Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA.
Department of Radiation Oncology, H. Lee Moffitt Cancer and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA.
Bull Math Biol. 2021 Nov 19;84(1):2. doi: 10.1007/s11538-021-00953-w.
The prostate is an exocrine gland of the male reproductive system dependent on androgens (testosterone and dihydrotestosterone) for development and maintenance. First-line therapy for prostate cancer includes androgen deprivation therapy (ADT), depriving both the normal and malignant prostate cells of androgens required for proliferation and survival. A significant problem with continuous ADT at the maximum tolerable dose is the insurgence of cancer cell resistance. In recent years, intermittent ADT has been proposed as an alternative to continuous ADT, limiting toxicities and delaying time-to-progression. Several mathematical models with different biological resistance mechanisms have been considered to simulate intermittent ADT response dynamics. We present a comparison between 13 of these intermittent dynamical models and assess their ability to describe prostate-specific antigen (PSA) dynamics. The models are calibrated to longitudinal PSA data from the Canadian Prospective Phase II Trial of intermittent ADT for locally advanced prostate cancer. We perform Bayesian inference and model analysis over the models' space of parameters on- and off-treatment to determine each model's strength and weakness in describing the patient-specific PSA dynamics. Additionally, we carry out a classical Bayesian model comparison on the models' evidence to determine the models with the highest likelihood to simulate the clinically observed dynamics. Our analysis identifies several models with critical abilities to disentangle between relapsing and not relapsing patients, together with parameter intervals where the critical points' basin of attraction might be exploited for clinical purposes. Finally, within the Bayesian model comparison framework, we identify the most compelling models in the description of the clinical data.
前列腺是男性生殖系统的外分泌腺，其发育和维持依赖于雄激素（睾酮和二氢睾酮）。前列腺癌的一线治疗包括雄激素剥夺疗法（ADT），剥夺正常和恶性前列腺细胞增殖和存活所需的雄激素。在最大耐受剂量下连续进行 ADT 的一个显著问题是癌细胞耐药性的出现。近年来，间歇性 ADT 已被提议作为连续 ADT 的替代方案，限制了毒性并延迟了进展时间。已经考虑了几种具有不同生物学耐药机制的数学模型来模拟间歇性 ADT 反应动力学。我们比较了 13 种这些间歇性动力学模型，并评估了它们描述前列腺特异性抗原（PSA）动力学的能力。这些模型根据局部晚期前列腺癌间歇性 ADT 的加拿大前瞻性 II 期试验的纵向 PSA 数据进行了校准。我们在治疗和非治疗期间对模型的参数空间进行贝叶斯推断和模型分析，以确定每个模型在描述患者特异性 PSA 动力学方面的优势和劣势。此外，我们对模型的证据进行了经典的贝叶斯模型比较，以确定最有可能模拟临床观察到的动力学的模型。我们的分析确定了一些具有重要能力的模型，可以区分复发和不复发的患者，以及参数区间，其中临界点的吸引域可能会被用于临床目的。最后，在贝叶斯模型比较框架内，我们确定了在描述临床数据方面最引人注目的模型。
