Andrea Pistillo .

Eating disorders (ED) are serious mental illnesses that affect millions of people around the world and entail considerable personal, family, and social costs. It is a hidden public health problem with a great population impact, of which the magnitude in our environment and its characteristics are unknown.
This project aims to characterize and determine the magnitude of eating disorders (ED) in Catalonia, and to describe the social inequalities of people diagnosed with ED in primary care or admitted to hospital.
Specific objectives:
1. To estimate the incidence and prevalence of ED in Catalonia among the individuals diagnosed in primary care or admitted to hospital between 2010 and 2024.
2. To examine, sex, age, nationality, rural/urban setting, and socioeconomic inequalities of ED diagnosis in Catalonia among the individuals who visited primary care or were admitted to the hospital between 2010 and 2024.
3. To identify comorbidities and lifestyle factors associated with ED diagnosed in primary care or admitted to the hospital between 2010 and 2024 in Catalonia.
Study design:
We will conduct a population-based cohort study using individual-level routinely collected Electronic Health Records (EHR) obtained from SIDIAP database.
The study will compromise two consecutive parts:
• Population-level cohort study: This part will estimate the incidence and prevalence of ED in the whole cohort and by specific subgroups (objective 1 and 2)
• Patient-level characterisation: This part aims to estimate comorbidities and associated factors among individuals diagnosed with ED (Obejctive 3).
Study period:
The study period will be from 1st of January 2010 until the end of data availability.
Statistical analyses:
We will estimate monthly incidence and prevalence rates with 95% CI of eating disorders over the study period (2010-2023) in the overall population. Incidence and prevalence will be calculated for the overall of ED and separately for each outcome (anorexia nervosa, bulimia nervosa, binge eating disorder, avoidant/restrictive eating disorder and unspecified eating disorders).
We will stratify our analyses on incidence and prevalence by age, sex, nationality, socioeconomic status (MEDEA), residence type (urban / rural) and other somatic comorbidities. Incidence rate ratios (IRR) with 95%CI will be calculated for each subgroup to compare the differences in the incidence of each strata using negative binomial regression models.
We will explore the effects of explanatory variables such other mental conditions diagnosis (neurodevelopmental disorder, alcohol and substance use disorders, mood and anxiety disorders, personality disorders, obsessive compulsive disorder, impulsivity disorders),, obesity, diabetes and lifestyle factors such as smoking and alcohol risk for each ED.
Finally, we will also conduct a large-scale characterization of the ED cohort to identify the medical conditions in the individuals’ history and compared them to a random subsample of individuals in SIDIAP.

Background
Climate change leading to extreme events represent pressing challenges for humanity. Short- term exposure
to ambient air pollution and temperature has been associated with exacerbations of chronic respiratory
diseases, yet significant knowledge gaps remain regarding specific diseases, such as interstitial lung diseases
and bronchiectasis, and potential adaptation strategies to decrease the risk of exacerbations.
Objectives
To investigate the short-term effects of air pollution and temperature, including their co- occurrence, on
chronic respiratory diseases exacerbations and sick leaves in Catalonia; to evaluate potential adaptation
strategies, including the role of inhaled corticosteroids, statins, SGLT-2 inhibitors, and vaccines in modifying
these effects; to incorporate patient perspectives to understand coping mechanisms against climate change
stressors and disease burden.
Methods
Using a well-characterised cohort with detailed environmental exposure data, we will analyze associations
between air pollution and temperature, and chronic respiratory diseases exacerbations, accounting for
hospitalisations, mortality, and sick leaves. We will apply advanced statistical modelling to disentangle
exposure-outcome relationships, assess effect modification, and integrate a qualitative research approach
to capture patient experiences.
Expected results
Identification of environmental triggers of chronic respiratory disease exacerbations, evaluation of
protective effects of pharmacological and behavioural adaptation measures, and generation of evidence to
inform public health policies and clinical guidelines.

Antecedents: There is a growing evidence in the recent literature of the relationship between exposure to environmental pollutants and the risk of suffering mental health issues. In particular, pollutants such as O3, NO2, PM1, PM2.5 and PM10 are associated with children’s and adolescents’ mental health and neurodevelopment issues. In addition, for children and adolescents, five specific groups of mental health issues have been identified: behavioral and developmental disorders, attention deficit hyperactivity disorder (ADHD), anxiety, eating disorders and other mental health problems. More recently, some studies analyzed the impact of exposure to environmental pollutants on adults’ mental health, but more evidence is needed in this direction, especially accounting for the potential lack of accuracy of national registers of lifetime mental health disorders.
Hipòtesis: The main hypothesis underlying this project is that exposure to environmental pollutants is significantly associated with an increased risk of mental health disorders in children, adolescents, and
adults, with variations in these associations influenced by factors such as age, gender, socioeconomic status, and spatio-temporal dynamics. Environmental pollutants, such as air pollution and toxic substances, are known to have systemic effects on the body, including neuroinflammatory and neurotoxic impacts that may disrupt mental health. These effects are likely to differ across demographic groups due to biological and social factors, such as hormonal differences, varying developmental stages, and unequal exposure levels tied to socioeconomic disparities. By leveraging Bayesian statistical methods, this project seeks to test this hypothesis and explore whether these associations vary across population subgroups and over time, providing a nuanced understanding of the complex interplay between environmental and psychosocial factors in mental health.
Objectius: The main objectives of this project are 1) to develop new statistical methodology to study the association between the exposure to pollutants and mental health and neurodevelopment issues, 2) to account for the potential underregistering of mental health issues in these statistical methods and 3) to use the introduced statistical techniques to analyze the potential association between the exposure to pollutants and mental health and neurodevelopment issues in Catalunya.
Metodologia: The study population will be all Catalan individuals between 3 and 90 years old with a diagnosis within the health mental diseaes using ICD-10 codes and ATC codes from IDIAP and CMDB-SM in the period 2012-2024, with an estimated size around 2,4 million individuals. This project will employ a comprehensive methodological approach combining statistical modeling, mathematical techniques, and epidemiological analysis. A Bayesian-based model will be developed to investigate the association between environmental pollutants and mental health disorders, incorporating key demographic variables such as gender, age, and socioeconomic status, along with spatio-temporal factors. Given the massive size and complexity of the dataset, the project will adapt and extend mathematical techniques, such as the Divide and Recombine framework, within the Bayesian inference paradigm to ensure computational feasibility and scalability. To enhance data reliability, the model will include components to estimate and correct for misreporting of mental health disorders, which will account for potential biases in the dataset. The statistical analysis will explore both direct and interaction effects of pollutants, demographic factors, and temporal trends. This robust methodological framework will generate detailed insights into the relationships between environmental exposures and mental health outcomes while addressing challenges posed by data volume, complexity, and quality.
Aplicabilitat i Rellevància: The findings could provide a scientific basis for policy changes aimed at mitigating environmental pollutants, improving mental health outcomes, and addressing health inequities. The regional focus on Catalunya also allows for localized recommendations, which can be scaled or adapted for broader applications. By combining methodological innovation with practical relevance, this project addresses an urgent need in public health and environmental science. Its outputs could significantly advance our understanding of how environmental factors influence mental health and guide both scientific inquiry and public health policy.

