What is the Safety of COVID-19 Vaccines in Immunocompromised Patients? Results from the European "Covid Vaccine Monitor" Active Surveillance Study.

BACKGROUND: The safety profile of COVID-19 vaccines in immunocompromised patients has not been comprehensively evaluated. AIM: To measure the frequency of patient-reported adverse drug reactions (ADRs) related to the first/second/booster dose of COVID-19 vaccine in immunocompromised subject versus matched cohort. As a secondary objective, the time course, evaluated as time to onset (TTO) and time to recovery (TTR), of COVID-19 vaccine-related ADRs was explored. METHODS: A prospective cohort study, based on electronic questionnaires filled by vaccinees from 11 European countries in the period February 2021 to February 2023 was conducted. All immunocompromised vaccinees who provided informed consent and registered to the project's web-app within 48 h after first/booster vaccine dose administration of any EMA-authorised COVID-19 vaccine were recruited. Participants filled baseline and up to six follow-up questionnaires (FU-Qs) over 6 months from vaccination, collecting information on suspected COVID-19 vaccine-related ADRs. As a control group, non-immunocompromised vaccinees from the same source population were 1:4 matched by sex, age, vaccine dose, and brand. A descriptive analysis of demographic/clinical characteristics of vaccinees was conducted. Heatmaps of the frequency of solicited ADRs, stratified by gender and vaccine brand, were generated. Median TTO/TTR of reported ADRs were visualised using violin/box-plots. RESULTS: A total of 773 immunocompromised vaccines were included in the analyses. Most participants were females (F/M ratio: 2.1 and 1.6) with a median age of 56 (43-74) and 51 (41-60) years, at the first vaccination cycle and booster dose, respectively. Injection-site pain and fatigue were the most frequently reported ADRs in immunocompromised vaccinees with higher frequency than matched control, especially after the first dose (41.2% vs 37.8% and 38.2% vs 32.9%, respectively). For both cohorts, all solicited ADRs were more frequently reported in females than males, and in those who had received a first dose of the Vaxzevria vaccine. Dizziness was the most frequently reported unsolicited ADR after the first dose in both groups (immunocompromised subjects: 2.5% and matched controls: 2.1%). At the booster dose, lymphadenopathy (3.9%) and lymphadenitis (1.8%) were the most reported unsolicited ADRs for immunocompromised subjects and matched controls, respectively. A very low number of subjects reported adverse event of special interest (AESI) (2 immunocompromised, 3 matched controls) and serious ADRs (5 immunocompromised, 5 matched controls). A statistically significant difference among study cohorts was observed for median TTO after the booster dose, and for median TTR after the first vaccination cycle and booster dose (p < 0.001). CONCLUSION: The overall safety profile of COVID-19 vaccines in immunocompromised people was favourable, with minor differences as compared to non-immunocompromised vaccinees. Participants mostly experienced mild ADRs, mainly reported after the first dose of Vaxzevria and Jcovden vaccines. Serious ADRs and AESI were rare.

Development and Validation of a META-Algorithm to Identify the Indications of Use of Biological Drugs Approved for the Treatment of Immune-Mediated Inflammatory Diseases from Claims Databases: Insights from the VALORE Project.

Purpose: This research aimed to develop and validate a META-algorithm combining individual immune-mediated inflammatory disease (IMID)-specific algorithms to identify the exact IMID indications for incident biological drug users from claims data within the context of the Italian VALORE project. Methods and Patients: All subjects with at least one dispensing of TNF-alpha inhibitors, anti-interleukin agents, and selective immunosuppressants approved for IMIDs were identified from claims databases of Latium region in Italy (observation period: 2010-2020). Validated coding algorithms for identifying individual IMIDs from claims databases were found from published literature and combined into a META-algorithm. Positive predictive value (PPV), sensitivity (Se), negative predictive value (NPV), specificity (Sp), and accuracy (Acc) were estimated for each indication against the electronic therapeutic plans (ETPs) of the Latium region as the reference standard. Lastly, the frequency of the indication of use across individual biologic drugs was compared with that reported in three other Italian regions (Lombardy, Apulia, and the Veneto region). Results: In total, 9755 incident biological drug users with a single IMID indication were identified. Using the newly developed META-algorithm, an indication of use was detected in 95% (n=9255) of the total cohort. The estimated Acc, Se, Sp, PPV, and NPV, against the reference standard were as follows: 0.96, 0.86, 0.97, 0.82, and 0.98 for Crohn's disease, 0.96, 0.80, 0.98, 0.85, and 0.97 for ulcerative colitis, 0.93, 0.76, 0.99, 0.95, and 0.92 for rheumatoid arthritis, 0.97, 0.75, 0.99, 0.85, and 0.98 for spondylarthritis, and 0.91, 0.92, 0.91, 0.88, and 0.94 for psoriatic arthritis/psoriasis, respectively. Additionally, no substantial difference was observed in the frequency of indication of use by active ingredient among Latium and the other three Italian regions included in the study. Conclusion: The newly developed META-algorithm demonstrated high validity estimates in the Italian claims data and was capable of discriminating with good performance among the most frequent IMID indications.

