Different Strategies to Execute Multi-Database Studies for Medicines Surveillance in Real-World Setting: A Reflection on the European Model

Metadata for Data dIscoverability aNd Study rEplicability in obseRVAtional Studies (MINERVA): Development and Pilot of a Metadata List and Catalogue in Europe

PURPOSE

Metadata for data dIscoverability aNd study rEplicability in obseRVAtional studies (MINERVA), a European Medicines Agency-funded project (EUPAS39322), defined a set of metadata to describe real-world data sources (RWDSs) and piloted metadata collection in a prototype catalogue to assist investigators from data source discoverability through study conduct.

METHODS

A list of metadata was created from a review of existing metadata catalogues and recommendations, structured interviews, a stakeholder survey, and a technical workshop. The prototype was designed to comply with the FAIR principles (findable, accessible, interoperable, reusable), using MOLGENIS software. Metadata collection was piloted by 15 data access partners (DAPs) from across Europe.

RESULTS

A total of 442 metadata variables were defined in six domains: institutions (organizations connected to a data source); data banks (data collections sustained by an organization); data sources (collections of linkable data banks covering a common underlying population); studies; networks (of institutions); and common data models (CDMs). A total of 26 institutions were recorded in the prototype. Each DAP populated the metadata of one data source and its selected data banks. The number of data banks varied by data source; the most common data banks were hospital administrative records and pharmacy dispensation records (10 data sources each). Quantitative metadata were successfully extracted from three data sources conforming to different CDMs and entered into the prototype.

CONCLUSIONS

A metadata list was finalized, a prototype was successfully populated, and a good practice guide was developed. Setting up and maintaining a metadata catalogue on RWDSs will require substantial effort to support discoverability of data sources and reproducibility of studies in Europe.

Adaptation of risk prediction equations for cardiovascular outcomes among patients with type 2 diabetes in real-world settings: a cross-institutional study using common data model approach

OBJECTIVE

To adapt risk prediction equations for myocardial infarction (MI), stroke, and heart failure (HF) among patients with type 2 diabetes in real-world settings using cross-institutional electronic health records (EHRs) in Taiwan.

METHODS

The EHRs from two medical centers, National Cheng Kung University Hospital (NCKUH; 11,740 patients) and National Taiwan University Hospital (NTUH; 20,313 patients), were analyzed using the common data model approach. Risk equations for MI, stroke, and HF from UKPDS-OM2, RECODe, and CHIME models were adapted for external validation and recalibration. External validation was assessed by (1) discrimination, evaluated by the area under the receiver operating characteristic curve (AUROC) and (2) calibration, evaluated by calibration slopes and intercepts and the Greenwood-Nam-D'Agostino (GND) test. Recalibration was conducted for unsatisfactory calibration (p-value of GND test < 0.05) by adjusting the baseline hazards of original equations to address variations in patients' cardiovascular risks across institutions.

RESULTS

The CHIME risk equations had acceptable discrimination (AUROC: 0.71-0.79) and better calibration than that for UKPDS-OM2 and RECODe, although the calibration remained unsatisfactory. After recalibration, the calibration slopes/intercepts of the CHIME-MI, CHIME-stroke, and CHIME-HF risk equations were 0.9848/- 0.0008, 1.1003/- 0.0046, and 0.9436/0.0063 in the NCKUH population and 1.1060/- 0.0011, 0.8714/0.0030, and 1.0476/- 0.0016 in the NTUH population, respectively. All the recalibrated risk equations showed satisfactory calibration (p-values of GND tests ≥ 0.05).

CONCLUSIONS

We provide valid risk prediction equations for MI, stroke, and HF outcomes in Taiwanese type 2 diabetes populations. A framework for adapting risk equations across institutions is also proposed.

Kidney outcomes with SGLT2is for type 2 diabetes patients: does background treatment with metformin or RASis matter?

Introduction

There is a lack of real-world evidence regarding the impact of concomitant metformin and renin-angiotensin system inhibitors (RASis) on sodium-glucose cotransporter-2 inhibitor (SGLT2i)-associated kidney outcomes. This study was aimed to investigate whether SGLT2i-associated kidney outcomes were modified by the concomitant use of metformin or RASis in patients with type 2 diabetes.

Methods

SGLT2i users were identified from three electronic health record databases during May 2016 and December 2017 and categorized into those with and without concomitant use of metformin or RASis. Propensity score matching was performed to minimize baseline differences between groups. Study outcomes were mean estimated glomerular filtration rate (eGFR) change and time to 30%, 40%, and 50% eGFR reductions. A meta-analysis was performed to combine the estimates across databases.

