Diagnostic Performance of Radiomics Modeling in Predicting the Human Papillomavirus Status of Oropharyngeal Cancer: A Systematic Review and Meta-Analysis

放射组学模型在预测口咽癌人乳头瘤病毒状态中的诊断性能:系统评价和荟萃分析

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Abstract

In this review, we sought to assess the diagnostic performance and methodological quality of studies utilizing radiomics for the prediction of human papillomavirus (HPV) status in patients with oropharyngeal squamous cell carcinoma. A comprehensive literature search of PubMed, Ovid, Cochrane, Web of Science, and Scopus from inception until June 7, 2022, was performed to identify eligible studies. Strict inclusion and exclusion criteria were applied to the identified studies. Data collection was performed by two independent reviewers with disagreements resolved by consensus review with a third reviewer. In total, 14 articles were chosen, with a total of 15 radiomics models. Of the included studies, 12 models reported sensitivity, with a mean of 0.778 (standard deviation (SD) = 0.073). Similarly, 12 models reported specificity, with a mean of 0.751 (SD = 0.111). The area under the curve (AUC) was reported by all 15 models, with a mean of 0.814 (SD = 0.081). Finally, accuracy was reported by eight models, with a mean of 0.768 (SD = 0.044). A meta-analysis was performed on eight studies that reported AUCs with confidence intervals (CIs), returning a pooled AUC of 0.764 (95% CI = 0.758 to 0.770). The Radiomics Quality Score (RQS) was applied to each included study as a measure of quality. RQS ranged from -1 to 22, with a mean of 13.4 and an intraclass coefficient of 0.874. Radiomics modeling has shown promise in serving as a diagnostic indicator for HPV status in patients with oropharyngeal cancer. Nevertheless, the quality of research methodologies in this area is a limiting factor for its broader clinical application and highlights the need for enhanced funding to support further research efforts.

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