To date, asthma prevalence has been mainly assessed from self or parental-reported questionnaires in cross-sectional studies, implying recall bias. Despite its noteworthy prevalence, its age-specific evolving incidence among children and adolescents remains unclear and region-specific data from Catalonia is scarce.
In this context, comprehensive, population-based data sources such as routinely collected electronic health records (EHR) that capture real-time healthcare information and minimise recall bias, can offer a valuable alternative.
The objective of this study is to investigate time trends in the prevalence and incidence of asthma, among individuals from 0 to 18 years in Catalonia, Spain. We will conduct a population-based open cohort with individual level data from the Information System for Research in Primary Care (SIDIAP) mapped to the OMOP-CDM from 2008 to 2024. We will estimate overall and annual incidence and prevalence of asthma among children and adolescents overall and stratified by sex, age, nationality and socioeconomic status. We will estimate crude and age-standardised rates of asthma. We will also investigate changes in time trends over the study period.
Our study will enable to identify temporal trends in asthma in Catalonia and will inform preventive strategies targeted to specific groups that are more vulnerable, helping to address asthma disparities across different demographics.

Mental disorders are increasing in the last years, in particular after COVID-19 pandemic, but its prevalence and incidence is still not quantified in particular subgroups of population and comparing different countries. We aim to investigate time trends of mental disorders from 2006 to 2024 using large real-world data. We propose to conduct a descriptive study on the prevalence and incidence of common mental problems (i.e. anxiety and depression), severe mental disorders (i.e. schizophrenia and bipolar disorder) and other mental conditions, such as self-harm, sleep disorders, developmental disorders, substance abuse and eating disorders among people of all ages. Using a network of large real-world data sources of primary healthcare, we aim to determine whether the long-term trends of prevalence and incidence of several mental problems remain stable over the time.
We will conduct a population-based cohort study to investigate the temporal trends of several mental conditions and whether the patterns vary according to sex, age groups, socioeconomic deprivation, and nationality. We will calculate the prevalence and incidence rates of diagnoses, prescriptions, and sick leaves/absences due to above-mentioned mental illnesses. The present study will be conducted in multiple databases in the Observational Health Data Sciences and Informatics (OHDSI) network willing to participate, including the Information System for Research in Primary Care (SIDIAP) which contains primary care records for approximately 6 million people in Catalonia, Spain.
Our study will enable to identify temporal trends in mental disorders in Catalonia, and potentially other countries, and will inform preventive strategies targeted to specific groups that are more vulnerable, helping to address mental health disparities across different demographics.

Las enfermedades reumáticas inflamatorias (IRMD) incluyendo la artritis reumatoide (AR), el lupus eritematoso sistémico (LES), la artritis psoriásica (APs), la esclerosis sistémica (SSc) y las espondiloartropatías (Spa) entre otras están asociadas con un aumento significativo de la morbilidad y mortalidad. La carga de enfermedad de dichas patologías en nuestro entorno no es bien conocida. Nuestros objetivos son:
1) Evaluar la carga de enfermedad de IRMD en Cataluña, estimando su prevalencia e incidencia,
2) determinar los factores independientes asociados con las complicaciones de las IRMD en comparación a la población sana, incluyendo la enfermedad coronaria, la enfermedad tromboembólica, la diabetes mellitus, las fracturas osteoporóticas, las infecciones graves, el cáncer y la insuficiencia renal crónica y
3) Estimar el impacto de las IRMD sobre la mortalidad en comparación a la población general.
Para ello proponemos un estudio poblacional retrospectivo que incluirá todos los casos identificados mediante códigos ICD-10 del programa del Sistema de Información para el Desarrollo de la Investigación en Atención Primaria (SIDIAP) del 2006 al 2021. El SIDIAP cuenta con información de mas de 5.7 millones de habitantes e incluye datos demográficos, diagnósticos, prescripciones/dispensaciones y fecha de muerte.
Se utilizará una cohorte de control sin IRMD apareada por el año de nacimiento, género, y estado socio-económico como grupo control.

«Rationale and Background
During the evaluation of the safety results of a clinical trial in patients with severe asthma, differences in rates of serious adverse events were observed in the experimental treatment arm compared to the control arm. In order to contextualise these differences, a non-interventional study was required to generate background rates of selected health outcomes in patients with severe asthma, with a disease definition that follows recently conducted clinical trials. The results of this study may inform future drug-related safety assessments in the same population.
The present study is to produce background information on the occurrence of the health outcomes in adolescent and adult patients with severe asthma using recent data.
Research Methods
Study design
Retrospective cohort studies will be conducted using routinely-collected health data from 5 databases.
The incidence rate of mortality and the outcomes of interest will be assessed using Population Level Disease Epidemiology analytical pipelines from the DARWIN EU Complete Catalogue of Standard Data Analyses.
Population
All individuals present in the database in the period between 01/01/2015 and 31/12/2021, with at least 1 year of prior history, being diagnosed with severe asthma and fulfilling inclusion and exclusion criteria.
Variables
Variables of interest will consist of outcomes, comorbidity, lifestyle factors, measurements and drug exposure data.
Data sources
1. Integrated Primary Care Information Project (IPCI), The Netherlands
2. Sistema d’Informació per al Desenvolupament de la Investigació en Atenció Primària (SIDIAP), Spain
3. Clinical Practice Research Datalink GOLD (CPRD GOLD), United Kingdom
4. Parc Salut Mar Barcelona (PSMAR), Hospital del Mar (IMIM) (hospital database), Spain
5. University of Tartu – Estonian Biobank, Estonia»

This project is part of Andrea Pistillo’s PhD thesis project. A part of the project has received funds from Ajuntament de Barcelona «Subvencions extraordinàries per a projectes de recerca i innovació en col·laboració amb la Fundació La Caixa, 2022». We lead the project from IDIAPJGol and other two institution are partners: ISGlobal and ICTA-BCNUEJ.

