Objective A reliable measure of the burden of inflammatory bowel diseases (IBDs), including ulcerative colitis and Crohn’s disease, are essential to monitor their epidemiology and plan appropriate health services. Methods This is a population-based study carried out in the Milan Agency for Health Protection. Incident and prevalent cases were identified according to specific codes in hospital discharges and copayment exemptions. Age-standardized incidence rates were computed for 2015–2018 and yearly rates from 2010 to 2018, as well as annual prevalence and prevalence on 31 December 2018. Incidence and prevalence estimates for Italy were also produced. Results During 2015–2018, 3434 citizens had an IBD diagnosis, 2154 (62.7%) ulcerative colitis and 1.280 (37.3%) Crohn’s disease. Age-adjusted incidence rates were 15.3 [95% confidence interval (CI), 14.7–16.0] for ulcerative colitis and 9.4 (8.9–9.9) for Crohn’s disease. Incidence was stable during 2010–2018 for both diseases. On 31 December 2018, there were 15 141 prevalent patients, corresponding to a proportion of 442.3 every 100 000 inhabitants/year (95% CI, 435.6–449.8). Prevalence proportion has increased to around +10% per year from 2010 to 2018. Projections for Italy assessed the burden of IBD in more than 15 000 new cases/year (55% ulcerative colitis) and around 260 000 prevalent cases (62% ulcerative colitis). Conclusions The exploitation of administrative data provides reliable and up-to-date measures of the burden of disease. Incidence of IBDs is stable while prevalence notably grows. The burden of IBDs and the consequent need for care and follow-up is going to increase in the future.

Background: New oral anticoagulant agents (NOACs) are valid alternatives for vitamin K antagonists (VKA) in patients with non-valvular atrial fibrillation (NVAF) for stroke prevention. In clinical practice, NOACs users may differ from patients enrolled in clinical trials in age or comorbidities, and thus it is a critical issue to evaluate the effectiveness and safety of NOACs in the real-world. Accordingly, we assessed two-year overall mortality and hospital admissions for myocardial infarction, stroke or bleeding in patients with NVAF users of NOACs compared to warfarin-treated patients. Methods: This is a population-based retrospective new user active comparator study. All atrial fibrillation patients who were naïve and not switcher users of oral anticoagulants from January 2017 to December 2019 were included (n = 8543). Data were obtained from the electronic health records of the Milan Agency for Health Protection, Italy. Two-year risks for overall mortality, myocardial infarction, stroke and bleeding were computed using Cox models. Age, sex, number of comorbidities, use of platelet aggregation inhibitors and Proton pump inhibitors and area of residence were used as confounding factors. We also controlled by indication bias-weighting NOACs and warfarin users based on the weights computed by a Kernel propensity score. Results: For all NOACs, we found a decrease in the risks compared with warfarin for mortality (from −25% to −49%), hospitalization for myocardial infarction (from −16% to −27%, statistically significant for apixaban, edoxaban and rivaroxaban) and ischemic stroke (from −23% to −41%, significant for dabigatran and apixaban). The risk of bleeding was decreased for rivaroxaban (−33%) and numerically but not significantly for the other NOACs. Conclusions: After two years of follow-up, in comparison with warfarin, NOACs users showed a significant reduction of overall mortality (all NOACs), hospital admission for myocardial infarction (apixaban and edoxaban), ischemic stroke (dabigatran) and bleeding (rivaroxaban).

To estimate the average treatment effect of immune checkpoint inhibitors in any line of treatment in a 2016-2018 population-based cohort of patients with advanced non-small-cell lung cancer (NSCLC). Materials and methods: The cohort, and information on the tumor, were derived from the cancer registry of the Agency for Health Protection of Milan, Italy. Inclusion criteria were adult age, microscopically confirmed NSCLC, stage IIIB or IV at diagnosis, and having received at least one line of treatment. Treatment with all licensed anti PD-1/PD-L1 inhibitors was derived from inpatients and outpatients' pharmaceutical databases of the ATS and vital status at 31 December 2019 from the health registry office of the Lombardy region. We investigated, with a causal approach, the relationship between survival and anti PD-1/PD-L1 treatment at any line constructing a directed acyclic graph and fitting a Marginal Structural Cox Model (MSCM). Results: Of 1673 subjects, 324 received anti PD-1/PD-L1 at any treatment line. Overall, one-year survival was 61.1% (95 %CI, 55.6-66.2%) in the group treated with anti PD-1/PD-L1 at any line and 31.1% (95 %CI, 28.6-33.5%) among not treated. One-year hazard ratio (HR) of death for not treated vs. treated was 2.15 (95 % CI, 1.91-2.41), decreasing to 1.23 (95 %CI, 1.03-1.46) at two years and reaching one in the third year. Conclusion:In un unselected population-based cohort with advanced lung cancer, treatment with anti PD-1/PD-L1 at any line lowered the hazard of death up to two-years from date of diagnosis, confirming the efficacy of immunotherapy outside clinical trials.

