BACKGROUNDMyeloproliferative neoplasms, such as polycythemia vera, essential thrombocythemia, and myelofibrosis, are chronic hematologic cancers with varied progression rates. The genomic characterization of patients with myeloproliferative neoplasms offers the potential for personalized diagnosis, risk stratification, and treatment. METHODSWe sequenced coding exons from 69 myeloid cancer genes in patients with myeloproliferative neoplasms, comprehensively annotating driver mutations and copynumber changes. We developed a genomic classification for myeloproliferative neoplasms and multistage prognostic models for predicting outcomes in individual patients. Classification and prognostic models were validated in an external cohort. RESULTSA total of 2035 patients were included in the analysis. A total of 33 genes had driver mutations in at least 5 patients, with mutations in JAK2, CALR, or MPL being the sole abnormality in 45% of the patients. The numbers of driver mutations increased with age and advanced disease. Driver mutations, germline polymorphisms, and demographic variables independently predicted whether patients received a diagnosis of essential thrombocythemia as compared with polycythemia vera or a diagnosis of chronic-phase disease as compared with myelofibrosis. We defined eight genomic subgroups that showed distinct clinical phenotypes, including blood counts, risk of leukemic transformation, and event-free survival. Integrating 63 clinical and genomic variables, we created prognostic models capable of generating personally tailored predictions of clinical outcomes in patients with chronic-phase myeloproliferative neoplasms and myelofibrosis. The predicted and observed outcomes correlated well in internal cross-validation of a training cohort and in an independent external cohort. Even within individual categories of existing prognostic schemas, our models substantially improved predictive accuracy. CONCLUSIONSComprehensive genomic characterization identified distinct genetic subgroups and provided a classification of myeloproliferative neoplasms on the basis of causal biologic mechanisms. Integration of genomic data with clinical variables enabled the personalized predictions of patients' outcomes and may support the treatment of patients with myeloproliferative neoplasms. (Funded by the Wellcome Trust and others.

Objective: A decrease over time in thyroid stimulating hormone (TSH) levels when initiating levothyroxine (L-T4) therapy for hypothyroidism has been reported, where treatment most often is initiated with TSH levels below 10 mIU/L. The primary objective of this study was to investigate whether this lower TSH threshold resulted in an increased number of overtreated patients. Design and Method: Retrospective cohort study comprising inhabitants in Copenhagen who had TSH measurements requested by general practitioners which led to a new prescription of L-T4 between 2001 and 2012. Over- and undertreatment were defined as TSH < 0.1 mIU/L or above 10 mIU/mL, respectively, in three consecutive measurements. Data were analysed by Aalen-Johansen estimators and Cox proportional hazards models. Results: In total, 14,533 initiations of L-T4 in the study. The cumulative risk of being over- or undertreated, was 4.7% and 7.4% after 10 years. The hazard of overtreatment was higher among women, younger adults and with lower initial TSH levels. The hazard of overtreatment decreased over the time period from 2001 to 2012. Among overtreated individuals, the chance of returning to a normal TSH was about 55% after 10 years. In 18% of the cases, L-T4 therapy was initiated on TSH levels less than 5 mIU/L. Conclusion: Although a still decreasing threshold for initiating L-T4 therapy is known, the risk of overtreatment (and undertreatment) was low and lessened in the period 2001 – 2012 among Danish primary care patients. Nevertheless, as many as 18% were started on L-T4 with normal TSH levels.

Objective: The incidence of hypothyroidism is not expected to differ by socioeconomic factors. However, the decision to test and initiate treatment may differ. We aimed to examine whether educational level influences the probability of thyroid stimulation hormone (TSH)-measurement and initiation of levothyroxine treatment. Design: Citizens in the greater Copenhagen Area during 2001-2015 were included.Individual-level data on educational level, diagnoses, GP-contact, TSH-measurement and medication were derived from administrative and healthcare registers. The relative risks (RR) between educational levels of annual TSH-measurement and treatment initiation following a TSH-measurement were analysed in Poisson regression models with generalized estimation equations.Results: A TSH-measurement was performed in 19% of 9,390,052 person years. The probability of TSH-measurement was higher with short (RR 1.16 [95% CI 1.15-1.16]) and medium (RR 1.11 [95% CI 1.06-1.12]) compared with long education.

No abstract