Results

After matching, there were 6,625 and 3,260 SGLT2i users with and without metformin, and 6,654 and 2,746 SGLT2i users with and without RASis, respectively. The eGFR dip was similar in SGLT2i users with and without metformin therapy, but was greater in SGLT2i users with RASis compared to those without RASis. Neither metformin nor RASi use had a significant effect on SGLT2i-associated eGFR reductions, as evidenced by the hazard ratios (95% CIs) of 30% eGFR reductions for SGLT2is with versus without metformin/RASis, namely 1.02 (0.87-1.20)/1.09 (0.92-1.31). Such findings were also observed in the outcomes of 40% and 50% eGFR reductions.

Conclusion

Using metformin or RASis did not modify SGLT2i-associated kidney outcomes in type 2 diabetes.

Cross-Regional Data Initiative for the Assessment and Development of Treatment for Neurological and Mental Disorders

Purpose

To describe and categorize detailed components of databases in the Neurological and Mental Health Global Epidemiology Network (NeuroGEN).

Methods

An online 132-item questionnaire was sent to key researchers and data custodians of NeuroGEN in North America, Europe, Asia and Oceania. From the responses, we assessed data characteristics including population coverage, data follow-up, clinical information, validity of diagnoses, medication use and data latency. We also evaluated the possibility of conversion into a common data model (CDM) to implement a federated network approach. Moreover, we used radar charts to visualize the data capacity assessments, based on different perspectives.

Results

The results indicated that the 15 databases covered approximately 320 million individuals, included in 7 nationwide claims databases from Australia, Finland, South Korea, Taiwan and the US, 6 population-based electronic health record databases from Hong Kong, Scotland, Taiwan, the Netherlands and the UK, and 2 biomedical databases from Taiwan and the UK.

Conclusion

The 15 databases showed good potential for a federated network approach using a common data model. Our study provided publicly accessible information on these databases for those seeking to employ real-world data to facilitate current assessment and future development of treatments for neurological and mental disorders.

Antidiabetic Therapy during Pregnancy: The Prescription Pattern in Italy

Pregestational and gestational diabetes mellitus are relevant complications of pregnancy, and antidiabetic drugs are prescribed to obtain glycemic control and improve perinatal outcomes. The objective of this study was to describe the prescription pattern of antidiabetics before, during and after pregnancy in Italy and to evaluate its concordance with the Italian guideline on treatment of diabetes mellitus. A multi-database cross-sectional population study using a Common Data Model was performed. In a cohort of about 450,000 women, the prescribing profile of antidiabetics seemed to be in line with the Italian guideline, which currently does not recommend the use of oral antidiabetics and non-insulin injection, even if practice is still heterogeneous (up to 3.8% in the third trimester used oral antidiabetics). A substantial variability in the prescription pattern was observed among the Italian regions considered: the highest increase was registered in Tuscany (4.2%) while the lowest was in Lombardy (1.5%). Women with multiple births had a higher proportion of antidiabetic prescriptions than women with singleton births both in the preconception period and during pregnancy (1.3% vs. 0.7%; 3.4% vs. 2.6%) and used metformin more frequently. The consumption of antidiabetics in foreign women was higher than Italians (second trimester: 1.8% vs. 0.9%, third trimester: 3.6% vs. 1.8%).

Pharmacoepidemiology: An Overview

The aims of this review are to provide a comprehensive overview of the definition and scope of pharmacoepidemiology, to summarize the study designs and methodologies used in the field, to discuss the future trends in the field and new methodologies to address bias and confounding, and finally to give some recommendations to clinicians interested in pharmacoepidemiologic research. Because drug efficacy and safety from randomized clinical trials do not reflect the real-world situation, pharmacoepidemiological studies on drug safety monitoring and drug effectiveness in large numbers of people are needed by healthcare professionals and regulatory institutions. We aim to highlight the importance of pharmacoepidemiologic research in informing evidence-based medicine and public health policy. The development of new designs and methodologies for the generation of valid evidence, as well as new initiatives to provide guidance and recommendations on how to incorporate real-world evidence into the drug development process, are reported on. In addition, we have touched on the implication of artificial intelligence in the management of real-world data. This overview aims to summarize all important aspects to consider when conducting or interpreting a pharmacoepidemiologic study.

