Clinical, Pathological, and Molecular Characteristics Correlating to the Occurrence of Radioiodine Refractory Differentiated Thyroid Carcinoma: A Systematic Review and Meta-Analysis.

Recently, radioiodine refractory differentiated thyroid cancer (RR-DTC) has received increasing attention due to its poor prognosis. The roles of clinical, pathological, and molecular features in the development of RR-DTC remain controversial and require additional investigation. This study aimed to evaluate the association between these risk factors and the occurrence of RR-DTC. We performed a systematic search for relevant literature following the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) in PubMed, EMBASE, Medline, SCOPUS, and Web of Science up to the July 15, 2020. Observational studies that investigated the risk factors for RR-DTC were included. Fixed- or random-effects models were used to calculate pooled odds ratios (ORs) or mean differences (MD) with corresponding 95% confidence intervals. We included 13 eligible studies incorporating 1,431 cases, of which 603 were patients with RR-DTC. The pooled analysis indicated that four parameters significantly increased the risk of RR-DTC: extrathyroidal extension (ETE) (OR: 2.28, 95% CI: 1.43-3.64, = 14%), mutation (OR: 3.60, 95% CI: 1.74-7.46, = 69%), promoter mutation (OR: 9.84, 95% CI: 3.60-26.89, = 61%) and high-risk histological subtype (OR: 1.94, 95% CI: 1.15-3.27, = 15%), including tall cell variant papillary thyroid carcinoma (PTC), sclerosing diffuse PTC, hobnail variant PTC, follicular thyroid carcinoma (FTC) (including Hürthle cell), and poorly differentiated thyroid carcinoma (PDTC). However, there was no statistical significance regarding sex, age, tumor size, multifocality, or lateral lymph node metastasis. Subgroup and sensitivity analyses were conducted to further confirm the robustness of the results. Histological subtype, ETE, mutation, and promoter mutation could be considered clinicopathological factors and biomarkers. They could assist in risk stratification, prognostic prediction, and individual therapy options for RR-DTC.