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Objectives: The Observational Medical Outcomes Partnership common data model (OMOP-CDM) is a useful tool for large-scale network analysis but currently lacks a structured approach to pregnancy episodes. We aimed to develop and implement a perinatal expansion for the OMOP-CDM to facilitate perinatal network research., Methods: We collaboratively developed a perinatal expansion with input from domain experts and stakeholders to reach consensus. The structure and vocabularies followed the OMOP-CDM ontological framework principles. We tested the expansion using SIDIAP and Norwegian databases. We developed a diagnostics package for quality control assessment and conducted a descriptive analysis on the captured perinatal data mapped to the OMOP-CDM., Results: The perinatal expansion consists of a pregnancy table and an infant table, each with required and optional variables incorporated into standardized vocabularies. Quality assessment of the perinatal expansion table in SIDIAP and Norwegian databases demonstrated accurate capture of perinatal characteristics. Descriptive analysis measured the number of pregnancies (SIDIAP: 646 530; Norway: 746 671), pregnancy outcomes (e.g., 0.5% stillbirths in SIDIAP and 0.4% in Norway), gestational length (median [IQR] in days, SIDIAP: 273 [56-280]; Norway: 280 [273-286]), number of infants (Norway: 758 806), and birth weight (median [IQR] in grams, Norway: 3520 [3175-3860)], among other relevant variables., Discussion and Conclusion: We developed and implemented a perinatal expansion that captures important variables for perinatal research and allows interoperability with existing tables in the OMOP-CDM, which is expected to facilitate future network studies. The publicly available diagnostics package enables testing the implementation of the extension table and the quality and completeness of available data on pregnancy and pregnancy-related outcomes in databases mapped to the OMOP CDM., (© 2025 The Author(s). Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd.)

This study examines remaining life expectancy (RLE) after a cancer diagnosis, focusing on age, sex, cancer type, and metabolic syndrome (MS) components, using data from the SIDIAP database in Catalonia (2006-2017). RLE was analyzed for 13 cancer types, stratified by sex and MS components. The cohort study includes 183,364 individuals followed from diagnosis until death, transfer, or study end (December 2017). RLE at age 68 (median diagnosis age) was calculated based on MS components (0, 1, 2, and ≥ 3). Men aged 68 with 0 MS components had an RLE of 13.2 years, compared to 8.9 years for those with ≥ 3 MS. Women had an RLE of 15.9 years with 0 MS components versus 11.4 years with ≥ 3 MS. RLE varied by cancer type, with the highest RLE in men seen in prostate cancer and in women in non-Hodgkin lymphoma. The lowest RLE for both sexes was in pancreatic cancer. The largest differences between 0 and ≥ 3 MS components were observed in non-Hodgkin lymphoma and the smallest in pancreatic cancer. Increased MS components were associated with reduced RLE in at least 8 cancer types for men and 9 for women. Prevention strategies targeting MS components could increase RLE in cancer patients., Competing Interests: Declarations. Ethics approval and consent to participate: This study adheres to both national and international guidelines, including the Declaration of Helsinki and Principles of Good Research Practice. In compliance with European and Spanish laws regarding confidentiality and data protection ([EU] 2016/679), all data within SIDIAP is consistently pseudo-anonymized. Hence, obtaining consent from the participants was deemed unnecessary and was waived by the Clinical Ethics Committee at IDIAPJGol. To establish a connection with the CMBD database, SIDIAP utilizes a third-party service to maintain confidentiality. Approval for the study protocol was granted by the Clinical Research Ethics Committee of IDIAPJGol (P17/212) on November 29, 2017. Anonymity and confidentiality of data and medical records were ensured throughout, following the guidelines outlined in the Organic Law 15/1999 on the Protection of Personal Data ( http://www.boe.es/boe/dias/1999/12/14/pdfs/A43088-43099.pdf ). Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Background: The burden of childhood overweight and obesity attributable to ambient air pollution and a lack of urban green spaces (UGS) remains unknown. This study aimed to estimate the attributable cases of childhood overweight and obesity due to air pollution and insufficient UGS exposure in Barcelona, Spain., Methods: We applied a quantitative health impact assessment approach. We collected childhood overweight and obesity prevalence levels and exposure data from 69 spatial basic health zones in Barcelona. We estimated particulate matter (PM 2.5 ) and nitrogen dioxide (NO 2 ) levels using land use regression models, normalized difference vegetation index (NDVI) levels using remote sensing and percentage of green area (%GA) using land use. We estimated relative risks, population attributable fractions, and preventable overweight/obesity cases in children under following scenarios: Compliance of World Health Organization (WHO) air quality guidelines (AQGs) for (1) PM 2.5 and (2) NO 2 ; achieving (3) city-target NDVI levels and (4) 25% green area (%GA) recommendations. The analyses were stratified by socioeconomic deprivation index (in quintiles). Uncertainty was quantified using Monte Carlos simulations., Results: Compliance of WHO AQGs could prevent 0.4% [253 (95%CI, -604; 1086)] and 4.2% [3000 (95%CI, 1009; 4943)] of childhood overweight/obesity cases due to excess PM 2.5 and NO 2 levels in Barcelona, respectively. Compliance of NDVI and %GA targeted levels could prevent 6% [4094 (95%CI, 1698; 6379)] and 10% [6853 (95%CI, 1440; 12779)] of childhood overweight/obesity cases respectively. The preventable burdens of childhood overweight/obesity cases were slightly higher in middle-class socioeconomic areas due to the higher adverse exposure levels at baseline (high air pollution, less UGS)., Discussion: Compliance with WHO AQGs and achieving UGS targets can reduce childhood overweight and obesity levels in Barcelona, and potentially in other locations as well. This underscores the need for policies that foster healthier urban environments of high environmental quality in order to protect child health., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Martine Vrijheid reports financial support was provided by Marathon Foundation of Tv3. Talita Duarte Salles reports financial support was provided by LaCaixa Foundation. Jeroen de Bont reports financial support was provided by Svenska Forskningsrådet Formas. Jeroen de Bont reports financial support was provided by Ulla Hamberg Angeby and Lennart Angeby Foundation. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Evidence is limited regarding the role of air pollution in acute lower respiratory infections among adults. We assessed the influence of long-term air pollution exposure on hospital admission for lower respiratory infections and whether there are vulnerable subgroups., Methods: We used a populational cohort in Catalonia, Spain, comprising 3,817,820 adults residing in Catalonia as of January 1, 2015. Air pollution exposure was assigned to individuaĺs residential address using locally-developed models. We characterized the concentration-response functions between long-term air pollution exposure and hospital admission for lower respiratory infections between 2015 and 2019. We assessed interaction between exposure and clinical and socio-economic factors on multiplicative and additive scales., Results: An interquartile range exposure increase was associated with an 8 % (95 % Confidence Interval: 5 %-11 %) for Nitrogen Dioxide, 10 % (95 % Confidence Interval: 8 %-13 %) for Particulate Matter with diameter equal to or smaller than 2.5 µm, 5 % (95 % Confidence Interval: 3 %-7%) for Particulate Matter with diameter equal to or smaller than 10 µm and 18 % (95 % Confidence Interval: 14 %-22%) for ozone (adjusted by Nitrogen Dioxide) increase in hospital admissions for respiratory infections. Concentration-response functions were non-linear, with steeper slopes at exposures below the median or at most extreme high values. Associations were consistently greater for individuals over 65 years or with hypertension diagnosis and males., Conclusions: Long-term exposure to air pollution was positively associated with hospital admission for lower respiratory infections. Individuals who were older than 65 years, hypertensive or male were most vulnerable., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Cathryn Tonne reports financial support was provided by Health Effects Institute. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Residential relocation leads to environmental changes, besides being likely to be influenced by sociodemographic characteristics. The relationship between them is, however, still not well described. We aimed to investigate changes in patterns of urban, natural and physical environmental exposures due to relocation and related sociodemographic determinants in a population-based cohort study of children and adolescents. We included individuals between 0 and 17 years of age, registered in primary healthcare records in Catalonia, Spain from 2006 to 2018 and categorized them as non-movers and movers (first residential change). Hierarchical clustering identified groups of individuals based on their exposure to air pollution, green spaces and built environment. Low, medium and high environmental hazard exposure clusters were identified, which were used to identify changes in environmental exposure patterns due to relocation, namely same, worse, and better environment. Multinomial logistic regression determined whether sex, age, nationality and area-level deprivation influenced these changes. From 1,316,138 individuals, 221,058 were movers. Compared to non-movers, movers were more frequently with foreign nationality (12.1% vs. 21.3%, respectively) and more likely to live in the most deprived areas at baseline (19.2% vs. 24.4%). Younger children had higher risk of moving to better or worse environments. Individuals living in areas with the highest levels of deprivation were least likely to move within the same environments (i.e., either moving to better (Odds Ratio [95% Confidence Interval] 1.39[1.34-1.44]) or worse environment (1.56[1.49-1.63])). Compared to people from Spain, those from Africa moved to similar environments (OR of moving to a better environment 0.90 (0.87-0.94) with respect to move to the same environment, and OR of moving to a worse environment 0.82 (0.78-0.85)), those from America tended to move to other environments (1.17 (1.12-1.23) better and 1.09 (1.03-1.15) worse), while those from Asia and Europe moved to better environments (1.22 (1.12-1.33) and 1.20 (1.14-1.27) respectively). No associations were found for sex. Changes in patterns of environmental exposures due to residential mobility are complex and may be determined by age, deprivation and nationality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Objective: Multiple treatment options are recommended for Systemic Lupus Erythematosus (SLE) by clinical guidelines. This study aimed to explore SLE treatment patterns as there is limited real-world data of SLE medication utilisation, especially in childhood-onset SLE (cSLE)., Methods: We conducted a longitudinal cohort study using five routinely collected healthcare databases from four European countries (United Kingdom, France, Germany, and Spain). We described the characteristics of adult and paediatric patients at time of SLE diagnosis. We calculated the percentage of patients commencing SLE treatments in the first month and year after diagnosis, reported number of prescriptions, starting dose, cumulative dose, and duration of each treatment, and characterised the line of therapy., Results: We characterised 11,255 patients with a first diagnosis of SLE and included 5718 in our medication utilisation analyses. The majority of adult SLE patients were female (range 80-88 %), with median age of 49 to 54 years at diagnosis. In the paediatric cohort (n = 378), 66-83 % of SLE patients were female, with median age of 12 to 16 years at diagnosis. Hydroxychloroquine and glucocorticoids were common first-line treatments in both adults and children, with second-line treatments including mycophenolate mofetil and methotrexate. Few cases of monoclonal antibody use were seen in either cohort. Initial glucocorticoid dosing in paediatric patients was often higher than in adults., Conclusion: Treatment choices for adult SLE patients across four European countries were in line with recent therapeutic consensus guidelines. High glucocorticoid prescriptions in paediatric patients suggests the need for steroid-sparing treatment alternatives and paediatric specific guidelines., Competing Interests: Declarations of competing interest DPA's department has received grant/s from Amgen, Chiesi-Taylor, Lilly, Janssen, Novartis, and UCB Biopharma. His research group has received consultancy fees from Astra Zeneca and UCB Biopharma. Amgen, Astellas, Janssen, Synapse Management Partners and UCB Biopharma have funded or supported training programmes organised by DPA's department. James Brash and Hanne van Ballegooijen are employees of IQVIA. All other authors have no conflicts of interest to declare., (Copyright © 2024. Published by Elsevier B.V.)

