Department of Pathology, University of Illinois at Chicago, Chicago, IL 60612, USA.
J Clin Oncol. 2010 Apr 1;28(10):1714-20. doi: 10.1200/JCO.2008.20.3422. Epub 2010 Feb 22.
To introduce a novel approach for the time-dependent quantification of risk factors for prostate cancer (PCa) detection after an initial negative biopsy.
Data for 1,871 men with initial negative biopsies and at least one follow-up biopsy were available. Piecewise exponential regression models were developed to quantify hazard ratios (HRs) and define cumulative incidence curves for PCa detection for subgroups with specific patterns of risk factors over time. Factors evaluated included age, race, serum prostate-specific antigen (PSA) concentration, PSA slope, digital rectal examination, dysplastic glands or prostatitis on biopsy, ultrasound gland volume, urinary symptoms, and number of negative biopsies.
Four hundred sixty-five men had PCa detected, after a mean follow-up time of 2.8 years. All of the factors were independent predictors of PCa detection except for PSA slope, as a result of its correlation with time-dependent PSA level, and race. PSA (HR = 3.90 for > 10 v 2.5 to 3.9 ng/mL), high-grade prostatic intraepithelial neoplasia/atypical glands (HR = 2.97), gland volume (HR = 0.39 for > 50 v < 25 mL), and number of repeat biopsies (HR = 0.36 for two v zero repeat biopsies) were the strongest predictors. Men with high-risk versus low-risk event histories had a 20-fold difference in PCa detection over 5 years.
Piecewise exponential models provide an approach to longitudinal analysis of PCa risk that allows clinicians to see the interplay of risk factors as they unfold over time for individual patients. With these models, it is possible to identify distinct subpopulations with dramatically different needs for monitoring and repeat biopsy.
介绍一种新方法，用于对初始阴性活检后前列腺癌（PCa）检测的危险因素进行时依性定量分析。
我们获得了 1871 名初始阴性活检且至少有一次后续活检的男性数据。我们开发了分段指数回归模型，以量化风险比（HR），并为具有特定危险因素模式的亚组定义 PCa 检测的累积发生率曲线。评估的因素包括年龄、种族、血清前列腺特异性抗原（PSA）浓度、PSA 斜率、直肠指检、活检时出现发育不良腺体或前列腺炎、超声腺体体积、尿路症状和阴性活检次数。
465 名男性在平均 2.8 年的随访后被检出患有 PCa。除了 PSA 斜率外，所有因素都是 PCa 检测的独立预测因子，这是由于 PSA 斜率与时间依赖性 PSA 水平相关，以及与种族相关。PSA（>10 v 2.5 至 3.9 ng/mL 的 HR = 3.90）、高级别前列腺上皮内瘤变/非典型腺体（HR = 2.97）、腺体体积（>50 v <25 mL 的 HR = 0.39）和重复活检次数（两次重复活检 v 零次重复活检的 HR = 0.36）是最强的预测因子。高危事件史与低危事件史男性在 5 年内 PCa 检出率相差 20 倍。
分段指数模型为 PCa 风险的纵向分析提供了一种方法，使临床医生能够随着时间的推移观察个体患者的危险因素相互作用。有了这些模型，就有可能识别出具有截然不同的监测和重复活检需求的不同亚群。
