A meta-analysis of based radiomics for predicting lymph node metastasis in patients with biliary tract cancers

Autor: Yuhu Ma, Yanyan Lin, Jiyuan Lu, Yulong He, Qianling Shi, Haoran Liu, Jianlong Li, Baoping Zhang, Jinduo Zhang, Yong Zhang, Ping Yue, Wenbo Meng, Xun Li
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Frontiers in Surgery, Vol 9 (2023)
Druh dokumentu: article
ISSN: 2296-875X
DOI: 10.3389/fsurg.2022.1045295
Popis: BackgroundTo assess the predictive value of radiomics for preoperative lymph node metastasis (LMN) in patients with biliary tract cancers (BTCs).MethodsPubMed, Embase, Web of Science, Cochrane Library databases, and four Chinese databases [VIP, CNKI, Wanfang, and China Biomedical Literature Database (CBM)] were searched to identify relevant studies published up to February 10, 2022. Two authors independently screened all publications for eligibility. We included studies that used histopathology as a gold standard and radiomics to evaluate the diagnostic efficacy of LNM in BTCs patients. The quality of the literature was evaluated using the Radiomics Quality Score (RQS) and the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). The diagnostic odds ratio (DOR), sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and area under the receiver operating characteristic curve (AUC) were calculated to assess the predictive validity of radiomics for lymph node status in patients with BTCs. Spearman correlation coefficients were calculated, and Meta-regression and subgroup analyses were performed to assess the causes of heterogeneity.ResultsSeven studies were included, with 977 patients. The pooled sensitivity, specificity and AUC were 83% [95% confidence interval (CI): 77%, 88%], 78% (95% CI: 71, 84) and 0.88 (95% CI: 0.85, 0.90), respectively. The substantive heterogeneity was observed among the included studies (I2 = 80%, 95%CI: 58,100). There was no threshold effect seen. Meta-regression showed that tumor site contributed to the heterogeneity of specificity analysis (P
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