Introduction: This study aims to investigate the relationship between deprivation, as measured by a socioeconomic deprivation index (SDI) score for census tract urban areas, and COVID-19 infections and vaccine uptake among children and adolescents before and after the vaccination rollout in Catalonia, Spain., Methods: We conducted a population-based cohort study using primary care records. Individuals were followed 3 months before the start of the vaccination campaign in Spain and 3 months after. Children (5-11 years) and adolescents (12-15 years) with at least 1 year of prior history observation available and without missing deprivation data. For each outcome, we estimated cumulative incidence and crude Cox proportional-hazard models by SDI quintiles, and hazard ratios (HRs) of COVID-19 infection and vaccine uptake relative to the least deprived quintile, Q1., Results: Before COVID-19 vaccination rollout, 290,625 children and 179,685 adolescents were analyzed. Increased HR of deprivation was associated with a higher risk of COVID-19 infection in both children [Q5: 1.55 (95% CI, 1.47-1.63)] and adolescents [Q5: 1.36 (95% CI, 1.29-1.43)]. After the rollout, this pattern changed among children, with lower risk of infection in more deprived areas [Q5: 0.62 (95% CI, 0.61-0.64)]. Vaccine uptake was higher among adolescents than children, but in both age groups, non-vaccination was more common among those living in more deprived areas (39.3% and 74.6% in Q1 vs. 26.5% and 66.9% in Q5 among children and adolescents, respectively)., Conclusions: Children and adolescents living in deprived areas were at higher risk of COVID-19 non-vaccination. Socioeconomic disparities in COVID-19 infection were also evident before vaccine rollout, with a higher infection risk in deprived areas across age groups. Our findings suggest that changes in the association between deprivation and infections among children after the vaccine rollout were likely due to testing disparities., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 López-Sánchez, Perramon-Malavez, Soriano-Arandes, Prats, Duarte-Salles, Raventós and Roel.)

Purpose: The generation of representative disease phenotypes is important for ensuring the reliability of the findings of observational studies. The aim of this manuscript is to outline a reproducible framework for reliable and traceable phenotype generation based on real world data for use in the Data Analysis and Real-World Interrogation Network (DARWIN EU). We illustrate the use of this framework by generating phenotypes for two diseases: pancreatic cancer and systemic lupus erythematosus (SLE)., Methods: The phenotyping process involves a 14-steps process based on a standard operating procedure co-created by the DARWIN EU Coordination Centre in collaboration with the European Medicines Agency. A number of bespoke R packages were utilised to generate and review codelists for two phenotypes based on real world data mapped to the OMOP Common Data Model., Results: Codelists were generated for both pancreatic cancer and SLE, and cohorts were generated in six OMOP-mapped databases. Diagnostic checks were performed, which showed these cohorts had broadly similar incidence and prevalence figures to previously published literature, despite significant inter-database variability. Co-occurrent symptoms, conditions, and medication use were in keeping with pre-specified clinical descriptions based on previous knowledge., Conclusions: Our detailed phenotyping process makes use of bespoke tools and allows for comprehensive codelist generation and review, as well as large-scale exploration of the characteristics of the resulting cohorts. Wider use of structured and reproducible phenotyping methods will be important in ensuring the reliability of observational studies for regulatory purposes., (© 2024 The Author(s). Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd.)

