Drug-Utilization, Healthcare Facilities Accesses and Costs of the First Generation of JAK Inhibitors in Rheumatoid Arthritis.

This study is aimed at describing tofacitinib and baricitinib users by characterizing their prescription and healthcare histories, drug and healthcare utilization patterns, and direct costs from a healthcare system perspective. This retrospective cohort study was performed using Tuscan administrative healthcare databases, which selected two groups of Janus kinase inhibitors (JAKi) incident users (index date) from 1st January 2018 to 31 December 2019 and from 1 January 2018 to 30 June 2019. We included patients ≥18 years old, at least 10 years of data, and six months of follow-up. In the first analysis, we describe mean time, standard deviation (SD), from the first-ever disease-modifying antirheumatic drug (DMARD) to the JAKi, and costs of healthcare facilities and drugs in the 5 years preceding the index date. In the second analysis, we assessed Emergency Department (ED) accesses and hospitalizations for any causes, visits, and costs in the follow-up. In the first analysis, 363 incident JAKi users were included (mean age 61.5, SD 13.6; females 80.7%, baricitinib 78.5%, tofacitinib 21.5%). The time to the first JAKi was 7.2 years (SD 3.3). The mean costs from the fifth to the second year before JAKi increased from 4325 € (0; 24,265) to 5259 € (0; 41,630) per patient/year, driven by hospitalizations. We included 221 incident JAKi users in the second analysis. We observed 109 ED accesses, 39 hospitalizations, and 64 visits. Injury and poisoning (18.3%) and skin (13.8%) caused ED accesses, and cardiovascular (69.2%) and musculoskeletal (64.1%) caused hospitalizations. The mean costs were 4819 € (607.5; 50,493) per patient, mostly due to JAKi. In conclusion, the JAKi introduction in therapy occurred in compliance with RA guidelines and the increase in costs observed could be due to a possible selective prescription.

Assessment of automated high-throughput serological assays for prediction of high-titer SARS-CoV-2 neutralizing antibody.

COVID19 convalescent patient plasma units with high titer neutralizing antibody can be used to treat patients with severe disease. Therefore, in order to select suitable donors, neutralizing antibody titer against SARS CoV-2 needs to be determined. Because the neutralization assay is highly demanding from several points of view, a pre-selection of sera would be desirable to minimize the number of sera to be tested. In this study, a total of 140 serum samples that had been titrated for SARS-CoV-2 neutralizing antibody by microneutralization assay were also tested for the presence of anti-SARS-CoV2 antibody using 5 different tests: Architect® immunoassay (Abbott Diagnostics), detecting IgG against the nucleocapsid protein, LIAISON XL® (Diasorin) detecting IgG against a recombinant form of the S1/S2 subunits of the spike protein, VITROS® (Ortho Clinical Diagnostics), detecting IgG against a recombinant form of the spike protein, and ELISA (Euroimmun AG), detecting IgA or IgG against a recombinant form of the S1 subunit. To determine which immunoassay had the highest chance to detect sera with neutralizing antibodies above a certain threshold, we compared the results obtained from the five immunoassays with the titers obtained by microneutralization assay by linear regression analysis and by using receiver operating characteristic curve and Youden's index. Our results indicate that the most suitable method to predict sera with high Nab titer is Euroimmun® IgG, followed closely by Ortho VITROS® Anti-SARS-CoV-2 IgG.

Assessment of serum cytokines predicts clinical and endoscopic outcomes to vedolizumab in ulcerative colitis patients.