In the claims database, the lack of information on the indication of use represents a well-known limitation for the conduct of observational studies. This study was conducted to develop and validate a META-algorithm that accurately identifies the exact indication for the use of biological drugs in treating various immune-mediated inflammatory diseases. Using claims databases from the Latium region, we developed and validated a META-algorithm. The META-algorithm combines disease-specific algorithms for different immune-mediated inflammatory diseases (ie, Crohn's disease, ulcerative colitis, rheumatoid arthritis, spondyloarthritis, psoriasis, and psoriatic arthritis) and was tested against a reference standard (electronic therapeutic plans of the Lazio region). The META-algorithm reported high validity estimates and was able to distinguish with a good performance among the most frequent IMIDs as indications for use. Applying this META-algorithm may facilitate post-marketing surveillance of biological drugs such as TNF-alpha inhibitors, anti-interleukin, and selective immunosuppressants in specific therapeutic areas in an Italian setting.

Switching patterns of biological drugs in patients with psoriasis and psoriatic arthritis: insight from the VALORE database network.

BACKGROUND: Switch patterns among different biologics and from originators to biosimilars (and vice versa) can be complex in patients with psoriasis (PsO) and psoriatic arthritis (PsA). OBJECTIVE: The aim of this study was to describe switching patterns of biological drugs in PsO/PsA patients and to explore predictors of multiple switches and switch-back. RESEARCH DESIGN AND METHODS: A large-scale retrospective cohort study was conducted using the Italian VALORE database. Bio-naïve users treated for PsO/PsA during 2010-2022 were included. Time to switch/swap and predictors of multiple switches and switch-back were analyzed. RESULTS: Thirty-thousand seven hundred bio-naïve users were included. At 3 and 5 years of follow-up, patients with at least one switch/swap were 37.1% and 47.8%, respectively. The median time to first switch/swap was significantly shorter (p< 0.001) for TNF-α inhibitors (2,068 days) than anti-IL (2,780 days). At 1 year of follow-up patients starting with IL-23 switched/swapped biological therapy less frequently than those with anti-IL-12/23 and anti-IL-17 (4.9% vs. 8.7% and 9.4%, respectively). Patients starting with anti-IL-12/23 reported a significantly lower risk of multiple switches and switch-back (0.74, 95% CI, 0.67-0.83; 0.58, 95% CI, 0.44-0.77, respectively) than those with TNF-α inhibitors. CONCLUSIONS: Patients with PsO/PsA starting with TNF-α inhibitors switch/swap more rapidly and frequently than those with anti-IL, which are also associated with a reduced risk of multiple switches during follow-up.

Epidemiological analysis to identify predictors of X-linked hypophosphatemia (XLH) diagnosis in an Italian pediatric population: the EPIX project.

PURPOSE: X-linked hypophosphatemia (XLH) is a rare multi-systemic disease characterized by low plasma phosphate levels. The aim of this study was to investigate the annual XLH prevalence and internally evaluate predictive algorithms' application performance for the early diagnosis of XLH. METHODS: The PediaNet database, containing data on more than 400,000 children aged up to 14 years, was used to identify a cohort of XLH patients, which were matched with up to 10 controls by date of birth and gender. The annual prevalence of XLH cases per 100,000 patients registered in PediaNet database was estimated. To identify possible predictors associated with XLH diagnosis, a logistic regression model and two machine learning algorithms were applied. Predictive analyses were separately carried out including patients with at least 1 or 2 years of database history in PediaNet. RESULTS: Among 431,021 patients registered in the PediaNet database between 2007-2020, a total of 12 cases were identified with a mean annual prevalence of 1.78 cases per 100,000 patients registered in PediaNet database. Overall, 8 cases and 60 matched controls were included in the analysis. The random forest algorithm achieved the highest area under the receiver operating characteristic curve (AUC) value both in the one-year prior ID (AUC = 0.99, 95% CI = 0.99-1.00) and the two-year prior ID (AUC = 1.00, 95% CI = 1.00-1.00) analysis. Overall, the XLH predictors selected by the three predictive methods were: the number of vitamin D prescriptions, the number of recorded diagnoses of acute respiratory infections, the number of prescriptions of antihistamine for systemic use, the number of prescriptions of X-ray of the lower limbs and pelvis and the number of allergology visits. CONCLUSION: Findings showed that data-driven machine learning models may play a prominent role for the prediction of the diagnosis of rare diseases such as XLH.

Safety Monitoring of COVID-19 Vaccines in Persons with Prior SARS-CoV-2 Infection: A European Multi-Country Study.

