S. Sayad, Seyyed Amir Yasin Ahmadi, M. Moradi, Reza Nekouian, K. Anbari, F. Shahsavar
{"title":"A meta-analysis on diagnostic accuracy of serum HLA-G level in breast cancer","authors":"S. Sayad, Seyyed Amir Yasin Ahmadi, M. Moradi, Reza Nekouian, K. Anbari, F. Shahsavar","doi":"10.1080/23808993.2020.1735936","DOIUrl":null,"url":null,"abstract":"ABSTRACT Background: According to the role of human leukocyte antigen (HLA)-G in tumor progression and tumor escape from immune system as well as diagnostic role of biomarkers in breast cancer, this meta-analysis is designed to reach a pooled diagnostic accuracy for this biomarker. Methods: The present work is a meta-analysis on diagnostic accuracy studies using preferred reporting items for systematic reviews and meta-analyses guideline. All documents studying the serum level of HLA-G both in breast cancer patients and in healthy controls using receiver operating characteristics (ROC) curve with reporting area under ROC curve (AUC) were eligible for inclusion. Results: Five articles including 754 participants were eligible for quantitative synthesis. The range of AUC of the selected studies was 0.735–0.953. The pooled AUC was 0.922 (95% confidence interval [CI] 0.903–0.941) based on fixed effect model (P < 0.001) and 0.896 (95% CI 0.834–0.959) based on random effect model (P < 0.001). Conclusion: This meta-analysis updated the level of evidence for using serum HLA-G in diagnosis of breast cancer. However, this piece of evidence cannot be used as a diagnostic tool. This biomarker can be used for investigation of recurrence and response to treatment in future. Further studies are suggested to complete this evidence gap.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2020-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23808993.2020.1735936","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert Review of Precision Medicine and Drug Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23808993.2020.1735936","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 7
Abstract
ABSTRACT Background: According to the role of human leukocyte antigen (HLA)-G in tumor progression and tumor escape from immune system as well as diagnostic role of biomarkers in breast cancer, this meta-analysis is designed to reach a pooled diagnostic accuracy for this biomarker. Methods: The present work is a meta-analysis on diagnostic accuracy studies using preferred reporting items for systematic reviews and meta-analyses guideline. All documents studying the serum level of HLA-G both in breast cancer patients and in healthy controls using receiver operating characteristics (ROC) curve with reporting area under ROC curve (AUC) were eligible for inclusion. Results: Five articles including 754 participants were eligible for quantitative synthesis. The range of AUC of the selected studies was 0.735–0.953. The pooled AUC was 0.922 (95% confidence interval [CI] 0.903–0.941) based on fixed effect model (P < 0.001) and 0.896 (95% CI 0.834–0.959) based on random effect model (P < 0.001). Conclusion: This meta-analysis updated the level of evidence for using serum HLA-G in diagnosis of breast cancer. However, this piece of evidence cannot be used as a diagnostic tool. This biomarker can be used for investigation of recurrence and response to treatment in future. Further studies are suggested to complete this evidence gap.
期刊介绍:
Expert Review of Precision Medicine and Drug Development publishes primarily review articles covering the development and clinical application of medicine to be used in a personalized therapy setting; in addition, the journal also publishes original research and commentary-style articles. In an era where medicine is recognizing that a one-size-fits-all approach is not always appropriate, it has become necessary to identify patients responsive to treatments and treat patient populations using a tailored approach. Areas covered include: Development and application of drugs targeted to specific genotypes and populations, as well as advanced diagnostic technologies and significant biomarkers that aid in this. Clinical trials and case studies within personalized therapy and drug development. Screening, prediction and prevention of disease, prediction of adverse events, treatment monitoring, effects of metabolomics and microbiomics on treatment. Secondary population research, genome-wide association studies, disease–gene association studies, personal genome technologies. Ethical and cost–benefit issues, the impact to healthcare and business infrastructure, and regulatory issues.