Environmental exposures may affect people’s lives. In particular heatwaves and peaks in air pollution had been associated with more mortality and hospitalizations, and a worst life quality. In Barcelona and its metropolitan area, these two types of exposures affect the neighbourhoods in a different way, both for geographic reasons (neighbourhoods nearer to the sea had a milder temperature during daytime) and sociodemographics ones (older population, energy poverty, areas with less green spaces, low education). Higher temperature and air pollution had been linked to respiratory, cardiovascular, mental, perinatal problems and infectious diseases. So far, this problems had been studied in hospital settings and a comprehensive study in primary care is needed to understand both the prevalence of the problems due to these environmental exposures and the burden of this on the primary care system. In this project we aim to analyze the relationship among temperature and air pollution on the health of the citizens of Barcelona and its metropolitan area. We will perform a quantitative study using the newest methodologies (case time series), and we will link daily environmental exposures with three types of health indicators (diagnosis, medications registered in primary care and sick leaves). The focus will be on neighborhoods and will take into account gender perspective and multidisciplinarity, justified with the synergy of the three institutions involved. An important part of the project will be dissemination of results, indeed we will publicly publish a risk map with the results in which citizens and policy makers will be able to interactively visualize the results of the project (at a neighborhood scale).

«Background
The current COVID-19 vaccines include mRNA vaccines, non-replicating viral vector vaccines and traditional inactivated whole virus vaccines. All of them have demonstrated their effectiveness against confirmed COVID-19 infection in previous and ongoing clinical trials However, vulnerable populations, such as pregnant women, children, individuals living in nursing homes, those with cancer, autoimmune diseases, immunodeficiencies or organ transplant recipients were systematically excluded from these trials, limiting the available evidence regarding the efficacy of the COVID-19 vaccines on these patients to retrospective observational studies, and small non-randomized trials with surrogate endpoints (e.g. antibody levels).

Objectives
To estimate coverage and the effectiveness of COVID-19 vaccines against COVID-19-related outcomes in vulnerable populations, overall and by sex, age, baseline comorbidities, and socioeconomic status, using electronic health records from Catalonia, Spain.
1- To provide periodic estimates of vaccine coverage in predefined subgroups of population at risk of being excluded from the general vaccine campaigns (i.e individuals with mental disorder), stratified by vaccine type/brand, vaccine dose, sex, age groups, socioeconomic status, and nationality.
2- To assess the effectiveness of COVID-19 vaccines in vulnerable population against COVID-19 related outcomes (COVID-19 infection, hospitalisation, intensive care admission, or death) in:
2.1- pregnant women and infants up to 12 months of age;
2.2- children and adolescents from the age of 5 to 19 years;
2.3- persons living with immunodeficient conditions, namely cancer, autoimmune conditions, primary immunodeficiencies, people living with HIV infection, organ transplant recipients or people taking immunosuppressive drugs;
2.4- persons living in nursing homes.

Methods
We will conduct a population-based matched cohort study using individual-level routinely-collected electronic health records (EHR) data from the Information System for Research in Primary Care (SIDIAP; www.sidiap.org) database in Catalonia mapped to the OMOP-CDM.

Study population
We will include all women with a pregnancy episode during the study period (mother-child linkage), children and adolescents, as well as those with history of cancer, immunodeficient conditions (HIV, autoimmune diseases, organ transplant recipients) and/or use of immunosuppressive drugs (including high chronic use of corticosteroids, biological and non-biological disease modifying drugs, antineoplastic drugs), persons living in nurse home residencies or persons with mental health conditions of any age, registered for at least 365 days in the SIDIAP database prior to the 27th of December 2020 (date of initiation of the vaccination in Spain) and up to December 2022 and December 2023.

Exposures
Four COVID-19 vaccines will be included: ChAdOx1-S, BNT162b2, mRNA-1273, and Ad26.COV2.S.

Outcomes
The main outcomes to evaluate effectiveness of COVID-19 vaccination will include: 1.SARS-CoV-2 infection will be defined as any confirmed infection identified by diagnostic codes and/or a positive RT-PCR or antigen test result, 2.COVID-19-related hospitalisation will be defined as a hospital admission (at least one night) where the individual had a positive RT-PCR test result or a clinical diagnosis of COVID-19 over the 21 days prior to their admission up to the end of their hospital stay,3. COVID-19-related intensive care unit (ICU) admission in those with COVID-19 related hospitalisation, 4.COVID-19-related death will be defined as death (any cause) registered after a COVID-19-related hospitalisation or 28 days after a SARS-CoV-2 infection.

Covariates
Covariates to be considered in the analyses will include demographics, socioeconomic status, nationality and diagnosis of mental health condition (only for coverage), BMI, pre-existing comorbid conditions, history of COVID-19 infection (6 months previous), period of predominant SARS-CoV-2 variants, number of GP visits per year, pregnancy variables (gestational age at vaccination, parity, breastfeeding, maternal lifestyle behaviour factors (when available).

Follow-up
For individuals from the age of 5 and above follow up will be from their index date to occurrence of an event, end of pregnancy (for pregnancy cohort), death, or loss of visibility in the database (e.g., person leaving the practice in electronic health records data). For cohorts that had received a first vaccine dose, we also censored follow-up if a second dose was observed before 21 days for BNT162b2 and before 27 days for mRNA-1273 and ChAdOx1-S.
The index date for exposed children (up to 12 months of age) will be the date of maternal vaccination. Children will be followed from the index date until occurrence of an event of interest, exit from the database, death, end of pre-defined follow-up time (12 months after birth), or end of data availability, whichever comes first.

