A Bronchial Genomic Classifier for the Diagnostic Evaluation of Lung Cancer.
A Bronchial Genomic Classifier for the Diagnostic Evaluation of Lung Cancer.
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DOI：
10.1056/nejmoa1504601
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发表时间：
2015-07-16
期刊：
影响因子：
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通讯作者：
AEGIS Study Team
中科院分区：
文献类型：
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作者：
Silvestri GA;Vachani A;Whitney D;Elashoff M;Porta Smith K;Ferguson JS;Parsons E;Mitra N;Brody J;Lenburg ME;Spira A;AEGIS Study Team
在怀疑为肺癌的肺部病变的患者中，支气管镜检查通常是不能诊断的。这通常会导致额外的侵入性检测，尽管许多病变是良性的。我们试图验证一种能够提高支气管镜诊断性能的支气管-呼吸道基因表达分类器。在两项多中心前瞻性研究(宙斯盾-1和宙斯盾-2)中，在28个中心登记了因疑似肺癌而接受支气管镜检查的现任或既往吸烟者。从外观正常的主支气管处收集的上皮细胞中测量了基因表达分类器，以评估患肺癌的可能性。宙斯盾-1(298名患者)和宙斯盾-2(341名患者)中共有639名患者符合纳入标准。共有43%的支气管镜检查对肺癌没有诊断，35%的良性病变患者在支气管镜检查后进行侵入性手术。在宙斯盾-1中，分类器在接收器操作特征曲线(AUC)下的面积为0.78(95%可信区间[CI]，0.73至0.83)，灵敏度为88%(95%CI，83至92)，特异度为47%(95%CI，37至58)。在Aegis-2中，分类器的AUC为0.74(95%CI，0.68至0.80)，敏感性为89%(95%CI，84至92)，特异性为47%(95%CI，36至59)。分类器联合支气管镜检查对Aegis-1和Aegis-2的敏感性分别为96%(95%CI，93~98)和98%(95%CI，96~99)，与病变大小和部位无关。在101例具有中等癌症预测概率的患者中，在进行非诊断性支气管镜检查的患者中，该分类器的阴性预测值为91%(95%CI，75~98)。基因表达分类器提高了支气管镜检查肺癌的诊断性能。在有非诊断性支气管镜检查的中等风险患者中，阴性分类评分为更保守的诊断方法提供了支持。(由Allegro Diagnostics和其他公司资助；Aegis-1和Aegis-2 ClinicalTrials.gov编号，NCT01309087和NCT00746759。)
Bronchoscopy is frequently nondiagnostic in patients with pulmonary lesions suspected to be lung cancer. This often results in additional invasive testing, although many lesions are benign. We sought to validate a bronchial-airway gene-expression classifier that could improve the diagnostic performance of bronchoscopy. Current or former smokers undergoing bronchoscopy for suspected lung cancer were enrolled at 28 centers in two multicenter prospective studies (AEGIS-1 and AEGIS-2). A gene-expression classifier was measured in epithelial cells collected from the normal-appearing mainstem bronchus to assess the probability of lung cancer. A total of 639 patients in AEGIS-1 (298 patients) and AEGIS-2 (341 patients) met the criteria for inclusion. A total of 43% of bronchoscopic examinations were non-diagnostic for lung cancer, and invasive procedures were performed after bronchoscopy in 35% of patients with benign lesions. In AEGIS-1, the classifier had an area under the receiver-operating-characteristic curve (AUC) of 0.78 (95% confidence interval [CI], 0.73 to 0.83), a sensitivity of 88% (95% CI, 83 to 92), and a specificity of 47% (95% CI, 37 to 58). In AEGIS-2, the classifier had an AUC of 0.74 (95% CI, 0.68 to 0.80), a sensitivity of 89% (95% CI, 84 to 92), and a specificity of 47% (95% CI, 36 to 59). The combination of the classifier plus bronchoscopy had a sensitivity of 96% (95% CI, 93 to 98) in AEGIS-1 and 98% (95% CI, 96 to 99) in AEGIS-2, independent of lesion size and location. In 101 patients with an intermediate pretest probability of cancer, the negative predictive value of the classifier was 91% (95% CI, 75 to 98) among patients with a nondiagnostic bronchoscopic examination. The gene-expression classifier improved the diagnostic performance of bronchoscopy for the detection of lung cancer. In intermediate-risk patients with a nondiagnostic bronchoscopic examination, a negative classifier score provides support for a more conservative diagnostic approach. (Funded by Allegro Diagnostics and others; AEGIS-1 and AEGIS-2 ClinicalTrials.gov numbers, NCT01309087 and NCT00746759.)