Tessler Idit, Leshno Moshe, Feinmesser Gilad, Alon Eran E, Avior Galit
Department of Otolaryngology Head and Neck Surgery, Sheba Medical Center, Ramat Gan 52621, Israel.
Faculty of Medicine, Tel Aviv University, Tel Aviv 6423906, Israel.
Cancers (Basel). 2023 Jan 27;15(3):786. doi: 10.3390/cancers15030786.
Molecular testing for thyroid nodules has been rapidly developed in recent years, aiming to predict the presence of malignancy and aggressive features. While commonly utilized to predict malignancy, its role in guiding the management approach is still developing. The high cost of genetic tests and long-term sequences of thyroid cancer is limiting to real-life studies. : To evaluate the cost effectiveness of molecular testing for low-risk differentiated thyroid cancer (lrDTC). : We developed a Markovian decision tree model of a simulated lrDTC cohort, comparing two management strategies: -patients are stratified into three risk groups for distant metastasis by the identified molecular markers: low-, intermediate- and high-risk molecular profile; followed by management accordingly: patients with low-risk will undergo hemithyroidectomy (HT), patients with intermediate-risk will undergo total thyroidectomy (TT), and high-risk patients will undergo TT with central neck dissection; -all patients will undergo HT according to the ATA recommendations for lrDTC. Outcomes were measured as quality-adjusted life years (QALYs) and costs of each strategy. GT was found as cost effective, leading to a gain of 1.7 QALYs with an additional cost of $327 per patient compared to wGT strategy. This yielded an incremental cost-effectiveness ratio of $190 per QALY. Sensitivity analysis demonstrated robust results across the variables' ranges. The most impactful variable was the benefit from performing TT rather than HT for intermediate to high-risk patients. Our model found that molecular testing for lrDTC is cost-effective, allowing tailored management according to the patient's personal risk level reflected in the genetic profile, hence improving outcomes.
近年来，甲状腺结节的分子检测发展迅速，旨在预测恶性肿瘤的存在和侵袭性特征。虽然它通常用于预测恶性肿瘤，但其在指导治疗方法方面的作用仍在发展中。基因检测的高成本和甲状腺癌的长期病程限制了实际研究。：评估低风险分化型甲状腺癌（lrDTC）分子检测的成本效益。：我们建立了一个模拟lrDTC队列的马尔可夫决策树模型，比较两种管理策略：- 通过识别的分子标记将患者分为远处转移的三个风险组：低、中、高风险分子特征；然后相应地进行管理：低风险患者将接受甲状腺半切术（HT），中风险患者将接受甲状腺全切术（TT），高风险患者将接受TT并进行中央区淋巴结清扫术；- 所有患者将根据美国甲状腺协会（ATA）对lrDTC的建议接受HT。结果以质量调整生命年（QALYs）和每种策略的成本来衡量。发现基因检测具有成本效益，与广泛基因检测（wGT）策略相比，每位患者额外花费327美元，可增加1.7个QALYs。这产生了每QALY 190美元的增量成本效益比。敏感性分析表明，在变量范围内结果稳健。最有影响的变量是中高风险患者进行TT而非HT的获益。我们的模型发现，lrDTC的分子检测具有成本效益，能够根据基因谱中反映的患者个人风险水平进行个性化管理，从而改善治疗结果。
