Zhang Bo, Ye Shangyuan, Shankara Sravya B, Zhang Hui, Zheng Qingfeng
Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, 01605, USA.
Division of Biostatistics, Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA.
Contemp Clin Trials Commun. 2019 Aug 21;16:100436. doi: 10.1016/j.conctc.2019.100436. eCollection 2019 Dec.
Study design and statistical analysis are crucial in pivotal clinical trials to evaluate the effectiveness and safety of new medical devices under investigation. In recent years, innovative intraoperative breast tumor diagnostic devices have been proposed to improve the accuracy and surgical outcomes of breast tumor patients undergoing resection. Although such technologies are promising, investigators need to obtain statistical evidence for the effectiveness and safety of these devices by conducting valid clinical trials. However, the study design and statistical analysis for these clinical trials are complicated. While these trials are designed to provide real-time intraoperative diagnosis of cancerous tissue, they also have clear therapeutic objectives to lower the reoperation rate of breast cancer surgery. This research article introduces the new concept of neutral diagnosis (ND), and the ND clinical trial design as an innovative study design to evaluate the effectiveness and safety of diagnostic devices with direct therapeutic purposes. A joint modeling approach is adopted to make inferences on the effectiveness and safety of these devices for non-neutral diagnosis (non-ND) clinical trials. Simulation studies were conducted to show the efficiency of the ND trials and strength of the joint modeling approach in the non-ND clinical trials. An example on a diagnostic medical device that provides real-time, intraoperative diagnosis of breast cancer tumor tissues during breast cancer surgeries is comprehensively discussed and analyzed.
在关键临床试验中,研究设计和统计分析对于评估正在研究的新型医疗设备的有效性和安全性至关重要。近年来,已提出创新的术中乳腺肿瘤诊断设备,以提高接受切除术的乳腺肿瘤患者的准确性和手术效果。尽管此类技术前景广阔,但研究人员需要通过开展有效的临床试验来获取这些设备有效性和安全性的统计证据。然而,这些临床试验的研究设计和统计分析较为复杂。虽然这些试验旨在提供癌组织的实时术中诊断,但它们也有明确的治疗目标,即降低乳腺癌手术的再次手术率。本文介绍了中性诊断(ND)的新概念,以及作为一种创新研究设计的ND临床试验设计,用于评估具有直接治疗目的的诊断设备的有效性和安全性。采用联合建模方法对这些设备在非中性诊断(非ND)临床试验中的有效性和安全性进行推断。进行了模拟研究,以展示ND试验的效率以及联合建模方法在非ND临床试验中的优势。全面讨论并分析了一个诊断医疗设备的实例,该设备在乳腺癌手术期间可对乳腺癌肿瘤组织进行实时术中诊断。