AIMS: Vedolizumab (VDZ) prevents migration of activated leucocytes into inflamed mucosa. This study aimed to assess the patterns of serum cytokines in ulcerative colitis (UC) patients at baseline and during VDZ treatment, and to investigate their association with mucosal healing and clinical remission. METHODS: We enrolled consecutive UC patients eligible for treatment with VDZ. A panel of serum cytokines were measured by fluorescence assay at weeks 0, 6 and 22. Colonoscopy was performed at baseline and week 54, to evaluate mucosal healing. The time trends of serum cytokines were analysed by log-linear mixed effect models, and their prognostic accuracy was evaluated by logistic regression. RESULTS: Out of 27 patients included in the analysis, at week 54 mucosal healing was achieved in 12 (44%) and clinical remission in 17 (63%). Mucosal healing was associated with higher interleukin (IL)-8 values at baseline and with significant decrease in IL-6 and IL-8 levels over the first 6 weeks. A significant reduction of IL-6 and IL-8 levels over the first 6 weeks of treatment was associated also with clinical remission. Logistic models including, among the predictors, IL-6 and IL-8 at baseline and their changes over the first 6 weeks of treatment had 83% sensitivity and 87% specificity to predict mucosal healing, and 82% sensitivity and 90% specificity to predict clinical remission. CONCLUSION: In UC patients, the serum patterns of IL-6 and IL-8 at baseline and over the first 6 weeks of treatment with VDZ could be useful to predict therapeutic outcome.

A Systematic Review of Case-Identification Algorithms for 18 Conditions Based on Italian Healthcare Administrative Databases: A Study Protocol.

BACKGROUND: there has been a long-standing, consistent use worldwide of Healthcare Administrative Databases (HADs) for epidemiological purposes, especially to identify acute and chronic health conditions. These databases are able to reflect health-related conditions at a population level through disease-specific case-identification algorithms that combine information coded in multiple HADs. In Italy, in the past 10 years, HAD-based case-identification algorithms have experienced a constant increase, with a significant extension of the spectrum of identifiable diseases. Besides estimating incidence and/or prevalence of diseases, these algorithms have been used to enroll cohorts, monitor quality of care, assess the effect of environmental exposure, and identify health outcomes in analytic studies. Despite the rapid increase in the use of case-identification algorithms, information on their accuracy and misclassification rate is currently unavailable for most conditions. OBJECTIVES: to define a protocol to systematically review algorithms used in Italy in the past 10 years for the identification of several chronic and acute diseases, providing an accessible overview to future users in the Italian and international context. METHODS: PubMed will be searched for original research articles, published between 2007 and 2017, in Italian or English. The search string consists of a combination of free text and MeSH terms with a common part on HADs and a disease-specific part. All identified papers will be screened for eligibility by two independent reviewers. All articles that used/defined an algorithm for the identification of each disease of interest using Italian HADs will be included. Algorithms with exclusive use of death certificates, pathology register, general practitioner or pediatrician data will be excluded. Pertinent papers will be classified according to the objective for which the algorithm was used, and only articles that used algorithms with "primary objectives" (I disease occurrence; II population/cohort selection; III outcome identification) will be considered for algorithm extraction. The HADs used (hospital discharge records, drug prescriptions, etc.), ICD-9 and ICD-10 codes, ATC classification of drugs, follow-back periods, and age ranges applied by the algorithms will be collected. Further information on specific accuracy measures from external validations, sensitivity analyses, and the contribution of each source will be recorded. This protocol will be applied for 16 different systematic reviews concerning eighteen diseases (Hypothyroidism, Hyperthyroidism, Diabetes mellitus, Type 1 diabetes mellitus, Acute myocardial infarction, Ischemic heart disease, Stroke, Hypertension, Heart failure, Congenital heart anomalies, Parkinson's disease, Multiple sclerosis, Epilepsy, Chronic obstructive pulmonary disease, Asthma, Inflammatory bowel disease, Celiac disease, Chronic kidney failure). CONCLUSION: this protocol defines a standardized approach to extensively examine and compare all experiences of case identification algorithms in Italy, on the 18 abovementioned diseases. The methodology proposed may be applied to other systematic reviews concerning diseases not included in this project, as well as other settings, including international ones. Considering the increasing availability of healthcare data, developing standard criteria to describe and update characteristics of published algorithms would be of great use to enhance awareness in the choice of algorithms and provide a greater comparability of results.

