SynthesisEuropean archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery2026
Predictors of thyroid cancer in paediatric patients with thyroid nodules: A systematic review and meta-analysis.
Synthesis in European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeThyroid nodules are rare in children but have a higher malignancy rate compared to adults. Risk factors and predictors of thyroid cancer in children with thyroid nodules are not well-characterised. This systematic review aims to evaluate risk factors and predictors of malignancy in paediatric thyroid nodules.
methodsPubMed, Embase and Cochrane databases were searched up to 6th April 2026. A quality assessment of the included articles was performed, along with a meta-analysis using the random-effects model.
resultsSixteen studies met the inclusion criteria, comprising 2,634 patients (794 malignant and 1,840 benign cases). Papillary thyroid cancer represented the majority of cancers (84.5%). Variables that were significantly associated with thyroid cancer in the meta-analysis were as follows: previous radiation exposure, odds ratio (OR) 1.96 [95% CI 1.15, 3.34]; palpable lymphadenopathy, OR 7.73 [95% CI 3.03, 19.75]; intranodal calcifications, OR 10.33 [95% CI 3.20, 33.37]; increased vascularity, OR 3.21 [95% CI 1.95, 5.28]; and elevated thyroid stimulating hormone levels, mean difference + 0.92 mIU/L [95% CI 0.50, 1.35]. Quality assessment using the Newcastle-Ottawa Scale, with a majority of studies scoring ≥ 7 stars.
conclusionThe identification of predictors of thyroid cancer in children with thyroid nodules will inform the development and evaluation of models with a view to improving preoperative diagnosis.
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