Statistical analysis
Vaccination uptake rate will be calculated as the number of persons receiving any COVID-19 vaccines in a certain population subgroup divided by all individuals eligible for vaccination in that group.
We will conduct a new user cohort study, to compare the effectiveness of COVID-19 vaccines against COVID-19-related outcomes. We will use propensity score (PS) matching to minimise the risk of confounding. Vaccinated individuals will be matched in a 1:3 ratio (if sample size allows) with eligible non-vaccinated individuals with no prior history of COVID-19 infection in the past 3 months. Matching will be done taking into account age group, sex, calendar time, baseline comorbidities associated with increased risks of severe COVID-19 (e.g., obesity, diabetes, immunosuppression), and smoking. We will also use a large-scale, data-driven approach to identify additional potential confounders to be included in the PS.

Serious adverse events have been reported among antidementia drug users. We aim to analyse the use and comparative safety of the antidementia drugs in primary care centres in Catalonia (Spain).
Design: A population-based cohort study using real-world primary health care data (SIDIAP database), standardized to the Common Data Model OMOP with hospital linkage (CMBD database). A nested case-control approach will be adopted to assess risk of adverse events (AE) during the study period (2007-2020). Inclusion criteria: for the drug utilization study (DUS) we will include individuals with at least 40 year or older with dementia, registered for at least 1 year before cohort entry and with at least 1 prescription of rivastigmine, galantamine, donepezil or memantine during study period. For the safety study we will include patients from the DUS with an incident use (no previous 365 days use) of any of the study drugs. For the nested case control analysis, we will create a cohort of patients with dementia without treatment (anytime). Exposure (DUS/Safety): prescription of rivastigmine, donepezil, galantamine or memantine. Outcomes: (DUS) demographics, comorbidities, prescriber-type, prescribing pattern and proportion of ‘prescription cascade’ drugs (prescriptions generated to alleviate adverse events). Outcomes (safety study): AEs related to disorders of the skin, cardiovascular, gastrointestinal, neurological, psychiatric, sleep, urinary and respiratory disorders, falls, hospitalizations and all-cause mortality.
Statistics: Yearly age-sex incidence rates (IR) and Kaplan Meier curves to assess the duration and drug discontinuation. Adjusted and unadjusted IR of AEs, Hazard Ratios (95% confidence intervals (CI)) using Cox proportional hazard models, and Odds Ratios (95% CI) using nested case-control analysis with conditional logistic regression will be assessed. Each case will be matched (age, sex, Charlson Comorbidity Index and socioeconomic status) with up to 10 controls.
Expected results: With this large population-based cohort study based on routinely collected primary care data with hospital linkage we expect to provide an in-depth characterization of the population that uses any of the currently commercialised antidementia drugs. Because we are using routinely collected real-world information, which differs from the information gathered in randomized controlled trials, we will be able to provide a more accurate picture of the patients that finally receive the drugs to treat dementia. We will also analyse the proportion of patients with a ‘prescription cascade’ and this will contribute to the identification of adverse events that have been misclassified as new medical conditions. Finally, the comparative safety study carried out will inform us about the risk of adverse events between users and non-users of antidementia drugs. Given the increasing availability of non-pharmacological treatments to treat dementia, this information will help clinicians to assess the risk-benefit of these drugs. The other comparative safety studies, between acetylcholinesterase inhibitors versus N-methyl-D-aspartate receptor antagonists and between galantamine and donepezil versus rivastigmine will also contribute to decision making of clinicians and can be the base of other prospective head-to-head comparison studies.
Relevance and aplicability: Population-based cohort studies that use routinely collected health care data have gained importance in the last years because of their ability to provide evidence that could not be generated through randomized controlled trials. This is more important in pharmacoepidemiology given that subjects that are included in the pivotal trials of the drugs usually differ greatly from the overall population that finally receives the medication. The ageing of the populations foresees an increase in the cognitive related disorders including dementia and Alzheimer disease. Although the actual medications to treat dementia (rivastigmine, galantamine, donepezil and memantine) were commercialized more than a decade ago, few are the studies that have analysed their real-world adverse effects at a population level, none of them in Spain, and even fewer are the ones that have done this comparing the different medications. Regardless of the new therapies that are being recently developed to treat dementia the great burden of the treatment still relies on these four medications and therefore is it necessary to fully identify, describe in depth the patients that are using these drugs. The comparative safety analysis results will help health care providers and clinicians to assess the risk-benefits of these drugs to avoid future adverse events or better target patients who receive medication. At last, this can also be a hypothesis generating study given that it will help identify the characteristics of the population at an increased risk of adverse events which could help design future antidementia drug studies.

We aim to estimate the risks of long-term COVID-19 outcomes among individuals with COVID-19 or exposed to COVID-19 during pregnancy, as well as the effect of vaccines on the development of long COVID and long-term COVID-19 outcomes.
Data will be obtained from SIDIAP, which includes primary care records for approximately 6 million people in Catalonia. To estimate long-term COVID-19 outcomes (Objective 1), we will conduct three population-based matched cohort studies using a target trial emulation design from September 2020 to December 2023. We will match COVID-19 infections to uninfected controls in a 1:5 ratio using propensity score (PS) matching. Cases/controls matched cohorts will include: Objective 1.1: people not vaccinated against COVID-19; Objective 1.2: people vaccinated against COVID-19; and Objective 1.3: newborns (cases: exposed to COVID-19 infection during pregnancy, controls: unexposed). Cohorts will be followed for 2 years. Our outcomes will include autoimmune, cardiovascular, mental, neurological, renal and early-life complications. We will estimate cause-specific Hazard Ratios (HR) for each outcome.To estimate vaccine effectiveness on the development of long COVID, we will first characterise long COVID based on persistent symptoms for >28 days (Objective 2.1). We will then estimate the effect of vaccines on the development of long COVID (Objective 2.2) using a staggered cohort study design. Vaccinated and unvaccinated cohorts will be compared using different PS techniques. We will then calculate HR for long COVID and long-term outcomes.
Our findings will inform preventive strategies and post-acute care pathways, thus contribute to prevent long COVID and improve COVID-19 survivors’ health.

Rationale and Background:
Vaproic acid/valproate-containing medicine (VPA) are first-line treatment for generalised tonic-clonic seizures (epilepsy) and adjunctive therapies in other types of seizures. They are also used as second-line treatments or adjuncts for the treatment of bipolar disorder, and for migraine prevention. Valproic acid is a teratogen, with prenatal exposure carrying a substantial risk of neurodevelopmental impairment and congenital malformations in the child. Therefore, its use in women of childbearing age is restricted to prevent valproate exposure during conception and pregnancy.
The European Medicines Agency (EMA) has issued risk minimisation measures in 2014 and 2018 including a compulsory pregnancy prevention program. Timely information on the use of VPA in young women across Europe is important.