In all pivotal trials of COVID-19 vaccines, the history of previous SARS-CoV-2 infection was mentioned as one of the main exclusion criteria. In the absence of clinical trials, observational studies are the primary source for evidence generation. This study aims to describe the patient-reported adverse drug reactions (ADRs) following the first COVID-19 vaccination cycle, as well as the administration of booster doses of different vaccine brands, in people with prior SARS-CoV-2 infection, as compared to prior infection-free matched cohorts of vaccinees. A web-based prospective study was conducted collecting vaccinee-reported outcomes through electronic questionnaires from eleven European countries in the period February 2021-February 2023. A baseline questionnaire and up to six follow-up questionnaires collected data on the vaccinee's characteristics, as well as solicited and unsolicited adverse reactions. Overall, 3886 and 902 vaccinees with prior SARS-CoV-2 infection and having received the first dose or a booster dose, respectively, were included in the analysis. After the first dose or booster dose, vaccinees with prior SARS-CoV-2 infection reported at least one ADR at a higher frequency than those matched without prior infection (3470 [89.6%] vs. 2916 [75.3%], and 614 [68.2%] vs. 546 [60.6%], respectively). On the contrary side, after the second dose, vaccinees with a history of SARS-CoV-2 infection reported at least one ADR at a lower frequency, compared to matched controls (1443 [85.0%] vs. 1543 [90.9%]). The median time to onset and the median time to recovery were similar across all doses and cohorts. The frequency of adverse reactions was higher in individuals with prior SARS-CoV-2 infection who received Vaxzevria as the first dose and Spikevax as the second and booster doses. The frequency of serious ADRs was low for all doses and cohorts. Data from this large-scale prospective study of COVID-19 vaccinees could be used to inform people as to the likelihood of adverse effects based on their history of SARS-CoV-2 infection, age, sex, and the type of vaccine administered. In line with pivotal trials, the safety profile of COVID-19 vaccines was also confirmed in people with prior SARS-CoV-2 infection.

Machine learning-based algorithms applied to drug prescriptions and other healthcare services in the Sicilian claims database to identify acromegaly as a model for the earlier diagnosis of rare diseases.

Acromegaly is a rare disease characterized by a diagnostic delay ranging from 5 to 10 years from the symptoms' onset. The aim of this study was to develop and internally validate machine-learning algorithms to identify a combination of variables for the early diagnosis of acromegaly. This retrospective population-based study was conducted between 2011 and 2018 using data from the claims databases of Sicily Region, in Southern Italy. To identify combinations of potential predictors of acromegaly diagnosis, conditional and unconditional penalized multivariable logistic regression models and three machine learning algorithms (i.e., the Recursive Partitioning and Regression Tree, the Random Forest and the Support Vector Machine) were used, and their performance was evaluated. The random forest (RF) algorithm achieved the highest Area under the ROC Curve value of 0.83 (95% CI 0.79-0.87). The sensitivity in the test set, computed at the optimal threshold of predicted probabilities, ranged from 28% for the unconditional logistic regression model to 69% for the RF. Overall, the only diagnosis predictor selected by all five models and algorithms was the number of immunosuppressants-related pharmacy claims. The other predictors selected by at least two models were eventually combined in an unconditional logistic regression to develop a meta-score that achieved an acceptable discrimination accuracy (AUC = 0.71, 95% CI 0.66-0.75). Findings of this study showed that data-driven machine learning algorithms may play a role in supporting the early diagnosis of rare diseases such as acromegaly.

Depth effect on point shear wave velocity elastography: Evidence in a chronic hepatitis C patient cohort.

Background and Aims: This study investigated the depth-related bias and the influence of scan plane angle on performance of point-shear-wave elastometry in a chronic hepatitis C patient cohort. Materials and Methods: We included 104 patients affected by chronic liver disease related to the hepatitis C virus. Liver surface nodularity was the reference to diagnose cirrhosis. The ultrasound platform was the Siemens S2000, equipped with point-shear-wave elastometry software. Measurements were obtained in left lateral decubitus from the liver surface to the maximum depth of 8 cm in two orthogonal scan planes according to a standard sampling plane. Scatterplot and box plots explored the depth-related bias graphically. The area under the receiver operating characteristic was used to determine the point-shear-wave elastometry diagnostic performance at progressive depths according to liver surface nodularity. Results: Of the 104 patients, 68 were cirrhotics. Depth-related bias equally modified point-shear-wave elastometry in the two orthogonal scan planes. A better point-shear-wave elastometry diagnostic performance was observed between depths of 4 and 5 cm. The frontal scan plane assured better discrimination between cirrhotic patients and non-cirrhotic patients. Conclusion: Depth is crucial for point-shear-wave elastometry performance. Excellent diagnostic performance at a depth between 4 and 5 cm can also be obtained with a smaller number of measurements than previously recommended.

