Background/Objectives: There is conflicting data on which factors predict progression events in active surveillance for early prostate cancer. Here, we explored the value of different clinicopathological variables and whether progression endpoint definitions impact predictive utility.Methods: Clinicopathological variables were extracted from the STRATified CANcer Surveillance (STRATCANs) prospective AS database and included biopsy features (core positivity, cancer core length, and percentage core involvement) and MRI features (Likert score, lesion size, and location), as well as baseline PSA density [PSAd] and Cambridge Prognostic Group (CPG). These were tested against AS endpoint definitions of (1) progression to ≥CPG3, (2) any pathological progression and two definitions from the literature, (3) ≥GG3 or change to treatment, and (4) ≥GG4, metastasis or cancer-related mortality. Predictors were assessed using regression analysis.Results: Data from 296 men were included (median age, 66; follow-up, 5 years). Progression per definition (1–4) occurred in 46 (15.5%), 54 (18.2%), 84 (28.4%), and 10 (3.4%) men. In univariate analysis using Definition 1, no biopsy parameter was independently predictive of progression, while the MRI Likert score (p= 0.02) was the only significant imaging parameter. For Definition 2, core positivity (p= 0.003) and MRI Likert score (p= 0.01) were significant predictors in univariate analyses, while for Definition 3, tumour core length (p= 0.005), core positivity (p= 0.002), and MRI Likert score (p= 0.003) were all predictive in univariate analyses. In multivariate analysis, however, the only consistent independent predictor was PSAd, regardless of endpoint definition. No variables predicted Definition 4 progression.Conclusions: AS endpoint selection appears to define which variables predict progression. Using progression to ≥CPG 3 as an unambiguous AS endpoint, neither biopsy nor MRI variables added incremental value in predicting progression. PSAd, however, appears to be a robust and independent generalisable progression predictor.
背景/目的：关于哪些因素可预测早期前列腺癌主动监测中的进展事件，现有数据存在矛盾。本研究探讨了不同临床病理变量的价值，以及进展终点的定义是否会影响预测效用。
方法：临床病理变量提取自STRATified CANcer Surveillance（STRATCANs）前瞻性主动监测数据库，包括活检特征（阳性核心数、癌组织核心长度及核心受累百分比）和磁共振成像特征（Likert评分、病灶大小及位置），以及基线PSA密度和剑桥预后组。这些变量针对以下主动监测终点定义进行检验：（1）进展至≥CPG3；（2）任何病理学进展，以及文献中的两种定义：（3）≥GG3或转为治疗，和（4）≥GG4、转移或癌症相关死亡。通过回归分析评估预测因子。
结果：研究纳入296名男性数据（中位年龄66岁；随访5年）。根据定义（1–4）发生进展的男性分别为46例（15.5%）、54例（18.2%）、84例（28.4%）和10例（3.4%）。在使用定义1的单变量分析中，无活检参数能独立预测进展，而MRI Likert评分（p=0.02）是唯一有显著意义的影像学参数。对于定义2，单变量分析中阳性核心数（p=0.003）和MRI Likert评分（p=0.01）是显著预测因子；对于定义3，单变量分析中肿瘤核心长度（p=0.005）、阳性核心数（p=0.002）和MRI Likert评分（p=0.003）均具有预测性。然而在多变量分析中，无论终点定义如何，唯一一致的独立预测因子是PSA密度。无变量可预测定义4的进展。
结论：主动监测终点的选择似乎决定了哪些变量可预测进展。以进展至≥CPG3作为明确的主动监测终点时，活检和MRI参数均未增加预测进展的增量价值。然而，PSA密度似乎是一个稳健且可推广的独立进展预测因子。
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