Research question and Objectives:
The objectives of this study are
1. To estimate the population-level use (incidence rate and prevalence) of VPA in women between 12 and 55 years of age
2. To characterise patient-level VPA use in women between 12 and 55 years of age initiating treatment with VPA.

Research Methods:
Study design
• Population level cohort study (Objective 1, Population-level VPA utilisation)
• New user cohort study (Objective 2, Patient-level VPA utilisation)
Population:
Population-level utilisation of VPA and alternative treatments: All women aged between 12 years and =55 years between 01/01/2010 and 31/12/2022, with at least 365 days of prior history before the day they become eligible for study inclusion (study period: 2009-2022 including 1 year of previous data). For incidence, anyone with prior use of VPA will be excluded from the analysis.
Patient-level VPA utilisation: New users of VPA in the period between 01/01/2010 and 31/12/2021 (or latest date available), with at least 365 days of visibility prior to the date of their first VPA prescription, and no used VPA in the previous 365 days.
Variables
Drug of interest: Valproic acid, Sodium valproate, Magnesium valproate, Valproate semisodium and Valpromide
Alternative treatments: Carbamazepine, Phenobarbital, Phenytoin, Primidone, Clobazam, Clonazepam, Eslicarbazepine acetate, Lamotrigine, Oxcarbazepine, Perampanel, Rufinamide, Topiramate, Zonisamide, Brivaracetam, Ethosuximide, Gabapentin, Lacosamide, Levetiracetam, Pregabalin, Tiagabine, Vigabatrin, Lithium, Quetiapine, Olanzapine, Lamotrigine, Propranolol, Metoprolol, Atenolol, Nadolol, Timolol, Bisprolol, Topiramate, Amitriptyline, Flunarizine, Pizotifen, Clonidine
Data sources
1. Integrated Primary Care Information Project (IPCI), The Netherlands
2. Sistema d’Informació per al Desenvolupament de la Investigació en Atenció Primària (SIDIAP), Spain
3. IQVIA Longitudinal Patient Database Belgium (IQVIA LPD Belgium), Belgium
4. IQVIA Disease Analyzer Germany (IQVIA DA Germany), Germany
5. Hospital District of Helsinki and Uusimaa (HUS), Finland
6. Clinical Practice Research Datalink GOLD (CPRD GOLD), United Kingdom
Sample size
No sample size has been calculated. Feasibility counts have been generated in the general population in each databases.
Data analyses
For all analyses a minimum cell count of 5 will be used when reporting results, with any smaller counts obscured.
Population-level VPA utilisation: Annual period prevalence of VPA use and alternative treatments will be estimated, as will annual incidence rates per 100,000 person years.
Patient-level VPA utilisation: Large-scale patient-level characterisation will be conducted. Medical History will be assessed for anytime – 366 days before index date, for 365 to 31 days before index date, for 30 to 1 day before index date, and at index date. Medication use will be reported for 365 to 31 days before index date , for 30 to 1 day before index date, and at index date. Frequency of indication, namely epilepsy, bipolar disorder and migraine at index date will be assessed. Initial dose/strength and treatment duration will be estimated and the minimum, p25, median, p75, and maximum will be provided.

Rationale and Background
Substantial uncertainty surrounds the prevalence of rare blood cancers. Using real-world data, brought together as part of DARWIN EU®, we aim to estimate the prevalence of rare blood cancers in order to see if they still meet the condition to be classified as a rare disease.
Research question and Objectives
Research question
What is the prevalence of rare blood cancers in Europe?
Study objectives
Objective 1: To estimate the prevalence of follicular lymphoma between 1st January 2010 and the end of available data in data sources from across Europe, stratified by age and sex
Objective 2: To estimate the prevalence of diffuse Large B-Cell Lymphoma between 1st January 2010 and the end of available data in data sources from across Europe, stratified by age and sex
Objective 3: To estimate the prevalence of multiple myeloma between 1st January 2010 and the end of available data in data sources from across Europe, stratified by age and sex
Objective 4: To estimate the prevalence of chronic lymphocytic leukaemia between 1st January 2010 and the end of available data in data sources from across Europe, stratified by age and sex
Objective 5: To estimate the prevalence of acute myeloid leukaemia between 1st January 2010 and the end of available data in data sources from across Europe, stratified by age and sex
Objective 6: To estimate the prevalence of acute lymphocytic leukaemia between 1st January 2010 and the end of available data in data sources from across Europe, stratified by age and sex
Research Methods
Study design
Population-based cohort
Population
All people in a database will be eligible for inclusion in the study. Included study participants will need to have some observation time during the study period and, for the primary analysis, have a year of prior history available. In sensitivity analyses the requirement for prior history will first be removed, and then increased to three years.
Variables
Two age groupings will be used in the study: 1) 0-9; 10-19; 20-29; 30-39; 40-49; 50-59; 60-69; 70-79; 80-89; 90-99; 100+, and 2) 0-44; 45-64; 65 and over. The sex (male/ female) of study participants will also be identified.
Study outcomes will be identified based on the presence of a relevant diagnosis or observation. For the primary analysis, 5-year partial prevalence will be estimated and so individuals will be considered as a prevalent case if they have had a such a record in the prior 5 years. In sensitivity analyses, 2-year partial prevalence and complete prevalence will be estimated. For the latter, once identified as a case, an individual will remain so until their exit from the study (i.e. considering people diagnosed with malignancies to always be affected by the condition).
Data sources
1. Integrated Primary Care Information Project (IPCI), The Netherlands
2. Sistema d’Informació per al Desenvolupament de la Investigació en Atenció Primària (SIDIAP), Spain
3. The Clinical Practice Research Datalink (CPRD) GOLD database
4. IQVIA LPD Belgium
5. IQVIA DA Germany
Sample size
No sample size has been calculated as this is a Disease Epidemiology Study where we are interested in the prevalence of haematological cancers in as large and representative a denominator population as possible.
Data analyses
In line with EMA guidelines for the estimation of the prevalence of rare disease, point prevalence will be used for the primary analysis. The prevalence of each outcome of interest calculated on an annual basis as of the 1st January for each year, estimated overall and stratified by age and sex. As a sensitivity analysis annual period prevalence will also be estimated. A minimum cell count of 5 will be used when reporting results, with any smaller counts obscured.

