Tempus Labs, Chicago, IL.
Stanford Comprehensive Cancer Institute, Stanford University School of Medicine, Stanford, CA.
Clin Breast Cancer. 2021 Aug;21(4):e340-e361. doi: 10.1016/j.clbc.2020.11.012. Epub 2020 Dec 18.
OBJECTIVE/BACKGROUND: We performed a retrospective analysis of longitudinal real-world data (RWD) from patients with breast cancer to replicate results from clinical studies and demonstrate the feasibility of generating real-world evidence. We also assessed the value of transcriptome profiling as a complementary tool for determining molecular subtypes.
De-identified, longitudinal data were analyzed after abstraction from records of patients with breast cancer in the United States (US) structured and stored in the Tempus database. Demographics, clinical characteristics, molecular subtype, treatment history, and survival outcomes were assessed according to strict qualitative criteria. RNA sequencing and clinical data were used to predict molecular subtypes and signaling pathway enrichment.
The clinical abstraction cohort (n = 4000) mirrored the demographics and clinical characteristics of patients with breast cancer in the US, indicating feasibility for RWE generation. Among patients who were human epidermal growth factor receptor 2-positive (HER2), 74.2% received anti-HER2 therapy, with ∼70% starting within 3 months of a positive test result. Most non-treated patients were early stage. In this RWD set, 31.7% of patients with HER2 immunohistochemistry (IHC) had discordant fluorescence in situ hybridization results recorded. Among patients with multiple HER2 IHC results at diagnosis, 18.6% exhibited intra-test discordance. Through development of a whole-transcriptome model to predict IHC receptor status in the molecular sequenced cohort (n = 400), molecular subtypes were resolved for all patients (n = 36) with equivocal HER2 statuses from abstracted test results. Receptor-related signaling pathways were differentially enriched between clinical molecular subtypes.
RWD in the Tempus database mirrors the overall population of patients with breast cancer in the US. These results suggest that real-time, RWD analyses are feasible in a large, highly heterogeneous database. Furthermore, molecular data may aid deficiencies and discrepancies observed from breast cancer RWD.
目的/背景：我们对来自美国（美国）乳腺癌患者的纵向真实世界数据（RWD）进行了回顾性分析，以复制临床研究结果并证明生成真实世界证据的可行性。我们还评估了转录组谱分析作为确定分子亚型的补充工具的价值。
从美国 Tempus 数据库中提取和存储的乳腺癌患者记录中分析了经过去标识的纵向数据。根据严格的定性标准评估人口统计学、临床特征、分子亚型、治疗史和生存结局。使用 RNA 测序和临床数据来预测分子亚型和信号通路富集。
临床提取队列（n=4000）反映了美国乳腺癌患者的人口统计学和临床特征，表明生成 RWE 的可行性。在人表皮生长因子受体 2 阳性（HER2）患者中，74.2%接受了抗 HER2 治疗，约 70%在阳性检测结果后 3 个月内开始治疗。大多数未接受治疗的患者处于早期阶段。在这个 RWD 中，31.7%的 HER2 免疫组化（IHC）患者的荧光原位杂交结果记录存在不一致。在诊断时具有多个 HER2 IHC 结果的患者中，18.6%表现出检测内不一致。通过开发一个全转录组模型来预测分子测序队列（n=400）中 IHC 受体状态，解决了所有具有不确定提取测试结果的 HER2 状态的患者（n=36）的分子亚型。受体相关的信号通路在临床分子亚型之间存在差异富集。
Tempus 数据库中的 RWD 反映了美国乳腺癌患者的总体人群。这些结果表明，在大型、高度异质的数据库中实时进行 RWD 分析是可行的。此外，分子数据可能有助于弥补从乳腺癌 RWD 中观察到的缺陷和差异。