Background: The World Health Organisation (WHO) has identified a range of symptomatic manifestations to aid in the clinical diagnosis of post-COVID conditions, herein referred to as post-acute COVID-19 symptoms. We conducted an international network cohort study to estimate the burden of these symptoms in North American, European, and Asian populations., Methods: A federated analysis was conducted including 10 databases from the United Kingdom, Netherlands, Norway, Estonia, Spain, France, South Korea, and the United States, between September 1st 2020 and latest data availability (which varied from December 31st 2021 to February 28th 2023), covering primary and secondary care, nationwide registries, and claims data, all mapped to the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM). We defined two cohorts for the main analyses: a SARS-CoV-2 infection cohort [positive polymerase chain reaction (PCR) or rapid lateral flow test (LFT) result or clinical COVID-19 diagnosis] and a general population cohort. Individuals with less than 365 days of prior history or 120 days of follow-up were excluded. We estimated incidence rates (IRs) of the 25 WHO-proposed post-acute COVID-19 symptoms, considering symptoms that occurred ≥90 and ≤365 days after index date, excluding individuals with the respective symptoms 180 days prior to the index event. Stratified analyses were conducted by age and sex. Incidence rate ratios (IRRs) were calculated comparing rates in the infected cohort versus the general population. Results from the different databases were combined using random-effects meta-analyses., Findings: 3,019,408 individuals were included in the infection cohort. 1,585,160 of them were female and 1,434,248 of them male. 929,351,505 individuals were included in the general population group. 461,195,036 of them were female and 466,022,004 of them male. The 1-year IR of any post-acute COVID-19 symptom in the COVID-19 infection cohort varied significantly across databases, from 4.4 (95% CI 3.8-5.1) per 100 person-years to 103.9 (95% CI 103.2-104.7). The five most common symptoms were joint pain (from 1.6 (95% CI 1.3-1.9) to 14.3 (95% CI 14.1-14.6)), abdominal pain (from 0.3 (95% CI 0.1-0.5) to 9.9 (95% CI 9.7-10.1)), gastrointestinal issues (from 0.6 (95% CI 0.4-0.9) to 13.3 (95% CI 13.1-13.6)), cough (from 0.3 (95% CI 0.2-0.5) to 9.1 (95% CI 8.9-9.3)), and anxiety (from 0.8 (95% CI 0.6-1.2) to 11.4 (95% CI 11.2-11.6)); whereas muscle spasms (from 0.01 (95% CI 0.008-0.2) to 1.7 (95% CI 1.6-1.8)), pins and needles (from 0.05 (95% CI 0.03-0.0.9) to 1.5 (95% CI 1.4-1.6)), memory issues (from 0.03 (95% CI 0.02-0.06) to 0.8 (95% CI 0.7-0.8)), cognitive dysfunction (from 0.007 (95% CI 0.004-0.01) to 0.6 (95% CI 0.4-0.8)), and altered smell and/or taste (from 0.04 (95% CI 0.03-0.04) to 0.7 (95% CI 0.6-0.8)) were least common. Incidence rates of any post-acute COVID-19 symptoms generally increased with age, with certain symptoms peaking in middle-aged adults (anxiety, depressive disorders, headache, altered smell and taste) and others in pre-school children (gastrointestinal issues and cough). Females had higher incidence rates for most symptoms. Based on the random-effects model, the infected cohort had a higher incidence of any post-acute COVID-19 symptom than the general population, with a meta-analytic incidence rate ratio (meta-IRR) of 1.4 (1-2). A similar pattern was seen for all individual symptoms. The highest meta-IRRs were depressive disorder, 2.6 (1.7-3.9); anxiety, 2.3 (1.4-3.8); allergy, 2.1 (1.7-2.8) and sleep disorders, 2.1 (1.5-2.6). The meta-IRR for altered smell and/or taste was 1.9 (1.3-2.8)., Interpretation: Post-acute COVID-19 symptoms, as listed by the WHO, were commonly observed following COVID-19 infection. However, even after standardising research methods, there was significant heterogeneity in the incidence rates from different healthcare settings and geographical locations. This is the first international study of the epidemiology of post-acute COVID-19 symptoms using the WHO-listed symptoms. Its findings contibute to understand the epidemiology of this condition from a multinational approach. Limitations of this study include the lack of consensus of the post-acute COVID-19 definition, as well as the difficulty to capture the impact on daily life of the post-acute COVID-19 symptoms in the available datasets., Funding: This work has been funded by the European Health Data Evidence Network (EHDEN) through an Evidence Generation Fund Grant and by the National Institute for Health and Care Research (NIHR) Oxford Biomedical Research Centre (BRC)., Competing Interests: D.P.A.‘s department has received grant/s from Amgen, Chiesi–Taylor, Lilly, Janssen, Novartis, and UCB Biopharma. His research group has received consultancy fees from Astra Zeneca and UCB Biopharma. Amgen, Astellas, Janssen, Synapse Management Partners and UCB Biopharma have funded or supported training programmes organised by DPA's department. R.P. reports serving on advisory boards for Gilead Sciences, Inc, Pfizer, Inc, Roche Therapeutics, MSD, GSK, ViiV Healthcare, Eli Lilly and Company, PharmaMar, and Atea Pharmaceuticals, Inc; and receiving research grants paid to his institution from MSD, ViiV Healthcare, Gilead Sciences, and PharmaMar. L.M. reports receiving grants from Grifols; receiving honoraria as a speaker from AstraZeneca, Gilead Sciences, GSK, and Pfizer; and participation in advisory boards for Gilead Sciences and Merck. M.M. works for a research group that in the past 3 years received unconditional research grants from Chiesi, UCB, Amgen, Johnson & Johnson, Innovative Medicines Initiative and the European Medicines Agency. D.Ded., Z.C. and J.O. are employees of the Medicines and Healthcare Products Regulatory Agency, which provides the CPRD research service. K.K. is a consortial author in the US National Institutes of Health National COVID Cohort Collaborative (funding expired in 2022 with no renewal or active impact on any current work). G.M. reports receiving consulting fees from Pfizer. A.N. reports grants or contracts from Alfred P. Sloan Foundation, National Institutes of Health and the U.S. Food and Drug Administration. L.P. was supported by a Sara Borrell fellowship awarded by the Spanish Institute of Health Carlos III (CD23/00223). K.L.G is funded through an MRC scholarship with Bayer AG as an industrial partner. All other co-authors declare no competing interests., (© 2024 The Authors.)

Background: Lung cancer is the leading cause of cancer-associated mortality worldwide. In the United Kingdom (UK), there has been a major reduction in smoking, the leading risk factor for lung cancer. Therefore, an up-to-date assessment of the trends of lung cancer is required in the UK. This study aims to describe lung cancer burden and trends in terms of incidence, prevalence, and survival from 2000-2021, using two UK primary care databases., Methods: We performed a population-based cohort study using the UK primary care Clinical Practice Research Datalink (CPRD) GOLD database, compared with CPRD Aurum. Participants aged 18+ years, with 1-year of prior data availability, were included. We estimated lung cancer incidence rates (IRs), period prevalence (PP), and survival at 1, 5 and 10 years after diagnosis using the Kaplan-Meier (KM) method., Results: Overall, 11,388,117 participants, with 45,563 lung cancer cases were studied. The IR of lung cancer was 52.0 [95% confidence interval (CI): 51.5 to 52.5] per 100,000 person-years, with incidence increasing from 2000 to 2021. Females aged over 50 years of age showed increases in incidence over the study period, ranging from increases of 8 to 123 per 100,000 person-years, with the greatest increase in females aged 80-89 years. Alternatively, for males, only cohorts aged over 80 years showed increases in incidence over the study period. The highest IR was observed in people aged 80-89 years. PP in 2021 was 0.18%, with the largest rise seen in participants aged over 60 years. Median survival post-diagnosis increased from 6.6 months in those diagnosed between 2000-2004 to 10.0 months between 2015-2019. Both short and long-term survival was higher in younger cohorts, with 82.7% 1-year survival in those aged 18-29 years, versus 24.2% in the age 90+ years cohort. Throughout the study period, survival was longer in females, with a larger increase in survival over time than in males., Conclusions: The incidence and prevalence of lung cancer diagnoses in the UK have increased, especially in female and older populations, with a small increase in median survival. This study will enable future comparisons of overall disease burden, so the overall impact may be seen., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-24-241/coif). N.L.B. receives grants/consultancy fees/payments from Theramex, F. Hoffmann-La Roche, Innovate UK, and Sleep Universal Limited. A.G. is the Vice President, and Global Head of Data Sciences, at Odysseus Data Services Inc, since September 2021. D.P.A. research group has received research grants from Amgen, Chiesi-Taylor, Lilly, Janssen, Novartis, and from UCB Biopharma; consultancy fees (paid to his department) from Astra Zeneca and UCB Biopharma; and other financial or non-financial interests from Amgen, Astellas, Janssen, Synapse Management Partners and UCB Biopharma have funded or supported training programmes organised by D.P.A. and his department. The other authors have no conflicts of interest to declare., (2024 AME Publishing Company. All rights reserved.)