Rationale and Background
The WHO 2021 AWaRe classification (who.int) of antibiotics for evaluation and monitoring of use classifies 258 antibiotics into 3 categories (Access/Watch/Reserve) according to their impact on antimicrobial resistance. The Watch list includes antibiotic classes that have higher resistance potential and includes most of the highest priority agents among the Critically Important Antimicrobials for Human Medicine and/or antibiotics that are at relatively high risk of selection of bacterial resistance. These medicines should be prioritized as key targets of stewardship programs and monitoring. This study will improve our understanding of the use of antibiotics in the Watch category in routine health care delivery, including indication, treatment duration and trends over time. The results will contribute to the EU efforts to monitor use of antibiotics as part of the global fight against antimicrobial resistance.
Research question and Objectives
The objectives of this study are (i) To investigate the incidence and prevalence of use of antibiotics (from the WHO Watch list) stratified by calendar year, age, sex and country/database during the study period 2012-2021. (ii) To explore duration of antibiotic use as well as indication for antibiotic prescribing/dispensing.
Research Methods
Study design: ? Population level cohort study (Objective 1, Population-level drug utilisation study on antibiotics) ? New drug user cohort study (Objective 2, Patient-level drug utilisation analysis with regard to duration and indication of antibiotic use)
Population
Population-level utilisation of antibiotics: All individuals present in the database in the period between 01/01/2012 and 31/12/2021 will be included in the analysis after 365 days of database history. For this population, incidence of use of antibiotics will be explored.
Patient-level antibiotic utilisation: All new users of antibiotics after not using the antibiotic of interest for 30 days in the period between 01/01/2012 and 31/12/2021, with at least 365 days of visibility prior to the date of their first antibiotic prescription.
Variables
Drug of interest: All antibiotics from the WHO Watch list (see also section 9.3.1 – exposure)
Data sources
1. Integrated Primary Care Information Project (IPCI), The Netherlands 2. Bordeaux University Hospital France 3. Sistema d’Informació per al Desenvolupament de la Investigació en Atenció Primària (SIDIAP)-OMOP, Spain 4. Parc Salut Mar Barcelona, Hospital del Mar (IMIM) (hospital database), Spain 5. IQVIA Disease Analyzer Germany (IQVIA DA Germany), Germany, 6. Clinical Practice Research Datalink GOLD (CPRD GOLD), United Kingdom
For all analyses a minimum cell count of 5 will be used when reporting results, with any smaller counts obscured.

Background: The global burden of mental and behavioral health disorders has been increasing in the last 30 years. These disorders cause premature mortality and pose an important public health burden. As the world population becomes more urbanized, the metropolitan environment continues to result in negative physical and mental health effects; however, green spaces have been shown to act as a buffer to these negative health effects. Although the relationship between mental health and green spaces has been investigated in previous studies, there are still gaps, especially with regards to the relationship between green spaces and specific mental and behavioral disorders.
Objective: To determine the association between green space (NDVI, percentage of green spaces) and the risk of developing depression, anxiety, stress, OCD and eating disorders in adults in Catalonia.
Methods: We will conduct a cohort study using data from the Information System for Research in Primary Care (SIDIAP). We will include all persons registered in the SIDIAP who are aged ?18 years between January 1, 2009 and December 31, 2018. The exposure of interest will be the availability of green spaces (measured using NDVI and the percentage of green space at the census tract level). Outcomes will be captured through diagnostic codes (ICD-10) of each mental and behavioral disorder. To evaluate the association between green spaces and the risk of each specific mental and behavioral disorder, cox proportional hazard models will be fitted to estimate cause specific hazard ratios (HR) and 95% confidence intervals (CIs).

The global pandemic of COVID-19 has resulted in over 50 million reported cases and over 1.2 million deaths globally. Meanwhile, hundreds of clinical trials of vaccines are ongoing and some of them show clinical efficacy. While planning for the large-scale immunization program, it is important to understand the potential adverse events after vaccination or viral infections. Electronic health records have been increasingly used in safety study, including SIDIAP. The ability to and the reliability of capturing the adverse events using suitable phenotyping algorithms in such databases is the foundation in conducting these studies. We will firstly identify the phenotyping algorithms of the AESI used in other studies, or develop the phenotypes if no existing one is found. Then we will evaluate the performance of these phenotypes using the diagnostic and evaluation tool that had been previously developed. The second objective is to estimate the background incidence rates (IR) of the AESI among the general population from year 2006 to 2019. Individuals who were observed for at least 365 days in the dataset during the study period will be included. The numerator of the incidence rate will be the total number of incident cases in a given year, and the denominator will be person-time at risk in each year. We will also estimate the IR among patients who were diagnosed or received a positive test for COVID-19 (after February 2020) or seasonal influenza. We will apply different algorithms in identifying both the exposures and the outcomes. We will also conduct a self-control case series analysis to explore the association between developing the AESI and COVID-19 or influenza infections.

Childhood overweight and obesity is an unprecedented public health challenge with immediate and adulthood effects. Findings on the relationship between playspace and overweight and obesity are mixed and studies limited, as mainly are cross-sectional and focused on green spaces. Some studies have explored how individual or area-based characteristics moderate the relationship between playspaces and overweight and obesity, finding lower effects for girls or younger children and mixed effects by race. Also, higher playspaces exposure has been linked to lower body mass index for low socioeconomic families, but higher outcome for high socioeconomic ones. Differential effects by area characteristics have been less explored, despite links between deprivation and higher risk of overweight and playspaces only benefiting privileged residents in gentrifying neighborhoods.
This study aims to assess the associations between the exposure of playspaces and overweight and obesity incidences and explore the role of individual and area-level characteristics. We will use a retrospective open longitudinal study with children aged between 2 and 5, identified as normal weight and registered in a primary healthcare record (SIDIAP database) between 2011 and 2018 in Barcelona (Spain). Overweight and obesity will be defined following the international reference and based on height and weight measures. We will estimate residential proximity to playspaces based on a local data from 2014.
We will estimate the risk of developing overweight and obesity per playspace exposure with Cox proportional hazard models by sex. To explore effect modification, interactions will be tested for individual and area-level characteristics, and stratification will be conducted for significant interaction.

