Division of Haematology, Alberta Public Laboratories, South Zone & Department of Pathology & Laboratory Medicine, University of Calgary, Calgary, Alberta, Canada
Department of Clinical Biochemistry and the Copenhagen General Population Study, Copenhagen University Hospital, Herlev and Gentofte Hospital, Herlev, Denmark.
J Clin Pathol. 2019 Feb;72(2):172-176. doi: 10.1136/jclinpath-2018-205527. Epub 2018 Dec 4.
The JAK2 V617F mutation is highly recurrent in many of the myeloproliferative neoplasms, a molecular variant that can be easily detected using sensitive and minimally invasive techniques. Given the ease of JAK2 V617F testing, this test may be improperly requested for the purposes of patient 'screening' and to optimise laboratory resource utilisation, it behooves clinicians and laboratorians to perform JAK2 V617F testing only when most appropriate.
To assist with the screening of patients being considered for JAK2 V617F testing, we developed a clinical decision rule, "JAK2-tree", which can be easily applied to basic CBC parameters (haemoglobin, platelet and white blood cell counts).
We tested JAK2-tree on two independent datasets, one an unselected population-based sample (the Copenhagen General Population Study) and the other an historical clinical laboratory referral set, with sensitivities for JAK2 V617F detection of 91% and 94%, respectively. As applied to the historical laboratory referral dataset, moreover, the JAK2-tree algorithm would have reduced JAK2 V617F testing volume over the period of evaluation by 15%.
Our work supports a simple decision-tree-based screening approach to optimize the selection of patients most appropriate for JAK2 V617F testing.
JAK2 V617F 突变在许多骨髓增殖性肿瘤中高度复发，这是一种可以使用敏感和微创技术轻松检测到的分子变异。鉴于 JAK2 V617F 检测的简便性，该检测可能被不适当地用于患者“筛查”目的，并优化实验室资源利用，因此临床医生和实验室人员在最合适的时候进行 JAK2 V617F 检测是很有必要的。
为了协助对考虑进行 JAK2 V617F 检测的患者进行筛查，我们开发了一个临床决策规则，即“JAK2 树”，它可以轻松应用于基本的 CBC 参数（血红蛋白、血小板和白细胞计数）。
我们在两个独立的数据集上测试了 JAK2 树，一个是未选择的基于人群的样本（哥本哈根一般人群研究），另一个是历史临床实验室转诊集，JAK2 V617F 检测的敏感性分别为 91%和 94%。此外，应用于历史实验室转诊数据集，JAK2 树算法将在评估期间减少 15%的 JAK2 V617F 检测量。
我们的工作支持一种简单的基于决策树的筛选方法，以优化选择最适合 JAK2 V617F 检测的患者。
