whether prediction of biochemical recurrence (BCR) after radical prostatectomy (RP) is enhanced by any of six parameters: prostate volume, total tumor volume (TV), high grade TV, ratio of high grade TV to TV, ratio of TV to prostate volume and/or ratio of high grade TV to prostate volume. 1261 patients who underwent RP over a 3 year period had tumor maps constructed with Gleason pattern denoted as either low (3) or high (4 or 5) and volumetric data generated using commercially available software. Univariate Cox regression models were used to assess whether each volume-related parameters was associated with BCR after RP. A multivariable Cox regression “base model” (age, PSA, Gleason score/grade group, pathologic stage and margin status) was compared with 6 additional models (base model + each volume-related parameter) to evaluate enhancement in predictive accuracy. Decision curve analysis was performed to determine the clinical utility of parameters that enhanced predictive accuracy. On univariate analysis, each parameter was significantly associated with BCR except prostate volume. Predictive accuracy of multivariable base model was high (c-index=0.861). Adding volume-related parameters marginally enhanced discrimination. Decision curve analysis failed to show added benefit even for high grade TV/TV (parameter with highest discriminative improvement). Tumor volume-related parameters are significantly associated with BCR, but do not add important discrimination to standard clinicopathologic variables for BCR prediction nor provide benefit across a range of clinically-relevant decision thresholds. Volume-related measurement is not warranted in routine pathologic evaluation and reporting.
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