Department of Pathology, Yale University School of Medicine, New Haven, CT, USA.
Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada.
Mod Pathol. 2019 Jan;32(1):59-69. doi: 10.1038/s41379-018-0109-4. Epub 2018 Aug 24.
The nuclear proliferation biomarker Ki67 has potential prognostic, predictive, and monitoring roles in breast cancer. Unacceptable between-laboratory variability has limited its clinical value. The International Ki67 in Breast Cancer Working Group investigated whether Ki67 immunohistochemistry can be analytically validated and standardized across laboratories using automated machine-based scoring. Sets of pre-stained core-cut biopsy sections of 30 breast tumors were circulated to 14 laboratories for scanning and automated assessment of the average and maximum percentage of tumor cells positive for Ki67. Seven unique scanners and 10 software platforms were involved in this study. Pre-specified analyses included evaluation of reproducibility between all laboratories (primary) as well as among those using scanners from a single vendor (secondary). The primary reproducibility metric was intraclass correlation coefficient between laboratories, with success considered to be intraclass correlation coefficient >0.80. Intraclass correlation coefficient for automated average scores across 16 operators was 0.83 (95% credible interval: 0.73-0.91) and intraclass correlation coefficient for maximum scores across 10 operators was 0.63 (95% credible interval: 0.44-0.80). For the laboratories using scanners from a single vendor (8 score sets), intraclass correlation coefficient for average automated scores was 0.89 (95% credible interval: 0.81-0.96), which was similar to the intraclass correlation coefficient of 0.87 (95% credible interval: 0.81-0.93) achieved using these same slides in a prior visual-reading reproducibility study. Automated machine assessment of average Ki67 has the potential to achieve between-laboratory reproducibility similar to that for a rigorously standardized pathologist-based visual assessment of Ki67. The observed intraclass correlation coefficient was worse for maximum compared to average scoring methods, suggesting that maximum score methods may be suboptimal for consistent measurement of proliferation. Automated average scoring methods show promise for assessment of Ki67 scoring, but requires further standardization and subsequent clinical validation.
核增殖标志物 Ki67 在乳腺癌中有潜在的预后、预测和监测作用。由于实验室间的不可接受的变异性，其临床价值受到限制。国际 Ki67 在乳腺癌工作组研究了 Ki67 免疫组化是否可以通过使用自动化机器评分在实验室间进行分析验证和标准化。将 30 例乳腺癌的预染色核心活检切片集分发给 14 个实验室进行扫描和自动评估 Ki67 阳性肿瘤细胞的平均和最大百分比。本研究涉及 7 个独特的扫描仪和 10 个软件平台。预指定的分析包括对所有实验室（主要）以及使用单个供应商的扫描仪的实验室（次要）之间的重复性进行评估。主要的重复性度量是实验室之间的组内相关系数，成功被认为是组内相关系数>0.80。16 名操作人员的自动平均评分的组内相关系数为 0.83（95%可信区间：0.73-0.91），10 名操作人员的最大评分的组内相关系数为 0.63（95%可信区间：0.44-0.80）。对于使用单个供应商的扫描仪的实验室（8 个评分集），自动平均评分的组内相关系数为 0.89（95%可信区间：0.81-0.96），这与使用相同幻灯片在之前的视觉阅读重复性研究中获得的 0.87（95%可信区间：0.81-0.93）的组内相关系数相似。平均 Ki67 的自动机器评估有可能实现类似于严格标准化的基于病理学家的 Ki67 视觉评估的实验室间重复性。与平均评分方法相比，最大评分方法的组内相关系数较差，这表明最大评分方法可能不适合增殖的一致测量。自动平均评分方法有望用于评估 Ki67 评分，但需要进一步标准化和随后的临床验证。