Comparing clinical trial population representativeness to real-world users of 17 biologics approved for immune-mediated inflammatory diseases: An external validity analysis of 66,639 biologic users from the Italian VALORE project.

To date, no population-based studies have specifically explored the external validity of pivotal randomized clinical trials (RCTs) of biologics simultaneously for a broad spectrum of immuno-mediated inflammatory diseases (IMIDs). The aims of this study were, firstly, to compare the patients' characteristics and median treatment duration of biologics approved for IMIDs between RCTs' and real-world setting (RW); secondly, to assess the extent of biologic users treated for IMIDs in the real-world setting that would not have been eligible for inclusion into pivotal RCT for each indication of use. Using the Italian VALORE distributed database (66,639 incident biologic users), adult patients with IMIDs treated with biologics in the Italian real-world setting were substantially older (mean age ± SD: 50 ± 15 years) compared to those enrolled in pivotal RCTs (45 ± 15 years). In the real-world setting, certolizumab pegol was more commonly used by adult women with psoriasis/ankylosing spondylitis (F/M ratio: 1.8-1.9) compared to RCTs (F/M ratio: 0.5-0.6). The median treatment duration (weeks) of incident biologic users in RW was significantly higher than the duration of pivotal RCTs in almost all indications for use and most biologics (4-100 vs. 6-167). Furthermore, almost half (46.4%) of biologic users from RW settings would have been ineligible for inclusion in the respective indication-specific pivotal RCTs. The main reasons were: advanced age, recent history of cancer and presence of other concomitant IMIDs. These findings suggest that post-marketing surveillance of biologics should be prioritized for those patients.

Exploring the Use of Monoclonal Antibodies and Antiviral Therapies for Early Treatment of COVID-19 Outpatients in a Real-World Setting: A Nationwide Study from England and Italy.

BACKGROUND: Real-world data on early treatment of coronavirus disease 2019 (COVID-19) outpatients with newly approved therapies are sparse. AIM: To explore the pattern of use of monoclonal antibodies (mAbs)/antiviral therapies approved for early COVID-19 treatment in non-hospitalized patients from England and Italy from December 2021 to October 2022. METHODS: Public national dashboards on weekly mAb/antiviral use and/or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection diagnoses from the Italian Medicines Agency, the Italian National Institute of Health, National Health Service in England and the UK Government were explored. Prevalence of antiviral use in outpatients during the entire study period and every two weeks was calculated, as a whole and by class and compounds. An interrupted time-series (ITS) analysis was carried out to assess the impact of predominant SARS-CoV-2 variants over time on the prevalence of use of mAbs/antivirals in England and Italy. RESULTS: Overall, 77,469 and 195,604 doses of mAbs/antivirals were respectively administered to a total of 10,630,903 (7.3 per 1000) and 18,168,365 (10.8 per 1000) patients diagnosed with SARS-CoV-2 infection in England and Italy. Prevalence of use every two weeks increased from 0.07% to 3.1% in England and 0.9% to 2.3% in Italy during the study period. Regarding individual compounds, sotrovimab (prevalence of use, 1.6%) and nirmatrelvir/ritonavir (1.6%) in England, and nirmatrelvir/ritonavir (1.7%) and molnupiravir (0.5%) in Italy, reported the highest prevalence during a 2-week period. In the ITS analysis, the transition from Delta to Omicron variant predominance was associated with a significant increase in the use of sotrovimab, molnupiravir, remdesivir and nirmatrelvir/ritonavir in both England and Italy, with a reduction of other marketed mAbs. The extent of the increase was higher in England than in Italy for all these drugs except for nirmatrelvir/ritonavir. CONCLUSIONS: In this dual nationwide study, the prevalence of use of mAbs/antivirals against SARS-CoV-2 for early outpatients' treatment increased slowly up to 2.0-3.0% of all patients diagnosed with SARS-CoV-2 infection in both England and Italy from December 2021 to October 2022. The trend of individual drug use varied in relation to predominant SARS-CoV-2 variants with some differences across countries. In line with scientific societies' guidelines, nirmatrelvir/ritonavir was the most frequently prescribed antiviral in both countries in the most recent period.

Testing of Coding Algorithms for Inflammatory Bowel Disease Identification, as Indication for Use of Biological Drugs, Using a Claims Database from Southern Italy.