Background: Sodium-glucose cotransporter 2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) reduce the risk of major adverse cardiovascular events (MACE) in patients with type 2 diabetes mellitus (T2DM). However, their effectiveness relative to each other and other second-line antihyperglycemic agents is unknown, without any major ongoing head-to-head clinical trials., Objectives: The aim of this study was to compare the cardiovascular effectiveness of SGLT2is, GLP-1 RAs, dipeptidyl peptidase-4 inhibitors (DPP4is), and clinical sulfonylureas (SUs) as second-line antihyperglycemic agents in T2DM., Methods: Across the LEGEND-T2DM (Large-Scale Evidence Generation and Evaluation Across a Network of Databases for Type 2 Diabetes Mellitus) network, 10 federated international data sources were included, spanning 1992 to 2021. In total, 1,492,855 patients with T2DM and cardiovascular disease (CVD) on metformin monotherapy were identified who initiated 1 of 4 second-line agents (SGLT2is, GLP-1 RAs, DPP4is, or SUs). Large-scale propensity score models were used to conduct an active-comparator target trial emulation for pairwise comparisons. After evaluating empirical equipoise and population generalizability, on-treatment Cox proportional hazards models were fit for 3-point MACE (myocardial infarction, stroke, and death) and 4-point MACE (3-point MACE plus heart failure hospitalization) risk and HR estimates were combined using random-effects meta-analysis., Results: Over 5.2 million patient-years of follow-up and 489 million patient-days of time at risk, patients experienced 25,982 3-point MACE and 41,447 4-point MACE. SGLT2is and GLP-1 RAs were associated with lower 3-point MACE risk than DPP4is (HR: 0.89 [95% CI: 0.79-1.00] and 0.83 [95% CI: 0.70-0.98]) and SUs (HR: 0.76 [95% CI: 0.65-0.89] and 0.72 [95% CI: 0.58-0.88]). DPP4is were associated with lower 3-point MACE risk than SUs (HR: 0.87; 95% CI: 0.79-0.95). The pattern for 3-point MACE was also observed for the 4-point MACE outcome. There were no significant differences between SGLT2is and GLP-1 RAs for 3-point or 4-point MACE (HR: 1.06 [95% CI: 0.96-1.17] and 1.05 [95% CI: 0.97-1.13])., Conclusions: In patients with T2DM and CVD, comparable cardiovascular risk reduction was found with SGLT2is and GLP-1 RAs, with both agents more effective than DPP4is, which in turn were more effective than SUs. These findings suggest that the use of SGLT2is and GLP-1 RAs should be prioritized as second-line agents in those with established CVD., Competing Interests: Funding Support and Author Disclosures This study was partially funded through National Institutes of Health grants R01 HL167858, K23 HL153775, R01 LM006910, R01 HG006139, and R01 HL169954 and the U.S. Department of Veterans Affairs under the research priority to “Put VA Data to Work for Veterans” (VA ORD 22-D4V). The funders had no role in the design and conduct of the protocol; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Dr Khera is an associate editor at JAMA; and has received support from the National Heart, Lung, and Blood Institute of the National Institutes of Health (awards R01 HL167858 and K23 HL153775) and the Doris Duke Charitable Foundation (award 2022060); has received research support, through Yale University, from Bristol Myers Squibb, Novo Nordisk, and BridgeBio; is a coinventor of U.S. provisional patent applications WO2023230345A1, US20220336048A1, 63/346,610, 63/428,569, 63/484,426, 63/508,315, 63/580,137, 63/606,203, 63/619,241, and 63/562,335, unrelated to the present work; and is a cofounder of Evidence2Health and Ensight-AI, precision health platforms to improve evidence-based cardiovascular care and cardiovascular diagnostics. Dr DuVall has received grants from Alnylam Pharmaceuticals, AstraZeneca Pharmaceuticals, Biodesix, Celgene, Cerner Enviza, GlaxoSmithKline, Janssen Pharmaceuticals, Novartis International, and Parexel International through the University of Utah or the Western Institute for Veteran Research (outside the submitted work). Dr Man has received support from the C.W. Maplethorpe Fellowship, the National Institute of Health Research, European Commission Framework Horizon 2020, the Hong Kong Research Grant Council, and the Innovation and Technology Commission of the Hong Kong Special Administration Region Government outside the submitted work). Dr Morales is supported by a Wellcome Trust Clinical Research Fellowship (214588/Z/18/Z). In the past 3 years, Dr Krumholz has received expenses and/or personal fees from UnitedHealth, Element Science, Aetna, Reality Labs, Tesseract/4Catalyst, F-Prime, the Siegfried and Jensen Law Firm, the Arnold and Porter Law Firm, and the Martin/Baughman Law Firm; is a cofounder of Refactor Health, HugoHealth, and Ensight-AI; and is associated with contracts, through Yale New Haven Hospital, from the Centers for Medicare and Medicaid Services and, through Yale University, from Johnson & Johnson. Dr You is chief technology officer of PHI Digital Healthcare. Dr Ross has received research support through Yale University from Johnson & Johnson to develop methods of clinical trial data sharing, from the Food and Drug Administration for the Yale-Mayo Clinic Center for Excellence in Regulatory Science and Innovation program (grant U01 FD005938), from the Agency for Healthcare Research and Quality (grant R01 HS022882), and from Arnold Ventures; has received research support from the Medical Device Innovation Consortium as part of the National Evaluation System for Health Technology and from the National Heart, Lung, and Blood Institute of the National Institutes of Health (grants R01 HS025164 and R01 HL144644); and was an expert witness at the request of the relator’s attorneys, the Greene Law Firm, in a qui tam suit alleging violations of the False Claims Act and Anti-Kickback Statute against Biogen that was settled September 2022. Dr Thangaraj is a coinventor on provisional patent 63/606,203, unrelated to the present work, and is funded by grant 5T32 HL155000-03. Ms Blacketer, Dr Ostropolets, and Dr Ryan are employees of Johnson & Johnson. Dr Schuemie is an employee and shareholder of Johnson & Johnson. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 American College of Cardiology Foundation. All rights reserved.)

Importance: Incidence, prevalence, and survival are pertinent measures to inform the management and provision of prostate cancer care., Objective: To calculate the incidence, prevalence, and survival rates for prostate cancer in the UK from 2000 to 2021., Design, Setting, and Participants: This population-based cohort study uses routinely collected primary care data from the UK. Male patients aged 18 years or older with at least 1 year of history registered in Clinical Practice Research Datalink (CPRD) GOLD or Aurum were included. Data were analyzed from January 2023 to March 2024., Main Outcomes and Measures: Prostate cancer incidence rates (IR), period prevalence (PP), and 1-, 5-, and 10-year survival after diagnosis between 2000 and 2021, stratified by age and calendar years., Results: This study included 64 925 and 133 200 patients with prostate cancer in CPRD GOLD and Aurum, respectively, with a median age of 72 (65-78) years. The overall IR of prostate cancer was 151.7 (95% CI, 150.6 to 152.9) per 100 000 person-years in GOLD to 153.1 (95% CI, 152.3 to 153.9) per 100 000 person-years for Aurum and increased with age. The incidence of prostate cancer increased from 109 per 100 000 person-years in 2000 to 159 per 100 000 person-years in 2021. Peaks of incidence occurred in 2004 and 2018, before a decline in 2020. PP increased 3.5 times over the study period for both databases, from 0.4% in 2000 to 1.4% in 2021. IR and PP were highest in those aged 80 to 89 years. Median (95% CI) survival was similar in both databases (GOLD: 10.9 [95% CI, 10.7-11.1] years and Aurum: 11.1 [95% CI, 11.0-11.2] years). Survival at 1, 5, and 10 years after diagnosis were 93.4% (95% CI, 93.2%-93.6%), 71.8% (95% CI, 71.4%-72.2%), 53.2% (95% CI, 52.6%-53.7%) in GOLD and 93.9% (95% CI, 93.7%-94.0%), 72.7% (95% CI, 72.5%-73.0%), 53.7% (95% CI, 53.3%-54.1%) in AURUM, respectively. Survival increased over time: 1-year survival was 94.8% (95% CI, 94.5%-95.2%) in those diagnosed between 2015 to 2019 compared with 90.8% (95% CI, 90.2%-91.3%) from 2000 to 2004; 5-year survival improved from 65.3% (95% CI, 64.4%-66.3%) from 2000 to 2004 to 75.3% (95% CI, 74.4%-76.3%) in 2015 to 2019., Conclusions and Relevance: In this population-based cohort study, incidence and prevalence increased with older age, with high survival rates reflecting a high burden of disease, particularly in the management of cancer survivorship in an aging population. Health care systems should consider this when managing the increasing numbers of people with prevalent prostate cancer.

