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BACKGROUND: Several studies have been focusing on the potential role of atmospheric pollutants in the diffusion and impact on health of Covid-19. This study's objective was to estimate the association between ≤10 µm diameter particulate matter (PM10) exposure and the likelihood of experiencing pneumonia due to Covid-19 using individual-level data in Italy. METHODS: Information on Covid-19 patients was retrieved from the Italian IQVIA® Longitudinal Patient Database (LPD), a computerized network of general practitioners (GPs) including anonymous data on patients' consultations and treatments. All patients with a Covid-19 diagnosis during March 18th, 2020 - June 30th, 2020 were included in the study. The date of first Covid-19 registration was the starting point of the 3-month follow-up (Index Date). Patients were classified based on Covid-19-related pneumonia registrations on the Index date and/or during follow-up presence/absence. Each patient was assigned individual exposure by calculating average PM10 during the 30-day period preceding the Index Date, and according to GP's office province. A multiple generalized linear mixed model, mixed-effects logistic regression, was used to assess the association between PM10 exposure tertiles and the likelihood of experiencing pneumonia. RESULTS: Among 6483 Covid-19 patients included, 1079 (16.6%) had a diagnosis of pneumonia. Pneumonia patients were older, more frequently men, more health-impaired, and had a higher individual-level exposure to PM10 during the month preceding Covid-19 diagnosis. The mixed-effects model showed that patients whose PM10 exposure level fell in the second tertile had a 30% higher likelihood of having pneumonia than that of first tertile patients, and the risk for those who were in the third tertile was almost doubled. CONCLUSION: The consistent findings toward a positive association between PM10 levels and the likelihood of experiencing pneumonia due to Covid-19 make the implementation of new strategies to reduce air pollution more and more urgent.
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Poluentes Atmosféricos , Poluição do Ar , COVID-19 , Poluentes Atmosféricos/efeitos adversos , Poluentes Atmosféricos/análise , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Teste para COVID-19 , Exposição Ambiental/efeitos adversos , Exposição Ambiental/análise , Humanos , Itália/epidemiologia , Masculino , Material Particulado/efeitos adversos , Material Particulado/análise , SARS-CoV-2RESUMO
Background: Since the COVID-19 pandemic has placed more attention on drugs' approval process and the importance of rapid decision-making in the healthcare sector, it is crucial to assess how time to market (TTM) of drugs varied. Objective: To estimate the impact of the COVID-19 pandemic on TTM of drugs in Italy. Methods: An IQVIA database was used to retrieve information on drugs that obtained positive opinion from the Committee for Medicinal Products for Human Use between January 2015 and December 2021. The available observations were divided into three groups (Pre COVID, Partially COVID, and Fully COVID) according to the timing of their negotiation process. Differences in average TTM among the three groups were analyzed in three steps: (1) descriptive statistics; (2) univariate analysis; (3) multivariate analysis, using a matching estimator. Results: A total of 363 unique combinations of molecule and indication met the inclusion criteria: 174 in the Pre COVID group, 69 in the Partially COVID group, and 123 in the Fully COVID group. Descriptive statistics and univariate analysis found a statistically significant difference in TTM among the three periods, with average TTM increasing during the pandemic (+136 days, p = 0.00) and then decreasing afterward (-23 days, p = 0.09). In the matching analysis, results for the Partially COVID period were confirmed (+108 days, p = 0.00) while results for the Fully COVID period lost significance but maintained a negative sign. Conclusions: The results suggest that after an adjustment phase in the Partially COVID period, a return to the status quo was reached.
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BACKGROUND: Vaborem is a fixed dose combination of vaborbactam and meropenem with potent activity against target Carbapenem-resistant Enterobacterales (CRE) pathogens, optimally developed for Klebsiella pneumoniae carbapenemase (KPC). The study aims to evaluate the cost-effectiveness of Vaborem versus best available therapy (BAT) for the treatment of patients with CRE-KPC associated infections in the Italian setting. METHODS: A cost-effectiveness analysis was conducted based on a decision tree model that simulates the clinical pathway followed by physicians treating patients with a confirmed CRE-KPC infection in a 5-year time horizon. The Italian National Health System perspective was adopted with a 3% discount rate. The clinical inputs were mostly sourced from the phase 3, randomised, clinical trial (TANGO II). Unit costs were retrieved from the Italian official drug pricing list and legislation, while patient resource use was validated by a national expert. Model outcomes included life years (LYs) and quality adjusted life years (QALYs) gained, incremental costs, incremental cost-effectiveness ratio (ICER) and incremental cost-utility ratio (ICUR). Deterministic and probabilistic sensitivity analyses were also performed. RESULTS: Vaborem is expected to decrease the burden associated with treatment failure and reduce the need for chronic renal replacement therapy while costs related to drug acquisition and long-term care (due to higher survival) may increase. Treatment with Vaborem versus BAT leads to a gain of 0.475 LYs, 0.384 QALYs, and incremental costs of 3549, resulting in an ICER and ICUR of 7473/LY and 9246/QALY, respectively. Sensitivity analyses proved the robustness of the model and also revealed that the probability of Vaborem being cost-effective reaches 90% when willingness to pay is 15,850/QALY. CONCLUSIONS: In the Italian setting, the introduction of Vaborem will lead to a substantial increase in the quality of life together with a minimal cost impact, therefore Vaborem is expected to be a cost-effective strategy compared to BAT.
