A Rational Approach to JAK2 Mutation Testing in Patients with Elevated Hemoglobin: Results from the JAK2 Prediction Cohort (JAKPOT) Study.

Chin-Yee, Benjamin; Bhai, Pratibha; Cheong, Ian; Matyashin, Maxim; Hsia, Cyrus C; Kawata, Eri; Ho, Jenny M; Levy, Michael A et al. · J Gen Intern Med · 2023

retrospective_cohort · Level III

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Abstract

Erythrocytosis, most often measured as an increase in hemoglobin and/or hematocrit, is a common reason for referral to internal medicine and hematology clinics and a rational approach is required to effectively identify patients with polycythemia vera while avoiding over-investigation. We aimed to develop and validate a simple rule to predict JAK2 mutation positivity based on complete blood count parameters to aid in the diagnostic approach to patients referred for elevated hemoglobin. Internal medicine and hematology clinics at an academic tertiary referral center. The JAK2 Prediction Cohort (JAKPOT), a large retrospective cohort (n = 901) of patients evaluated by internal medicine and hematology specialists for elevated hemoglobin. JAK2 mutation analysis was performed in all patients and clinical and laboratory variables were collected. Patients were randomly divided into derivation and validation cohorts. A prediction rule was developed using data from the derivation cohort and tested in the validation cohort. The JAKPOT prediction rule included three variables: (i) red blood cell count >6.45×10<sup>12</sup>/L, (ii) platelets >350×10<sup>9</sup>/L, and (iii) neutrophils >6.2×10<sup>9</sup>/L; absence of all criteria was effective at ruling out JAK2-positivity with sensitivities 94.7% and 100%, and negative predictive values of 98.8% and 100% in the derivation and validation cohorts, respectively, with an overall low false negative rate of 0.4%. The rule was validated for three different methods of JAK2 testing. Applying this rule to our entire cohort would have resulted in over 50% fewer tests. In patients with elevated hemoglobin, the use of a simple prediction rule helps to accurately identify patients with a low likelihood of having a JAK2 mutation, potentially limiting costly over-investigation in this common referral population.

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