We investigated whether inter-patient variation in the dynamic trajectory of hemoglobin (Hb), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR), and prostate-specific antigen (PSA) can prognosticate overall survival (OS) in de novo mHSPC. This is a secondary analysis of the LATITUDE trial in which high-risk de novo mHSPC patients were randomly assigned to receive either androgen deprivation therapy (ADT) plus abiraterone or ADT plus placebo. We used a five-fold cross-validated joint model approach to determine the association of temporal changes in the serological markers with OS. Decision curve analysis was applied to determine the net benefit. When dynamic changes in Hb, LMR, NLR, PLR, and PSA were included in a multivariate joint model, an increase in the log of the current value of PSA (HR: 1.24 [1.20–1.28]) was associated with inferior OS. A multivariate joint model that captured dynamic trajectory of Hb, NLR, PLR, LMR, and PSA up to 24 months, showed a net benefit over the “treat all” strategy at a threshold of probability of approximately ≥30% while no net benefit was seen when dynamic change in PSA was omitted. Our joint model could be used for designing future adaptive trials investigating sequential treatment personalization.
本研究旨在探讨血红蛋白（Hb）、中性粒细胞与淋巴细胞比值（NLR）、血小板与淋巴细胞比值（PLR）、淋巴细胞与单核细胞比值（LMR）以及前列腺特异性抗原（PSA）的动态轨迹在患者间的差异是否能够预测初诊转移性激素敏感性前列腺癌（mHSPC）患者的总生存期（OS）。本研究是对LATITUDE试验的二次分析，该试验将高危初诊mHSPC患者随机分配接受雄激素剥夺疗法（ADT）联合阿比特龙或ADT联合安慰剂治疗。我们采用五折交叉验证的联合模型方法，以确定血清学标志物随时间变化与OS之间的关联。应用决策曲线分析来确定净获益。当将Hb、LMR、NLR、PLR和PSA的动态变化纳入多变量联合模型时，PSA当前值的对数增加（HR：1.24 [1.20–1.28]）与较差的OS相关。一个捕捉了长达24个月的Hb、NLR、PLR、LMR和PSA动态轨迹的多变量联合模型显示，在概率阈值约为≥30%时，相较于“全部治疗”策略具有净获益；而当省略PSA的动态变化时，未观察到净获益。我们的联合模型可用于设计未来研究序贯治疗个体化的适应性试验。
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