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Background: Few studies have analysed long-term effects of immunomodulatory disease modifying drugs (DMDs)., Objective: Assessment of the efficacy of DMDs on long-term evolution of multiple sclerosis, using a Bayesian approach to overcome methodological problems related to open-label studies., Methods: MS patients from three different Italian multiple sclerosis centres were divided into subgroups according to the presence of treatment in their disease history before the endpoint, which was represented by secondary progression. Patients were stratified on the basis of the risk score BREMS (Bayesian risk estimate for multiple sclerosis), which is able to predict the unfavourable long-term evolution of MS at an early stage., Results: We analysed data from 1178 patients with a relapsing form of multiple sclerosis at onset and at least 10 years of disease duration, treated (59%) or untreated with DMDs. The risk of secondary progression was significantly lower in patients treated with DMDs, regardless of the initial prognosis predicted by BREMS., Conclusions: DMDs significantly reduce the risk of multiple sclerosis progression both in patients with initial high-risk and patients with initial low-risk. These findings reinforce the role of DMDs in modifying the natural course of the disease, suggesting that they have a positive effect not only on the inflammatory but also on the neurodegenerative process. The study also confirms the capability of the BREMS score to predict MS evolution., (© The Author(s), 2012.)

The inclusion of patients' perspectives in clinical practice has become an important matter for health professionals, in view of the increasing attention to patient-centered care. In this regard, this report illustrates a method for developing a visual aid that supports the physician in the process of informing patients about a critical decisional problem. In particular, we focused on interpretation of the results of decision trees embedding Markov models implemented with the commercial tool TreeAge Pro. Starting from patient-level simulations and exploiting some advanced functionalities of TreeAge Pro, we combined results to produce a novel graphical output that represents the distributions of outcomes over the lifetime for the different decision options, thus becoming a more informative decision support in a context of shared decision making. The training example used to illustrate the method is a decision tree for thromboembolism risk prevention in patients with nonvalvular atrial fibrillation., (© The Author(s) 2015.)

Background: Pollen allergy represents a relevant health issue. Betulaceae sensitization significantly increased in Genoa, Italy, in the last decades. This study investigated possible relationships among pollen count, meteorological changes, air pollution, and sensitizations in this city during a 30-year period., Methods: Betulaceae, Urticaceae, Gramineae, and Oleaceae pollen counts were measured from 1981 to 2010 in Genoa. Sensitization to these pollens was also considered in large populations of allergic patients. Meteorological parameters and pollutants were also measured in the same area., Results: Betulaceae sensitization increased over time. All pollen species significantly increased over this time. Pollen season advanced for Betulaceae and Urticaceae. Only Urticaceae season significantly increased. Temperature increased while rainfall decreased over the time. Pollutants significantly decreased. There were some relationships between pollen changes and climatic and air pollution parameters., Conclusion: This 30-year study conducted in an urbanized area provided evidence that Betulaceae sensitization significantly increased, pollen load significantly augmented, and climate and air pollution changed with a possible influence on pollen release.

The objective of this study was to compare oxidative status and homocysteinemia in patients with lupus nephritis (LN) and in controls. Total antioxidant capacity (TAC), reactive oxygen species (ROS), homocysteine and related vitamins were measured in 68 patients with LN and in 50 controls. LN patients had lower TAC (p = 0.05) and higher ROS and homocysteinemia (p = 0.01) than controls. TAC, significantly lower in active than in quiescent LN (p = 0.01), was correlated with albuminemia (p = 0.02), inversely with proteinuria (p = 0.01) and anti-DNA antibodies (p = 0.004). ROS values, higher both in active and in inactive LN, correlated with age (p = 0.02), C-reactive protein (CRP) (p = 0.0005) and inversely with prednisone dosage (p = 0.05). At multivariate analysis, CRP (p = 0.04) and age (p = 0.005) were independent ROS predictors. Homocysteine, higher in active than in quiescent LN (p = 0.016) and in patients with antiphospholipid antibodies (p=0.05), correlated with serum creatinine (p = 0.00001) and proteinuria (p = 0.015). At multivariate analysis serum creatinine (p = 0.006) and active nephritis (p = 0.003) were independent predictors of hyperhomocysteinemia. Patients with LN showed impaired oxidative status, even without clinical signs of renal activity. ROS production may be counterbalanced by adequate antioxidant capacity in some patients with quiescent LN. The association of hyperhomocysteinemia and antiphospholipid antibodies positivity may increase the risk of cardiovascular and/or thrombotic events in LN patients.

Graft-versus-host disease (GVHD) represents one of the major complications of allogeneic bone marrow transplantation (BMT). Nevertheless, the occurrence of mild GVHD could be desirable in high-risk leukemic patients, due to a relapse-preventing effect known as the graft-versus-leukemia (GVL) effect. Given that different prophylactic interventions are available to prevent GVHD development, the decision problem consists in assessing both type and dosage of the drugs in order to avoid or induce GVHD, according to the specific patient's condition. The decision problem can be represented and solved by using an influence diagram. The choice of this formalism allows using new available methods for building and updating the model of the decision problem. The qualitative structure of the model and the conditional probabilities were first derived by combining literature results with a medical expert's judgement. More specifically, probabilities were initially assigned as ranges rather than as point values. Then, conditional probabilities were updated, by using a learning algorithm, as new cases became available. The authors analyzed 50 cases of pediatric patients affected by either malignant or nonmalignant diseases, undergoing BMT and receiving GVHD prophylaxis. They used the first 25 cases to adjust the initially assigned conditional probabilities, then checked the model obtained on the remaining patients. The overall performance for GVHD prediction was about 80%.