Academic Urology Group, Department of Surgery, University of Cambridge, Cambridge, United Kingdom.
Department of Urology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom.
PLoS Med. 2019 Mar 12;16(3):e1002758. doi: 10.1371/journal.pmed.1002758. eCollection 2019 Mar.
Prognostic stratification is the cornerstone of management in nonmetastatic prostate cancer (PCa). However, existing prognostic models are inadequate-often using treatment outcomes rather than survival, stratifying by broad heterogeneous groups and using heavily treated cohorts. To address this unmet need, we developed an individualised prognostic model that contextualises PCa-specific mortality (PCSM) against other cause mortality, and estimates the impact of treatment on survival.
Using records from the United Kingdom National Cancer Registration and Analysis Service (NCRAS), data were collated for 10,089 men diagnosed with nonmetastatic PCa between 2000 and 2010 in Eastern England. Median follow-up was 9.8 years with 3,829 deaths (1,202 PCa specific). Totals of 19.8%, 14.1%, 34.6%, and 31.5% of men underwent conservative management, prostatectomy, radiotherapy (RT), and androgen deprivation monotherapy, respectively. A total of 2,546 men diagnosed in Singapore over a similar time period represented an external validation cohort. Data were randomly split 70:30 into model development and validation cohorts. Fifteen-year PCSM and non-PCa mortality (NPCM) were explored using separate multivariable Cox models within a competing risks framework. Fractional polynomials (FPs) were utilised to fit continuous variables and baseline hazards. Model accuracy was assessed by discrimination and calibration using the Harrell C-index and chi-squared goodness of fit, respectively, within both validation cohorts. A multivariable model estimating individualised 10- and 15-year survival outcomes was constructed combining age, prostate-specific antigen (PSA), histological grade, biopsy core involvement, stage, and primary treatment, which were each independent prognostic factors for PCSM, and age and comorbidity, which were prognostic for NPCM. The model demonstrated good discrimination, with a C-index of 0.84 (95% CI: 0.82-0.86) and 0.84 (95% CI: 0.80-0.87) for 15-year PCSM in the UK and Singapore validation cohorts, respectively, comparing favourably to international risk-stratification criteria. Discrimination was maintained for overall mortality, with C-index 0.77 (95% CI: 0.75-0.78) and 0.76 (95% CI: 0.73-0.78). The model was well calibrated with no significant difference between predicted and observed PCa-specific (p = 0.19) or overall deaths (p = 0.43) in the UK cohort. Key study limitations were a relatively small external validation cohort, an inability to account for delayed changes to treatment beyond 12 months, and an absence of tumour-stage subclassifications.
'PREDICT Prostate' is an individualised multivariable PCa prognostic model built from baseline diagnostic information and the first to our knowledge that models potential treatment benefits on overall survival. Prognostic power is high despite using only routinely collected clinicopathological information.
预后分层是非转移性前列腺癌（PCa）管理的基石。然而，现有的预后模型并不完善，通常使用治疗结果而不是生存情况进行分层，使用广泛的异质群体进行分层，并使用经过大量治疗的队列。为了解决这一未满足的需求，我们开发了一种个体化的预后模型，该模型将 PCa 特异性死亡率（PCSM）与其他原因死亡率进行对比，并估计治疗对生存的影响。
利用英国国家癌症登记和分析服务（NCRAS）的数据，我们对 2000 年至 2010 年期间在英格兰东部被诊断为非转移性 PCa 的 10089 名男性患者的数据进行了汇总。中位随访时间为 9.8 年，共有 3829 人死亡（1202 人死于 PCa）。分别有 19.8%、14.1%、34.6%和 31.5%的男性接受了保守治疗、前列腺切除术、放疗（RT）和雄激素剥夺单药治疗。新加坡在相似的时间段内诊断出的 2546 名男性代表了一个外部验证队列。数据被随机分为 70:30 的模型开发和验证队列。我们在竞争风险框架内使用单独的多变量 Cox 模型来探索 15 年的 PCSM 和非 PCa 死亡率（NPCM）。使用分数多项式（FP）拟合连续变量和基线风险。我们分别使用 Harrell C 指数和卡方拟合优度检验来评估模型在两个验证队列中的准确性。我们构建了一个多变量模型，该模型通过结合年龄、前列腺特异性抗原（PSA）、组织学分级、活检核心受累、分期和主要治疗来估计个体 10 年和 15 年的生存结果，这些因素都是 PCSM 的独立预后因素，而年龄和合并症是 NPCM 的预后因素。该模型具有良好的判别能力，在英国和新加坡验证队列中，15 年 PCSM 的 C 指数分别为 0.84（95%CI：0.82-0.86）和 0.84（95%CI：0.80-0.87），与国际风险分层标准相比表现良好。对于总死亡率，判别能力也得到了保持，C 指数分别为 0.77（95%CI：0.75-0.78）和 0.76（95%CI：0.73-0.78）。该模型具有良好的校准能力，在英国队列中，预测的 PCa 特异性（p=0.19）或总死亡（p=0.43）与观察结果之间没有显著差异。研究的主要局限性是外部验证队列相对较小，无法考虑 12 个月后治疗的延迟变化，以及缺乏肿瘤分期亚分类。
“PREDICT Prostate”是一种基于基线诊断信息的个体化多变量 PCa 预后模型，是第一个我们所知的能够预测整体生存中潜在治疗益处的模型。尽管只使用了常规收集的临床病理信息，但预后能力仍然很高。