Background: Inflammatory bowel diseases (IBDs), Crohn's disease (CD) and ulcerative colitis (UC), are chronic diseases that have been increasingly treated with biological drugs in recent years. Newly developed coding algorithms for IBD identification using claims databases are needed to improve post-marketing surveillance of biological drugs. Objective: To test algorithms to identify CD and UC, as indication for use of biological drugs approved for IBD treatment, using a claims database. Methods: Data were extracted from the Caserta Local Health Unit database between 2015 and 2018. CD/UC diagnoses reported by specialists in electronic therapeutic plans (ETPs) were considered as gold standard. Five algorithms were developed based on ICD-9-CM codes as primary cause of hospital admissions, exemption from healthcare service co-payment codes and drugs dispensing with only indication for CD/UC. The accuracy was assessed by sensitivity (Se), specificity (Sp), positive (PPV) and negative predicted values (NPV) along with computation of the Youden Index and F-score. Results: In the study period, 1205 subjects received at least one biological drug dispensing approved for IBD and 134 (11.1%) received ≥1 ETP with IBD as use indication. Patients with CD and CU were 83 (61.9%) and 51 (38.1%), respectively. Sensitivity of the different algorithms ranged from 71.1% (95% CI: 60.1-80.5) to 98.8 (95% CI: 93.5-100.0) for CD and from 64.7% (95% CI: 50.1-77.6) to 94.1 (95% CI: 83.8-98.8) for UC, while specificity was always higher than 91%. The best CD algorithm was "Algorithm 3", based on hospital CD diagnosis code OR CD exemption code OR [IBD exemption code AND dispensing of non-biological drugs with only CD indication] (Se: 98.8%; Sp: 97.2%; PPV: 84.5%, NPV: 99.8%), achieving the highest diagnostic accuracy (Youden Index=0.960). The best UC algorithm was "Algorithm 3", based on specific hospital UC diagnosis code OR UC exemption code OR [IBD exemption code AND golimumab dispensing] OR dispensing of non-biological drugs with only UC indication (Se: 94.1%; Sp: 91.6%; PPV: 50.0%; NPV: 99.4%), and achieving the highest diagnostic accuracy (Youden Index=0.857). Conclusion: In a population-based claims database, newly coding algorithms including diagnostic and exemption codes plus specific drug dispensing yielded highly accurate identification of CD and UC as distinct indication for biological drug use.

Development and testing of diagnostic algorithms to identify patients with acromegaly in Southern Italian claims databases.

Acromegaly is a rare disease characterized by an excessive production of growth-hormone and insulin-like growth factor 1, typically resulting from a GH-secreting pituitary adenoma. This study was aimed at comparing and measuring accuracy of newly and previously developed coding algorithms for the identification of acromegaly using Italian claims databases. This study was conducted between January 2015 and December 2018, using data from the claims databases of Caserta Local Health Unit (LHU) and Sicily Region in Southern Italy. To detect acromegaly cases from the general target population, four algorithms were developed using combinations of diagnostic, surgical procedure and co-payment exemption codes, pharmacy claims and specialist's visits. Algorithm accuracy was assessed by measuring the Youden Index, sensitivity, specificity, positive and negative predictive values. The percentage of positive cases for each algorithm ranged from 7.9 (95% CI 6.4-9.8) to 13.8 (95% CI 11.7-16.2) per 100,000 inhabitants in Caserta LHU and from 7.8 (95% CI 7.1-8.6) to 16.4 (95% CI 15.3-17.5) in Sicily Region. Sensitivity of the different algorithms ranged from 71.1% (95% CI 54.1-84.6%) to 84.2% (95% CI 68.8-94.0%), while specificity was always higher than 99.9%. The algorithm based on the presence of claims suggestive of acromegaly in ≥ 2 different databases (i.e., hospital discharge records, copayment exemptions registry, pharmacy claims and specialist visits registry) achieved the highest Youden Index (84.2) and the highest positive predictive value (34.8; 95% CI 28.6-41.6). We tested four algorithms to identify acromegaly cases using claims databases with high sensitivity and Youden Index. Despite identifying rare diseases using real-world data is challenging, this study showed that robust validity testing may yield the identification of accurate coding algorithms.

Overview of the European post-authorisation study register post-authorization studies performed in Europe from September 2010 to December 2018.

