Active surveillance (AS), where biopsies are conducted to detect cancer progression, has been acknowledged as an efficient way to reduce the overtreatment of prostate cancer. Most AS cohorts use fixed biopsy schedules for all patients. However, the ideal test frequency remains unknown, and the routine use of such invasive tests burdens the patients. An emerging idea is to generate personalized biopsy schedules based on each patient's progression-specific risk. To achieve that, we propose the interval-censored cause-specific joint model (ICJM), which models the impact of longitudinal biomarkers on cancer progression while considering the competing event of early treatment initiation. The underlying likelihood function incorporates the interval-censoring of cancer progression, the competing risk of treatment, and the uncertainty about whether cancer progression occurred since the last biopsy in patients that are right-censored or experience the competing event. The model can produce patient-specific risk profiles until a horizon time. If the risk exceeds a certain threshold, a biopsy is conducted. The optimal threshold can be chosen by balancing two indicators of the biopsy schedules: the expected number of biopsies and expected delay in detection of cancer progression. A simulation study showed that our personalized schedules could considerably reduce the number of biopsies per patient by 34%-54% compared to the fixed schedules, though at the cost of a slightly longer detection delay.
翻译:进行主动监测(AS)是为了检测癌症的演变情况,被确认为是减少前列腺癌过量治疗的有效方法,大多数组群都使用固定的生物检查时间表,但是,理想的测试频率仍然未知,这种侵入性测试的例行使用给病人造成负担。一个新出现的想法是,根据每个病人的进化风险制定个性化生物检查时间表。为了实现这一目标,我们提议了间歇性检查特定原因的联合模型(ICEM),该模型在考虑早期治疗开始的竞争性事件的同时,对纵向生物标志对癌症进展的影响进行模拟。潜在可能性功能包括癌症进化的间隔检查、相互竞争的治疗风险、以及自上一次正确检查或经历竞争事件以来癌症进化是否发生的不确定性。模型可以产生具体病人的风险概况,直到一个时段时间。如果风险超过某一阈值,则进行生物检查。可以通过平衡两种生物检查时间表的指标来选择最佳阈值:预期的生物观察结果的数量和预期的病人在诊断过程中的延迟时间,而个人检查时间表则比个人癌症的缓慢时间要长一些。 模拟研究显示,比个人检查的进度要大大降低成本。