ObjectivesThis study describes a new strategy to reduce the impact of COVID-19 on the elderly and other clinically vulnerable subjects, where general practitioners (GPs) play an active role in managing high-risk patients, reducing adverse health outcomes.DesignRetrospective cohort study.SettingPopulation-based study including subjects resident in the province of Milan and Lodi.Participants127 735 residents older than 70 years, with specific chronic conditions.InterventionsWe developed a predictive algorithm for overall mortality risk based on demographic and clinical characteristics. All residents older than 70 years were classified as being at low or high risk of death from COVID-19 infection according to the algorithm. The high-risk group was assigned to their GPs for telephone triage and consultation. The high-risk cohort was divided into two groups based on GP intervention: patients who were not contacted and patients who were contacted by their GPs.Outcome measuresOverall mortality, COVID-19 morbidity and hospitalisation.ResultsPatients with increased risk of death from COVID-19 were 127 735; 495 669 patients were not at high risk and were not included in the intervention. Out of the high-risk subjects, 79 110 were included but not contacted by their GPs, while 48 625 high-risk subjects were included and contacted. Overall mortality, morbidity and hospitalisation was higher in high-risk patients compared with low-risk populations. High-risk patients contacted by their GPs had a 50% risk reduction in COVID-19 mortality, and a 70% risk reduction in morbidity and hospitalisation for COVID-19 compared with non-contacted patients.ConclusionsThe study showed that, during the COVID-19 outbreak, involvement of GPs and changes in care management of high-risk groups produced a significant reduction in all adverse health outcomes.

Background The COVID-19 pandemic has placed a huge strain on the health care system globally. The metropolitan area of Milan, Italy, was one of the regions most impacted by the COVID-19 pandemic worldwide. Risk prediction models developed by combining administrative databases and basic clinical data are needed to stratify individual patient risk for public health purposes. Objective This study aims to develop a stratification tool aimed at improving COVID-19 patient management and health care organization. Methods A predictive algorithm was developed and applied to 36,834 patients with COVID-19 in Italy between March 8 and the October 9, 2020, in order to foresee their risk of hospitalization. Exposures considered were age, sex, comorbidities, and symptoms associated with COVID-19 (eg, vomiting, cough, fever, diarrhea, myalgia, asthenia, headache, anosmia, ageusia, and dyspnea). The outcome was hospitalizations and emergency department admissions for COVID-19. Discrimination and calibration of the model were also assessed. Results The predictive model showed a good fit for predicting COVID-19 hospitalization (C-index 0.79) and a good overall prediction accuracy (Brier score 0.14). The model was well calibrated (intercept –0.0028, slope 0.9970). Based on these results, 118,804 patients diagnosed with COVID-19 from October 25 to December 11, 2020, were stratified into low, medium, and high risk for COVID-19 severity. Among the overall study population, 67,030 (56.42%) were classified as low-risk patients; 43,886 (36.94%), as medium-risk patients; and 7888 (6.64%), as high-risk patients. In all, 89.37% (106,179/118,804) of the overall study population was being assisted at home, 9% (10,695/118,804) was hospitalized, and 1.62% (1930/118,804) died. Among those assisted at home, most people (63,983/106,179, 60.26%) were classified as low risk, whereas only 3.63% (3858/106,179) were classified at high risk. According to ordinal logistic regression, the odds ratio (OR) of being hospitalized or dead was 5.0 (95% CI 4.6-5.4) among high-risk patients and 2.7 (95% CI 2.6-2.9) among medium-risk patients, as compared to low-risk patients. Conclusions A simple monitoring system, based on primary care data sets linked to COVID-19 testing results, hospital admissions data, and death records may assist in the proper planning and allocation of patients and resources during the ongoing COVID-19 pandemic.