Department of Pharmaceutical Sciences, College of Pharmacy, University of Kentucky, Lexington, KY, United States of America.
Department of Statistics, University of Kentucky, Lexington, KY, United States of America.
PLoS One. 2020 Mar 24;15(3):e0230571. doi: 10.1371/journal.pone.0230571. eCollection 2020.
Androgen deprivation therapy (ADT) is a widely used treatment for patients with hormone-sensitive prostate cancer (PCa). However, duration of treatment response varies, and most patients eventually experience disease progression despite treatment. Leuprorelin is a luteinizing hormone-releasing hormone (LHRH) agonist, a commonly used form of ADT. Prostate-specific antigen (PSA) is a biomarker for monitoring disease progression and predicting treatment response and survival in PCa. However, time-dependent profile of tumor regression and growth in patients with hormone-sensitive PCa on ADT has never been fully characterized. In this analysis, nationwide medical claims database provided by Humana from 2007 to 2011 was used to construct a population-based disease progression model for patients with hormone-sensitive PCa on leuprorelin. Data were analyzed by nonlinear mixed effects modeling utilizing Monte Carlo Parametric Expectation Maximization (MCPEM) method in NONMEM. Covariate selection was performed using a modified Wald's approximation method with backward elimination (WAM-BE) proposed by our group. 1113 PSA observations from 264 subjects with malignant PCa were used for model development. PSA kinetics were well described by the final covariate model. Model parameters were well estimated, but large between-patient variability was observed. Hemoglobin significantly affected proportion of drug-resistant cells in the original tumor, while baseline PSA and antiandrogen use significantly affected treatment effect on drug-sensitive PCa cells (Ds). Population estimate of Ds was 3.78 x 10-2 day-1. Population estimates of growth rates for drug-sensitive (Gs) and drug-resistant PCa cells (GR) were 1.96 x 10-3 and 6.54 x 10-4 day-1, corresponding to a PSA doubling time of 354 and 1060 days, respectively. Proportion of the original PCa cells inherently resistant to treatment was estimated to be 1.94%. Application of population-based disease progression model to clinical data allowed characterization of tumor resistant patterns and growth/regression rates that enhances our understanding of how PCa responds to ADT.
雄激素剥夺疗法 (ADT) 是广泛用于治疗激素敏感型前列腺癌 (PCa) 的方法。然而，治疗反应的持续时间各不相同，大多数患者最终尽管接受了治疗，但仍会出现疾病进展。亮丙瑞林是一种促黄体生成素释放激素 (LHRH) 激动剂，是常用的 ADT 形式。前列腺特异性抗原 (PSA) 是监测 PCa 疾病进展和预测治疗反应及生存的生物标志物。然而，激素敏感型 PCa 患者在 ADT 下肿瘤消退和生长的时间依赖性特征从未被充分描述过。在这项分析中，我们使用 Humana 提供的 2007 年至 2011 年全国性医疗索赔数据库，构建了基于人群的激素敏感型 PCa 患者亮丙瑞林疾病进展模型。利用 NONMEM 中的蒙特卡罗参数期望最大化法 (MCPEM) 对数据进行非线性混合效应建模分析。采用我们组提出的改良 Wald 近似法（WAM-BE）进行协变量选择。使用 264 例恶性 PCa 患者的 1113 个 PSA 观测值进行模型开发。最终协变量模型很好地描述了 PSA 动力学。模型参数得到了很好的估计，但观察到患者间的变异性较大。血红蛋白显著影响原肿瘤中耐药细胞的比例，而基线 PSA 和抗雄激素的使用显著影响对药物敏感型 PCa 细胞 (Ds) 的治疗效果。Ds 的群体估计值为 3.78 x 10-2 天-1。药物敏感型 (Gs) 和耐药型 PCa 细胞 (GR) 的增长率的群体估计值分别为 1.96 x 10-3 和 6.54 x 10-4 天-1，相应的 PSA 倍增时间分别为 354 天和 1060 天。原 PCa 细胞中固有耐药的比例估计为 1.94%。将基于人群的疾病进展模型应用于临床数据，能够对肿瘤耐药模式和生长/消退率进行特征描述，从而增强我们对 PCa 对 ADT 反应方式的理解。