Breast cancer is the most frequently diagnosed cancer in females globally. However, we know relatively little about trends in males. This study describes United Kingdom (UK) secular trends in breast cancer from 2000 to 2021 for both sexes. We describe a population-based cohort study using UK primary care Clinical Practice Research Datalink (CPRD) GOLD and Aurum databases. There were 5,848,436 eligible females and 5,539,681 males aged 18+ years, with ≥ one year of prior data availability in the study period. We estimated crude breast cancer incidence rates (IR), prevalence and survival probability at one-, five- and 10-years after diagnosis using the Kaplan-Meier method. Analyses were further stratified by age. Crude IR of breast cancer from 2000 to 2021 was 194.4 per 100,000 person-years for females and 1.16 for males. Crude prevalence in 2021 was 2.1% for females and 0.009% for males. Both sexes have seen around a 2.5-fold increase in prevalence across time. Incidence increased with age for both sexes, peaking in females aged 60-69 years and males 90+ . There was a drop in incidence for females aged 70-79 years. From 2003-2019, incidence increased > twofold in younger females (aged 18-29: IR 2.12 in 2003 vs. 4.58 in 2018); decreased in females aged 50-69 years; and further declined from 2015 onwards in females aged 70-89 years. Survival probability for females after one-, five-, and ten-years after diagnosis was 95.1%, 80.2%, and 68.4%, and for males 92.9%, 69.0%, and 51.3%. Survival probability at one-year increased by 2.08% points, and survival at five years increased by 5.39% from 2000-2004 to 2015-2019 for females, particularly those aged 50-70 years. For males, there were no clear time-trends for short-term and long-term survival probability. Changes in incidence of breast cancer in females largely reflect the success of screening programmes, as rates rise and fall in synchronicity with ages of eligibility for such programmes. Overall survival from breast cancer for females has improved from 2000 to 2021, again reflecting the success of screening programmes, early diagnosis, and improvements in treatments. Male breast cancer patients have worse survival outcomes compared to females, highlighting the need to develop male-specific diagnosis and treatment strategies to improve long-term survival in line with females., (© 2024. The Author(s).)

Background: Metabolic syndrome (MS) has emerged as a significant global health concern. The relationship between MS and the risk of cancer doesn't seem clear, whether examining by components or in combination. The objective of this study is to examine the relationship between MS, its components, and the overall risk of cancer, including the risk of 13 specific cancer types., Methods: We included 3,918,781 individuals aged 40 years or older sourced from the SIDIAP database between 2008 and 2017. Cox models were employed with MS components and their combinations. A subsample was created using a matched cohort (by age and sex). Incidence curves were computed to determine the time elapsed between the date of having 1-5 MS components and cancer incidence, compared to matched participants with no MS components, which showed that individuals who had one MS component experienced a greater incidence of cancer over 5 and 10 years than individuals with no MS, and the incidence rose with an increase in the number of MS components., Results: Individuals exposed to MS components were diagnosed with cancer earlier than those who were not exposed to them. In the Cox model, HDL (HR 1.46, 95% CI: 1.41-1.52) and Glycemia (HR 1.40, 95% CI: 1.37-1.44) were the individual combinations with the highest risk of overall cancer. In combinations with two components, the highest HR was HDL+Glycemia (HR 1.52, 95% CI: 1.45-1.59) and Glycemia+HBP (HR 1.48, 95% CI: 1.45-1.50). In combinations with three components, the highest HR was HDL+Glycemia+HBP (HR 1.58, 95% CI: 1.55-1.62)., Conclusion: In summary, having one or more MS components raises the risk of developing at least 11 cancer types and these risk differ according to type of component included. Some sex differences are also observed. Our findings suggest that implementing prevention measures aimed at specific MS components may lower the risk of various cancer types., (© 2024 The Author(s). Cancer Medicine published by John Wiley & Sons Ltd.)

Patients with cancer were excluded from pivotal randomized clinical trials of COVID-19 vaccine products, and available observational evidence on vaccine effectiveness (VE) focused mostly on mild, and not severe COVID-19, which is the ultimate goal of vaccination for high-risk groups. Here, using primary care electronic health records from Catalonia, Spain (SIDIAP), we built two large cohorts of vaccinated and matched control cancer patients with a primary vaccination scheme (n = 184,744) and a booster (n = 108,534). Most patients received a mRNA-based product in primary (76.2%) and booster vaccination (99.9%). Patients had 51.8% (95% CI 40.3%-61.1%) and 58.4% (95% CI 29.3%-75.5%) protection against COVID-19 hospitalization and COVID-19 death respectively after full vaccination (two-doses) and 77.9% (95% CI 69.2%-84.2%) and 80.2% (95% CI 63.0%-89.4%) after booster. Compared to primary vaccination, the booster dose provided higher peak protection during follow-up. Calibration of VE estimates with negative outcomes, and sensitivity analyses with slight different population and COVID-19 outcomes definitions provided similar results. Our results confirm the role of primary and booster COVID-19 vaccination in preventing COVID-19 severe events in patients with cancer and highlight the need for the additional dose in this population., (© 2024. The Author(s).)

