Multi-parametric assessment of the anti-angiogenic effects of liposomal glucocorticoids

Inflammation plays a prominent role in tumor growth. Anti-inflammatory drugs have therefore been proposed as anti-cancer therapeutics. In this study, we determined the anti-angiogenic activity of a single dose of liposomal prednisolone phosphate (PLP-L), by monitoring tumor vascular function and viability over a period of one week. C57BL/6 mice were inoculated subcutaneously with B16F10 melanoma cells. Six animals were PLP-L-treated and six served as control. Tumor tissue and vascular function were probed using MRI before and at three timepoints after treatment. DCE-MRI was used to determine Ktrans, ve, time-to-peak, initial slope and the fraction of non-enhancing pixels, complemented with immunohistochemistry. The apparent diffusion coefficient (ADC), T2 and tumor size were assessed with MRI as well. PLP-L treatment resulted in smaller tumors and caused a significant drop in Ktrans 48 h post-treatment, which was maintained until one week after drug administration. However, this effect was not sufficient to significantly distinguish treated from non-treated animals. The therapy did not affect tumor tissue viability but did prevent the ADC decrease observed in the control group. No evidence for PLP-L-induced tumor vessel normalization was found on histology. Treatment with PLP-L altered tumor vascular function. This effect did not fully explain the tumor growth inhibition, suggesting a broader spectrum of PLP-L activities

Cost-effectiveness analysis of rivaroxaban for treatment and secondary prevention of venous thromboembolism in the Netherlands

Background: Until recently, standard treatment of venous thromboembolism (VTE) concerned a combination of short-term low-molecular-weight heparin (LMWH) and long-term vitamin-K antagonist (VKA). Risk of bleeding and the requirement for regular anticoagulation monitoring are, however, limiting their use. Rivaroxaban is a novel oral anticoagulant associated with a significantly lower risk of major bleeds (hazard ratio=0.54, 95% confidence interval=0.37-0.79) compared to LMWH/VKA therapy, and does not require regular anticoagulation monitoring. Aims: To evaluate the health economic consequences of treating acute VTE patients with rivaroxaban compared to treatment with LMWH/VKA, viewed from the Dutch societal perspective. Methods: A life-time Markov model was populated with the findings of the EINSTEIN phase III clinical trial to analyze cost-effectiveness of rivaroxaban therapy in treatment and prevention of VTE from a Dutch societal perspective. Primary model outcomes were total and incremental quality-adjusted life years (QALYs), as well as life expectancy and costs. Results: Over a patient's lifetime, rivaroxaban was shown to be dominant, with health gains of 0.047 QALYs and cost savings of Euro304 compared to LMWH/VKA therapy. Dominance was robustly present in all sensitivity analyses. Major drivers of the differences between the two treatment arms were related to anticoagulation monitoring (medical costs, travel costs, and loss of productivity) and the occurrence of major bleeds. Conclusion: Rivaroxaban treatment of patients with venous thromboembolism results in health gains and cost savings compared to LMWH/VKA therapy. This conclusion holds for the Dutch setting, both for the societal perspective, as well as the healthcare perspective

Impact of the arterial input function on the classification of contrast-agent uptake curves in dynamic contrast-enhanced (DCE) MR images based on heuristic shape modeling

Purpose: To demonstrate that inter-patient differences in the spreading of the contrast agent throughout the blood, described by the arterial input function (AIF), should be considered in the classification of contrast-agent uptake curves in the tissue of interest, e.g., a suspicious lesion in the breast. In the application of heuristic shape modeling (Kuhl et al. 1999, three-time-point (3TP) by Weinstein et al. 1999), the AIF is not extracted from the DCE-MR image series and, therefore, not taken into account.Methods and Materials: A two-compartment model (extended Kety) with fixed pharmacokinetic parameters is used to simulate the tissue-response curves for different AIFs. The shape of these curves is classified into benign, suspicious or malignant by means of the 3TP method.Results: While AIFs are known to differ in a wide range, our simulations indicate that already small changes of the AIF considerably alter the shape of the response curve. These changes may even lead to different curve classifications, although the simulated response curves relate to ’tissue’ with fixed pharmacokinetic properties. Conclusion: The shape of contrast-agent uptake curves expressed by simulated tissue with fixed pharmacokinetic properties can get classified differently in different patients owing to inter-patient variations of the AIF. Evaluation of the influence of variation in AIFs in real patient data is work in progress. Validation of our observation with real patient data might suggest that deconvolution with patient-specific AIFs, as it is done in pharmacokinetic modeling, improves reliability of tissue classification derived from the shape of contrast-agent uptake curves