BACKGROUND: The European post-authorisation study (EU PAS) register is a repository launched in 2010 by the European Medicines Agency (EMA). All EMA-requested PAS, commonly observational studies, must be recorded in this register. Multi-database studies (MDS) leveraging secondary data have become an important strategy to conduct PAS in recent years, as reflected by the type of studies registered in the EU PAS register. OBJECTIVES: To analyse and describe PAS in the EU PAS register, with focus on MDS. METHODS: Studies in the EU PAS register from inception to 31st December 2018 were described concerning transparency, regulatory obligations, scope, study type (e.g., observational study, clinical trial, survey, systematic review/meta-analysis), study design, type of data collection and target population. MDS were defined as studies conducted through secondary use of >1 data source not linked at patient-level. Data extraction was carried out independently by 14 centres with expertise in pharmacoepidemiology, using publicly available information in the EU PAS register including study protocol, whenever available, using a standardised data collection form. For validation purposes, a second revision of key fields for a 15% random sample of studies was carried out by a different centre. The inter-rater reliability (IRR) was then calculated. Finally, to identify predictors of primary data collection-based studies/versus those based on secondary use of healthcare databases) or MDS (vs. non-MDS), odds ratios (OR) and 95% confidence intervals (CI) were calculated fitting univariate logistic regression models. RESULTS: Overall, 1426 studies were identified. Clinical trials (N = 30; 2%), systematic reviews/meta-analyses (N = 16; 1%) and miscellaneous study designs (N = 46; 3%) were much less common than observational studies (N = 1227; 86%). The protocol was available for 63% (N = 360) of 572 observational studies requested by a competent authority. Overall, 36% (N = 446) of observational studies were based fully or partially on primary data collection. Of 757 observational studies based on secondary use of data alone, 282 (37%) were MDS. Drug utilisation was significantly more common as a study scope in MDS compared to non-MDS studies. The overall percentage agreement among collaborating centres that collected the data concerning study variables was highest for study type (93.5%) and lowest for type of secondary data (67.8%). CONCLUSIONS: Observational studies were the most common type of studies in the EU PAS register, but 30% used primary data, which is more resource-intensive. Almost half of observational studies using secondary data were MDS. Data recording in the EU PAS register may be improved further, including more widespread availability of study protocols to improve transparency.

Large-Scale Postmarketing Surveillance of Biological Drugs for Immune-Mediated Inflammatory Diseases Through an Italian Distributed Multi-Database Healthcare Network: The VALORE Project.

BACKGROUND: Biological drugs have improved the management of immune-mediated inflammatory diseases (IMIDs) despite being associated with important safety issues such as immunogenicity, infections, and malignancies in real-world settings. OBJECTIVE: The aim of this study was to explore the potential of a large Italian multi-database distributed network for use in the postmarketing surveillance of biological drugs, including biosimilars, in patients with IMID. METHODS: A retrospective cohort study was conducted using 13 Italian regional claims databases during 2010-2019. A tailor-made R-based tool developed for distributed analysis of claims data using a study-specific common data model was customized for this study. We measured the yearly prevalence of biological drug users and the frequency of switches between originator and biosimilars for infliximab, etanercept, and adalimumab separately and stratified them by calendar year and region. We then calculated the cumulative number of users and person-years (PYs) of exposure to individual biological drugs approved for IMIDs. For a number of safety outcomes (e.g., severe acute respiratory syndrome coronavirus 2 [SARS-COV-2] infection), we conducted a sample power calculation to estimate the PYs of exposure required to investigate their association with individual biological drugs approved for IMIDs, considering different strengths of association. RESULTS: From a total underlying population of almost 50 million inhabitants from 13 Italian regions, we identified 143,602 (0.3%) biological drug users, with a cumulative exposure of 507,745 PYs during the entire follow-up. The mean age ± standard deviation of biological drug users was 49.3 ± 16.3, with a female-to-male ratio of 1.2. The age-adjusted yearly prevalence of biological drug users increased threefold from 0.7 per 1000 in 2010 to 2.1 per 1000 in 2019. Overall, we identified 40,996 users of biosimilars of tumor necrosis factor (TNF)-α inhibitors (i.e., etanercept, adalimumab, and infliximab) in the years 2015-2019. Of these, 46% (N = 18,845) switched at any time between originator and biosimilars or vice versa. To investigate a moderate association (incidence rate ratio 2) between biological drugs approved for IMIDs and safety events of interest, such as optic neuritis (lowest background incidence rate 10.4/100,000 PYs) or severe infection (highest background incidence rate 4312/100,000 PYs), a total of 43,311 PYs and 104 PYs of exposure to individual biological drugs, respectively, would be required. As such, using this network, of 15 individual biological drugs approved for IMIDs, the association with those adverse events could be investigated for four (27%) and 14 (93%), respectively. CONCLUSION: The VALORE project multi-database network has access to data on more than 140,000 biological drug users (and > 0.5 million PYs) from 13 Italian regions during the years 2010-2019, which will be further expanded with the inclusion of data from other regions and more recent calendar years. Overall, the cumulated amount of person-time of exposure to biological drugs approved for IMIDs provides enough statistical power to investigate weak/moderate associations of almost all individual compounds and the most relevant safety outcomes. Moreover, this network may offer the opportunity to investigate the interchangeability of originator and biosimilars of several TNFα inhibitors in different therapeutic areas in real-world settings.

Cancer Patients at Risk for Medication-Related Osteonecrosis of the Jaw. A Case and Control Study Analyzing Predictors of MRONJ Onset.

