ObjectiveTo develop and validate a novel comorbidity score (multisource comorbidity score (MCS)) predictive of mortality, hospital admissions and healthcare costs using multiple source information from the administrative Italian National Health System (NHS) databases.MethodsAn index of 34 variables (measured from inpatient diagnoses and outpatient drug prescriptions within 2 years before baseline) independently predicting 1-year mortality in a sample of 500 000 individuals aged 50 years or older randomly selected from the NHS beneficiaries of the Italian region of Lombardy (training set) was developed. The corresponding weights were assigned from the regression coefficients of a Weibull survival model. MCS performance was evaluated by using an internal (ie, another sample of 500 000 NHS beneficiaries from Lombardy) and three external (each consisting of 500 000 NHS beneficiaries from Emilia-Romagna, Lazio and Sicily) validation sets. Discriminant power and net reclassification improvement were used to compare MCS performance with that of other comorbidity scores. MCS ability to predict secondary health outcomes (ie, hospital admissions and costs) was also investigated.ResultsPrimary and secondary outcomes progressively increased with increasing MCS value. MCS improved the net 1-year mortality reclassification from 27% (with respect to the Chronic Disease Score) to 69% (with respect to the Elixhauser Index). MCS discrimination performance was similar in the four regions of Italy we tested, the area under the receiver operating characteristic curves (95% CI) being 0.78 (0.77 to 0.79) in Lombardy, 0.78 (0.77 to 0.79) in Emilia-Romagna, 0.77 (0.76 to 0.78) in Lazio and 0.78 (0.77 to 0.79) in Sicily.ConclusionMCS seems better than conventional scores for predicting health outcomes, at least in the general population from Italy. This may offer an improved tool for risk adjustment, policy planning and identifying patients in need of a focused treatment approach in the everyday medical practice.

PurposeTo explore the prescription patterns of erythropoiesis-stimulating agents (ESAs) in four large Italian geographic areas, where different health policy interventions to promote biosimilar use in routine care are undertaken.MethodsA retrospective drug utilization study was conducted during the years 2009–2013. The data sources were the administrative databases of the Tuscany region and of the Caserta, Palermo, and Treviso Local Health Units (LHUs). The characteristics, prevalence, and switching patterns of different ESAs (biosimilars and reference products), stratified by indication for use, were calculated over time and across centers.ResultsOverall, 49,491 patients were treated with ESAs during the years 2009–2013 in the four centers. Of these, 41,286 patients (83.4 %) were naive users. The prevalence of ESA use increased from 2.9 to 3.4 per 1000 inhabitants in the years 2009–2011 but decreased thereafter (3.0 per 1000 in 2013). Moreover, the proportion of biosimilar users increased overall from 1.8 % in 2010 to 33.6 % in 2013, with larger increase in Treviso (from 0.0 to 45.0 %) and Tuscany (from 0.7 to 37.6 %) than in Caserta (from 7.5 to 22.9 %) and Palermo (from 0.0 to 27.7 %). Switching between different ESAs during the first year of therapy was frequent (17.0 %), much more toward reference products than toward biosimilars.ConclusionOverall, the prevalence of ESA use decreased slightly, while use of biosimilar ESAs, especially in naive patients, increased significantly but to different extents in these four large Italian geographic areas. Switching between different ESAs during the first year of treatment was very frequent, which may affect pharmacovigilance monitoring. New strategies are necessary to further improve market penetration of low-cost medicines, such as biosimilars, and also to harmonize effective health policy interventions that aim to reduce pharmaceutical expenses and optimize patient benefit across all regions.Electronic supplementary materialThe online version of this article (doi:10.1007/s40259-015-0132-7) contains supplementary material, which is available to authorized users.

Background and aims Diabetes mellitus (DM) has been associated with higher incidence of severe cases of COVID-19 in hospitalized patients, but it is unknown whether DM is a risk factor for the overall COVID-19 incidence. The aim of present study was to investigate whether there is an association of DM with COVID-19 prevalence and case fatality, and between different DM medications and risk for COVID-19 infection and death. Methods and Results retrospective observational study on all SARS-CoV-2 positive (SARS-CoV-2 + ) cases and deaths in Sicily up to 2020, May 14 th . No difference in COVID-19 prevalence was found between people with and without DM (RR 0.92 [0.79-1.09]). Case fatality was significantly higher in SARS-CoV-2 + with DM (RR 4.5 [3.55-5.71]). No diabetes medication was associated with differences in risk for SARS-Cov2 infection. Conclusions in Sicily, DM was not a risk factor for COVID-19 infection, whereas it was associated with a higher case fatality.

Heterogeneity in the use of G-CSF and, in particular, biosimilar filgrastim across different Italian centres was observed, probably due to different regional healthcare policy interventions. During the first year of treatment, switching between different G-CSFs was frequent. Considering the impact of biological drugs on pharmaceutical expenses, it is necessary to harmonize healthcare policies promoting the use of biological drugs with the lowest cost.