In the past decades, our increasing understanding of the complex biology of cancer has spurred the development of higher-resolution diagnostic technologies, numerous innovative therapeutic oncologic agents as well as vast knowledge regarding how treatment outcomes vary with a wide range of factors. Whilst this has already greatly improved the standard of care in oncology, it is also accompanied by a myriad of challenges. If we are to address these challenges, we must build on the huge potential of the large volumes of continuously updated real-world data that are now available through Electronic Health Records (EHR) across Europe, and the promise of Artificial Intelligence (AI).

Our vision is that every patient should have access to the most up-to-date individualised treatments and to innovative therapies. By strengthening shared decision-making based on dynamic computer-interpretable guidelines (CIGs), innovative broad data access and AI-driven technology and tools, we envision revolutionizing oncology care in Europe.
Our mission is to design, develop and deliver the first interoperable and GDPR-compliant European real-world oncology data and evidence generation platform from the onset based on the needs of the clinicians and patients, in an inclusive and sustainable way. It will be built on a combination of federated and centralised access to a vast network of European data providers to help answer the highest priority research questions in prostate, breast and lung cancer, especially where current existing evidence underpinning clinical practice guidelines is weak or not covered at all in current guidelines. In parallel, comprehensive decision support toolsets based on national and international guidelines with approved regular updates of guideline recommendations underpinned by evidence from advanced statistical analysis and AI will be made available to fill the guidelines gaps and better support shared decision making by clinicians and patients.

*This is a new IMI2 project in which IDIAPJGol is participating as full partner and will have an important role in WP6 ((Non)interventional study data and real-world data gathering, preparation and Integration; for more details, please check page 41 of the proposal). The presented document is not a study protocol but the project submitted to IMI2. Different study protocols will be submitted to this committee as part of this project in the next 5 years. Data used in SIDIAP will be data mapped to the OMOP-CDM. The study will be focused on patients with breast, prostate, or lung cancer, and thevariable sused in each study is still to be defined.

Background: The overwhelming numbers of COVID-19 infections have led to an unprecedented crisis for healthcare systems worldwide. Understanding the impact of this pandemic on health is an urgent priority.
Objectives: UNCOVER aims to unravel the mid- and long-term effects of the pandemic on COVID-19 and non-COVID-19 morbidity and mortality through the use of large real-world databases from Catalonia and the UK.
Methods: UNCOVER will conduct a cohort study using longitudinal electronic health records from Catalonia (SIDIAP) and the UK (CPRD). These databases have been transformed to an international common data model (CDM), and when possible, the study will be replicated in other databases around the world. COVID-19 testing, diagnosis in primary care, hospitalisations, and deaths will be identified from March 1st 2020. Study periods will be defined as pre-COVID-19, COVID-19-pre-vaccine, and COVID-19-vaccination. Different periods will be defined for the study of non-pharmaceutical interventions by country. Mid- and long-term symptoms and outcomes will be identified. Time-series and multi-state models will be used for data analyses.
Expected results: UNCOVER will provide novel scientific knowledge aimed at helping decision-makers and clinicians in the control and management of the pandemic on a national and international level, whilst improving populations’ health and quality of life.

This is a study protocol for an observational health data analysis, submitted as a preprint to facilitate transparency and open science. Watchful waiting (WW) represents a deferred treatment option for prostate cancer (PCa) patients when curative treatment seems overtreatment right from the outset. Patients are ‘watched’ for the development of local or systemic progression with disease-related symptoms, at which stage they are then treated palliatively according to their symptoms, in order to maintain quality of life. When choosing WW, it is important to adequately assess life expectancy of patients. Although previous studies reported the outcomes of PCa patients managed with WW, which is the impact of individual patient characteristics and comorbidities on long-term outcomes is still largely unknown. The PIONEER, which is a novel project of the Innovative Medicine Initiative’s (IMI’s) «»Big Data for Better Outcomes»» program
with the mission to transform PCa care with particular focus on improving cancer related outcomes, health system efficiency and the quality of health and social care across Europe, aims at assessing which are the long-term outcomes of PCa patients undergoing WW overall and after stratification according to disease characteristics, comorbidities and life expectancy. This topic emerged as the second one with the
highest agreement score among different stakeholders after an international consensus to identify and prioritize the most important questions in the field of PCa. This study aims to describe demographics, clinical characteristics and estimate outcomes of PCa patients under WW across a network of databases in the overall
population and subgroups of patients identified by individual disease characteristics, demographics and comorbidities. The study will rely on large observational data, namely population-based registries, electronic health records and insurance claims data. The study will be an observational cohort study based on routinely collected health care data which has been mapped to the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM).

*In SIDIAP, the study will be performed in the data mapped to OMOP. Not all the objectives presented in the protocol will be studies in SIDIAP, data availability will be taken into account. For example, cause-specific survival or cancer treatment are not available in SIDIAP and therefore will not be investigated.

Antecedentes. Se estima que la endometriosis afecta al 10% de mujeres, estando el 60% de los casos sin diagnosticar. A pesar de estas estimaciones se desconoce la prevalencia e incidencia de la endometriosis en Cataluña. Tampoco, cómo mejorar el sistema sanitario para reducir su diagnóstico tardío y mejorar la calidad asistencial. Objetivos. Este proyecto tiene como objetivo determinar la prevalencia, incidencia y factores de riesgo asociados a la endometriosis, así como identificar y explorar los factores relacionados con el diagnóstico tardío. Metodología. Esta propuesta incluye un un proyecto de metodología mixta, integrando un estudio observacional de cohorte retrospectivo con «real world data», utilizando la base de datos SIDIAP (Estudio 1) y de dos estudios de metodología cualitativa con pacientes, profesionales sanitarios, gestores y otros agentes del sistema sanitario (Estudios 2 y 3). Este es un proyecto participativo que cuenta con la colaboración activa de la Asociación de Afectadas por la Endometriosis de Cataluña. Análisis de datos. Los datos se analizarán diferencialmente para cada estudio. Se llevará a cabo un análisis descriptivo y análisis de series temporales usando una regresión de Poisson (Estudio 1). Los datos cualitativos se analizarán a través del método-técnica Fotovoz (Estudio 2) y utilizando el Análisis de Contenido Temático (Estudio 3). Aplicabilidad y relevancia. El estudio permitirá conocer la magnitud de la afectación de la endometriosis en Cataluña, así como la detección de necesidades para su diagnóstico y abordaje temprano. Con ello, se generarán recomendaciones para la mejora del circuito diagnóstico de la endometriosis en Cataluña, aplicables al sistema sanitario catalán.?