Ab initio calculation of conformation and vibrational spectrum for the pyrosulfate ion

Flow diagram. This figure depicts the flow of patients, who were included in this study. (TIFF 709 kb

Additional file 1: of Drug survival of second biological DMARD therapy in patients with rheumatoid arthritis: a retrospective non-interventional cohort analysis

DDD-based drug supply of different agents that were available in the German market 2010–2013. (DOCX 15 kb

Additional file 3: of Drug survival of second biological DMARD therapy in patients with rheumatoid arthritis: a retrospective non-interventional cohort analysis

Flow diagram. This figure depicts the flow of patients, who were included in this study. (TIFF 709 kb

Pharmacokinetic analysis of dynamic contrast-enhanced (DCE) MR breast images

DCE-MR breast imaging is becoming an important modality as a problem-solving tool and in screening of high-risk patients. In DCE-MR a T1-weighted time series is recorded during the uptake of a contrast agent (CA: Gd-DTPA) that enables the assessment of voxel-specific dynamic tissue properties. Tumor malignancy often goes hand in hand with high vascularity and high vessel wall permeability because of angiogenesis; i.e. a large number of new vessels is formed at such a rate that their walls are not properly constructed and therefore highly permeable. These 'malignant' tissue characteristics affect the shape of the CA-uptake curve. The goal is to investigate the use of a pharmacokinetic two-compartment model (extended Kety [1]) in the context of dynamic analysis of CA-uptake curves as a contribution to automatic detection and characterization of breast cancer. The equations: ve*(dCe(t)/dt)=Ktrans(Cp(t)-Ce(t)) and Ct(t)=vp*Cp(t)+ve*Ce(t)describe the model. Ktrans = volume transfer constant [min-1], vc = cell fraction [-], ve = extravascular, extracellular fraction [-] (EES), vp = blood plasma fraction [-], vbc = blood cell fraction [-]. Ct / Cp / Ce = tissue / blood plasma / EES concentration CA [mM]. However, the models that are currently dominating the clinical practice are 'heuristic shape models' such as Kuhl's model [2] and the Three-Time-Point (3TP) model [3]. These models classify the shape of the CA-uptake curves into three categories: (1) persistent uptake (benign), (2) plateau uptake in the intermediate to late phase (suspicious), and (3) washout in the late to intermediate phase (malignant). This type of classification is based on clinical experience and statistics supported by biopsy-proven data. One of our aims is to uncover the limitations of these shape models and to investigate if two-compartment modeling can lead to a better, i.e. physiology-based, tissue classification

Assessing Response in Atopic Dermatitis: A Systematic Review of the Psychometric Performance of Measures Used in HTAs and Clinical Trials

Abstract Introduction Assessing treatment response is key to determining treatment value in atopic dermatitis (AD). Currently, response is assessed using various clinician- or patient-reported measures and response criteria. This variation creates a mismatch of evidence across trials, hindering the ability of clinicians, regulators, and payers to compare the efficacy of treatments. This review identifies which measures and criteria are used to determine response in clinical trials and health technology assessments (HTAs). Moreover, it systematically reviews the psychometric performance of those measures and criteria to understand which perform best in capturing patient-relevant symptoms and treatment benefits. Methods A scoping review of clinical trials and HTAs in AD identified the following measures for inclusion: the Eczema Area and Severity Index (EASI), the Investigator’s Global Assessment (IGA), the Dermatology Life Quality Index (DLQI) and the Peak Pruritus Numerical Rating Scale (PP-NRS). A systematic search was performed in MEDLINE and Embase to identify studies testing the psychometric performance of these measures in adults or adolescents with AD. Results A lack of consistency in the assessment of response was observed across clinical trials and HTAs. Important gaps in psychometric evidence were identified. No content validations of the EASI and IGA in AD were found, while some quantitative studies suggested that these measures fail to capture itch, a core symptom. The PP-NRS and DLQI performed well. No studies compared the performance of different response criteria. Conclusion Content validation of the PP-NRS confirmed the importance of itch as a core symptom and treatment priority in AD; however, itch is not well covered in the EASI or IGA. Including the PP-NRS in clinical trials and HTAs will better capture patient-relevant benefit and response. Although various response criteria were used, no studies compared the performance of different criteria to inform which were most appropriate to compare treatments in clinical trials and HTAs