The 100 top-cited meta-analyses of diagnostic accuracy in radiology journals: a bibliometric analysis

Yaxley, Kaspar L.; To, Minh‐Son

doi:10.1186/s13244-020-00936-w

Cited by 8 publications

(4 citation statements)

References 31 publications

(38 reference statements)

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“…The number of citations has still been used as a reliable objective marker of the quality and impact of a paper; it is variable in different subdisciplines and depends on the size of the field of study. In our data, the number of citations times of the top 100 cited original articles and reviews is 131 to 1,144, with a total cited of 25,723; it is lower than some hot research fields such as lncRNAs (15) and neuro-interventional (16) but higher than that of a meta-analysis of radiology (17), suggesting that PPGL research worldwide was in a tepid period. The PPGL research field was still not prominent enough in the world.…”

Section: Discussionmentioning

confidence: 52%

The top 100 most-cited papers in pheochromocytomas and paragangliomas: A bibliometric study

Duan

Qi²,

Li³

et al. 2022

Front. Oncol.

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BackgroundThe purpose of this study was to define and analyze the characteristics of the top 100 most-cited articles and reviews on the topic of pheochromocytomas and paragangliomas (PPGLs) by using bibliometric methods.MethodsWe explored the Web of Science Core Collection database to gather the 100 top-cited original articles and reviews of PPGL from 1985 to 20 December 2020. We conducted a bibliometric study to identify the most influential journals, authors, countries, and institutions in the PPGL field.ResultsThe 100 top-cited papers were cited a total number of 25,723 times, ranging from 131 to 1,144 (mean, 257.23 ± 173.64). All of these 100 top-cited papers were published between 1999 and 2017, and the number of top-cited papers published before 2008 (1999–2008) was significantly higher than that after 2008 (2009–2017) (p = 0.043). The journal with the highest number of published papers is the Journal of Clinical Endocrinology & Metabolism (n = 23). The United States was the most productive country in this topic, which published about half of these publications (n = 51). The National Institutes of Health (NIH) had the largest number of publications (n = 17). Genes or genetics is still the hottest topic in the field of PPGLs.ConclusionsWe defined and analyzed the top 100 most-cited papers in the field of PPGLs by gathering detailed information. These data provided insights into the most influential studies related to PPGL. We hoped to inspire researchers and readers in this field to improve their understanding of PPGL research trends and provide ideas for future research from unique perspectives.

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Section: Discussionmentioning

confidence: 52%

The top 100 most-cited papers in pheochromocytomas and paragangliomas: A bibliometric study

Duan

Qi²,

Li³

et al. 2022

Front. Oncol.

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“…This study had several limitations. The search strategy was specific to the 40 highest impact medical imaging journals . Therefore, relevant imaging DTA meta-analyses published in other journals may have not been captured, resulting in our cohort of 242 included studies not being fully representative of work published in nonmedical imaging or lower impact factor journals.…”

Section: Discussionmentioning

confidence: 99%

Heterogeneity in Systematic Reviews of Medical Imaging Diagnostic Test Accuracy Studies

