COVID-19 mortality attenuated during widespread Omicron transmission, Denmark, 2020 to 2022.

BackgroundIt sparked considerable attention from international media when Denmark lifted restrictions against COVID-19 in February 2022 amidst widespread transmission of the new SARS-CoV-2 Omicron variant and a steep rise in reported COVID-19 mortality based on the 30-day COVID-19 death count.AimOur aim was to investigate how coincidental infections affected COVID-19 mortality estimates following the introduction of the Omicron variant in late 2021.MethodsWe compared the 30-day COVID-19 death count with the observed mortality using three alternative mortality estimation methods; (i) a mathematical model to correct the 30-day COVID-19 death count for coincidental deaths, (ii) the Causes of Death Registry (CDR) and (iii) all-cause excess mortality.ResultsThere was a substantial peak in the 30-day COVID-19 death count following the emergence of the Omicron variant in late 2021. However, there was also a substantial change in the proportion of coincidental deaths, increasing from 10-20% to around 40% of the recorded COVID-19 deaths. The high number of 30-day COVID-19 deaths was not reflected in the number of COVID-19 deaths in the CDR and the all-cause excess mortality surveillance.ConclusionOur analysis showed a distinct change in the mortality pattern following the introduction of Omicron in late 2021 with a markedly higher proportion of people estimated to have died with, rather than of, COVID-19 compared with mortality patterns observed earlier in the COVID-19 pandemic. Our findings highlight the importance of incorporating alternative mortality surveillance methods to more correctly estimate the burden of COVID-19 as the pandemic continues to evolve.

A novel integrated biomarker index for the assessment of hematological responses in MPNs during treatment with hydroxyurea and interferon-alpha2.

BACKGROUND: Conventional cytoreductive therapy for patients with chronic Philadelphia-negative myeloproliferative neoplasms (MPNs) includes hydroxyurea (HU), interferon-alpha2 (IFN), and anagrelide. HU is worldwide the most used cytoreductive agent, which lowers elevated blood cell counts within days in the large majority of patients. However, some patients may experience rebound cytosis when HU is reduced due to cytopenia, thereby potentially giving rise to fluctuating cell counts during therapy. Such rapid oscillations may be harmful and potentially elicit thrombosis. Treatment with IFN gradually lowers elevated cell counts within weeks and when the dosage is reduced, the cell counts do not rapidly increase but are sustained within the normal range in the large majority of patients. Conventional hematological response criteria are among others based upon single absolute cell count values and do not take into account the relative decreases toward normal for each cell count. MATERIALS, METHODS & RESULTS: Using serial data from the Danish DALIAH trial, we herein describe a novel integrated biomarker index for the assessment of hematological and molecular (JAK2V617F) responses in patients with MPNs during treatment with IFN or HU. DISCUSSION: This novel tool convincingly displays the superiority of IFN versus HU in normalizing elevated cell counts. Our results need to be validated in larger studies but already now call for studies of the safety and efficacy of combination therapy during the initial treatment of patients with MPNs.

Clonal haematopoiesis of indeterminate potential and impaired kidney function-A Danish general population study with 11 years follow-up.

The myeloproliferative neoplasms are associated with chronic kidney disease but whether clonal haematopoiesis of indeterminate potential (CHIP) is associated with impaired kidney function is unknown. In the Danish General Suburban Population Study (N = 19 958) from 2010 to 2013, 645 individuals were positive for JAK2V617F (N = 613) or CALR (N = 32) mutations. Mutation-positive individuals without haematological malignancy were defined as having CHIP (N = 629). We used multiple and inverse probability weighted (IPW)-adjusted linear regression analysis to estimate adjusted mean (95% confidence interval) differences in estimated glomerular filtration rate (eGFR; ml/min/1.73 m2 ) by mutation status, variant allele frequency (VAF%), blood cell counts, and neutrophil-to-lymphocyte ratio (NLR). We performed 11-year longitudinal follow-up of eGFR in all individuals. Compared to CHIP-negative individuals, the mean differences in eGFR were -5.6 (-10.3, -0.8, p = .02) for CALR, -11.9 (-21.4, -2.4, p = 0.01) for CALR type 2, and -10.1 (-18.1, -2.2, p = .01) for CALR with VAF ≥ 1%. The IPW-adjusted linear regression analyses showed similar results. NLR was negatively associated with eGFR. Individuals with CALR type 2 had a worse 11-year longitudinal follow-up on eGFR compared to CHIP-negative individuals (p = .004). In conclusion, individuals with CALR mutations, especially CALR type 2, had impaired kidney function compared to CHIP-negative individuals as measured by a lower eGFR at baseline and during 11-year follow-up.