A Systematic Review of Case-Identification Algorithms Based on Italian Healthcare Administrative Databases for Three Relevant Diseases of the Cardiovascular System: Acute Myocardial Infarction, Ischemic Heart Disease, and Stroke.

BACKGROUND: acute myocardial infarction (AMI), ischemic heart diseases (IHDs) and stroke are serious cardiovascular diseases (CVDs) which may lead to hospitalizations, require periodical medical monitoring and life-long drugs use, thus having a high impact on public health and Healthcare Service expenditure. In this contest, Italian Healthcare Administrative Databases (HADs), which routinely collect patientlevel information on healthcare services reimbursed by the National Healthcare service, are increasingly used for identification of these CVDs. OBJECTIVES: to identify and describe all AMI, IHDs and stroke case-identification algorithms by means of Italian HADs, through the review of papers published in the past 10 years. METHODS: this study is part of a project that systematically reviewed case-identification algorithms for 18 acute and chronic conditions by means of HADs in Italy. PubMed was searched for original articles, published between 2007 and 2017, in Italian or English. The search string consisted of a combination of free text and MeSH terms with a common part that focused on HADs and a disease-specific part. All identified papers were screened by two independent reviewers. Pertinent papers were classified according to the objective for which the algorithm had been used, and only articles that used algorithms for primary objectives (I disease occurrence; II population/cohort selection; III outcome identification) were considered for algorithm extraction. The HADs used (hospital discharge records, drug prescriptions, etc.), ICD-9 and ICD-10 codes, ATC classification of drugs, follow-back periods, and age ranges applied by the algorithms have been reported. Further information on specific objective(s), accuracy measures, sensitivity analyses and the contribution of each HAD, have also been recorded. RESULTS: the search strategy has led to the identification of 611 papers for AMI,801 for IHDs and 791 for stroke. Among these,45,12 and 31 papers for AMI, IHDs and stroke respectively, were considered pertinent for inclusion in the systematic review. The majority of the works was published during 2014-2017. The setting of the studies was mainly regional for AMI and stroke, while the majority of IHD's papers was based on a national multicenter context. By screening full texts, a total of 17,5 and 28 original algorithms for AMI, IHDs and stroke respectively, intended for the above-mentioned objectives, were found. Moreover, 3 original algorithms for STEMI, 3 for NSTEMI, 8 for ischemic stroke and 3 for hemorrhagic stroke were identified. The hospital discharge diagnosis database (HDD) was used in all algorithms. In only a few cases the co-payment exemption registry, drug prescription database, and mortality registry database were used as additional algorithm components. For the same event, there was always a difference of >=1 code. External validation was performed in only one case for AMI and stroke identification. CONCLUSION: a remarkable heterogeneity, in terms of both data sources and codes used, was observed for algorithms aimed to identify AMI, IHDs and stroke in HADs. This was likely due to the paucity of validation studies. Administrative data sources other than HDD remain underutilized.

The Role of European Healthcare Databases for Post-Marketing Drug Effectiveness, Safety and Value Evaluation: Where Does Italy Stand?

Enormous progress has been made globally in the use of evidence derived from patients' clinical information as they access their routine medical care. The value of real-world data lies in their complementary nature compared with data from randomised controlled trials: less detailed information on drug efficacy but longer observational periods and larger, more heterogeneous study populations reflecting clinical practice because individuals are included who would not usually be recruited in trials. Real-world data can be collected in various types of electronic sources, such as electronic health records, claims databases and drug or disease registries. These data sources vary in nature from country to country, according to national healthcare system structures and national policies. In Italy, a growing number of healthcare databases have been used to evaluate post-marketing drug utilisation and safety in the last two decades. The aim of this narrative review is to describe the available Italian sources of real-world data and their contribution to generating post-marketing evidence on drug use and safety. We also discuss the strengths and limitations of the most commonly used Italian healthcare databases in addressing various research questions concerning drug utilisation, comparative effectiveness and safety studies, as well as health technology assessment and other areas.