Background: An updated time-trend analysis of anti-dementia drugs (ADDs) is lacking. The aim of this study is to assess the incident rate (IR) of ADD in individuals with dementia using real-world data., Setting: Primary care data (country/database) from the UK/CPRD-GOLD (2007-20), Spain/SIDIAP (2010-20) and the Netherlands/IPCI (2008-20), standardised to a common data model., Methods: Cohort study. Participants: dementia patients ≥40 years old with ≥1 year of previous data. Follow-up: until the end of the study period, transfer out of the catchment area, death or incident prescription of rivastigmine, galantamine, donepezil or memantine. Other variables: age/sex, type of dementia, comorbidities. Statistics: overall and yearly age/sex IR, with 95% confidence interval, per 100,000 person-years (IR per 105 PY (95%CI))., Results: We identified a total of (incident anti-dementia users/dementia patients) 41,024/110,642 in UK/CPRD-GOLD, 51,667/134,927 in Spain/SIDIAP and 2,088/17,559 in the Netherlands/IPCI.In the UK, IR (per 105 PY (95%CI)) of ADD decreased from 2007 (30,829 (28,891-32,862)) to 2010 (17,793 (17,083-18,524)), then increased up to 2019 (31,601 (30,483 to 32,749)) and decrease in 2020 (24,067 (23,021-25,148)). In Spain, IR (per 105 PY (95%CI)) of ADD decreased by 72% from 2010 (51,003 (49,199-52,855)) to 2020 (14,571 (14,109-15,043)). In the Netherlands, IR (per 105 PY (95%CI)) of ADD decreased by 77% from 2009 (21,151 (14,967-29,031)) to 2020 (4763 (4176-5409)). Subjects aged ≥65-79 years and men (in the UK and the Netherlands) initiated more frequently an ADD., Conclusions: Treatment of dementia remains highly heterogeneous. Further consensus in the pharmacological management of patients living with dementia is urgently needed., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objective: To study the association between COVID-19 vaccination and the risk of post-COVID-19 cardiac and thromboembolic complications., Methods: We conducted a staggered cohort study based on national vaccination campaigns using electronic health records from the UK, Spain and Estonia. Vaccine rollout was grouped into four stages with predefined enrolment periods. Each stage included all individuals eligible for vaccination, with no previous SARS-CoV-2 infection or COVID-19 vaccine at the start date. Vaccination status was used as a time-varying exposure. Outcomes included heart failure (HF), venous thromboembolism (VTE) and arterial thrombosis/thromboembolism (ATE) recorded in four time windows after SARS-CoV-2 infection: 0-30, 31-90, 91-180 and 181-365 days. Propensity score overlap weighting and empirical calibration were used to minimise observed and unobserved confounding, respectively.Fine-Gray models estimated subdistribution hazard ratios (sHR). Random effect meta-analyses were conducted across staggered cohorts and databases., Results: The study included 10.17 million vaccinated and 10.39 million unvaccinated people. Vaccination was associated with reduced risks of acute (30-day) and post-acute COVID-19 VTE, ATE and HF: for example, meta-analytic sHR of 0.22 (95% CI 0.17 to 0.29), 0.53 (0.44 to 0.63) and 0.45 (0.38 to 0.53), respectively, for 0-30 days after SARS-CoV-2 infection, while in the 91-180 days sHR were 0.53 (0.40 to 0.70), 0.72 (0.58 to 0.88) and 0.61 (0.51 to 0.73), respectively., Conclusions: COVID-19 vaccination reduced the risk of post-COVID-19 cardiac and thromboembolic outcomes. These effects were more pronounced for acute COVID-19 outcomes, consistent with known reductions in disease severity following breakthrough versus unvaccinated SARS-CoV-2 infection., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Background: Although vaccines have proved effective to prevent severe COVID-19, their effect on preventing long-term symptoms is not yet fully understood. We aimed to evaluate the overall effect of vaccination to prevent long COVID symptoms and assess comparative effectiveness of the most used vaccines (ChAdOx1 and BNT162b2)., Methods: We conducted a staggered cohort study using primary care records from the UK (Clinical Practice Research Datalink [CPRD] GOLD and AURUM), Catalonia, Spain (Information System for Research in Primary Care [SIDIAP]), and national health insurance claims from Estonia (CORIVA database). All adults who were registered for at least 180 days as of Jan 4, 2021 (the UK), Feb 20, 2021 (Spain), and Jan 28, 2021 (Estonia) comprised the source population. Vaccination status was used as a time-varying exposure, staggered by vaccine rollout period. Vaccinated people were further classified by vaccine brand according to their first dose received. The primary outcome definition of long COVID was defined as having at least one of 25 WHO-listed symptoms between 90 and 365 days after the date of a PCR-positive test or clinical diagnosis of COVID-19, with no history of that symptom 180 days before SARS-Cov-2 infection. Propensity score overlap weighting was applied separately for each cohort to minimise confounding. Sub-distribution hazard ratios (sHRs) were calculated to estimate vaccine effectiveness against long COVID, and empirically calibrated using negative control outcomes. Random effects meta-analyses across staggered cohorts were conducted to pool overall effect estimates., Findings: A total of 1 618 395 (CPRD GOLD), 5 729 800 (CPRD AURUM), 2 744 821 (SIDIAP), and 77 603 (CORIVA) vaccinated people and 1 640 371 (CPRD GOLD), 5 860 564 (CPRD AURUM), 2 588 518 (SIDIAP), and 302 267 (CORIVA) unvaccinated people were included. Compared with unvaccinated people, overall HRs for long COVID symptoms in people vaccinated with a first dose of any COVID-19 vaccine were 0·54 (95% CI 0·44-0·67) in CPRD GOLD, 0·48 (0·34-0·68) in CPRD AURUM, 0·71 (0·55-0·91) in SIDIAP, and 0·59 (0·40-0·87) in CORIVA. A slightly stronger preventative effect was seen for the first dose of BNT162b2 than for ChAdOx1 (sHR 0·85 [0·60-1·20] in CPRD GOLD and 0·84 [0·74-0·94] in CPRD AURUM)., Interpretation: Vaccination against COVID-19 consistently reduced the risk of long COVID symptoms, which highlights the importance of vaccination to prevent persistent COVID-19 symptoms, particularly in adults., Funding: National Institute for Health and Care Research., Competing Interests: Declaration of interests DP-A's department has received grants from Amgen, Chiesi-Taylor, Lilly, Janssen, Novartis, UCB Biopharma, the European Medicines Agency, and the Innovative Medicines Initiative. DP-A's research group has received consultancy fees from Astra Zeneca and UCB Biopharma. DP-A's department has organised training programmes funded or supported by Amgen, Astellas, Janssen, Synapse Management Partners, and UCB Biopharma. RK's research group has received consultancy fees from AstraZeneca and the Estonian Ministry of Social Affairs through RITA CORIVA and RITA MAITT (Machine learning and AI powered public services) projects. AU reports funding from the European Regional Development Fund (RITA 1/02–120) for her institution (Department of Family Medicine and Public Health, University of Tartu). HMEN reports support from the European Health Data and Evidence Network project grant, Innovative Medicines Initiative 2 Joint Undertaking (grant agreement 806968) for harmonisation of the Norwegian registry data into the Observational Medical Outcomes Partnership (OMOP) common data model (CDM). TD-S reports funding from the Innovative Medicines Initiative 2 Joint Undertaking (grant agreement 806968) for the institute to map the SIDIAP data to the OMOP CDM. This initiative received support from the EU Horizon 2020 research and innovation programme and European Federation of Pharmaceutical Industries and Associations. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Objective: Factors that shape individuals' vulnerability to the effects of air pollution on COVID-19 severity remain poorly understood. We evaluated whether the association between long-term exposure to ambient NO 2 , PM 2.5 , and PM 10 and COVID-19 hospitalisation differs by age, sex, individual income, area-level socioeconomic status, arterial hypertension, diabetes mellitus, and chronic obstructive pulmonary disease., Methods: We analysed a population-based cohort of 4,639,184 adults in Catalonia, Spain, during 2020. We fitted Cox proportional hazard models adjusted for several potential confounding factors and evaluated the interaction effect between vulnerability indicators and the 2019 annual average of NO 2 , PM 2.5 , and PM 10 . We evaluated interaction on both additive and multiplicative scales., Results: Overall, the association was additive between air pollution and the vulnerable groups. Air pollution and vulnerability indicators had a synergistic (greater than additive) effect for males and individuals with low income or living in the most deprived neighbourhoods. The Relative Excess Risk due to Interaction (RERI) was 0.21, 95 % CI, 0.15 to 0.27 for NO 2 and 0.16, 95 % CI, 0.11 to 0.22 for PM 2.5 for males; 0.13, 95 % CI, 0.09 to 0.18 for NO 2 and 0.10, 95 % CI, 0.05 to 0.14 for PM 2.5 for lower individual income and 0.17, 95 % CI, 0.12 to 0.22 for NO 2 and 0.09, 95 % CI, 0.05 to 0.14 for PM 2.5 for lower area-level socioeconomic status. Results for PM 10 were similar to PM 2.5 . Results on multiplicative scale were inconsistent., Conclusions: Long-term exposure to air pollution had a larger synergistic effect on COVID-19 hospitalisation for males and those with lower individual- and area-level socioeconomic status., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: There is a lack of knowledge on how patients with asthma or chronic obstructive pulmonary disease (COPD) are globally treated in the real world, especially with regard to the initial pharmacological treatment of newly diagnosed patients and the different treatment trajectories. This knowledge is important to monitor and improve clinical practice., Methods: This retrospective cohort study aims to characterise treatments using data from four claims (drug dispensing) and four electronic health record (EHR; drug prescriptions) databases across six countries and three continents, encompassing 1.3 million patients with asthma or COPD. We analysed treatment trajectories at drug class level from first diagnosis and visualised these in sunburst plots., Results: In four countries (USA, UK, Spain and the Netherlands), most adults with asthma initiate treatment with short-acting ß2 agonists monotherapy (20.8%-47.4% of first-line treatments). For COPD, the most frequent first-line treatment varies by country. The largest percentages of untreated patients (for asthma and COPD) were found in claims databases (14.5%-33.2% for asthma and 27.0%-52.2% for COPD) from the USA as compared with EHR databases (6.9%-15.2% for asthma and 4.4%-17.5% for COPD) from European countries. The treatment trajectories showed step-up as well as step-down in treatments., Conclusion: Real-world data from claims and EHRs indicate that first-line treatments of asthma and COPD vary widely across countries. We found evidence of a stepwise approach in the pharmacological treatment of asthma and COPD, suggesting that treatments may be tailored to patients' needs., Competing Interests: Competing interests: AFM, PRR, JAK and KMV work for a department that receives/received unconditional research grants from Amgen, Chiesi, Johnson and Johnson, UCB Biopharma, the European Medicines Agency and the Innovative Medicines Initiative. DP-A’s department has received grants from Amgen, Chiesi-Taylor, Lilly, Johnson and Johnson, Novartis, UCB Biopharma, the European Medicines Agency, and the Innovative Medicines Initiative. DP-A’s research group has received consultancy fees from Astra Zeneca and UCB Biopharma. DP-A’s department has organised training programmes funded or supported by Amgen, Astellas, Johnson and Johnson, Synapse Management Partners, and UCB Biopharma. JK’s institute has received grants from the American Lung Association, COPD Foundation, National Heart Lung and Blood institute, PCORI, Regeneron, Sergey Brin Family Foundation and US National Institutes of Health. JK has received consultancy fees from AstraZeneca, BData and GlaxoSmithKline. JK has received honoraria from University of Chicago, University of Washington/VA Puget Sound and travel support from the Global Initiative for Asthma, American Thoracic Society. GBB’s institute has received grants from Merck Sharp & Dohme. GBB has received honoraria from AstraZeneca, Boehringer-Ingelheim, Chiesi, GlaxoSmithKline, Novartis and Sanofi. All other authors declare no competing interests., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.

