Chen Yan, Xiao Huangmeng, Zhou Xieda, Huang Xiaoyu, Li Yanbing, Xiao Haipeng, Cao Xiaopei
Endocr Pract. 2017 Oct;23(10):1169-1177. doi: 10.4158/EP171877.OR. Epub 2017 Jul 13.
Various studies have validated plasma free metanephrines (MNs) as biomarkers for pheochromocytoma and paraganglioma (PPGL). This meta-analysis aimed to estimate the overall diagnostic accuracy of this biochemical test for PPGL.
We searched the PubMed, the Cochrane Library, Web of Science, Embase, Scopus, OvidSP, and ProQuest Dissertations & Theses databases from January 1, 1995 to December 2, 2016 and selected studies written in English that assessed plasma free MNs in the diagnosis of PPGL. Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) was used to evaluate the quality of the included studies. We calculated pooled sensitivities, specificities, positive and negative likelihood ratios, diagnostic odds ratios (DORs) and areas under curve (AUCs) with their 95% confidence intervals (95% CIs). Heterogeneity was assessed by I. To identify the source of heterogeneity, we evaluated the threshold effect and performed a meta-regression. Deeks' funnel plot was selected for investigating any potential publication bias.
Although the combination of metanephrine (MN) and normetanephrine (NMN) carried lower specificity (0.94, 95% CI 0.90-0.97) than NMN (0.97, 95% CI 0.92-0.99), NMN was generally more accurate than individual tests, with the highest AUC (0.99, 95% CI 0.97-0.99), DOR (443.35, 95% CI 216.9-906.23), and pooled sensitivity (0.97, 95% CI 0.94-0.98) values. Threshold effect and meta-regression analyses showed that different cut-offs, blood sampling positions, study types and test methods contributed to heterogeneity.
This meta-analysis suggested an effective value for combined plasma free MNs for the diagnosis of PPGL, but testing for MNs requires more standardization using tightly regulated studies.
AUC = area under curve; CI = confidence interval; DOR = diagnostic odds ratio; EIA = enzyme immunoassay; LC-ECD = liquid chromatography-electrochemical detection; LC-MS/MS = liquid chromatography-tandem mass spectrometry; MN = metanephrine; NMN = normetaneprhine; PPGL = pheochromocytoma and paraganglioma; QUADAS-2 = Quality Assessment of Diagnostic Accuracy Studies 2.
多项研究已证实血浆游离甲氧基肾上腺素(MNs)作为嗜铬细胞瘤和副神经节瘤(PPGL)的生物标志物。本荟萃分析旨在评估这项生化检测对PPGL的总体诊断准确性。
我们检索了1995年1月1日至2016年12月2日期间的PubMed、Cochrane图书馆、科学网、Embase、Scopus、OvidSP和ProQuest学位论文数据库,并选择了以英文撰写的评估血浆游离MNs在PPGL诊断中的研究。使用诊断准确性研究质量评估2(QUADAS - 2)来评估纳入研究的质量。我们计算了合并敏感度、特异度、阳性和阴性似然比、诊断比值比(DORs)以及曲线下面积(AUCs)及其95%置信区间(95% CIs)。通过I²评估异质性。为了确定异质性的来源,我们评估了阈值效应并进行了荟萃回归分析。选择Deeks漏斗图来研究任何潜在的发表偏倚。
尽管甲氧基肾上腺素(MN)和去甲氧基肾上腺素(NMN)联合检测的特异度(0.94,95% CI 0.90 - 0.97)低于NMN(0.97,95% CI 0.92 - 0.99),但NMN总体上比单项检测更准确,其AUC(0.99,95% CI 0.97 - 0.99)、DOR(443.35,95% CI 216.9 - 906.23)和合并敏感度(0.97,95% CI 0.94 - 0.98)值最高。阈值效应和荟萃回归分析表明,不同的截断值、采血部位、研究类型和检测方法导致了异质性。
本荟萃分析表明联合检测血浆游离MNs对PPGL诊断具有有效价值,但MNs检测需要通过严格规范的研究实现更多标准化。
AUC = 曲线下面积;CI = 置信区间;DOR = 诊断比值比;EIA = 酶免疫测定;LC - ECD = 液相色谱 - 电化学检测;LC - MS/MS = 液相色谱 - 串联质谱;MN = 甲氧基肾上腺素;NMN = 去甲氧基肾上腺素;PPGL = 嗜铬细胞瘤和副神经节瘤;QUADAS - 2 = 诊断准确性研究质量评估2