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利用前列腺疾病研究中心和前列腺癌战略泌尿学研究计划数据库预测根治性前列腺切除术后前列腺特异性抗原复发风险。

Predicting risk of prostate specific antigen recurrence after radical prostatectomy with the Center for Prostate Disease Research and Cancer of the Prostate Strategic Urologic Research Endeavor databases.

作者信息

Moul J W, Connelly R R, Lubeck D P, Bauer J J, Sun L, Flanders S C, Grossfeld G D, Carroll P R

机构信息

Urology Service, Department of Surgery, Walter Reed Army Medical Center, Washington, DC, USA.

出版信息

J Urol. 2001 Oct;166(4):1322-7.

Abstract

PURPOSE

Biostatistical models to predict stage or outcome in patients with clinically localized prostate cancer with pretreatment prostate specific antigen (PSA), Gleason sum on biopsy or prostatectomy specimen, clinical or pathological stage and other variables, including ethnicity, have been developed. However, to date models have relied on small subsets from academic centers or military populations that may not be representative. Our study validates and updates a model published previously with the Cancer of the Prostate Strategic Urologic Research Endeavor (CaPSURE, UCSF, Urology Outcomes Research Group and TAP Pharmaceutical Products, Inc.), a large multicenter, community based prostate cancer database and Center for Prostate Disease Research (CPDR), a large military database.

MATERIALS AND METHODS

We validated a biostatistical model that includes pretreatment PSA, highest Gleason sum on prostatectomy specimen, prostatectomy organ confinement status and ethnicity, including white and black patients. We then revised it with the Cox regression analysis of the combined 503 PSA era surgical cases from the CPDR prospective cancer database and 1,012 from the CaPSURE prostate cancer outcomes database.

RESULTS

The original equation with 3 risk groups stratified CaPSURE cases into distinct categories with 7-year disease-free survival rates of 72%, 42.1% and 27.6% for low, intermediate and high risk men, respectively. Parameter estimates obtained from a Cox regression analysis provided a revised model equation that calculated the relative risk of recurrence as: exponent (exp)[(0.54 x Race) + (0.05 x sigmoidal transformation of PSA [PSA(ST)]) + (0.23 x Postop Gleason) + (0.69 x Pathologic stage). The relative risk of recurrence, as calculated by the aforementioned equation, was used to stratify the cases into 4 risk groups. Very low-4.7 or less, low-4.7 to 7.1, high-7.1 to 16.7 and very high-greater than 16.7, and patients at risk had 7-year disease-free survival rates of 85.4%, 66.0%, 50.6% and 21.3%, respectively.

CONCLUSIONS

With a broad cohort of community based, academic and military cases, we developed an equation that stratifies men into 4 discrete risk groups of recurrence after radical prostatectomy and confirmed use of a prior 3 risk group model. Although the variables of ethnicity, pretreatment PSA, highest Gleason sum on prostatectomy specimen and organ confinement status on surgical pathology upon which the model is based are easily obtained, more refined modeling with additional variables are needed to improve prediction of intermediate risk in individuals.

摘要

目的

已开发出生物统计学模型,用于根据治疗前前列腺特异性抗原(PSA)、活检或前列腺切除标本的Gleason评分、临床或病理分期以及其他变量(包括种族)来预测临床局限性前列腺癌患者的分期或预后。然而,迄今为止,模型所依赖的是学术中心或军人人群的小样本子集,可能不具有代表性。我们的研究对先前发表的一个模型进行了验证和更新,该模型来自前列腺癌战略泌尿学研究项目(CaPSURE,加利福尼亚大学旧金山分校、泌尿学预后研究组和泰普制药产品公司),这是一个大型多中心、基于社区的前列腺癌数据库,以及前列腺疾病研究中心(CPDR),一个大型军事数据库。

材料与方法

我们验证了一个生物统计学模型,该模型包括治疗前PSA、前列腺切除标本上的最高Gleason评分、前列腺切除的器官局限状态以及种族,包括白人和黑人患者。然后,我们对来自CPDR前瞻性癌症数据库的503例PSA时代手术病例和来自CaPSURE前列腺癌预后数据库的1012例病例进行了Cox回归分析,对模型进行了修订。

结果

原始方程有3个风险组,将CaPSURE病例分为不同类别,低、中、高风险男性的7年无病生存率分别为72%、42.1%和27.6%。通过Cox回归分析获得的参数估计值提供了一个修订后的模型方程,该方程计算复发相对风险的公式为:指数(exp)[(0.54×种族)+(0.05×PSA的S形转换[PSA(ST)])+(0.23×术后Gleason评分)+(0.69×病理分期)]。根据上述方程计算出的复发相对风险用于将病例分为4个风险组。极低风险组(风险值为4.7或更低)、低风险组(风险值为4.7至7.1)、高风险组(风险值为7.1至16.7)和极高风险组(风险值大于16.7),处于这些风险组的患者7年无病生存率分别为85.4%、66.0%、50.6%和21.3%。

结论

通过广泛的基于社区、学术和军事的病例队列,我们开发了一个方程,将男性分为前列腺癌根治术后复发的4个离散风险组,并证实了之前3个风险组模型的应用。尽管该模型所基于的种族、治疗前PSA、前列腺切除标本上的最高Gleason评分以及手术病理上的器官局限状态等变量很容易获得,但仍需要用更多变量进行更精细的建模,以改善对个体中风险的预测。

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