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BACKGROUND: Primary biliary cholangitis is an autoimmune disease affecting the interlobular bile ducts. Limited information is available on its epidemiology and treatment in Italy. AIMS: To describe primary biliary cholangitis epidemiology and investigate treatment patterns for Italian patients with this disease. METHODS: Electronic medical records from 900 general practitioners (part of the QuintilesIMS™ Longitudinal Patient Databases) were examined. Demographics were compared with those from the Italian National Institute of Statistics dataset. The International Classification of Diseases, Ninth Revision, biliary cirrhosis code 571.6 was used for diagnosis, and data on comorbidities, concomitant medications, medical examinations, specialist referrals, and treatments were collected. RESULTS: This dataset was representative of the Italian population. Point prevalence of primary biliary cholangitis was calculated as 27.90 per 100,000 and incidence as 5.31 per 100,000 inhabitants/year. Some associations between the disease and comorbidities were sex specific. The most common laboratory assays requested were for liver enzymes, and the majority of patients were not referred to a specialist. Ursodeoxycholic acid was the most common therapy. CONCLUSION: This can be used as a benchmark for monitoring and identifying unmet needs to improve treatment in Italy.
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Colagogos e Coleréticos/uso terapêutico , Cirrose Hepática Biliar/tratamento farmacológico , Cirrose Hepática Biliar/epidemiologia , Ácido Ursodesoxicólico/uso terapêutico , Adulto , Idoso , Comorbidade , Bases de Dados Factuais , Doença Hepática Terminal/etiologia , Feminino , Humanos , Incidência , Itália/epidemiologia , Masculino , Pessoa de Meia-IdadeRESUMO
BACKGROUND AND OBJECTIVES: External reference pricing (ERP) is a price regulation tool widely used by policy makers in the European Union (EU) Member States (MS) to contain drug cost, although in theory, it may contribute to modulate prices up and down. The objective of this article was to summarise and discuss the main findings of part of a large project conducted for the European Commission ('External reference pricing of medicinal products: simulation-based considerations for cross-country coordination'; see www.ec.europa.eu/health/healthcare/docs/erp_reimbursement_medicinal_products_en.pdf) that aimed to provide an overview of ERP systems, both on processes and potential issues in 31 European countries (28 EU MS, Iceland, Norway, and Switzerland). METHODS: A systematic structured literature review was conducted to identify and characterise the use of ERP in the selected countries, to describe its impact on the prices of pharmaceuticals, and to discuss the possible cross-country coordination issues in EU MS. This research was complemented with a consultation of competent authorities' and international organisations' representatives to address the main issues or uncertainties identified through the literature review. RESULTS: All selected countries applied ERP, except the United Kingdom and Sweden. Twenty-three countries used ERP as the main systematic criterion for pricing. In the majority of European countries, ERP was based on legislated pricing rules with different levels of accuracy. ERP was applied either for all marketed drugs or for specific categories of medicines; it was mainly used for publicly reimbursed medicines. The number of reference countries included in the basket varied from 1 to 31. There was a great variation in the calculation methods used to compute the price; 15 countries used the average price, 7 countries used the lowest price, and 7 countries used other calculation methods. Reported limitations of ERP application included the lack of reliable sources of price information, price heterogeneity, exchange rate volatility, and hidden discounts. Spill-over effect and downward price convergence have often been mentioned as ERP's consequences leading to pricing strategies from pharmaceutical companies. CONCLUSION: While ERP is widely used in Europe, processes and availability of price information vary from one country to another, thus limiting ERP implementation. Furthermore, ERP spill-over effect is a major concern of pharmaceutical firms leading to implementation of the so-called 'launch sequence strategies'.
