IgG subclasses as biomarkers for persistence of factor VIII inhibitors in previously untreated patients with severe haemophilia A.

We investigated longitudinally the behaviour of anti-factor VIII (anti-FVIII) IgG subclasses for 6 months from inhibitor development in 43 patients from the Survey of Inhibitors in Plasma-Products Exposed Toddlers (SIPPET) trial who developed persistent or transient inhibitors. We first analysed 43 patients within 60 days post inhibitor detection. Then, 14 of these 43 patients were studied at five time points over 6 months. Our study showed that during the first 60 days, the risk of inhibitor persistence increased with the concomitant presence of an increasing number of IgG subclasses. Over the 6-month period post inhibitor detection, only the IgG2 subclass could be considered a hallmark of inhibitor persistence.

Performance of a clinical risk prediction model for inhibitor formation in severe haemophilia A.

BACKGROUND: There is a need to identify patients with haemophilia who have a very low or high risk of developing inhibitors. These patients could be candidates for personalized treatment strategies. AIMS: The aim of this study was to externally validate a previously published prediction model for inhibitor development and to develop a new prediction model that incorporates novel predictors. METHODS: The population consisted of 251 previously untreated or minimally treated patients with severe haemophilia A enrolled in the SIPPET study. The outcome was inhibitor formation. Model discrimination was measured using the C-statistic, and model calibration was assessed with a calibration plot. The new model was internally validated using bootstrap resampling. RESULTS: Firstly, the previously published prediction model was validated. It consisted of three variables: family history of inhibitor development, F8 gene mutation and intensity of first treatment with factor VIII (FVIII). The C-statistic was 0.53 (95% CI: 0.46-0.60), and calibration was limited. Furthermore, a new prediction model was developed that consisted of four predictors: F8 gene mutation, intensity of first treatment with FVIII, the presence of factor VIII non-neutralizing antibodies before treatment initiation and lastly FVIII product type (recombinant vs. plasma-derived). The C-statistic was 0.66 (95 CI: 0.57-0.75), and calibration was moderate. Using a model cut-off point of 10%, positive- and negative predictive values were 0.22 and 0.95, respectively. CONCLUSION: Performance of all prediction models was limited. However, the new model with all predictors may be useful for identifying a small number of patients with a low risk of inhibitor formation.

Hypercoagulability and the risk of recurrence in young women with myocardial infarction or ischaemic stroke: a cohort study.

BACKGROUND: We aimed to investigate the role of hypercoagulability on the risk of lifetime cardiovascular recurrences after myocardial infarction or ischaemic stroke. METHODS: Young women (< 50 years) with either myocardial infarction (n = 197) or ischaemic stroke (n = 107) were followed between 1995 and 2012 in the RATIO follow-up study. To determine whether hypercoagulability affects the risk or recurrence, a coagulation score based on acquired and inherited markers was compiled and used in a quartile analysis. Hazard ratios (HRs) obtained from Cox proportional models and adjusted for several cardiovascular risk factors were used to compare quartiles of the coagulation score for the risk of recurrence. RESULTS: During a median follow-up of 19 years, 59 cardiovascular recurrences occurred. In patients with myocardial infarction no association was found between a high prothrombotic score and recurrences (highest quartile vs lowest quartile HR 0.7, 95% CI, 0.3-1.8). Conversely, ischaemic stroke patients with a high prothrombotic score showed a doubling in risk of long-term cardiovascular recurrences (HR 1.9, 95% CI 0.6-6.3) compared with ischaemic stroke patients and low levels of the score, with a dose response relationship. CONCLUSIONS: An increased coagulation tendency might be associated with long-term cardiovascular risk in women with ischaemic stroke, but not in women with myocardial infarction.

The Netherlands Epidemiology of Obesity (NEO) study: study design and data collection.

Obesity is a well-established risk factor for many chronic diseases. Incomplete insight exists in the causal pathways responsible for obesity-related disorders and consequently, in the identification of obese individuals at risk of these disorders. The Netherlands Epidemiology of Obesity (NEO) study is designed for extensive phenotyping to investigate pathways that lead to obesity-related diseases. The NEO study is a population-based, prospective cohort study that includes 6,673 individuals aged 45-65 years, with an oversampling of individuals with overweight or obesity. At baseline, data on demography, lifestyle, and medical history have been collected by questionnaires. In addition, samples of 24-h urine, fasting and postprandial blood plasma and serum, and DNA were collected. Participants underwent an extensive physical examination, including anthropometry, electrocardiography, spirometry, and measurement of the carotid artery intima-media thickness by ultrasonography. In random subsamples of participants, magnetic resonance imaging of abdominal fat, pulse wave velocity of the aorta, heart, and brain, magnetic resonance spectroscopy of the liver, indirect calorimetry, dual-energy X-ray absorptiometry, or accelerometry measurements were performed. The collection of data started in September 2008 and completed at the end of September 2012. Participants are followed for the incidence of obesity-related diseases and mortality. The NEO study investigates pathways that lead to obesity-related diseases. A better understanding of the mechanisms underlying the development of disease in obesity may help to identify individuals who are susceptible to the detrimental metabolic, cardiovascular and other consequences of obesity and has implications for the development of prevention and treatment strategies.

The usefulness of D-dimer as a predictive marker for mortality in patients with COVID-19 hospitalized during the first wave in Italy.

BACKGROUND: The coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Identification of predictors of poor outcomes will assist medical staff in treatment and allocating limited healthcare resources. AIMS: The primary aim was to study the value of D-dimer as a predictive marker for in-hospital mortality. METHODS: This was a cohort study. The study population consisted of hospitalized patients (age >18 years), who were diagnosed with COVID-19 based on real-time PCR at 9 hospitals during the first COVID-19 wave in Lombardy, Italy (Feb-May 2020). The primary endpoint was in-hospital mortality. Information was obtained from patient records. Statistical analyses were performed using a Fine-Gray competing risk survival model. Model discrimination was assessed using Harrell's C-index and model calibration was assessed using a calibration plot. RESULTS: Out of 1049 patients, 507 patients (46%) had evaluable data. Of these 507 patients, 96 died within 30 days. The cumulative incidence of in-hospital mortality within 30 days was 19% (95CI: 16%-23%), and the majority of deaths occurred within the first 10 days. A prediction model containing D-dimer as the only predictor had a C-index of 0.66 (95%CI: 0.61-0.71). Overall calibration of the model was very poor. The addition of D-dimer to a model containing age, sex and co-morbidities as predictors did not lead to any meaningful improvement in either the C-index or the calibration plot. CONCLUSION: The predictive value of D-dimer alone was moderate, and the addition of D-dimer to a simple model containing basic clinical characteristics did not lead to any improvement in model performance.