甲状腺乳头状癌的预后生物标志物:减少过度治疗,提高临床效率,增强患者体验。

IF 2.8 4区 医学 Q3 ONCOLOGY
Technology in Cancer Research & Treatment Pub Date : 2025-01-01 Epub Date: 2025-07-31 DOI:10.1177/15330338251361633
Oliver F Bathe, Cynthia Stretch
{"title":"甲状腺乳头状癌的预后生物标志物:减少过度治疗,提高临床效率,增强患者体验。","authors":"Oliver F Bathe, Cynthia Stretch","doi":"10.1177/15330338251361633","DOIUrl":null,"url":null,"abstract":"<p><p>Papillary thyroid cancer (PTC), the most prevalent form of thyroid malignancy, is generally indolent but poses a recurrence risk of 10%-15%, leading to a clinical paradox: the need to mitigate recurrence while avoiding overtreatment. Current prognostic frameworks, reliant on anatomical and histopathological factors, often result in inefficient treatment pathways, unnecessary surgical interventions, and increased patient burden. The advent of molecular diagnostics presents a paradigm shift in risk stratification. Implementing preoperative molecular tests could transform PTC management by enabling tailored therapeutic strategies, reducing the need for completion thyroidectomies, optimizing the selection of patients for active surveillance, and refining the use of adjuvant therapies such as radioactive iodine. While genomic alterations such as <i>BRAF</i> and <i>TERT</i> mutations have been explored as prognostic markers, their predictive utility remains limited. In contrast, transcriptomic profiling has emerged as a powerful tool for identifying aggressive PTC subtypes with greater precision. Transcriptomic-based prognostic tests, like the novel Thyroid GuidePx<sup>®</sup> classifier, effectively stratify PTCs into distinct molecular subgroups with differing recurrence risks, surpassing traditional clinicopathological models in predictive accuracy. By shifting toward biologically informed decision-making, we can enhance clinical efficiency, minimize patient morbidity, and improve overall healthcare resource utilization.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":"24 ","pages":"15330338251361633"},"PeriodicalIF":2.8000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12317244/pdf/","citationCount":"0","resultStr":"{\"title\":\"Prognostic Biomarkers for Papillary Thyroid Cancer: Reducing Overtreatment, Improving Clinical Efficiency, and Enhancing Patient Experience.\",\"authors\":\"Oliver F Bathe, Cynthia Stretch\",\"doi\":\"10.1177/15330338251361633\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Papillary thyroid cancer (PTC), the most prevalent form of thyroid malignancy, is generally indolent but poses a recurrence risk of 10%-15%, leading to a clinical paradox: the need to mitigate recurrence while avoiding overtreatment. Current prognostic frameworks, reliant on anatomical and histopathological factors, often result in inefficient treatment pathways, unnecessary surgical interventions, and increased patient burden. The advent of molecular diagnostics presents a paradigm shift in risk stratification. Implementing preoperative molecular tests could transform PTC management by enabling tailored therapeutic strategies, reducing the need for completion thyroidectomies, optimizing the selection of patients for active surveillance, and refining the use of adjuvant therapies such as radioactive iodine. While genomic alterations such as <i>BRAF</i> and <i>TERT</i> mutations have been explored as prognostic markers, their predictive utility remains limited. In contrast, transcriptomic profiling has emerged as a powerful tool for identifying aggressive PTC subtypes with greater precision. Transcriptomic-based prognostic tests, like the novel Thyroid GuidePx<sup>®</sup> classifier, effectively stratify PTCs into distinct molecular subgroups with differing recurrence risks, surpassing traditional clinicopathological models in predictive accuracy. By shifting toward biologically informed decision-making, we can enhance clinical efficiency, minimize patient morbidity, and improve overall healthcare resource utilization.</p>\",\"PeriodicalId\":22203,\"journal\":{\"name\":\"Technology in Cancer Research & Treatment\",\"volume\":\"24 \",\"pages\":\"15330338251361633\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12317244/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Technology in Cancer Research & Treatment\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/15330338251361633\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/7/31 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technology in Cancer Research & Treatment","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/15330338251361633","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/31 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

甲状腺乳头状癌(PTC)是最常见的甲状腺恶性肿瘤,通常是惰性的,但有10%-15%的复发风险,这导致了一个临床悖论:需要减轻复发,同时避免过度治疗。目前的预后框架,依赖于解剖和组织病理学因素,往往导致低效的治疗途径,不必要的手术干预,并增加患者负担。分子诊断学的出现呈现了风险分层的范式转变。实施术前分子检测可以通过定制治疗策略、减少完成甲状腺切除术的需要、优化主动监测患者的选择以及改进辅助治疗(如放射性碘)的使用,改变PTC的管理。虽然BRAF和TERT突变等基因组改变已被作为预后标志物进行了探索,但它们的预测效用仍然有限。相比之下,转录组学分析已经成为一种强大的工具,可以更精确地识别侵袭性PTC亚型。基于转录组学的预后测试,如新型甲状腺GuidePx®分类器,有效地将ptc分层为具有不同复发风险的不同分子亚组,在预测准确性方面优于传统的临床病理模型。通过向生物学知情决策转变,我们可以提高临床效率,最大限度地减少患者发病率,并提高整体医疗资源利用率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Prognostic Biomarkers for Papillary Thyroid Cancer: Reducing Overtreatment, Improving Clinical Efficiency, and Enhancing Patient Experience.

Prognostic Biomarkers for Papillary Thyroid Cancer: Reducing Overtreatment, Improving Clinical Efficiency, and Enhancing Patient Experience.

Prognostic Biomarkers for Papillary Thyroid Cancer: Reducing Overtreatment, Improving Clinical Efficiency, and Enhancing Patient Experience.

Prognostic Biomarkers for Papillary Thyroid Cancer: Reducing Overtreatment, Improving Clinical Efficiency, and Enhancing Patient Experience.

Papillary thyroid cancer (PTC), the most prevalent form of thyroid malignancy, is generally indolent but poses a recurrence risk of 10%-15%, leading to a clinical paradox: the need to mitigate recurrence while avoiding overtreatment. Current prognostic frameworks, reliant on anatomical and histopathological factors, often result in inefficient treatment pathways, unnecessary surgical interventions, and increased patient burden. The advent of molecular diagnostics presents a paradigm shift in risk stratification. Implementing preoperative molecular tests could transform PTC management by enabling tailored therapeutic strategies, reducing the need for completion thyroidectomies, optimizing the selection of patients for active surveillance, and refining the use of adjuvant therapies such as radioactive iodine. While genomic alterations such as BRAF and TERT mutations have been explored as prognostic markers, their predictive utility remains limited. In contrast, transcriptomic profiling has emerged as a powerful tool for identifying aggressive PTC subtypes with greater precision. Transcriptomic-based prognostic tests, like the novel Thyroid GuidePx® classifier, effectively stratify PTCs into distinct molecular subgroups with differing recurrence risks, surpassing traditional clinicopathological models in predictive accuracy. By shifting toward biologically informed decision-making, we can enhance clinical efficiency, minimize patient morbidity, and improve overall healthcare resource utilization.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
4.40
自引率
0.00%
发文量
202
审稿时长
2 months
期刊介绍: Technology in Cancer Research & Treatment (TCRT) is a JCR-ranked, broad-spectrum, open access, peer-reviewed publication whose aim is to provide researchers and clinicians with a platform to share and discuss developments in the prevention, diagnosis, treatment, and monitoring of cancer.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信