Association of ferritin and transferrin saturation with all-cause mortality, and the effect of concurrent inflammation: a danish cohort study.

The association between ferritin and transferrin saturation (TS), respectively, and all-cause mortality is unclear. Furthermore, the influence of concurrent inflammation has not been sufficiently elucidated. We investigated these associations and the effect of concurrently elevated C-reactive protein (CRP), and accordingly report the levels associated with lowest all-cause mortality for females and males with and without inflammation.Blood test results from 161,921 individuals were included. Statistical analyses were performed in sex-stratified subpopulations, with ferritin or TS level as continuous exposure variables, and were adjusted for age, co-morbidity and inflammation status using CRP. An interaction was used to investigate whether the effect of ferritin or TS on all-cause mortality was modified by inflammation status (CRP ≥ 10 mg/L or CRP < 10 mg/L). Low and high ferritin and TS levels were respectively associated with increased all-cause mortality in females and in males. These associations persisted with concurrent CRP ≥ 10 mg/L. The ferritin level associated with lowest mortality was 60 µg/L for females and 125 µg/L for males with CRP < 10 mg/L. It was 52 µg/L for females and 118 µg/L for males with CRP ≥ 10 mg/L. The TS level associated with lowest mortality was 33.9% for females and 32.3% for males with CRP < 10 mg/L. It was 28.7% for females and 30.6% for males with CRP ≥ 10 mg/L.Our findings can nuance clinical interpretation and further aid in defining recommended ranges for ferritin and TS.

Classification and Personalized Prognosis in Myeloproliferative Neoplasms.

BACKGROUND: Myeloproliferative 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. METHODS: We sequenced coding exons from 69 myeloid cancer genes in patients with myeloproliferative neoplasms, comprehensively annotating driver mutations and copy-number 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. RESULTS: A 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. CONCLUSIONS: Comprehensive 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.).

Tobacco use in the Myeloproliferative neoplasms: symptom burden, patient opinions, and care.

BACKGROUND: Patients with Philadelphia-negative Myeloproliferative Neoplasms (MPN) suffer from numerous symptoms and decreased quality of life. Smoking is associated with an increased symptom burden in several malignancies. The aim of this study was to analyze the association between smoking and MPN-related symptom burden and explore MPN patients' opinions on smoking. METHODS: A total of 435 patients with MPN participated in a cross-sectional internet-based survey developed by the Mayo Clinic and the Myeloproliferative Neoplasm Quality of Life Group. Patients reported their demographics, disease characteristics, tobacco use, and opinions on tobacco use. In addition, MPN-related symptoms were reported via the validated 10-item version of the Myeloproliferative Neoplasms Symptom Assessment Form. RESULTS: Current/former smokers reported worse fatigue (mean severity 5.6 vs. 5.0, p = 0.02) and inactivity (mean severity 4.0 vs. 3.4, p = 0.03) than never smokers. Moreover, current/former smokers more frequently experienced early satiety (68.5% vs. 58.3%, p = 0.03), inactivity (79.9% vs. 71.1%, p = 0.04), and concentration difficulties (82.1% vs. 73.1%, p = 0.04). Although not significant, a higher total symptom burden was observed for current/former smokers (mean 30.4 vs. 27.0, p = 0.07). Accordingly, overall quality of life was significantly better among never smokers than current/former smokers (mean 3.5 vs. 3.9, p = 0.03). Only 43.2% of the current/former smokers reported having discussed tobacco use with their physician, and 17.5% did not believe smoking increased the risk of thrombosis. CONCLUSION: The current study suggests that smoking may be associated with increased prevalence and severity of MPN symptoms and underscores the need to enhance patient education and address tobacco use in the care of MPN patients.

Drug-drug interaction between warfarin and statins: A Danish cohort study.

Initiation of statin treatment is suggested to increase the international normalised ratio (INR) among warfarin users. However, available data is limited and conflicting. We conducted a register-based cohort study to evaluate the drug-drug interaction between warfarin and statins. By linking data on INR measurements and filled prescriptions, we identified warfarin users 2000-2015 initiating simvastatin (n = 1363), atorvastatin (n = 165) or rosuvastatin (n = 23). Simvastatin initiation led to an increase in mean INR from 2.40 to 2.71, with INRs peaking after 4 weeks, corresponding to a mean change of 0.32 (95%CI 0.25-0.38). High-dose and low-dose simvastatin led to comparable changes (mean change 0.33 vs 0.29). Initiation of atorvastatin and rosuvastatin lead to INR increases of 0.27 (95%CI 0.12-0.42) and 0.30 (95%CI -0.09-0.69). In conclusion, initiation of simvastatin, atorvastatin or rosuvastatin among warfarin users led to a minor increase in INR. The magnitude of this change is for most patients likely of limited clinical relevance.