Background: A growing body of evidence has reported positive associations between long-term exposure to air pollution and poor COVID-19 outcomes. Inconsistent findings have been reported for short-term air pollution, mostly from ecological study designs. Using individual-level data, we studied the association between short-term variation in air pollutants [nitrogen dioxide (NO2), particulate matter with a diameter of <2.5 µm (PM2.5) and a diameter of <10 µm (PM10) and ozone (O3)] and hospital admission among individuals diagnosed with COVID-19., Methods: The COVAIR-CAT (Air pollution in relation to COVID-19 morbidity and mortality: a large population-based cohort study in Catalonia, Spain) cohort is a large population-based cohort in Catalonia, Spain including 240 902 individuals diagnosed with COVID-19 in the primary care system from 1 March until 31 December 2020. Our outcome was hospitalization within 30 days of COVID-19 diagnosis. We used individual residential address to assign daily air-pollution exposure, estimated using machine-learning methods for spatiotemporal prediction. For each pandemic wave, we fitted Cox proportional-hazards models accounting for non-linear-distributed lagged exposure over the previous 7 days., Results: Results differed considerably by pandemic wave. During the second wave, an interquartile-range increase in cumulative weekly exposure to air pollution (lag0&#95;7) was associated with a 12% increase (95% CI: 4% to 20%) in COVID-19 hospitalizations for NO2, 8% (95% CI: 1% to 16%) for PM2.5 and 9% (95% CI: 3% to 15%) for PM10. We observed consistent positive associations for same-day (lag0) exposure, whereas lag-specific associations beyond lag0 were generally not statistically significant., Conclusions: Our study suggests positive associations between NO2, PM2.5 and PM10 and hospitalization risk among individuals diagnosed with COVID-19 during the second wave. Cumulative hazard ratios were largely driven by exposure on the same day as hospitalization., (© The Author(s) 2024; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Purpose: Few studies have examined how the absolute risk of thromboembolism with COVID-19 has evolved over time across different countries. Researchers from the European Medicines Agency, Health Canada, and the United States (US) Food and Drug Administration established a collaboration to evaluate the absolute risk of arterial (ATE) and venous thromboembolism (VTE) in the 90 days after diagnosis of COVID-19 in the ambulatory (eg, outpatient, emergency department, nursing facility) setting from seven countries across North America (Canada, US) and Europe (England, Germany, Italy, Netherlands, and Spain) within periods before and during COVID-19 vaccine availability., Patients and Methods: We conducted cohort studies of patients initially diagnosed with COVID-19 in the ambulatory setting from the seven specified countries. Patients were followed for 90 days after COVID-19 diagnosis. The primary outcomes were ATE and VTE over 90 days from diagnosis date. We measured country-level estimates of 90-day absolute risk (with 95% confidence intervals) of ATE and VTE., Results: The seven cohorts included 1,061,565 patients initially diagnosed with COVID-19 in the ambulatory setting before COVID-19 vaccines were available (through November 2020). The 90-day absolute risk of ATE during this period ranged from 0.11% (0.09-0.13%) in Canada to 1.01% (0.97-1.05%) in the US, and the 90-day absolute risk of VTE ranged from 0.23% (0.21-0.26%) in Canada to 0.84% (0.80-0.89%) in England. The seven cohorts included 3,544,062 patients with COVID-19 during vaccine availability (beginning December 2020). The 90-day absolute risk of ATE during this period ranged from 0.06% (0.06-0.07%) in England to 1.04% (1.01-1.06%) in the US, and the 90-day absolute risk of VTE ranged from 0.25% (0.24-0.26%) in England to 1.02% (0.99-1.04%) in the US., Conclusion: There was heterogeneity by country in 90-day absolute risk of ATE and VTE after ambulatory COVID-19 diagnosis both before and during COVID-19 vaccine availability., Competing Interests: VLR III reports research grants to his institution from the US Food and Drug Administration (FDA) and the National Institutes of Health (NIH); consulting fees from Entasis, Takeda, and Urovant Sciences; and participation on the FDA Drug Safety and Risk Management Advisory Committee. NMC reports research funding from FDA via a Department of Health and Human Services (HHS) contract during the conduct of the study and funding from HPHCI (a non-profit organization that conducts work for government and private organizations, including pharmaceutical companies) outside the submitted work. RAH reports grants from FDA, NIH, and Merck. AMP reports royalties from UpToDate (including for an article on anticoagulation), consulting fees via advisory board from BioMarin LLC outside the submitted work, and speaker honorarium from the American Society of Hematology. DAD reports stock options in CVS Health. JLK reports unrelated research grants to her institution from Vir Biotechnology, Pfizer, Novartis, and the Centers for Disease Control and Prevention. PRR reports unrelated research grants to his institution from Chiesi, UCB, Amgen, Johnson & Johnson, Innovative Medicines Initiative, and the European Medicines Agency. KV reports unrelated research grants to her institution from Chiesi, UCB, Amgen, Johnson & Johnson, and the European Medicines Agency. DPA reports research grants to his institution from Amgen, Chiesi-Taylor, Lilly, Janssen, Novartis, and UCB Biopharma as well as consulting fees from Astra Zeneca and UCB Biopharma. The authors report no other conflicts of interest in this work., (© 2024 Lo Re III et al.)

Background: SGLT2 inhibitors (SGLT2is) and GLP-1 receptor agonists (GLP1-RAs) reduce major adverse cardiovascular events (MACE) in patients with type 2 diabetes mellitus (T2DM). However, their effectiveness relative to each other and other second-line antihyperglycemic agents is unknown, without any major ongoing head-to-head trials., Methods: Across the LEGEND-T2DM network, we included ten federated international data sources, spanning 1992-2021. We identified 1,492,855 patients with T2DM and established cardiovascular disease (CVD) on metformin monotherapy who initiated one of four second-line agents (SGLT2is, GLP1-RAs, dipeptidyl peptidase 4 inhibitor [DPP4is], sulfonylureas [SUs]). We used large-scale propensity score models to conduct an active comparator, target trial emulation for pairwise comparisons. After evaluating empirical equipoise and population generalizability, we fit on-treatment Cox proportional hazard models for 3-point MACE (myocardial infarction, stroke, death) and 4-point MACE (3-point MACE + heart failure hospitalization) risk, and combined hazard ratio (HR) estimates in a random-effects meta-analysis., Findings: Across cohorts, 16·4%, 8·3%, 27·7%, and 47·6% of individuals with T2DM initiated SGLT2is, GLP1-RAs, DPP4is, and SUs, respectively. Over 5·2 million patient-years of follow-up and 489 million patient-days of time at-risk, there were 25,982 3-point MACE and 41,447 4-point MACE events. SGLT2is and GLP1-RAs were associated with a lower risk for 3-point MACE compared with DPP4is (HR 0·89 [95% CI, 0·79-1·00] and 0·83 [0·70-0·98]), and SUs (HR 0·76 [0·65-0·89] and 0·71 [0·59-0·86]). DPP4is were associated with a lower 3-point MACE risk versus SUs (HR 0·87 [0·79-0·95]). The pattern was consistent for 4-point MACE for the comparisons above. There were no significant differences between SGLT2is and GLP1-RAs for 3-point or 4-point MACE (HR 1·06 [0·96-1·17] and 1·05 [0·97-1·13])., Interpretation: In patients with T2DM and established CVD, we found comparable cardiovascular risk reduction with SGLT2is and GLP1-RAs, with both agents more effective than DPP4is, which in turn were more effective than SUs. These findings suggest that the use of GLP1-RAs and SGLT2is should be prioritized as second-line agents in those with established CVD., Funding: National Institutes of Health, United States Department of Veterans Affairs.

