Evidence map›Paper›PMID 41862948›Full record

ArticleThyroid research2026

Assessing the clinical diagnostic utility of multiplex ddPCR assays in thyroid nodules.

Xiubo Li, Chunhui Shen, Xiang Peng, Qianfeng Xu, Jun Zhang, Minghui He, Minyi Kong, Zhao Lin, Jingyan Luo, Yan Wang

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Article in Thyroid research, 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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5 · Who and what money

Authors and funding

10 authors.

Xiubo Li *Department of Pathology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China.
Chunhui Shen *Department of Thoracic and Cardiovascular Surgical, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Xiang PengDepartment of Pathology, Guangdong Provincial People's Hospital, Zhuhai Hospital (Jinwan Central Hospital of Zhuhai), Zhuhai, China.
Qianfeng XuDepartment of Urology, Guangzhou First People's Hospital, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, China.
Jun ZhangDepartment of Liver, Gallbladder and Pancreatic Surgery, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, China.
Minghui HeForevergen Biosciences Center, Guangzhou, China.
Minyi KongGuangdong Forevergen Medical Technology Co., Ltd., Foshan, China.
Zhao LinForevergen Biosciences Center, Guangzhou, China.
Jingyan LuoForevergen Biosciences Center, Guangzhou, China. ljy@forevergen.cn.
Yan WangCenter for Medical Research on Innovation and Translation, Institute of Clinical Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China. yan_wang522@163.com.

Funding

the Guangzhou Science and Technology Program 2023A03J0952the Young Scientists Fund of the National Natural Science Foundation of China 82403736
6 · The paper itself

Abstract

backgroundUltrasound-guided fine-needle aspiration cytology (FNAC) is the standard method for evaluating thyroid nodules, but 20–40% of specimens are still cytologically indeterminate (Bethesda III–IV), leading to repeat biopsies or diagnostic lobectomy. We hypothesized that a multiplex droplet digital PCR (ddPCR) assay covering key thyroid-cancer driver mutations would increase the pre-operative diagnostic yield.

methodsA six-gene ddPCR panel was developed to detect BRAF p.V600E, TERT promoter mutations c.-124 C > T (C228T) and c.-146 C > T (C250T), PIK3CA p.H1047R/L, and all clinically relevant variants in NRAS, HRAS, and KRAS at codons 12, 13, and 61. Analytical performance was established using plasmid controls. The assays were subsequently applied to 210 prospectively collected fine-needle aspiration (FNA) specimens from 201 patients, with parallel ARMS-PCR testing for BRAF p.V600E and histopathological confirmation available for 49 surgically excised nodules.

resultsThe six-gene ddPCR panel demonstrated 100% analytical specificity and a limit of detection of 0.1% variant allele frequency (VAF). In clinical samples, 103 of 210 nodules (49%) harbored at least one mutation, with BRAF p.V600E being the most prevalent alteration (81/103, 78.6%). ddPCR identified five low-abundance BRAF p.V600E mutations (VAF 0.37–2.96%) that were missed by ARMS-PCR, one of which was confirmed as papillary thyroid carcinoma on postoperative pathology. Mutation prevalence increased progressively across Bethesda categories, ranging from 33% in Bethesda I to 89% in Bethesda VI. Compared with surgical pathology, the combination of the six-gene ddPCR panel and FNAC achieved 100% sensitivity, 71% specificity, and 96% diagnostic accuracy, significantly outperforming FNAC alone or FNAC combined with ARMS-PCR (P < 0.05).

conclusionsThis study developed a six-gene mutation detection panel composed of four multiplex droplet digital PCR (ddPCR) assays for thyroid nodule analysis. Integration with cytology substantially reduces indeterminate diagnoses and may guide personalized management, including the avoidance of unnecessary surgery.

Identifiers

PMID41862948
PMCPMC13005521

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