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BACKGROUND AND OBJECTIVE: With constant incentives for healthcare payers to contain their pharmaceutical budgets, modelling policy decision impact became critical. The objective of this project was to test the impact of various policy decisions on pharmaceutical budget (developed for the European Commission for the project 'European Union (EU) Pharmaceutical expenditure forecast' - http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). METHODS: A model was built to assess policy scenarios' impact on the pharmaceutical budgets of seven member states of the EU, namely France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. The following scenarios were tested: expanding the UK policies to EU, changing time to market access, modifying generic price and penetration, shifting the distribution chain of biosimilars (retail/hospital). RESULTS: Applying the UK policy resulted in dramatic savings for Germany (10 times the base case forecast) and substantial additional savings for France and Portugal (2 and 4 times the base case forecast, respectively). Delaying time to market was found be to a very powerful tool to reduce pharmaceutical expenditure. Applying the EU transparency directive (6-month process for pricing and reimbursement) increased pharmaceutical expenditure for all countries (from 1.1 to 4 times the base case forecast), except in Germany (additional savings). Decreasing the price of generics and boosting the penetration rate, as well as shifting distribution of biosimilars through hospital chain were also key methods to reduce pharmaceutical expenditure. Change in the level of reimbursement rate to 100% in all countries led to an important increase in the pharmaceutical budget. CONCLUSIONS: Forecasting pharmaceutical expenditure is a critical exercise to inform policy decision makers. The most important leverages identified by the model on pharmaceutical budget were driven by generic and biosimilar prices, penetration rate, and distribution. Reducing, even slightly, the prices of generics had a major impact on savings. However, very aggressive pricing of generic and biosimilar products might make this market unattractive and can be counterproductive. Worth noting, delaying time to access innovative products was also identified as an effective leverage to increase savings but might not be a desirable policy for breakthrough products. Increasing patient financial contributions, either directly or indirectly via their private insurances, is a more likely scenario rather than expanding the national pharmaceutical expenditure coverage.
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BACKGROUND AND OBJECTIVES: With constant incentives for healthcare payers to contain their pharmaceutical budgets, forecasting has become critically important. Some countries have, for instance, developed pharmaceutical horizon scanning units. The objective of this project was to build a model to assess the net effect of the entrance of new patented medicinal products versus medicinal products going off-patent, with a defined forecast horizon, on selected European Union (EU) Member States' pharmaceutical budgets. This model took into account population ageing, as well as current and future country-specific pricing, reimbursement, and market access policies (the project was performed for the European Commission; see http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). METHOD: In order to have a representative heterogeneity of EU Member States, the following countries were selected for the analysis: France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. A forecasting period of 5 years (2012-2016) was chosen to assess the net pharmaceutical budget impact. A model for generics and biosimilars was developed for each country. The model estimated a separate and combined effect of the direct and indirect impacts of the patent cliff. A second model, estimating the sales development and the risk of development failure, was developed for new drugs. New drugs were reviewed individually to assess their clinical potential and translate it into commercial potential. The forecast was carried out according to three perspectives (healthcare public payer, society, and manufacturer), and several types of distribution chains (retail, hospital, and combined retail and hospital). Probabilistic and deterministic sensitivity analyses were carried out. RESULTS: According to the model, all countries experienced drug budget reductions except Poland (+41 million). Savings were expected to be the highest in the United Kingdom (-9,367 million), France (-5,589 million), and, far behind them, Germany (-831 million), Greece (-808 million), Portugal (-243 million), and Hungary (-84 million). The main source of savings came from the cardiovascular, central nervous system, and respiratory areas and from biosimilar entries. Oncology, immunology, and inflammation, in contrast, lead to additional expenditure. The model was particularly sensitive to the time to market of branded products, generic prices, generic penetration, and the distribution of biosimilars. CONCLUSIONS: The results of this forecast suggested a decrease in pharmaceutical expenditure in the studied period. The model was sensitive to pharmaceutical policy decisions.
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BACKGROUND AND OBJECTIVE: The value appreciation of new drugs across countries today features a disruption that is making the historical data that are used for forecasting pharmaceutical expenditure poorly reliable. Forecasting methods rarely addressed uncertainty. The objective of this project was to propose a methodology to perform pharmaceutical expenditure forecasting that integrates expected policy changes and uncertainty (developed for the European Commission as the 'EU Pharmaceutical expenditure forecast'; see http://ec.europa.eu/health/healthcare/key_documents/index_en.htm). METHODS: 1) Identification of all pharmaceuticals going off-patent and new branded medicinal products over a 5-year forecasting period in seven European Union (EU) Member States. 2) Development of a model to estimate direct and indirect impacts (based on health policies and clinical experts) on savings of generics and biosimilars. Inputs were originator sales value, patent expiry date, time to launch after marketing authorization, price discount, penetration rate, time to peak sales, and impact on brand price. 3) Development of a model for new drugs, which estimated sales progression in a competitive environment. Clinical expected benefits as well as commercial potential were assessed for each product by clinical experts. Inputs were development phase, marketing authorization dates, orphan condition, market size, and competitors. 4) Separate analysis of the budget impact of products going off-patent and new drugs according to several perspectives, distribution chains, and outcomes. 5) Addressing uncertainty surrounding estimations via deterministic and probabilistic sensitivity analysis. RESULTS: This methodology has proven to be effective by 1) identifying the main parameters impacting the variations in pharmaceutical expenditure forecasting across countries: generics discounts and penetration, brand price after patent loss, reimbursement rate, the penetration of biosimilars and discount price, distribution chains, and the time to reach peak sales for new drugs; 2) estimating the statistical distribution of the budget impact; and 3) testing different pricing and reimbursement policy decisions on health expenditures. CONCLUSIONS: This methodology was independent of historical data and appeared to be highly flexible and adapted to test robustness and provide probabilistic analysis to support policy decision making.