Heller Glenn, Devlin Sean M
Memorial Sloan Kettering Cancer Center, New York, USA.
J R Stat Soc Ser C Appl Stat. 2024 Sep 3;74(1):83-99. doi: 10.1093/jrsssc/qlae045. eCollection 2025 Jan.
Survival is poor for patients with metastatic cancer, and it is vital to examine new biomarkers that can improve patient prognostication and identify those who would benefit from more aggressive therapy. In metastatic prostate cancer, 2 new assays have become available: one that quantifies the number of cancer cells circulating in the peripheral blood, and the other a marker of the aggressiveness of the disease. It is critical to determine the magnitude of the effect of these biomarkers on the discrimination of a model-based risk score. To do so, most analysts frequently consider the discrimination of 2 separate survival models: one that includes both the new and standard factors and a second that includes the standard factors alone. However, this analysis is ultimately incorrect for many of the scale-transformation models ubiquitous in survival, as the reduced model is misspecified if the full model is specified correctly. To circumvent this issue, we developed a projection-based approach to estimate the impact of the 2 prostate cancer biomarkers. The results indicate that the new biomarkers can influence model discrimination and justify their inclusion in the risk model; however, the hunt remains for an applicable model to risk-stratify patients with metastatic prostate cancer.
转移性癌症患者的生存率很低，因此研究能够改善患者预后并确定哪些患者将从更积极的治疗中获益的新生物标志物至关重要。在转移性前列腺癌中，有两种新的检测方法可供使用：一种用于量化外周血中循环癌细胞的数量，另一种是疾病侵袭性的标志物。确定这些生物标志物对基于模型的风险评分的区分效果的大小至关重要。为此，大多数分析人员经常考虑两个独立生存模型的区分度：一个模型同时包含新因素和标准因素，另一个模型仅包含标准因素。然而，对于生存中普遍存在的许多尺度转换模型而言，这种分析最终是不正确的，因为如果完整模型指定正确，简化模型就会被错误指定。为了解决这个问题，我们开发了一种基于投影的方法来估计这两种前列腺癌生物标志物的影响。结果表明，新的生物标志物可以影响模型区分度，并证明将它们纳入风险模型是合理的；然而，寻找一种适用于对转移性前列腺癌患者进行风险分层的模型的工作仍在继续。
