Goebel Consulting Inc., Mountain View, 780 Montague Expressway, Suite 703, San Jose, CA, 95131, USA.
Louden Consulting, San Antonio, TX, USA.
BMC Cancer. 2020 Feb 21;20(1):137. doi: 10.1186/s12885-020-6625-x.
In a previous study (Goebel et. al, Cancer Genomics Proteomics 16:229-244, 2019), we identified 33 biomarkers for an early stage (I-II) Non-Small Cell Lung Cancer (NSCLC) test with 90% accuracy, 80.3% sensitivity, and 95.4% specificity. For the current study, we used a narrowed ensemble of 21 biomarkers while retaining similar accuracy in detecting early stage lung cancer.
A multiplex platform, 486 human plasma samples, and 21 biomarkers were used to develop and validate our algorithm which detects early stage NSCLC. The training set consisted of 258 human plasma with 79 Stage I-II NSCLC samples. The 21 biomarkers with the statistical model (Lung Cancer Detector Test 1, LCDT1) was then validated using 228 novel samples which included 55 Stage I NSCLC.
The LCDT1 exhibited 95.6% accuracy, 89.1% sensitivity, and 97.7% specificity in detecting Stage I NSCLC on the blind set. When only NSCLC cancers were analyzed, the specificity increased to 99.1%.
Compared to current approved clinical methods for diagnosing NSCLC, the LCDT1 greatly improves accuracy while being non-invasive; a simple, cost-effective, early diagnostic blood test should result in expanding access and increase survival rate.
在之前的一项研究(Goebel 等人,癌症基因组蛋白质组学 16:229-244, 2019)中,我们发现了 33 个用于早期非小细胞肺癌(NSCLC)测试的生物标志物,准确率为 90%,灵敏度为 80.3%,特异性为 95.4%。在当前的研究中,我们使用了一个缩小的 21 个生物标志物的集合,同时在检测早期肺癌方面保持了类似的准确性。
我们使用了一个多重平台、486 个人血浆样本和 21 个生物标志物来开发和验证我们的算法,该算法用于检测早期 NSCLC。训练集由 258 个人血浆和 79 个 I-II 期 NSCLC 样本组成。然后,使用包含 55 个 I 期 NSCLC 的 228 个新样本验证了具有统计模型(肺癌检测测试 1,LCDT1)的 21 个生物标志物。
LCDT1 在盲集上检测 I 期 NSCLC 的准确率为 95.6%,灵敏度为 89.1%,特异性为 97.7%。当仅分析 NSCLC 癌症时,特异性增加到 99.1%。
与目前用于诊断 NSCLC 的临床方法相比,LCDT1 在提高准确性的同时具有非侵入性;一种简单、经济有效的早期诊断血液测试应该会扩大获得途径并提高生存率。