Decreased plasma lipid levels in a statin-free Danish primary health care cohort between 2001 and 2018.

BACKGROUND: Lipid levels in blood have decreased considerably during the past decades in the general population partly due to use of statins. This study aims to investigate the trends in lipid levels between 2001 and 2018 in a statin-free population from primary health care, overall and by sex and age. METHODS: In a cohort of 634,119 patients from general practice with no diagnoses or medical treatments that affected lipid levels of total cholesterol (TC; n = 1,574,339) between 2001 and 2018 were identified. Similarly, measurements of low-density lipoprotein cholesterol (LDL-C; n = 1,302,440), high-density lipoprotein cholesterol (HDL-C; n = 1,417,857) and triglycerides (TG; n = 1,329,477) were identified. RESULTS: Mean TC decreased from 5.64 mmol/L (95% CI: 5.63-5.65) in 2001 to 5.17 mmol/L (95% CI: 5.16-5.17) in 2018 while LDL-C decreased from 3.67 mmol/L (95% CI: 3.66-3.68) to 3.04 mmol/L (95% CI: 3.03-3.04). Women aged 70-74 years experienced the largest decreases in TC levels corresponding to a decrease of 0.7 mmol/L. The decrease in LDL-C levels was most pronounced in men ≥85 years with a decrease of 0.9 mmol/L. For both genders, TC and LDL-C levels increased with advancing age until around age 50. After menopause the women had higher TC and LDL-C levels than the men. The median (geometric mean) TG level decreased by 0.4 mmol/L from 2001 to 2008, after which it increased slightly by 0.1 mmol/L until 2018. During life the TG levels of the men were markedly higher than the women's until around age 65-70. HDL-C levels showed no trend during the study period. CONCLUSIONS: The levels of TC and LDL-C decreased considerably in a statin-free population from primary health care from 2001 to 2018. These decreases were most pronounced in the elderly population and this trend is not decelerating. For TG, levels have started to increase, after an initial decrease.

The impact of cancer on diabetes outcomes.

BACKGROUND: Survival from many cancer types is steadily increasing, and as a result, a growing number of cancer patients will live with other chronic diseases, of which diabetes is one of the most prevalent. This study aims to describe the impact of cancer on health outcomes in patients with type 2 diabetes and to compare the effectiveness of a multifactorial intervention in diabetes patients with and without cancer. METHODS: The randomized controlled trial Diabetes Care in General Practice (DCGP) included 1381 patients newly diagnosed with type 2 diabetes. Patients were randomized to either six years of structured personal diabetes care or routine care. In a post hoc analysis, we followed patients for 19 years in Danish national registries for the occurrence of diabetes-related outcomes. We used Cox regression models to estimate hazard ratios for outcomes. RESULTS: At diagnosis 48 patients had cancer, and 243 patients were diagnosed with cancer during follow up. Patients with diabetes and cancer had excess all-cause mortality (HR 3.33; 95%CI 2.72-4.06), as well as an increased incidence of myocardial infarction (HR 1.76; 95%CI 1.29-2.39) and any diabetes-related outcome (HR 1.36; 95%CI 1.07-1.71). The intervention reduced the risk of both these endpoints in patients without cancer. Furthermore, there was no statistically significant difference in the effectiveness of the intervention among patients with and without cancer. CONCLUSIONS: Diabetes patients with cancer had an increased risk of myocardial infarction and any diabetes-related outcome. The observed positive effect of structured personal diabetes care on clinical outcomes did not differ between patients with and without cancer. Attention to and prevention of diabetes complications in patients with both type 2 diabetes and cancer is warranted. TRIAL REGISTRATION: ClinicalTrials.gov NCT01074762 (February 24, 2010).

Brain Natriuretic Peptide in Plasma as Predictor of All-Cause Mortality in a Large Danish Primary Health Care Population Suspected of Heart Failure.

