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CT、MRI和F-18 FDG PET用于检测非小细胞肺癌(NSCLC):诊断试验准确性网络荟萃分析方案

CT, MRI, and F-18 FDG PET for the detection of non-small-cell lung cancer (NSCLC): A protocol for a network meta-analysis of diagnostic test accuracy.

作者信息

Zhang Yi, Ni Jinman, Wei Kongyuan, Tian Jinhui, Sun Shaobo

机构信息

School of Basic Medical Sciences, Lanzhou University Department of General Surgery, First Affiliated Hospital of Lanzhou University Evidence-based Medicine Center, School of Basic Medical Sciences Gansu university of Chinese Medicine, Lanzhou University, Lanzhou, China.

出版信息

Medicine (Baltimore). 2018 Sep;97(38):e12387. doi: 10.1097/MD.0000000000012387.

Abstract

BACKGROUND

Non-small-cell lung cancer (NSCLC) is a rare cancer in lung carcinomas and has been widely known as a difficult curable disease among all the tumors. However, early detection of malignant potential in patients with NSCLC has still been a huge challenge all around the world. CT, MRI, and F-18 FDG PET are all considered as good tests for diagnosing malignant NSCLC efficiently, but no recommended suggestion presents that which test among the 3 is the prior one in diagnose. We perform this study through network meta-analysis method, and to rank these tests using a superiority index.

METHODS AND ANALYSIS

PubMed, Embase.com, and the Cochrane Central Register of Controlled Trials (CENTRAL) will be searched from their inception to March 2018. We will include diagnostic tests which assessed the accuracy of CT, MRI, and F-18 FDG PET for diagnosing NSCLC. The risk of bias for each study will be independently assessed as low, moderate, or high using criteria adapted from Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Network meta-analysis will be performed using STATA 12.0 and R 3.4.1 software. The competing diagnostic tests will be ranked by a superiority index.

RESULTS

This study is ongoing, and will be submitted to a peer-reviewed journal for publication.

CONCLUSION

This study will provide systematically suggestions to select different diagnostic measures for detecting the early NSCLC.

ETHICS AND DISSEMINATION

Ethical approval and patient consent are not required since this study is a network meta-analysis based on published studies. The results of this network meta-analysis will be submitted to a peer-reviewed journal for publication.

PROSPERO REGISTRATION NUMBER

PROSPEROCRD42018094542.

摘要

背景

非小细胞肺癌(NSCLC)在肺癌中是一种罕见的癌症,在所有肿瘤中一直被广泛认为是一种难以治愈的疾病。然而,在全球范围内,早期检测非小细胞肺癌患者的恶性潜能仍然是一个巨大的挑战。CT、MRI和F-18 FDG PET都被认为是有效诊断恶性非小细胞肺癌的良好检查方法,但没有推荐意见表明这三种检查中哪一种在诊断中是首选。我们通过网络荟萃分析方法进行这项研究,并使用优势指数对这些检查进行排名。

方法与分析

将检索PubMed、Embase.com和Cochrane对照试验中心注册库(CENTRAL),检索时间从建库至2018年3月。我们将纳入评估CT、MRI和F-18 FDG PET诊断NSCLC准确性的诊断性检查。将根据改编自《诊断准确性研究质量评估2》(QUADAS-2)的标准,独立评估每项研究的偏倚风险,分为低、中或高。将使用STATA 12.0和R 3.4.1软件进行网络荟萃分析。将通过优势指数对相互竞争的诊断性检查进行排名。

结果

本研究正在进行中,将提交给同行评审期刊发表。

结论

本研究将为选择不同的诊断措施来检测早期非小细胞肺癌提供系统性建议。

伦理与传播

由于本研究是基于已发表研究的网络荟萃分析,因此无需伦理批准和患者同意。本网络荟萃分析的结果将提交给同行评审期刊发表。

PROSPERO注册号:PROSPEROCRD42018094542。

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