Department of Medicine, Division of Hematology-Oncology, Massachusetts General Hospital, Boston, MA.
Novartis Pharmaceuticals Corporation, Cambridge, MA.
JCO Precis Oncol. 2024 Jun;8:e2400230. doi: 10.1200/PO.24.00230.
The clinical application of PD-L1 immunohistochemistry (IHC) testing is complicated by the availability of multiple IHC assays, scoring algorithms, and cutoffs. This study assessed the analytical comparability of three commercially available PD-L1 assays and two scoring algorithms used to assess PD-L1 status in gastric cancer (GC) samples.
Serial sections of 100 resected GC samples, with PD-L1 expression levels across the dynamic range, were stained with three in vitro diagnostic-grade PD-L1 assays (28-8, 22C3, and SP263). Three trained pathologists blindly and independently scored slides using combined positive score (CPS) and tumor area positivity (TAP) algorithms. Comprehensive statistical analyses were performed to evaluate analytical concordance. Digital image analysis (DIA) was used to objectively compare the technical performance of each assay by simulating CPS and TAP.
Comparable staining patterns were observed with these three PD-L1 assays. Despite discernible variation in staining intensity, reproducible evaluations of PD-L1 positivity were observed. Inter- and intra-assay assessments of all three assays, using either CPS or TAP and the same PD-L1 cutoffs, demonstrated moderate to almost-perfect (interassay Cohen's kappa [κ] range, 0.47-0.83) and substantial to almost-perfect (intra-assay κ range, 0.77-1.00) agreement. Interpathologist assessment exhibited a significant level of concordance (intraclass correlation coefficient ≥0.92). No difference in technical performance was observed using DIA.
This study highlights analytical concordance in PD-L1 testing between three major PD-L1 assays when TAP and CPS are applied. Comparability of the technical assay performance was further supported by independent DIA. These observations support cross-application flexibility of the different PD-L1 assays and scoring algorithms to characterize PD-L1 expression in GC.
PD-L1 免疫组织化学（IHC）检测的临床应用受到多种 IHC 检测、评分算法和截断值的影响。本研究评估了三种市售 PD-L1 检测方法和两种用于评估胃癌（GC）样本 PD-L1 状态的评分算法的分析可比性。
对 100 例切除的 GC 样本进行连续切片，这些样本的 PD-L1 表达水平跨越动态范围，使用三种体外诊断级 PD-L1 检测方法（28-8、22C3 和 SP263）进行染色。三名经过培训的病理学家使用联合阳性评分（CPS）和肿瘤面积阳性率（TAP）算法对切片进行盲法和独立评分。进行全面的统计分析以评估分析一致性。通过模拟 CPS 和 TAP，使用数字图像分析（DIA）客观比较每种检测方法的技术性能。
这三种 PD-L1 检测方法观察到相似的染色模式。尽管染色强度存在明显差异，但仍观察到 PD-L1 阳性的可重复评估。使用 CPS 或 TAP 以及相同的 PD-L1 截断值，对所有三种检测方法进行的组内和组间评估均显示出中度至几乎完美（组间 Cohen's kappa [κ] 范围为 0.47-0.83）和高度至几乎完美（组内 κ 范围为 0.77-1.00）的一致性。病理学家之间的评估显示出显著的一致性（组内相关系数≥0.92）。使用 DIA 未观察到技术性能的差异。
本研究强调了三种主要 PD-L1 检测方法在应用 TAP 和 CPS 时在 PD-L1 检测中的分析一致性。独立的 DIA 进一步支持技术检测性能的可比性。这些观察结果支持不同 PD-L1 检测方法和评分算法在 GC 中表征 PD-L1 表达的交叉应用灵活性。
