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肿瘤区域阳性(TAP)评分程序性死亡配体 1(PD-L1):一种联合肿瘤细胞和免疫细胞评分的新型可视化评估方法。

Tumor Area Positivity (TAP) score of programmed death-ligand 1 (PD-L1): a novel visual estimation method for combined tumor cell and immune cell scoring.

机构信息

Roche Tissue Diagnostics, 1910 E. Innovation Park Dr., Oro Valley, Tucson, AZ, 85755, USA.

出版信息

Diagn Pathol. 2023 Apr 19;18(1):48. doi: 10.1186/s13000-023-01318-8.

Abstract

BACKGROUND

Determination of programmed death-ligand 1 (PD-L1) protein expression level in tumor cells and tumor-associated immune cells is critical for identifying patients eligible for immunotherapy. PD-L1 manual scoring algorithms can generally be divided into two categories: cell counting and visual estimation. Cell counting can be time-consuming and is not in sync with pathology practice, which classically uses a Gestalt approach based on pattern recognition and visual estimation. In this study, we introduce the Tumor Area Positivity (TAP) score, which is a novel, straightforward method for scoring tumor cells and immune cells together using visual estimation.

METHODS

To demonstrate the reproducibility of TAP scoring among pathologists, between- and within-reader precision studies were performed both within (internal) and outside of (external) our organization. We also compared the TAP score to the Combined Positive Score (CPS), which is based on cell counting, for concordance and time efficacy.

RESULTS

The average positive agreement, average negative agreement, and overall percent agreement between and within readers were all above 85% for both internal and combined external reader precision studies. TAP score had high concordance rate at 5% cutoff compared with CPS at cutoff 1: positive percent agreement, negative percent agreement, and overall percent agreement were all above 85%.

CONCLUSIONS

Our study showed the TAP scoring method to be straightforward, significantly less time-consuming, and highly reproducible with a high concordance rate between TAP score and CPS.

摘要

背景

在肿瘤细胞和肿瘤相关免疫细胞中测定程序性死亡配体 1(PD-L1)蛋白表达水平对于确定适合免疫治疗的患者至关重要。PD-L1 手动评分算法通常可分为两类:细胞计数和视觉估计。细胞计数可能很耗时,并且与病理实践不同,病理实践通常基于基于模式识别和视觉估计的整体方法使用 Gestalt 方法。在这项研究中,我们介绍了肿瘤区域阳性(TAP)评分,这是一种新颖的,简单的方法,可用于通过视觉估计一起对肿瘤细胞和免疫细胞进行评分。

方法

为了证明病理学家之间 TAP 评分的可重复性,我们在内部和外部进行了读者间和读者内的精确性研究。我们还将 TAP 评分与基于细胞计数的组合阳性评分(CPS)进行了比较,以评估一致性和时间效率。

结果

内部和组合外部读者精度研究中,读者间和读者内的平均阳性一致性,平均阴性一致性和总体百分比一致性均高于 85%。与 CPS 在 1:阳性百分比一致性,阴性百分比一致性和总体百分比一致性均高于 85%的 5%截断值相比,TAP 评分具有很高的一致性率。

结论

我们的研究表明,TAP 评分方法简单,耗时明显减少,并且具有很高的重复性,TAP 评分与 CPS 之间具有很高的一致性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c019/10114344/19ca873cc7b0/13000_2023_1318_Fig1_HTML.jpg

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