St John Edward Robert, Al-Khudairi Rashed, Ashrafian Hutan, Athanasiou Thanos, Takats Zoltan, Hadjiminas Dimitri John, Darzi Ara, Leff Daniel Richard
*Department of BioSurgery and Surgical Technology, Imperial College London, London, UK †Imperial College School of Medicine, Imperial College London, London, UK ‡Division of Computational and Systems Medicine, Imperial College London, London, UK §Breast Unit, Charing Cross Hospital, Imperial College NHS Trust, London, UK.
Ann Surg. 2017 Feb;265(2):300-310. doi: 10.1097/SLA.0000000000001897.
The aim of this study was to conduct a systematic review and meta-analysis to clarify the diagnostic accuracy of intraoperative breast margin assessment (IMA) techniques against which the performance of emerging IMA technologies may be compared.
IMA techniques have failed to penetrate routine practice due to limitations, including slow reporting times, technical demands, and logistics. Emerging IMA technologies are being developed to reduce positive margin and re-excision rates and will be compared with the diagnostic accuracy of existing techniques.
Studies were identified using electronic bibliographic searches up to January 2016. MESH terms and all-field search terms included "Breast Cancer" AND "Intraoperative" AND "Margin." Only clinical studies with raw diagnostic accuracy data as compared with final permanent section histopathology were included. A bivariate model for diagnostic meta-analysis was used to attain overall pooled sensitivity and specificity.
Eight hundred thirty-eight unique studies revealed 35 studies for meta-analysis. Pooled sensitivity (Sens), specificity (Spec), and area under the receiver operating characteristic curve (AUROC) values were calculated per group (Sens, Spec, AUROC): frozen section = 86%, 96%, 0.96 (n = 9); cytology = 91%, 95%, 0.98 (n = 11); intraoperative ultrasound = 59%, 81%, 0.78 (n = 4); specimen radiography = 53%, 84%, 0.73 (n = 9); optical spectroscopy = 85%, 87%, 0.88 (n = 3).
Pooled data suggest that frozen section and cytology have the greatest diagnostic accuracy. However, these methods are resource intensive and turnaround times for results have prevented widespread international adoption. Emerging technologies need to compete with the diagnostic accuracy of existing techniques while offering advantages in terms of speed, cost, and reliability.
本研究旨在进行一项系统评价和荟萃分析，以阐明术中切缘评估（IMA）技术的诊断准确性，从而能够与新兴IMA技术的性能进行比较。
由于存在局限性，包括报告时间长、技术要求高和后勤问题，IMA技术未能普及到常规实践中。正在开发新兴的IMA技术以降低切缘阳性率和再次切除率，并将与现有技术的诊断准确性进行比较。
通过电子文献检索确定截至2016年1月的研究。医学主题词（MESH）和全字段检索词包括“乳腺癌”、“术中”和“切缘”。仅纳入与最终永久切片组织病理学相比具有原始诊断准确性数据的临床研究。采用诊断荟萃分析的双变量模型来获得总体合并敏感性和特异性。
838项独特研究中有35项纳入荟萃分析。计算每组的合并敏感性（Sens）、特异性（Spec）和受试者操作特征曲线下面积（AUROC）值（Sens、Spec、AUROC）：冰冻切片=86%、96%、0.96（n = 9）；细胞学=91%、95%、0.98（n = 11）；术中超声=59%、81%、0.78（n = 4）；标本射线照相=53%、84%、0.73（n = 9）；光学光谱=85%、87%、0.88（n = 3）。
汇总数据表明，冰冻切片和细胞学具有最高的诊断准确性。然而，这些方法资源消耗大，结果周转时间长，阻碍了其在国际上的广泛应用。新兴技术需要在与现有技术的诊断准确性竞争的同时，在速度、成本和可靠性方面具有优势。
