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三种最常用的术前模型预测前列腺癌根治术后生化复发的头对头比较。

Head-to-head comparison of the three most commonly used preoperative models for prediction of biochemical recurrence after radical prostatectomy.

机构信息

Cancer Prognostics and Health Outcomes Unit, University of Montreal Health Centre, Montreal, Canada.

出版信息

Eur Urol. 2010 Apr;57(4):562-8. doi: 10.1016/j.eururo.2009.12.003. Epub 2009 Dec 10.

Abstract

BACKGROUND

Several models can predict the rate of biochemical recurrence (BCR) after radical prostatectomy (RP).

OBJECTIVE

We tested the three most commonly used models-the D'Amico risk stratification scheme, the Cancer of the Prostate Risk Assessment (CAPRA) score, and the Stephenson nomogram-in a European cohort of RP patients.

DESIGN, SETTING, AND PARTICIPANTS: We relied on preoperative characteristics and prostate-specific antigen follow-up data of 1976 patients, as required by the three tested models. All patients were treated with an open RP between 1992 and 2006.

MEASUREMENTS

Analyses included tests of accuracy (Harrell's concordance index) and calibration between predicted and observed BCR rates at 3 yr and 5 yr after RP. Additionally, we relied on decision curve analyses to compare the three models directly in a head-to-head fashion.

RESULTS AND LIMITATIONS

The median follow-up of censored patients was 32 mo. BCR-free rates at 3 yr and 5 yr after RP were 80.2% and 72.6%, respectively. The concordance index for 3-yr BCR predictions was 70.4%, 74.3%, and 75.2% for the D'Amico, CAPRA, and Stephenson models, respectively, versus 67.4%, 72.9%, and 73.5% for 5-yr BCR predictions. Calibration results supported the use of either the CAPRA or Stephenson models. Decision curve analyses indicated a small benefit for the CAPRA score relative to the Stephenson nomogram. Our findings apply to German patients treated with RP at a high-volume tertiary care centre. Consequently, the rank order reported in this paper may not be the same in North American or other European cohorts.

CONCLUSIONS

Different methods yield different results, and it may be difficult to reconcile concordance index, calibration, and decision curve analysis findings. Our data suggest that the CAPRA score outperforms the other models when decision curve analysis and calibration were used as benchmarks. Conversely, the Stephenson nomogram outperformed the other models when concordance index was used as a metric.

摘要

背景

有几种模型可以预测根治性前列腺切除术(RP)后生化复发(BCR)的速率。

目的

我们在一组接受 RP 治疗的欧洲患者队列中测试了三种最常用的模型:D'Amico 风险分层方案、前列腺癌风险评估(CAPRA)评分和 Stephenson 列线图。

设计、设置和参与者:我们依赖于三种测试模型所需的 1976 名患者的术前特征和前列腺特异性抗原随访数据。所有患者均在 1992 年至 2006 年间接受开放 RP 治疗。

测量

分析包括准确性(Harrell 一致性指数)和在 RP 后 3 年和 5 年时预测与观察到的 BCR 率之间的校准检验。此外,我们还依赖决策曲线分析,以直接比较三种模型的头对头表现。

结果和局限性

中位随访时间为 32 个月。RP 后 3 年和 5 年的无 BCR 生存率分别为 80.2%和 72.6%。3 年 BCR 预测的一致性指数分别为 D'Amico、CAPRA 和 Stephenson 模型的 70.4%、74.3%和 75.2%,而 5 年 BCR 预测的一致性指数分别为 67.4%、72.9%和 73.5%。校准结果支持使用 CAPRA 或 Stephenson 模型。决策曲线分析表明,与 Stephenson 列线图相比,CAPRA 评分具有较小的优势。我们的发现适用于在高容量三级护理中心接受 RP 治疗的德国患者。因此,本文报告的排名可能与北美或其他欧洲队列不同。

结论

不同的方法产生不同的结果,可能难以协调一致性指数、校准和决策曲线分析的结果。我们的数据表明,当使用决策曲线分析和校准作为基准时,CAPRA 评分优于其他模型。相反,当使用一致性指数作为指标时,Stephenson 列线图优于其他模型。

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