Jo Yeonjung, Chipman Jonathan J, Haaland Benjamin, Greene Tom, Kohli Manish
Division of Biostatistics, Department of Population Health Sciences, School of Medicine, University of Utah, Salt Lake City, UT.
Cancer Biostatistics, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT.
JCO Precis Oncol. 2024 Dec;8:e2400399. doi: 10.1200/PO-24-00399. Epub 2024 Dec 3.
A composite multigene risk score derived from tumor-biology alterations specific to metastatic castrate-resistant prostate cancer (mCRPC) state was evaluated as a classifier to design biomarker-based enrichment clinical trials.
A plasma cell-free DNA copy number alteration risk score based on alterations in 24 genes was simulated to develop a biomarker classifier-based clinical trial design enriched for high-risk patients to detect a survival advantage of a novel treatment (hazard ratio of 0.70 with 80% power). We determined the design trade-offs between the number of patients screened and enrolled when varying the type of patients to enrich and the extent of enrichment needed.
For a 2-year overall survival end point in mCRPC state, fully enriching patients with mCRPC having a high-risk score of 3 or more (the 95th percentile of a range of risk scores in patients with mCRPC) was determined to require screening to a maximum of 4,149 patients to enroll 259 patients for the targeted effect size. A nonenriched trial was determined to require enrolling 689 patients to be equivalently powered. We identified a pragmatic alternative, which is to enrich patients with mCRPC with a risk score of 1 or more (the 67th percentile) and an enrichment fraction of 0.25. This would require screening 658 patients to enroll 584 patients, and it maximizes the ability to detect a difference in treatment effect by risk score.
A plasma multi-CNA risk score classifier can feasibly be leveraged to design an enrichment trial in mCRPC. Enriching 25% of patients screened with a risk score >1 was observed to be optimal for obtaining an adequately powered, biomarker-based mCRPC-enriched clinical trial.
评估一种基于转移性去势抵抗性前列腺癌（mCRPC）状态特异性肿瘤生物学改变的复合多基因风险评分，作为一种分类器，用于设计基于生物标志物的富集临床试验。
模拟基于24个基因改变的血浆游离DNA拷贝数改变风险评分，以开发一种基于生物标志物分类器的临床试验设计，该设计富集高危患者，以检测一种新疗法的生存优势（风险比为0.70，检验效能为80%）。我们确定了在改变要富集的患者类型和所需富集程度时，筛选患者数量和入组患者数量之间的设计权衡。
对于mCRPC状态下2年总生存终点，确定完全富集风险评分为3或更高（mCRPC患者风险评分范围的第95百分位数）的mCRPC患者，为达到目标效应量，最多需要筛选4149名患者以入组259名患者。确定非富集试验需要入组689名患者才能达到等效的检验效能。我们确定了一种实用的替代方案，即富集风险评分为1或更高（第67百分位数）且富集比例为0.25的mCRPC患者。这将需要筛选658名患者以入组584名患者，并且它最大限度地提高了通过风险评分检测治疗效果差异的能力。
血浆多拷贝数改变风险评分分类器可切实用于设计mCRPC的富集试验。观察到用风险评分>1筛选25%的患者进行富集，对于获得一项检验效能充足、基于生物标志物且富集mCRPC的临床试验而言是最优的。
