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Analytical validation of the Percepta genomic sequencing classifier; an RNA next generation sequencing assay for the assessment of Lung Cancer risk of suspicious pulmonary nodules.对 Percepta 基因组测序分类器的分析验证;一种用于评估可疑肺结节肺癌风险的 RNA 下一代测序检测。
BMC Cancer. 2021 Apr 13;21(1):400. doi: 10.1186/s12885-021-08130-x.
2
Improving lung cancer risk stratification leveraging whole transcriptome RNA sequencing and machine learning across multiple cohorts.利用全转录组 RNA 测序和机器学习对多个队列进行分析,提高肺癌风险分层能力。
BMC Med Genomics. 2020 Oct 22;13(Suppl 10):151. doi: 10.1186/s12920-020-00782-1.
3
Impact of the Percepta Genomic Classifier on Clinical Management Decisions in a Multicenter Prospective Study.多中心前瞻性研究中 Percepta 基因组分类器对临床管理决策的影响。
Chest. 2021 Jan;159(1):401-412. doi: 10.1016/j.chest.2020.07.067. Epub 2020 Aug 3.
4
Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial.随机试验中 CT 容积筛查降低肺癌死亡率
N Engl J Med. 2020 Feb 6;382(6):503-513. doi: 10.1056/NEJMoa1911793. Epub 2020 Jan 29.
5
Electromagnetic Navigation Bronchoscopy for Peripheral Pulmonary Lesions: One-Year Results of the Prospective, Multicenter NAVIGATE Study.电磁导航支气管镜检查用于周围性肺部病变:前瞻性、多中心 NAVIGATE 研究的一年结果。
J Thorac Oncol. 2019 Mar;14(3):445-458. doi: 10.1016/j.jtho.2018.11.013. Epub 2018 Nov 23.
6
Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017.CT 图像上偶然发现的肺结节管理指南:来自 2017 年 Fleischner 学会。
Radiology. 2017 Jul;284(1):228-243. doi: 10.1148/radiol.2017161659. Epub 2017 Feb 23.
7
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Chest. 2016 Jul;150(1):210-8. doi: 10.1016/j.chest.2016.02.636. Epub 2016 Feb 16.
9
Diagnostic Yield and Complications of Bronchoscopy for Peripheral Lung Lesions. Results of the AQuIRE Registry.支气管镜检查对周围型肺病变的诊断率及并发症。AQuIRE注册研究结果
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Percepta GSC 用于肺癌评估的临床验证和实用性。

Clinical validation and utility of Percepta GSC for the evaluation of lung cancer.

机构信息

Department of Pulmonary Medicine, Cleveland Clinic, Respiratory Institute, Cleveland, OH, United States of America.

Division of Pulmonary and Critical Care, Wake Forest Baptist Health, Winston-Salem, NC, United States of America.

出版信息

PLoS One. 2022 Jul 13;17(7):e0268567. doi: 10.1371/journal.pone.0268567. eCollection 2022.

DOI:10.1371/journal.pone.0268567
PMID:35830375
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9278743/
Abstract

The Percepta Genomic Sequencing Classifier (GSC) was developed to up-classify as well as down-classify the risk of malignancy for lung lesions when bronchoscopy is non-diagnostic. We evaluated the performance of Percepta GSC in risk re-classification of indeterminate lung lesions. This multicenter study included individuals who currently or formerly smoked undergoing bronchoscopy for suspected lung cancer from the AEGIS I/ II cohorts and the Percepta Registry. The classifier was measured in normal-appearing bronchial epithelium from bronchial brushings. The sensitivity, specificity, and predictive values were calculated using predefined thresholds. The ability of the classifier to decrease unnecessary invasive procedures was estimated. A set of 412 patients were included in the validation (prevalence of malignancy was 39.6%). Overall, 29% of intermediate-risk lung lesions were down-classified to low-risk with a 91.0% negative predictive value (NPV) and 12.2% of intermediate-risk lesions were up-classified to high-risk with a 65.4% positive predictive value (PPV). In addition, 54.5% of low-risk lesions were down-classified to very low risk with >99% NPV and 27.3% of high-risk lesions were up-classified to very high risk with a 91.5% PPV. If the classifier results were used in nodule management, 50% of patients with benign lesions and 29% of patients with malignant lesions undergoing additional invasive procedures could have avoided these procedures. The Percepta GSC is highly accurate as both a rule-out and rule-in test. This high accuracy of risk re-classification may lead to improved management of lung lesions.

摘要

Percepta 基因组测序分类器 (GSC) 旨在提高和降低支气管镜检查非诊断性肺病变的恶性肿瘤风险。我们评估了 Percepta GSC 在不确定肺病变风险再分类中的性能。这项多中心研究包括来自 AEGIS I/II 队列和 Percepta 注册中心的当前或以前吸烟的疑似肺癌患者。分类器在支气管刷取的正常支气管上皮中进行测量。使用预定义的阈值计算敏感性、特异性和预测值。估计分类器减少不必要的侵入性程序的能力。一组 412 例患者纳入验证(恶性肿瘤患病率为 39.6%)。总体而言,29%的中度风险肺病变被降级为低风险,阴性预测值 (NPV) 为 91.0%,12.2%的中度风险病变被升级为高风险,阳性预测值 (PPV) 为 65.4%。此外,54.5%的低风险病变被降级为极低风险,NPV 超过 99%,27.3%的高风险病变被升级为极高风险,PPV 为 91.5%。如果在结节管理中使用分类器结果,可以避免 50%良性病变和 29%恶性病变患者进行额外的侵入性程序。Percepta GSC 作为排除和纳入测试均具有高度准确性。这种风险再分类的高度准确性可能会改善肺病变的管理。