Clinical pharmacology facing the real-world setting: Pharmacovigilance, pharmacoepidemiology and the economic evaluation of drugs

Traditionally, clinical pharmacology has focused its activities on drug-organism interaction, from an individual or collective perspective. Drug efficacy assessment by performing randomized clinical trials and analysis of drug use in clinical practice by carrying out drug utilization studies have also been other areas of interest. From now on, Clinical pharmacology should move from the analysis of the drug-individual interaction to the analysis of the drug-individual-society interaction. It should also analyze the clinical and economic consequences of the use of drugs in the conditions of normal clinical practice, beyond clinical trials. The current exponential technological development that facilitates the analysis of real-life data offers us a golden opportunity to move to all these other areas of interest. This review describes the role that clinical pharmacology has played at the beginning and during the evolution of pharmacovigilance, pharmacoepidemiology and economic drug evaluations in Spain. In addition, the challenges that clinical pharmacology is going to face in the following years in these three areas are going to be outlined too.

A methodology to assess the population size and estimate the needed resources for new licensed medications by combining clinical and administrative databases: The example of glycated haemoglobin in type 2 diabetes

PURPOSE

To develop and validate a model to estimate glycated haemoglobin (HbA1c) values in patients with type 2 diabetes mellitus (T2DM) using a clinical data source, with the aim to apply this equation to administrative databases.

METHODS

Using a primary care and administrative Italian databases, namely the Health Search database (HSD) and the ReS (Ricerca e Salute) database, we selected all patients aged 18 years or older on 31 December 2018 being diagnosed with T2DM and without prior prescription of sodium-glucose cotransporter-2 (SGLT-2) inhibitors. We included patients prescribed with and adherent to metformin. HSD was used to develop and test (using 2019 data as well) the algorithm imputing HbA1c values ≥7% according to a series of covariates. The algorithm was gathered by combining beta-coefficients being estimated by logistic regression models using complete case (excluding missing values) and imputed (after multiple imputation) dataset. The final algorithm was applied to ReS database using the same covariates.

RESULTS

The tested algorithms were able to explain 17%-18% variation in assessing HbA1c values. Good discrimination (70%) and calibration were obtained as well. The best algorithm (three) cut-offs, namely those providing correct classifications ranging 66%-70% was therefore calculated and applied to ReS database. By doing so, from 52 999 (27.9, 95% CI: 27.7%-28.1%) to 74 250 (40.1%, 95% CI: 38.9%-39.3%) patients were estimated with HbA1c ≥7%.

CONCLUSION

Through this methodology, healthcare authorities should be able to quantify the population eligible to a new licensed medication, such as SGLT-2 inhibitors, and to simulate scenarios to assess reimbursement criteria according to precise estimates.

Epidemiology of pediatric psoriasis: a population-based study using two Italian data sources

BACKGROUND

Psoriasis can be associated with certain comorbidities. This information is important for family pediatricians (FPs) and general practitioners (GPs) who have a key role in the identification and management of skin diseases. This study aimed to assess the incidence and prevalence rates of pediatrics psoriasis and its association with specific comorbidities.

METHODS

A retrospective cohort study was performed in patients aged less than 18 years registered in two Italian primary care databases (Pedianet and HSD) between 2015 and 2019. Prevalence and incidence of psoriasis were estimated, and a case-control design was adopted to assess specific comorbidities in psoriasis patients.

RESULTS

The annual prevalence rate of psoriasis was 0.2% in Pedianet and between 0.5% and 0.7% in HSD. The incidence rate ranged from 0.47 to 0.58 and from 1.3 to 1.77 per 1000 person-years in Pedianet and HSD, respectively. Allergic rhinitis, asthma, celiac disease, other malabsorption disease and non-infective cutaneous diseases showed a statistically significant association with psoriasis in Pedianet, while no statistically significant difference was found in HSD.

CONCLUSION

Given the FP-GP transition of patients, there is a need for accurate registration of clinical correlates, enabling GPs to implement strategies to minimize the lifetime risk of psoriatic progression.

Postmarketing observational study on the safety of 2021/2022 and 2022/2023 influenza vaccination campaigns in Italy: TheShinISS-Vax|Flu study protocol

INTRODUCTION

The purpose of TheShinISS-Vax|Flu study is to examine the association between influenza vaccines and adverse events requiring hospital admission or emergency care during the influenza vaccination campaigns 2021/2022 and 2022/2023 in Italy.

