Risk prediction model for cervical lymph node metastasis of papillary thyroid microcarcinoma: a systematic review and meta-analysis

作者：Xiaoli He, Qiang Zhang, Kaiju Yang, Jian Li, Mingzhu Luo, Ruihan Liu, Xi Yang · 发表于：Frontiers in Endocrinology · 年份：2025 · DOI：10.3389/fendo.2025.1709773 · 被引用次数：2 · 研究领域：Thyroid Cancer Diagnosis and Treatment、Thyroid and Parathyroid Surgery、Head and Neck Cancer Studies

Background: A growing number of risk prediction models for cervical lymph node metastasis (CLNM) in papillary thyroid microcarcinoma (PTMC) have been developed, but their performance and methodological rigor remain unclear. This study systematically reviews these models to evaluate their predictive performance and critically appraise their risk of bias. Methods: We conducted a systematic search of seven databases up to July 29, 2025. The methodological quality of the included studies was assessed using PROBAST. Model performance, measured by the area under the curve (AUC), was pooled using a random-effects meta-analysis. Results: = 89.6%). Subgroup analysis revealed a performance drop from the training set (pooled AUC, 0.812) to the validation set (pooled AUC, 0.774). The PROBAST assessment revealed that 12 of the 15 studies (80%) were critically at a high risk of bias, primarily due to flaws in participant selection. Conclusion: Although existing CLNM prediction models for PTMC show moderate to good discrimination on average, their clinical utility is severely limited by widespread methodological weaknesses and a high risk of bias. The current evidence is not robust enough to recommend any specific model for routine clinical use, and future research must prioritize methodological rigor and independent external validation.