White,

Phua,

et al. 2024

JAMA Netw Open

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ImportanceSystematic reviews of medical imaging diagnostic test accuracy (DTA) studies are affected by between-study heterogeneity due to a range of factors. Failure to appropriately assess the extent and causes of heterogeneity compromises the interpretability of systematic review findings.ObjectiveTo assess how heterogeneity has been examined in medical imaging DTA studies.Evidence ReviewThe PubMed database was searched for systematic reviews of medical imaging DTA studies that performed a meta-analysis. The search was limited to the 40 journals with highest impact factor in the radiology, nuclear medicine, and medical imaging category in the InCites Journal Citation Reports of 2021 to reach a sample size of 200 to 300 included studies. Descriptive analysis was performed to characterize the imaging modality, target condition, type of meta-analysis model used, strategies for evaluating heterogeneity, and sources of heterogeneity identified. Multivariable logistic regression was performed to assess whether any factors were associated with at least 1 source of heterogeneity being identified in the included meta-analyses. Methodological quality evaluation was not performed. Data analysis occurred from October to December 2022.FindingsA total of 242 meta-analyses involving a median (range) of 987 (119-441 510) patients across a diverse range of disease categories and imaging modalities were included. The extent of heterogeneity was adequately described (ie, whether it was absent, low, moderate, or high) in 220 studies (91%) and was most commonly assessed using the I2 statistic (185 studies [76%]) and forest plots (181 studies [75%]). Heterogeneity was rated as moderate to high in 191 studies (79%). Of all included meta-analyses, 122 (50%) performed subgroup analysis and 87 (36%) performed meta-regression. Of the 242 studies assessed, 189 (78%) included 10 or more primary studies. Of these 189 studies, 60 (32%) did not perform meta-regression or subgroup analysis. Reasons for being unable to investigate sources of heterogeneity included inadequate reporting of primary study characteristics and a low number of included primary studies. Use of meta-regression was associated with identification of at least 1 source of variability (odds ratio, 1.90; 95% CI, 1.11-3.23; P = .02).Conclusions and RelevanceIn this systematic review of assessment of heterogeneity in medical imaging DTA meta-analyses, most meta-analyses were impacted by a moderate to high level of heterogeneity, presenting interpretive challenges. These findings suggest that, despite the development and availability of more rigorous statistical models, heterogeneity appeared to be incomplete, inconsistently evaluated, or methodologically questionable in many cases, which lessened the interpretability of the analyses performed; comprehensive heterogeneity assessment should be addressed at the author level by improving personal familiarity with appropriate statistical methodology for assessing heterogeneity and involving biostatisticians and epidemiologists in study design, as well as at the editorial level, by mandating adherence to methodologic standards in primary DTA studies and DTA meta-analyses.

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“…Among the imaging modalities used in the studies, CT, PET-CT and radiomics were predominant. The increasing use of PET-CT for cancer staging, technological advances in PET-CT imaging and the discovery of new radiotracers, and clinical use of hybrid and molecular imaging modalities reflect the growing interest in PET-CT (25)(26)(27)(28). In Liang et al's (24) literature analysis, radiomics were reported to be promising for lung cancer.…”

Section: Discussionmentioning

confidence: 99%

Bibliometric analysis of the 50 most cited articles on artificial intelligence for lung cancer imaging

Serindere

2023

Journal of Health Sciences and Medicine

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Aim: The use of machine learning has now become widespread in lung cancer. However, the research trend is still unclear. This study aimed to analyze the most influential publications on artificial intelligence (AI) for lung cancer. Material and Method: A comprehensive PubMed and SCImago Journal and Country Rank (SJR) search was performed. The 50 most cited articles were recorded according to the citation numbers, the country and institute of articles, the name and metrics of the publishing journal, the year of publication, and the content of the articles. Results: The citation numbers ranged from 24 to 628. Annual citations per article was between 1.47 and 104.6. The USA was the country with the most publications (n=22) followed by The Netherlands (n=9) and Peoples R China (n=5). The journal and institution that highly contributed to the 50 most cited articles were Radiology (n=5) and Harvard Medical School (n=5), respectively. Conclusion: The importance of deep learning and AI in lung cancer imaging is increasing day by day. In this study, a detailed bibliometric analysis of the literature on AI in lung cancer imaging was performed. In addition, this bibliometric analysis informs researchers about current influential papers in this field, the characteristics of these studies, and potential future trends in the rapidly evolving field of AI in lung cancer screening.

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The 100 top-cited meta-analyses of diagnostic accuracy in radiology journals: a bibliometric analysis

Cited by 8 publications

References 31 publications

The top 100 most-cited papers in pheochromocytomas and paragangliomas: A bibliometric study

The top 100 most-cited papers in pheochromocytomas and paragangliomas: A bibliometric study

Heterogeneity in Systematic Reviews of Medical Imaging Diagnostic Test Accuracy Studies

Bibliometric analysis of the 50 most cited articles on artificial intelligence for lung cancer imaging

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