METHODS AND ANALYSIS

This is a Self-Controlled Case Series multiregional study using linked routinely collected data from regional healthcare databases of the participating regions. Study participants will be persons aged ≥6 months, unvaccinated or who have received influenza vaccine during the influenza vaccination campaigns in the seasons 2021/2022 and 2022/2023 in Italy and who have experienced the outcome of interest for the first time during the study period (1 September 2021-30 June 2022 and 1 September 2022-30 June 2023 for the first and second vaccination campaigns, respectively). Risk periods will be specifically defined for each outcome and further subdivided into periods of 7 days. The exposures will be the first or second dose of the influenza vaccines administered during the two vaccination campaigns. Statistical analysis will be conducted separately for the data of the two campaigns. Exposure risk period will be compared with baseline risk period defined as any time of observation out of the risk periods. The modified SCCS method will be applied to handle event-dependent exposure and mortality and fitted using unbiased estimating equations to estimate relative incidences and excess of cases per 100 000 vaccinated by dose, age, sex and type of vaccine. Calendar period will be included as time-varying confounder in the model, where appropriate.

ETHICS AND DISSEMINATION

The study received the approval from the National ethics committee for clinical trials of public research bodies and other national public institutions (PRE BIO CE n.0036723, 23/09/2022). Results will be published in peer-reviewed journals and reports in accordance with the publication policies of the Italian National Institute of Health and of the Italian Medicines Agency.

Safety of drugs used for the treatment of migraine during pregnancy: a narrative review

INTRODUCTION

Migraine is common in females of childbearing age and negatively impacts quality of life. The majority of those with migraine who become pregnant see an improvement in their condition but not all do. Providing evidence-based recommendations for the pharmacological management of migraine in pregnancy is challenging.

AREAS COVERED

This narrative review provides an update on the safety of drugs used for migraine in pregnancy. National and international guidelines on the management of episodic migraine in adults were used to select the drugs of relevance to pregnant women. The final list of drugs was chosen by a pain specialist who categorized them according to drug class and use in acute management or prevention. PubMed was searched from inception to 31st July 2022 for evidence on drug safety.

EXPERT OPINION

Obtaining high-quality drug safety data in pregnant migraineurs is difficult not least because exposing a fetus to research-related risks is often considered unethical. There is reliance on observational studies which often group drugs together and lack specificities pertinent to drug prescribing like timing, dosing and duration. Improved statistical tools, study designs and the creation of international collaborative frameworks are ways to advance knowledge on drug safety in pregnancy.

Federated analyses of multiple data sources in drug safety studies

PURPOSE

Studies of rare side effects of new drugs with limited exposure may require pooling of multiple data sources. Federated Analyses (FA) allow real-time, interactive, centralized statistical processing of individual-level data from different data sets without transfer of sensitive personal data.

METHODS

We review IT-architecture, legal considerations, and statistical methods in FA, based on a Swedish Medical Products Agency methodological development project.

RESULTS

In a review of all post-authorisation safety studies assessed by the EMA during 2019, 74% (20/27 studies) reported issues with lack of precision in spite of mean study periods of 9.3 years. FA could potentially improve precision in such studies. Depending on the statistical model, the federated approach can generate identical results to a standard analysis. FA may be particularly attractive for repeated collaborative projects where data is regularly updated. There are also important limitations. Detailed agreements between involved parties are strongly recommended to anticipate potential issues and conflicts, document a shared understanding of the project, and fully comply with legal obligations regarding ethics and data protection. FA do not remove the data harmonisation step, which remains essential and often cumbersome. Reliable support for technical integration with the local server architecture and security solutions is required. Common statistical methods are available, but adaptations may be required.

CONCLUSIONS

Federated Analyses require competent and active involvement of all collaborating parties but have the potential to facilitate collaboration across institutional and national borders and improve the precision of postmarketing drug safety studies.

Assessment and Improvement of Drug Data Structuredness From Electronic Health Records: Algorithm Development and Validation

BACKGROUND

Digitization offers a multitude of opportunities to gain insights into current diagnostics and therapies from retrospective data. In this context, real-world data and their accessibility are of increasing importance to support unbiased and reliable research on big data. However, routinely collected data are not readily usable for research owing to the unstructured nature of health care systems and a lack of interoperability between these systems. This challenge is evident in drug data.

OBJECTIVE

This study aimed to present an approach that identifies and increases the structuredness of drug data while ensuring standardization according to Anatomical Therapeutic Chemical (ATC) classification.

METHODS

Our approach was based on available drug prescriptions and a drug catalog and consisted of 4 steps. First, we performed an initial analysis of the structuredness of local drug data to define a point of comparison for the effectiveness of the overall approach. Second, we applied 3 algorithms to unstructured data that translated text into ATC codes based on string comparisons in terms of ingredients and product names and performed similarity comparisons based on Levenshtein distance. Third, we validated the results of the 3 algorithms with expert knowledge based on the 1000 most frequently used prescription texts. Fourth, we performed a final validation to determine the increased degree of structuredness.