El projecte inclou dos estudis:
El primer estudi, ja fet fa una setmana durant 4 dies amb diverses bases de dades internacionals online, ha estudiat el comportament d’infeccions víriques similars que hi ha hagut en el passat: s’han descrit les característiques de les persones amb complicacions d’infeccions víriques com la grip, s’han valorat els predictors de resultats adversos entre els pacients hospitalitzats amb pneumònies virals, s’han generat algoritmes per identificar els pacients amb més risc de complicacions i/o morbimortalitat, i s’ha avaluat la seguretat dels tractaments utilitzats per a un ús potencial en Covid-19.
El segon estudi vol descriure les característiques de les persones amb Covid-19 a Catalunya, així com desenvolupar models predictius de les complicacions de la Covid-19 fent servir els mètodes i resultats obtinguts en el primer estudi. Per això, es farà la integració de la informació dels pacients infectats amb Covid-19 a Catalunya, la transformació de la nova informació a un model de dades internacional, i després de contrastar les dades amb altres bases de dades d’altres països, s’elaboraran uns criteris pronòstic aplicables a les polítiques de control de pandèmia de Covid-19 al nostre país.
Els models predictius de casos greus d’infecció vírica permetran classificar els pacients amb Covid-19 per gestionar-los adequadament, avaluant la necessitat de que el malalt vagi a l’hospital o es quedi a casa, i les condicions necessàries per al seu tractament.

A goal of Discovery and Translational Sciences is to implement new technology platforms to accelerate research. This grant allows the rapid acquisition and analysis of emerging data from the ongoing global outbreak of Covid-19. The clinical and epidemiological data will inform the foundation’s response to the outbreak including expanding our understanding of risk factors for disease progression and the design of efficient clinical trials.

Background:
Increased body mass index (BMI), indicating general adiposity, is an established risk factor for several cancers. There is convincing evidence for associations between BMI and cancers of the oesophagus (adenocarcinoma), pancreas, colon, rectum, breast (postmenopausal), endometrium, liver, kidney and probable evidence for gallbladder, ovary, and prostate. However, data are currently limited for many other cancer sites. Recently, a population-based cohort study of 5.24 million UK adults reported associations between BMI and 17 cancers, suggesting wider-ranging associations. These observations are important and need replication in other populations. Furthermore, BMI alone may not fully capture the complex biology underlying associations between adiposity and cancer risk, and individuals with similar BMI may have distinct disease risks depending on their body fat distribution. Waist circumference (WC) is often used as an indicator of central adiposity and have even been suggested to be a superior predictor of cancer risk. Furthermore, there is still a crucial need for better characterisation of existing obesity-cancer links to determine dose-response relationships and effect modification by important individual level factors across a wide range of cancer sites.
Hypothesis and Objectives:
The main objective of this project is to investigate the relationships between adiposity and 22 major cancers using measured BMI and outcome data from prospectively collected primary care records in 6 million individuals from a Mediterranean population.
Specific objectives are to investigate (1) non-linear dose-response associations and effect modification by individual level factors (e.g., age group, smoking, hormone use); (2) relations of duration of overweight/obesity to site-specific cancer using repeated measures of BMI; and (3) to derive standardized risk estimates for general (BMI) and central (WC) adiposity in relation to site-specific cancers.
Setting and Methods:
The proposed study will use comprehensive data from a prospective population-based database from the Information System for the Development of Research in Primary Care (SIDIAP). SIDIAP includes data of anonymized patient records for nearly six million people throughout Catalonia since 2006. SIDIAP includes all data collected by health professionals during routine visits, including anthropometric measurements, clinical diagnoses, as well as demographic and lifestyle information. The quality of these data has been previously documented.
All people in SIDIAP aged 15 years or older with BMI data and subsequent follow-up will be included. Baseline measured BMI will be calculated and assigned as the earliest BMI recorded. Repeated weight measurements will be used to predict individual BMI trajectories for each study participant. Approximately 260,900 first primary cancers have been recorded from 2006-2014. Hazard ratios will be calculated using Cox models, and spline models will be fitted to investigate the dose-response nature of the observed associations. Overweight/obesity duration will be estimated using quadratic growth models.
Impact:
This project will represent one of the largest studies in this area of research to date and will substantially advance our understanding of the impact of obesity on cancer risk, including rarer cancers and cancer at younger age. It will strengthen the rationale to implement strategies of obesity prevention and mitigating the public health effects of cancer due to obesity.

Background: Understanding the determinants of childhood obesity has never been more urgent, given the rapid rise in obesity worldwide. Individual-level interventions, focused on changing dietary and physical activity behaviours, have had limited success. It is increasingly recognized that the urban environment contributes to the obesity epidemic and that it provides important potential for community-level intervention.

There are important gaps, though, in knowledge about multiple urban exposures and mediators, and there is no data in Catalonia on which to base impact assessments.

Main objective: ECHOCAT aims to examine whether the urban environment (air pollution, green spaces, social environment, built environment, unhealthy food environment) influences childhood obesity across Catalonia in three unique and complementary study populations.

Methodology: ECHOCAT will exploit the large resource of available primary care data of 1.6 million children (80% of the population) and the extensive individual data already available in a mother-child cohort in Catalonia. ECHOCAT will also collect new data on school children (10-12 years) in one Catalan city, Sabadell, where anthropometric measurements will be combined with questionnaires to obtain data on obesity and important risk factors. Geographical information system technologies will be used to estimate exposure to the different urban environment indicators at census tract level for the whole Catalonia and at home and school address level for Sabadell city. Individual-level mediators including diet, physical activity, and psychological well-being will be evaluated for their role in the association between urban environment indicators and childhood obesity. A health impact assessment will be developed based on this study and available literature.

Expected results: ECHOCAT will be novel in modelling multiple community-level urban environment
indicators and by evaluating potential individual-level mediators. A final impact assessment will help decision makers to develop urban environment policies aimed at reducing and preventing childhood obesity in
Catalonia.