Data-driven analysis of the kinetics of the JAK2V617F allele burden and blood cell counts during hydroxyurea treatment of patients with polycythemia vera, essential thrombocythemia, and primary myelofibrosis.

BACKGROUND: Hydroxyurea (HU) treatment of patients with essential thrombocythemia (ET), polycythemia vera (PV), and primary myelofibrosis (PMF) (MPNs) normalizes elevated blood cell counts within weeks in the large majority of patients. Studies on the impact of HU upon the kinetics of the JAK2V617F allele burden, leukocyte, and platelet counts over time are scarce. PURPOSE: Using data-driven analysis as a novel tool to model the kinetics of the JAK2V617F allele burden and blood cell counts over time during treatment with HU. MATERIAL AND METHODS: Using serial measurements of JAK2V617F and correlation analysis of routine hematological values (the Hb-concentration, leukocyte count, platelet count, and lactic dehydrogenase), we present a detailed description and analysis of the kinetics of the JAK2V617F, leukocyte, and platelet counts and lactic dehydrogenase in 27 patients (PV = 18; ET = 7; PMF = 2), who were followed in the Danish randomized trial (DALIAH). To further analyze the JAK2V617F kinetics, we use a machine learning clustering algorithm to group the response patterns. RESULTS: Response patterns were highly heterogeneous, with clustering resulting in 3 groups and 3 outliers. In the large majority of patients, HU treatment was initially associated with a modest decline in the JAK2V617F allele burden in concert with a decline in leukocyte and platelet counts. However, HU did not induce a sustained and continuous decrease in the JAK2V617F allele burden. CONCLUSION: Using data-driven analysis of the JAK2V617F allele burden, leukocyte, and platelet kinetics during treatment with HU, we have shown that HU does not induce a sustained decrease in the JAK2V617F allele burden and neither induces sustained normalization of elevated cell counts in MPN patients. Our results may explain why MPN patients during treatment with HU still have a substantially increased risk of thrombosis.

Mathematical Modeling of MPNs Offers Understanding and Decision Support for Personalized Treatment.

(1) Background: myeloproliferative neoplasms (MPNs) are slowly developing hematological cancers characterized by few driver mutations, with JAK2V617F being the most prevalent. (2) Methods: using mechanism-based mathematical modeling (MM) of hematopoietic stem cells, mutated hematopoietic stem cells, differentiated blood cells, and immune response along with longitudinal data from the randomized Danish DALIAH trial, we investigate the effect of the treatment of MPNs with interferon-α2 on disease progression. (3) Results: At the population level, the JAK2V617F allele burden is halved every 25 months. At the individual level, MM describes and predicts the JAK2V617F kinetics and leukocyte- and thrombocyte counts over time. The model estimates the patient-specific treatment duration, relapse time, and threshold dose for achieving a good response to treatment. (4) Conclusions: MM in concert with clinical data is an important supplement to understand and predict the disease progression and impact of interventions at the individual level.

Data-driven analysis of JAK2V617F kinetics during interferon-alpha2 treatment of patients with polycythemia vera and related neoplasms.