The goal of this investigation was to identify potential risk factors to predict the onset of medication-related osteonecrosis of the jaw (MRONJ). Through the identification of the multiple variables positively associated to MRONJ, we aim to write a paradigm for integrated MRONJ risk assessment built on the combined analysis of systemic and local risk factors. The characteristics of a cohort of cancer patients treated with zoledronic acid and/or denosumab were investigated; beyond the set of proven risk factors a new potential one, the intake of new molecules for cancer therapy, was addressed. Registered data were included in univariate and multivariate logistic regression analysis in order to individuate significant independent predictors of MRONJ; a propensity score-matching method was performed adjusting by age and sex. Univariate logistic regression analysis showed a significant effect of the parameters number of doses of zoledronic acid and/or denosumab (OR = 1.03; 95% CI = 1.01-1.05; p = 0.008) and chemotherapy (OR = 0.35; 95% CI = 0.17-0.71; p = 0.008). The multiple logistic regression model showed that breast, multiple myeloma, and prostate cancer involved a significantly higher risk compared to lung cancer; a significant effect of the combined variables number of doses of zoledronic acid and/or denosumab (OR = 1.03; 95% CI = 1.01-1.06); p-value = 0.03) and exposure to novel molecule treatment (OR = 34.74; 95% CI = 1.39-868.11; p-value = 0.03) was observed. The results suggest that a risk assessment paradigm is needed for personalized prevention strategies in the light of patient-centered care.

COVID-19 Patient Management in Outpatient Setting: A Population-Based Study from Southern Italy.

Evidence on treatments for early-stage COVID-19 in outpatient setting is sparse. We explored the pattern of use of drugs prescribed for COVID-19 outpatients' management in Southern Italy in the period February 2020-January 2021. This population-based cohort study was conducted using COVID-19 surveillance registry from Caserta Local Health Unit, which was linked to claims databases from the same catchment area. The date of SARS-CoV-2 infection diagnosis was the index date (ID). We evaluated demographic and clinical characteristics of the study drug users and the pattern of use of drugs prescribed for outpatient COVID-19 management. Overall, 40,030 patients were included in the analyses, with a median (IQR) age of 44 (27-58) years. More than half of the included patients were asymptomatic at the ID. Overall, during the study period, 720 (1.8%) patients died due to COVID-19. Azithromycin and glucocorticoids were the most frequently prescribed drugs, while oxygen was the less frequently prescribed therapy. The cumulative rate of recovery from COVID-19 was 84.2% at 30 days from ID and it was lower among older patients. In this study we documented that the drug prescribing patterns for COVID-19 treatment in an outpatient setting from Southern Italy was not supported from current evidence on beneficial therapies for early treatment of COVID-19, thus highlighting the need to implement strategies for improving appropriate drug prescribing in general practice.

Real World Use of Antidiabetic Drugs in the Years 2011-2017: A Population-Based Study from Southern Italy.

Diabetes mellitus is a metabolic disease characterized by chronic hyperglycemia. The availability of new antidiabetic drugs (ADs) has led to complex treatment patterns and to changes in the patterns of specific drug utilization. The aim of this population-based study was to describe the pattern of antidiabetic drugs (ADs) use in Southern Italy in the years 2011-2017, in relation to the updated type 2 diabetes mellitus (T2DM) therapy guidelines. A retrospective cohort study was conducted on T2DM patients using data from the Palermo Local Health Unit (LHU) claims database and diabetologist registry. The first-line treatment was investigated and incident treatments were identified and characterized at baseline in terms of demographics, complications, comorbidities, concomitant drugs and clinical parameters. Persistence to AD treatment was also evaluated. During the study period, one-third of first ever ADs users started the treatment with ADs other than metformin, in contrast to guideline recommendations. Among 151,711 incident AD treatments, the male to female ratio was 1.0 and the median age was 66 (57-75) years. More than half (55.0%) of incident treatments discontinued the therapy during the first year of treatment. In Italy, general practitioners (GPs) can only prescribe first-generation ADs, while the prescription of more recently marketed ADs, such as GLP-1RA, DPP4i and SGLT2i, is restricted to diabetologists only, based on a therapeutic plan. The role of GPs in the management of T2DM in Italy should be re-evaluated.

Combined use of sonographic and elastosonographic parameters can improve the diagnostic accuracy in thyroid nodules at risk of malignancy at cytological examination.

BACKGROUND: Thyroid nodules diagnosed as Thy3B at fine-needle aspiration biopsy have a relevant risk of malignancy (15-30%) and are usually addressed to surgery. However surgery will result unnecessary in most cases. The present study aims at evaluating the possible increase of diagnostic accuracy for predicting malignancy using novel sonographic and elastographic parameters. METHODS: In fifty patients undergoing thyroidectomy because of a Thy3B thyroid nodule, sonographic and elastosonographic evaluation was carried out by single operator before surgery. Five sonographic parameters (echogenicity, irregular margins, microcalcifications, intra-nodule blood flow and its irregularity) and two elastosonographic parameters (intra-nodule stiffness and its extension to adjacent tissue) were considered. After obtaining histological diagnosis, diagnostic accuracy was calculated. RESULTS: When the two procedures were analyzed separately, sensitivity, specificity, positive (PPV) and negative (NPV) predictive values were 100%, 85%, 63% and 100% for ultrasonography and 60%, 92.5%, 67%, 90% for elastrosonography, respectively. The newly introduced evaluation procedures increased sensitivity. When a combined sonographic and elastosonographic evaluation was introduced, diagnostic accuracy was significantly improved: when ≥4 out of the seven parameters indicated were present, the risk of malignancy was very high (sensitivity 100%, specificity 92.55%, PPV 77%, NPV 100%). CONCLUSIONS: A novel combined sonographic and elastosonographic parameter evaluation improved diagnostic accuracy for identifying thyroid nodules suspicious of malignancy.