Purpose: Real-world data (RWD) offers a valuable resource for generating population-level disease epidemiology metrics. We aimed to develop a well-tested and user-friendly R package to compute incidence rates and prevalence in data mapped to the observational medical outcomes partnership (OMOP) common data model (CDM)., Materials and Methods: We created IncidencePrevalence, an R package to support the analysis of population-level incidence rates and point- and period-prevalence in OMOP-formatted data. On top of unit testing, we assessed the face validity of the package. To do so, we calculated incidence rates of COVID-19 using RWD from Spain (SIDIAP) and the United Kingdom (CPRD Aurum), and replicated two previously published studies using data from the Netherlands (IPCI) and the United Kingdom (CPRD Gold). We compared the obtained results to those previously published, and measured execution times by running a benchmark analysis across databases., Results: IncidencePrevalence achieved high agreement to previously published data in CPRD Gold and IPCI, and showed good performance across databases. For COVID-19, incidence calculated by the package was similar to public data after the first-wave of the pandemic., Conclusion: For data mapped to the OMOP CDM, the IncidencePrevalence R package can support descriptive epidemiological research. It enables reliable estimation of incidence and prevalence from large real-world data sets. It represents a simple, but extendable, analytical framework to generate estimates in a reproducible and timely manner., (© 2023 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd.)

Introduction: Ranitidine, a histamine H 2 -receptor antagonist (H 2 RA), is indicated in the management of gastric acid-related disorders. In 2020, the European Medicines Agency (EMA) recommended suspension of all ranitidine-containing medicines in the European Union (EU) due to the presence of N-nitrosodimethylamine (NDMA) impurities, which were considered to be carcinogenic. The aim of this study was to investigate the impact of regulatory intervention on use patterns of ranitidine-containing medicines and their therapeutic alternatives., Objectives: The aim was to study drug utilisation patterns of ranitidine and report discernible trends in treatment discontinuation and switching to alternative medications., Methods: This retrospective, population-based cohort study was conducted using primary care records from six European countries between 2017 and 2023. To explore drug utilisation patterns, we calculated (1) incident use of ranitidine, other H 2 RAs, and other alternative drugs for the treatment of gastric ulcer and/or gastric bleeding; (2) ranitidine discontinuation; and (3) switching from ranitidine to alternative drugs (H 2 RAs, proton-pump inhibitors [PPIs], and other medicinal products for acid-related disorders)., Results: During the study period, 385,273 new ranitidine users were observed, with most users being female and aged 18-74 years. Ranitidine was the most commonly prescribed H 2 RA in the pre-referral period (September 2017-August 2019), with incidence rates between 0.8 and 9.0/1000 person years (PY). A steep decline to 0.3-3.8/1000 PY was observed in the referral period (September 2019-March 2020), eventually dropping to 0.0-0.4/1000 PY in the post-referral period (April 2020-March 2022). Switching from ranitidine to alternative drugs increased in the post-referral period, with the majority of patients switching to PPIs. Discontinuation of ranitidine use ranged from 270 to 380/1000 users in 2017 and decreased over time., Conclusions: Ranitidine was commonly used prior to referral, but it was subsequently discontinued and replaced primarily with PPIs., (© 2023. The Author(s).)

Introduction: Individual case reports are the main asset in pharmacovigilance signal management. Signal validation is the first stage after signal detection and aims to determine if there is sufficient evidence to justify further assessment. Throughout signal management, a prioritization of signals is continually made. Routinely collected health data can provide relevant contextual information but are primarily used at a later stage in pharmacoepidemiological studies to assess communicated signals., Objective: The aim of this study was to examine the feasibility and utility of analysing routine health data from a multinational distributed network to support signal validation and prioritization and to reflect on key user requirements for these analyses to become an integral part of this process., Methods: Statistical signal detection was performed in VigiBase, the WHO global database of individual case safety reports, targeting generic manufacturer drugs and 16 prespecified adverse events. During a 5-day study-a-thon, signal validation and prioritization were performed using information from VigiBase, regulatory documents and the scientific literature alongside descriptive analyses of routine health data from 10 partners of the European Health Data and Evidence Network (EHDEN). Databases included in the study were from the UK, Spain, Norway, the Netherlands and Serbia, capturing records from primary care and/or hospitals., Results: Ninety-five statistical signals were subjected to signal validation, of which eight were considered for descriptive analyses in the routine health data. Design, execution and interpretation of results from these analyses took up to a few hours for each signal (of which 15-60 minutes were for execution) and informed decisions for five out of eight signals. The impact of insights from the routine health data varied and included possible alternative explanations, potential public health and clinical impact and feasibility of follow-up pharmacoepidemiological studies. Three signals were selected for signal assessment, two of these decisions were supported by insights from the routine health data. Standardization of analytical code, availability of adverse event phenotypes including bridges between different source vocabularies, and governance around the access and use of routine health data were identified as important aspects for future development., Conclusions: Analyses of routine health data from a distributed network to support signal validation and prioritization are feasible in the given time limits and can inform decision making. The cost-benefit of integrating these analyses at this stage of signal management requires further research., (© 2023. The Author(s).)

Objective: Developing accurate phenotype definitions is critical in obtaining reliable and reproducible background rates in safety research. This study aims to illustrate the differences in background incidence rates by comparing definitions for a given outcome., Materials and Methods: We used 16 data sources to systematically generate and evaluate outcomes for 13 adverse events and their overall background rates. We examined the effect of different modifications (inpatient setting, standardization of code set, and code set changes) to the computable phenotype on background incidence rates., Results: Rate ratios (RRs) of the incidence rates from each computable phenotype definition varied across outcomes, with inpatient restriction showing the highest variation from 1 to 11.93. Standardization of code set RRs ranges from 1 to 1.64, and code set changes range from 1 to 2.52., Discussion: The modification that has the highest impact is requiring inpatient place of service, leading to at least a 2-fold higher incidence rate in the base definition. Standardization showed almost no change when using source code variations. The strength of the effect in the inpatient restriction is highly dependent on the outcome. Changing definitions from broad to narrow showed the most variability by age/gender/database across phenotypes and less than a 2-fold increase in rate compared to the base definition., Conclusion: Characterization of outcomes across a network of databases yields insights into sensitivity and specificity trade-offs when definitions are altered. Outcomes should be thoroughly evaluated prior to use for background rates for their plausibility for use across a global network., Competing Interests: R.M., A.S., G.R., E.A.V., A.G.S., K.H., and P.B.R. are employees of Janssen Pharmaceutical Company of Johnson & Johnson and shareholder of Johnson & Johnson. A.O. has received funding from the US National Institutes of Health and the US Food and Drug Administration. G.H. received support through a grant to Columbia University (NIH R01 LM006910). M.A.S. receives grants from the US Department of Veterans Affairs within the scope of this work, and grants and contracts from the US National Institutes of Health, US Food & Drug Administration, and Janssen Research & Development outside the scope of this work. P.R.R. has received funding from the Innovative Medicines Initiative (IMI) 2 Joint Undertaking (JU) under grant agreement No 806968. M.A.M., F.N., J.M.R.-A., F.M., T.D.-S., S.D., V.P., L.Y.H.L., and T.M.A. have no conflicts of interest to declare that are directly relevant to the contents of this study., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Persistent symptoms following the acute phase of COVID-19 present a major burden to both the affected and the wider community. We conducted a cohort study including over 856,840 first COVID-19 cases, 72,422 re-infections and more than 3.1 million first negative-test controls from primary care electronic health records from Spain and the UK (Sept 2020 to Jan 2022 (UK)/March 2022 (Spain)). We characterised post-acute COVID-19 symptoms and identified key symptoms associated with persistent disease. We estimated incidence rates of persisting symptoms in the general population and among COVID-19 patients over time. Subsequently, we investigated which WHO-listed symptoms were particularly differential by comparing their frequency in COVID-19 cases vs. matched test-negative controls. Lastly, we compared persistent symptoms after first infections vs. reinfections.Our study shows that the proportion of COVID-19 cases affected by persistent post-acute COVID-19 symptoms declined over the study period. Risk for altered smell/taste was consistently higher in patients with COVID-19 vs test-negative controls. Persistent symptoms were more common after reinfection than following a first infection. More research is needed into the definition of long COVID, and the effect of interventions to minimise the risk and impact of persistent symptoms., (© 2023. The Author(s).)