Treatment with PEGylated interferon-alpha2 (IFN) of patients with essential thrombocythemia and polycythemia vera induces major molecular remissions with a reduction in the JAK2V617F allele burden to undetectable levels in a subset of patients. A favorable response to IFN has been argued to depend upon the tumor burden, implying that institution of treatment with IFN should be as early as possible after the diagnosis. However, evidence for this statement is not available. We present a thorough analysis of unique serial JAK2V617F measurements in 66 IFN-treated patients and in 6 untreated patients. Without IFN treatment, the JAK2V617F allele burden increased exponentially with a period of doubling of 1.4 year. During monotherapy with IFN, the JAK2V617F allele burden decreased mono- or bi-exponentially for 33 responders of which 28 patients satisfied both descriptions. Bi-exponential description improved the fits in 19 cases being associated with late JAK2V617F responses. The decay of the JAK2V617F allele burden during IFN treatment was estimated to have half-lives of 1.6 year for the monoexponential response and 1.0 year in the long term for the bi-exponential response. In conclusion, through data-driven analysis of the JAK2V617F allele burden, we provide novel information regarding the JAK2V617F kinetics during IFN-treatment, arguing for early intervention.

Bridging blood cancers and inflammation: The reduced Cancitis model.

A novel mechanism-based model - the Cancitis model - describing the interaction of blood cancer and the inflammatory system is proposed, analyzed and validated. The immune response is divided into two components, one where the elimination rate of malignant stem cells is independent of the level of the blood cancer and one where the elimination rate depends on the level of the blood cancer. A dimensional analysis shows that the full 6-dimensional system of nonlinear ordinary differential equations may be reduced to a 2-dimensional system - the reduced Cancitis model - using Fenichel theory. The original 18 parameters appear in the reduced model in 8 groups of parameters. The reduced model is analyzed. Especially the steady states and their dependence on the exogenous inflammatory stimuli are analyzed. A semi-analytic investigation reveals the stability properties of the steady states. Finally, positivity of the system and the existence of an attracting trapping region in the positive octahedron guaranteeing global existence and uniqueness of solutions are proved. The possible topologies of the dynamical system are completely determined as having a Janus structure, where two qualitatively different topologies appear for different sets of parameters. To classify this Janus structure we propose a novel concept in blood cancer - a reproduction ratio R. It determines the topological structure depending on whether it is larger or smaller than a threshold value. Furthermore, it follows that inflammation, affected by the exogenous inflammatory stimulation, may determine the onset and development of blood cancers. The body may manage initial blood cancer as long as the self-renewal rate is not too high, but fails to manage it if an inflammation appears. Thus, inflammation may trigger and drive blood cancers. Finally, the mathematical analysis suggests novel treatment strategies and it is used to discuss the in silico effect of existing treatment, e.g. interferon-α or T-cell therapy, and the impact of malignant cells becoming resistant.

Mathematical modelling as a proof of concept for MPNs as a human inflammation model for cancer development.

The chronic Philadelphia-negative myeloproliferative neoplasms (MPNs) are acquired stem cell neoplasms which ultimately may transform to acute myelogenous leukemia. Most recently, chronic inflammation has been described as an important factor for the development and progression of MPNs in the biological continuum from early cancer stage to the advanced myelofibrosis stage, the MPNs being described as "A Human Inflammation Model for Cancer Development". This novel concept has been built upon clinical, experimental, genomic, immunological and not least epidemiological studies. Only a few studies have described the development of MPNs by mathematical models, and none have addressed the role of inflammation for clonal evolution and disease progression. Herein, we aim at using mathematical modelling to substantiate the concept of chronic inflammation as an important trigger and driver of MPNs.The basics of the model describe the proliferation from stem cells to mature cells including mutations of healthy stem cells to become malignant stem cells. We include a simple inflammatory coupling coping with cell death and affecting the basic model beneath. First, we describe the system without feedbacks or regulatory interactions. Next, we introduce inflammatory feedback into the system. Finally, we include other feedbacks and regulatory interactions forming the inflammatory-MPN model. Using mathematical modeling, we add further proof to the concept that chronic inflammation may be both a trigger of clonal evolution and an important driving force for MPN disease progression. Our findings support intervention at the earliest stage of cancer development to target the malignant clone and dampen concomitant inflammation.