BACKGROUND: Measurement of B-type natriuretic peptide (BNP) in plasma may have its greatest potential in primary care, as general practitioners need to rapidly identify patients who warrant further medical review. The aim of the present study was to examine the prognostic information of BNP measurement on all-cause mortality in a large Danish primary care cohort. METHODS: This study covered a cohort of Danish primary care patients (n = 61665) with a median follow-up period of 4.36 years (interquartile range, 2.29-6.62 years). BNP was measured in plasma using the ADVIA Centaur/CentaurXP platform. The association of BNP with mortality was assessed with a hazard ratio for all-cause mortality from a multivariable Cox proportional hazards model. RESULTS: Kaplan-Meier curves showed decreasing survival probability with increasing BNP (P < 0.001). Each doubling of BNP increased mortality by 32.3% (95% CI, 30.8-33.8) when adjusted for sex and age, and by 25.3% (95% CI, 23.8-26.8) when further adjusted for Charlson comorbidity index, hemoglobin, estimated glomerular filtration rate, glycohemoglobin, and thyroid-stimulating hormone. Also, in a subcohort (n = 10824) without biochemical signs of severe kidney failure, anemia, polycythemia, hypothyroidism or hyperthyroidism, or dysregulated diabetes, each doubling of BNP increased mortality by 28.6% (95% CI, 22.8-34.7). CONCLUSIONS: Our results show that even in a primary care population, BNP measurements contain prognostic information regarding all-cause mortality.

Association of the blood eosinophil count with hematological malignancies and mortality.

Blood eosinophilia (≥0.5 × 10(9) /l) may be an early sign of hematological malignancy. We investigated associations between levels of blood eosinophils and risks of hematological malignancies and mortality in order to provide clinically derived cut-offs for referral to specialist hematology care. From the Copenhagen Primary Care Differential Count (CopDiff) Database, we identified 356,196 individuals with at least one differential cell count encompassing the eosinophil count during 2000-2007 and matched these laboratory data with Danish nationwide health registers. We used multivariable logistic regression to calculate odds ratios (ORs) for the 4-year incidences of hematological malignancies and mortality between the eosinophil counts and a reference count of 0.16 × 10(9) /l which was the median eosinophil count in our data. Risks of hematological malignancies and mortality increased above the median eosinophil count. At the 99th percentile, corresponding to an eosinophil count of 0.75 × 10(9) /l, risks of hematological malignancies were increased more than twofold with OR (95% C.I.) of 2.39 (1.91-2.99). Interestingly, risks reached a plateau around an eosinophil count of 1.0 × 10(9) /l. Risks also increased when the eosinophil count approached zero. Here, counts associated relatively more with acute myeloid leukemia and myelodysplastic syndromes whereas counts above 0.16 × 10(9) /l associated more with myeloproliferative neoplasms. Eosinophil counts associate with hematological malignancies and mortality even below the definition of eosinophilia. The observed plateau of risks around 1.0 × 10(9) /l is important for physicians encountering patients with eosinophilia since even mild-to-moderate eosinophilia according to traditional definitions confers maximally increased risks of subsequent/subclinical hematological malignancy.

A phase II study of vorinostat (MK-0683) in patients with polycythaemia vera and essential thrombocythaemia.

Inhibition of histone deacetylases may be an important target in patients with myeloproliferative neoplasms. This investigator-initiated, non-randomized, open-label phase II multi-centre study included 63 patients (19 essential thrombocythaemia, 44 polycythaemia vera) from 15 centres. The primary objective was to evaluate if vorinostat was followed by a decline in clonal myeloproliferation as defined by European Leukaemia Net. Thirty patients (48%) completed the intervention period (24 weeks of therapy). An intention-to-treat response rate of 35% was identified. Pruritus was resolved [19% to 0% (P = 0·06)] and the prevalence of splenomegaly was lowered from 50% to 27% (P = 0·03). Sixty-five per cent of the patients experienced a decrease in JAK2 V617F allele burden (P = 0·006). Thirty-three patients (52% of patients) discontinued study drug before end of intervention due to adverse events (28 patients) or lack of response (5 patients). In conclusion, vorinostat showed effectiveness by normalizing elevated leucocyte and platelet counts, resolving pruritus and significantly reducing splenomegaly. However, vorinostat was associated with significant side effects resulting in a high discontinuation rate. A lower dose of vorinostat in combination with conventional and/or novel targeted therapies may be warranted in future studies.

Machine learning can identify newly diagnosed patients with CLL at high risk of infection.

Infections have become the major cause of morbidity and mortality among patients with chronic lymphocytic leukemia (CLL) due to immune dysfunction and cytotoxic CLL treatment. Yet, predictive models for infection are missing. In this work, we develop the CLL Treatment-Infection Model (CLL-TIM) that identifies patients at risk of infection or CLL treatment within 2 years of diagnosis as validated on both internal and external cohorts. CLL-TIM is an ensemble algorithm composed of 28 machine learning algorithms based on data from 4,149 patients with CLL. The model is capable of dealing with heterogeneous data, including the high rates of missing data to be expected in the real-world setting, with a precision of 72% and a recall of 75%. To address concerns regarding the use of complex machine learning algorithms in the clinic, for each patient with CLL, CLL-TIM provides explainable predictions through uncertainty estimates and personalized risk factors.