转移性去势抵抗性前列腺癌多基因拷贝数改变风险评分基于生物标志物的富集研究设计。

IF 5.3 2区 医学 Q1 ONCOLOGY
JCO precision oncology Pub Date : 2024-12-01 Epub Date: 2024-12-03 DOI:10.1200/PO-24-00399
Yeonjung Jo, Jonathan J Chipman, Benjamin Haaland, Tom Greene, Manish Kohli
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引用次数: 0

摘要

目的:从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中获得的复合多基因风险评分作为设计基于生物标志物的富集临床试验的分类器进行评估。方法:模拟基于24个基因改变的无浆细胞DNA拷贝数改变风险评分,开发基于生物标志物分类的临床试验设计,丰富高危患者,以检测新治疗的生存优势(风险比为0.70,功率为80%)。我们确定了在筛选和入组的患者数量之间的设计权衡,当改变患者的类型和需要的富集程度时。结果:对于mCRPC状态的2年总生存终点,确定高风险评分为3分或以上(mCRPC患者风险评分范围的第95百分位)的mCRPC患者完全富集,需要筛查最多4149例患者,以招募259例患者进行目标效应大小。一项非强化试验确定需要入组689名患者才能获得同等疗效。我们确定了一种实用的替代方案,即对风险评分为1或更高(第67百分位)且富集分数为0.25的mCRPC患者进行富集。这将需要筛选658名患者来招募584名患者,并且通过风险评分最大化检测治疗效果差异的能力。结论:血浆多cna风险评分分类器可用于mCRPC的富集试验设计。观察到25%的风险评分为>.1的筛查患者的富集是获得充分动力的、基于生物标志物的mcrpc富集临床试验的最佳选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multigene Copy Number Alteration Risk Score Biomarker-Based Enrichment Study Designs in Metastatic Castrate-Resistant Prostate Cancer.

Purpose: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

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CiteScore
9.10
自引率
4.30%
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