Abstract

Poorly differentiated thyroid carcinoma (PDTC) is a distinct entity with intermediate prognosis between indolent follicular thyroid cancers and anaplastic carcinoma. The management guidelines are not standardized for these cancers due its low prevalence and limited available literature. Therefore, we did this systematic review with emphasis on current evidence on diagnosis, imaging, molecular markers, and management of these carcinomas. We searched four databases, PubMed, Medline, EMBASE, and Emcare to identify studies published till October 2023. All studies reporting diagnostic tests, imaging, molecular marker expression and management of PDTC were included in the review. The meta-analysis was conducted on expression of molecular markers in these cancers following recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Random-effects meta-analysis was used to calculate pooled estimated prevalence with 95% confidence intervals. Based on the inclusion criteria, 62 articles were selected to be incorporated for the review. Differences in pathological diagnostic criteria of PDTC was noted in literature which was addressed in WHO 2022 diagnostic terminologies with expansion of the definition. Surgical management is uniformly recommended for early stage PDTC. However, literature is divided and anecdotal for recommendations on radioactive iodine (RAI), extent of neck dissection and adjuvant treatment in PDTC. Evidence for Next Generation Sequencing (NGS), novel theragnostic approaches, immunotherapy targets are evolving. Based on the subset analysis for expression of molecular markers, we found the most common markers expressed were TERT (41%), BRAF (28%) and P 53 (25%). Poorly differentiated thyroid carcinomas have a high case fatality rate (up to 31%). Eighty-five % of the patients who succumb to the disease have distant metastasis. Even though under-represented in literature, evidence-based management of these aggressive tumors can help personalize the treatment for optimal outcomes.

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