Indoor air quality in schools of a highly polluted south Mediterranean area.

This study aimed at surveying lower secondary schools in southern Italy, in a highly polluted area. A community close to an industrial area and three villages in rural areas was investigated. Indoor temperature, relative humidity (RH), gaseous pollutants (CO2 and NO2 ), selected biological pollutants in indoor dust, and the indoor/outdoor mass concentration and elemental composition of PM2.5 were ascertained. Temperature and RH were within, or close to, the comfort range, while CO2 frequently exceeded the threshold of 1000 ppm, indicating inadequate air exchange rate. In all the classrooms, median NO2 levels were above the WHO threshold value. Dermatophagoides p. allergen concentration was below the sensitizing threshold, while high endotoxin levels were detected in the classrooms, suggesting schools may produce significant risks of endotoxin exposure. Concentration and solubility of PM2.5 elements were used to identify the sources of indoor particles. Indoor concentration of most elements was higher than outdoors. Resuspension was responsible for the indoor increase in soil components. For elements from industrial emission (Cd, Co, Ni, Pb, Sb, Tl, V), the indoor concentration depended on penetration from the outside. For these elements, differences in rural vs industrial concentrations were found, suggesting industrial sources may influence indoor air quality nearby schools.

Relationship between domestic smoking and metals and rare earth elements concentration in indoor PM2.5.

Cigarette smoke is the main source of indoor chemical and toxic elements. Cadmium (Cd), Thallium (Tl), Lead (Pb) and Antimony (Sb) are important contributors to smoke-related health risks. Data on the association between Rare Earth Elements (REE) Cerium (Ce) and Lanthanum (La) and domestic smoking are scanty. To evaluate the relationship between cigarette smoke, indoor levels of PM2.5 and heavy metals, 73 children were investigated by parental questionnaire and skin prick tests. The houses of residence of 41 "cases" and 32 "controls" (children with and without respiratory symptoms, respectively) were evaluated by 48-h PM2.5 indoor/outdoor monitoring. PM2.5 mass concentration was determined by gravimetry; the extracted and mineralized fractions of elements (As, Cd, Ce, La, Mn, Pb, Sb, Sr, Tl) were evaluated by ICP-MS. PM2.5 and Ce, La, Cd, and Tl indoor concentrations were higher in smoker dwellings. When corrected for confounding factors, PM2.5, Ce, La, Cd, and Tl were associated with more likely presence of respiratory symptoms in adolescents. We found that: i) indoor smoking is associated with increased levels of PM2.5, Ce, La, Cd, and Tl and ii) the latter with increased presence of respiratory symptoms in children.

A new sampling method for spleen stiffness measurement based on quantitative acoustic radiation force impulse elastography for noninvasive assessment of esophageal varices in newly diagnosed HCV-related cirrhosis.

In our study, we evaluated the feasibility of a new sampling method for splenic stiffness (SS) measurement by Quantitative Acoustic Radiation Force Impulse Elastography (Virtual Touch Tissue Quantification (VTTQ)).We measured SS in 54 patients with HCV-related cirrhosis of whom 28 with esophageal varices (EV), 27 with Chronic Hepatitis C (CHC) F1-F3, and 63 healthy controls. VTTQ-SS was significantly higher among cirrhotic patients with EV (3.37 m/s) in comparison with controls (2.19 m/s, P<0.001), CHC patients (2.37 m/s, P<0.001), and cirrhotic patients without EV (2.7 m/s, P<0.001). Moreover, VTTQ-SS was significantly higher among cirrhotic patients without EV in comparison with both controls (P<0.001) and CHC patients (P<0.01). The optimal VTTQ-SS cut-off value for predicting EV was 3.1 m/s (AUROC=0.96, sensitivity 96.4%, specificity 88.5%, positive predictive value 90%, negative predictive value 96%, positive likelihood ratio 8.36, and negative likelihood ratio 0.04). In conclusion, VTTQ-SS is a promising noninvasive and reliable diagnostic tool to screen cirrhotic patients for EV and reduce the need for upper gastrointestinal endoscopy. By using our cut-off value of 3.1 m/s, we would avoid endoscopy in around 45% of cirrhotic subjects, with significant time and cost savings.