Alaa Al Nofal1,2,3, Michael R Gionfriddo2,4, Asma Javed1, Qusay Haydour5, Juan P Brito6, Larry J Prokop2, Siobhan T Pittock1, Mohammad Hassan Murad2,3,7. 1. Division of Paediatric Endocrinology, Mayo Clinic, Rochester, MN, USA. 2. Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA. 3. Evidence-Based Practice Research Program, Mayo Clinic, Rochester, MN, USA. 4. Mayo Graduate School, Rochester, MN, USA. 5. Internal Medicine Program, Georgia Regents University, Augusta, GA, USA. 6. Division of Diabetes, Endocrinology, Metabolism and Nutrition, Department of Medicine, Mayo Clinic, Rochester, MN, USA. 7. Division of Preventive Medicine, Mayo Clinic, Rochester, MN, USA.
Abstract
INTRODUCTION: Thyroid ultrasound (US) is a widely used tool for evaluating thyroid nodules. Various US features have been suggested as predictors of thyroid cancer in children. OBJECTIVE: To conduct a systematic review and meta-analysis to assess the diagnostic accuracy of different thyroid US features in detecting thyroid cancer in children. METHODS: We searched multiple online databases for cohort studies that enrolled paediatric patients with thyroid nodules (age <21 years) and evaluated the accuracy of 12 relevant ultrasound features. Diagnostic measures were pooled across studies using a random effects model. RESULTS: The search strategy yielded 1199 citations, of which 12 studies met the predefined inclusion criteria (750 nodules). The prevalence of thyroid cancer was 27·2% (40·8% in patients with a history of radiation exposure and 23·2% in patients without a history of exposure to radiation). The most common cancer was papillary thyroid cancer (86·7%). The presence of internal calcifications and enlarged cervical lymph nodes were the US features with the highest likelihood ratio [4·46 (95% CI: 1·87-10·64) and 4·96 (95% CI: 2·01-12·24), respectively] for thyroid cancer. A cystic nodule was the feature with highest likelihood ratio for benign nodules [1·96 (95% CI: 0·87-4·43)]. CONCLUSION: Thyroid US features are not highly accurate predictors of benign or malignant aetiology of thyroid nodules in children. Internal calcification may predict malignancy, and cystic appearance may suggest benign aetiology.
INTRODUCTION: Thyroid ultrasound (US) is a widely used tool for evaluating thyroid nodules. Various US features have been suggested as predictors of thyroid cancer in children. OBJECTIVE: To conduct a systematic review and meta-analysis to assess the diagnostic accuracy of different thyroid US features in detecting thyroid cancer in children. METHODS: We searched multiple online databases for cohort studies that enrolled paediatric patients with thyroid nodules (age <21 years) and evaluated the accuracy of 12 relevant ultrasound features. Diagnostic measures were pooled across studies using a random effects model. RESULTS: The search strategy yielded 1199 citations, of which 12 studies met the predefined inclusion criteria (750 nodules). The prevalence of thyroid cancer was 27·2% (40·8% in patients with a history of radiation exposure and 23·2% in patients without a history of exposure to radiation). The most common cancer was papillary thyroid cancer (86·7%). The presence of internal calcifications and enlarged cervical lymph nodes were the US features with the highest likelihood ratio [4·46 (95% CI: 1·87-10·64) and 4·96 (95% CI: 2·01-12·24), respectively] for thyroid cancer. A cystic nodule was the feature with highest likelihood ratio for benign nodules [1·96 (95% CI: 0·87-4·43)]. CONCLUSION: Thyroid US features are not highly accurate predictors of benign or malignant aetiology of thyroid nodules in children. Internal calcification may predict malignancy, and cystic appearance may suggest benign aetiology.
Authors: Claudia Martinez-Rios; Alan Daneman; Lydia Bajno; Danielle C M van der Kaay; Rahim Moineddin; Jonathan D Wasserman Journal: Pediatr Radiol Date: 2017-10-05
Authors: Naykky Singh Ospina; Juan P Brito; Spyridoula Maraka; Ana E Espinosa de Ycaza; Rene Rodriguez-Gutierrez; Michael R Gionfriddo; Ana Castaneda-Guarderas; Khalid Benkhadra; Alaa Al Nofal; Patricia Erwin; John C Morris; M Regina Castro; Victor M Montori Journal: Endocrine Date: 2016-04-12 Impact factor: 3.633