用于预测嗜铬细胞瘤和副神经节瘤转移风险的 5 种评分系统的验证和评估

IF 4.5 1区 医学 Q1 PATHOLOGY
American Journal of Surgical Pathology Pub Date : 2024-07-01 Epub Date: 2024-05-07 DOI:10.1097/PAS.0000000000002238
Qin Li, Zhigang Lan, Yong Jiang, Rui Wang, Ziyao Li, Xiaolin Jiang
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引用次数: 0

摘要

目前,文献中提出了 5 种预测嗜铬细胞瘤和副神经节瘤(PPGL)转移风险的评分系统:肾上腺嗜铬细胞瘤标度评分(PASS)、肾上腺嗜铬细胞瘤和副神经节瘤分级系统(GAPP)、嗜铬细胞瘤/副神经节瘤综合预后评分(COPPS)、年龄、大小、肾上腺外位置、分泌类型(ASES)评分以及大小、遗传、年龄和 PASS(SGAP)模型。为了验证和评估这5种评分系统,我们对2012年1月至2019年12月期间在四川大学华西医院病理科确诊为PPGL的病例进行了回顾性研究。共纳入185例PPGL病例,其中35例有转移,150例术后8年以上无转移。采用5种评分系统的标准进行评分和风险分类。采用一致性指数(C-index)和决策曲线分析(DCA)对 5 种评分系统的预测性能进行了验证、比较和评估。PASS、GAPP 和 SGAP 的 C 指数分别为 0.600、0.547 和 0.547,表明它们的判别能力较低。相比之下,COPPS 和 ASES 的 C 指数分别为 0.740 和 0.706,显示出较好的判别能力。DCA 还表明,COPPS 的预测能力优于 ASES,两者都优于 PASS,而 PASS 的预测能力优于 GAPP 和 SGAP。我们的分析表明,基于病理学的评分系统不能准确预测PPGL的转移风险。建立精确的预测系统需要整合临床、病理和分子信息,并采用科学的方法进行预测因子选择和权重评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Validation and Evaluation of 5 Scoring Systems for Predicting Metastatic Risk in Pheochromocytoma and Paraganglioma.

Currently, 5 scoring systems have been proposed in the literature for predicting metastatic risk in pheochromocytoma and paraganglioma (PPGL): Pheochromocytoma of the Adrenal Gland Scaled Score (PASS), Grading System for Adrenal Pheochromocytoma and Paraganglioma (GAPP), Composite Pheochromocytoma/paraganglioma Prognostic Score (COPPS), Age, Size, Extra-adrenal location, Secretion type (ASES) score, and Size, Genetic, Age, and PASS (SGAP) model. To validate and evaluate these 5 scoring systems, we conducted a retrospective review of cases diagnosed as PPGL at the Department of Pathology, West China Hospital of Sichuan University, between January 2012 and December 2019. A total of 185 PPGL cases were included, comprising 35 cases with metastasis and 150 cases remained metastasis-free for over 8 years after surgery. The criteria of the 5 scoring systems were used for scoring and risk classification. The predictive performance of the 5 scoring systems was validated, compared, and evaluated using concordance index (C-index) and decision curve analysis (DCA). The C-indices for PASS, GAPP, and SGAP were 0.600, 0.547, and 0.547, respectively, indicating low discriminative ability. In contrast, COPPS and ASES had C-indices of 0.740 and 0.706, respectively, indicating better discriminative performance. DCA also showed that the predictive capability of COPPS was superior to that of ASES, with both outperformed PASS, while PASS had better predictive ability than GAPP and SGAP. Our analysis indicated that pathology-based scoring systems cannot accurately predict metastatic risk of PPGL. Establishing a precise prediction system requires integrating clinical, pathologic, and molecular information, using a scientific methodology for predictive factor selection and weight assessment.

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来源期刊
CiteScore
10.30
自引率
5.40%
发文量
295
审稿时长
1 months
期刊介绍: The American Journal of Surgical Pathology has achieved worldwide recognition for its outstanding coverage of the state of the art in human surgical pathology. In each monthly issue, experts present original articles, review articles, detailed case reports, and special features, enhanced by superb illustrations. Coverage encompasses technical methods, diagnostic aids, and frozen-section diagnosis, in addition to detailed pathologic studies of a wide range of disease entities. Official Journal of The Arthur Purdy Stout Society of Surgical Pathologists and The Gastrointestinal Pathology Society.
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