School of Medicine, University of California, San Francisco, San Francisco, California, USA.
Department of Urology, UCSF-Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California, USA.
Prostate. 2023 Jul;83(10):922-928. doi: 10.1002/pros.24533. Epub 2023 Apr 20.
The University of California, San Francisco Cancer of the Prostate Risk Assessment (CAPRA) score is a validated tool using factors at diagnosis to predict prostate cancer outcomes after radical prostatectomy (RP). This study evaluates whether substitution of prostate-specific antigen (PSA) density for serum PSA improves predictive performance of the clinical CAPRA model.
Participants were diagnosed in 2000-2019 with stage T1/T2 cancer, underwent RP, with at least a 6-month follow-up. We computed standard CAPRA score using diagnostic age, Gleason grade, percent positive cores, clinical T stage, and serum PSA, and an alternate score using similar variables but substituting PSA density for PSA. We reported CAPRA categories as low (0-2), intermediate (3-5), and high (6-10) risk. Recurrence was defined as two consecutive PSA ≥ 0.2 ng/mL or receipt of salvage treatment. Life table and Kaplan-Meier analysis evaluated recurrence-free survival after prostatectomy. Cox proportional hazards regression models tested associations of standard or alternate CAPRA variables with recurrence risk. Additional models tested associations between standard or alternate CAPRA score with recurrence risk. Cox log-likelihood ratio test (-2 LOG L) assessed model accuracy.
A total of 2880 patients had median age 62 years, GG1 30% and GG2 31%, median PSA 6.5, and median PSA density 0.19. Median postoperative follow-up was 45 months. Alternate CAPRA model was associated with shifts in risk scores, with 16% of patients increasing and 7% decreasing (p < 0.01). Recurrence-free survival after RP was 75% at 5 years and 62% at 10 years. Both CAPRA component models were associated with recurrence risk after RP on Cox regression. Covariate fit statistics showed better fit for standard CAPRA model versus alternate (p < 0.01). Standard (hazard ratio [HR]: 1.55; 95% confidence interval [CI]: 1.50-1.61) and alternate (HR: 1.50; 95% CI: 1.44-1.55) CAPRA scores were associated with recurrence risk, with better fit for standard model (p < 0.01).
In a 2880 patient cohort followed for median 45 months after RP, alternate CAPRA model using PSA density was associated with higher biochemical recurrence (BCR) risk, but performed inferior to standard CAPRA at predicting BCR. While PSA density is an established prognostic variable in prediagnostic settings and sub-stratifying low-risk disease, it does not improve BCR model predictive accuracy when applied across a range of cancer risk.
加利福尼亚大学旧金山分校前列腺癌风险评估（CAPRA）评分是一种经过验证的工具，它使用诊断时的因素来预测根治性前列腺切除术（RP）后前列腺癌的结局。本研究评估了用前列腺特异性抗原（PSA）密度替代血清 PSA 是否能提高临床 CAPRA 模型的预测性能。
参与者于 2000 年至 2019 年间被诊断为 T1/T2 期癌症，接受了 RP，并至少有 6 个月的随访。我们使用诊断年龄、Gleason 分级、阳性核心百分比、临床 T 分期和血清 PSA 计算了标准 CAPRA 评分，并使用类似的变量但用 PSA 密度替代 PSA 计算了替代评分。我们将 CAPRA 类别报告为低（0-2）、中（3-5）和高（6-10）风险。复发定义为两次连续 PSA≥0.2ng/ml 或接受挽救性治疗。生命表和 Kaplan-Meier 分析评估了前列腺切除术后无复发生存率。Cox 比例风险回归模型测试了标准或替代 CAPRA 变量与复发风险的相关性。额外的模型测试了标准或替代 CAPRA 评分与复发风险之间的关系。Cox 对数似然比检验（-2 LOG L）评估了模型准确性。
共有 2880 名患者的中位年龄为 62 岁，GG1 为 30%，GG2 为 31%，中位 PSA 为 6.5ng/ml，中位 PSA 密度为 0.19ng/ml/ml。术后中位随访时间为 45 个月。替代 CAPRA 模型与风险评分的变化有关，有 16%的患者评分升高，7%的患者评分降低（p<0.01）。RP 后 5 年无复发生存率为 75%，10 年为 62%。CAPRA 成分模型在 Cox 回归中均与 RP 后的复发风险相关。协变量拟合统计数据显示，标准 CAPRA 模型比替代模型的拟合度更好（p<0.01）。标准（危险比[HR]：1.55；95%置信区间[CI]：1.50-1.61）和替代（HR：1.50；95% CI：1.44-1.55）CAPRA 评分与复发风险相关，标准模型的拟合度更好（p<0.01）。
在接受 RP 后中位随访 45 个月的 2880 名患者队列中，使用 PSA 密度的替代 CAPRA 模型与更高的生化复发（BCR）风险相关，但在预测 BCR 方面的表现不如标准 CAPRA 模型。虽然 PSA 密度是预测前列腺癌诊断前和分层低危疾病的既定预后变量，但在应用于一系列癌症风险时，它并不能提高 BCR 模型的预测准确性。