RESULTS

Initially, 47.73% (n=843,980) of 1,768,153 drug prescriptions were classified as structured. With the application of the 3 algorithms, we were able to increase the degree of structuredness to 85.18% (n=1,506,059) based on the 1000 most frequent medication prescriptions. In this regard, the combination of algorithms 1, 2, and 3 resulted in a correctness level of 100% (with 57,264 ATC codes identified), algorithms 1 and 3 resulted in 99.6% (with 152,404 codes identified), and algorithms 1 and 2 resulted in 95.9% (with 39,472 codes identified).

CONCLUSIONS

As shown in the first analysis steps of our approach, the availability of a product catalog to select during the documentation process is not sufficient to generate structured data. Our 4-step approach reduces the problems and reliably increases the structuredness automatically. Similarity matching shows promising results, particularly for entries with no connection to a product catalog. However, further enhancement of the correctness of such a similarity matching algorithm needs to be investigated in future work.

Background rates of 41 adverse events of special interest for COVID-19 vaccines in 10 European healthcare databases - an ACCESS cohort study

BACKGROUND

In May 2020, the ACCESS (The vACCine covid-19 monitoring readinESS) project was launched to prepare real-world monitoring of COVID-19 vaccines. Within this project, this study aimed to generate background incidence rates of 41 adverse events of special interest (AESI) to contextualize potential safety signals detected following administration of COVID-19 vaccines.

METHODS

A dynamic cohort study was conducted using a distributed data network of 10 healthcare databases from 7 European countries (Italy, Spain, Denmark, The Netherlands, Germany, France and United Kingdom) over the period 2017 to 2020. A common protocol (EUPAS37273), common data model, and common analytics programs were applied for syntactic, semantic and analytical harmonization. Incidence rates (IR) for each AESI and each database were calculated by age and sex by dividing the number of incident cases by the total person-time at risk. Age-standardized rates were pooled using random effect models according to the provenance of the events.

FINDINGS

A total number of 63,456,074 individuals were included in the study, contributing to 211.7 million person-years. A clear age pattern was observed for most AESIs, rates also varied by provenance of disease diagnosis (primary care, specialist care). Thrombosis with thrombocytopenia rates were extremely low ranging from 0.06 to 4.53/100,000 person-years for cerebral venous sinus thrombosis (CVST) with thrombocytopenia (TP) and mixed venous and arterial thrombosis with TP, respectively.

INTERPRETATION

Given the nature of the AESIs and the setting (general practitioners or hospital-based databases or both), background rates from databases that show the highest level of completeness (primary care and specialist care) should be preferred, others can be used for sensitivity. The study was designed to ensure representativeness to the European population and generalizability of the background incidence rates.

FUNDING

The project has received support from the European Medicines Agency under the Framework service contract nr EMA/2018/28/PE.

An overview of methodological flaws of real-world studies investigating drug safety in the post-marketing setting

INTRODUCTION

The evaluation of the post-marketing safety profile of drugs is a continuous monitoring process for approved and marketed medicines and it is crucial for detecting new adverse drug reactions. As such, real-world studies are essential to complement pre-marketing evidence with information concerning drug risk-benefit profile and use in wider patient populations and they have a great potential to support post-marketing drug safety evaluations.

AREAS COVERED

A detailed description of the main limitations of real-world data sources (i.e. claims databases, electronic healthcare records, drug/disease registers and spontaneous reporting system databases) and of the main methodological challenges of real-world studies in generating real-world evidence is provided.

EXPERT OPINION

Real-world evidence biases can be ascribed to both the methodological approach and the specific limitations of the different real-world data sources used to carry out the study. As such, it is crucial to characterize the quality of real-world data, by establishing guidelines and best practices for the assessment of data fitness for purpose. On the other hand, it is important that real-world studies are conducted using a rigorous methodology, aimed at minimizing the risk of bias.

Challenges and opportunities for mining adverse drug reactions: perspectives from pharma, regulatory agencies, healthcare providers and consumers

Monitoring drug safety is a central concern throughout the drug life cycle. Information about toxicity and adverse events is generated at every stage of this life cycle, and stakeholders have a strong interest in applying text mining and artificial intelligence (AI) methods to manage the ever-increasing volume of this information. Recognizing the importance of these applications and the role of challenge evaluations to drive progress in text mining, the organizers of BioCreative VII (Critical Assessment of Information Extraction in Biology) convened a panel of experts to explore ‘Challenges in Mining Drug Adverse Reactions’. This article is an outgrowth of the panel; each panelist has highlighted specific text mining application(s), based on their research and their experiences in organizing text mining challenge evaluations. While these highlighted applications only sample the complexity of this problem space, they reveal both opportunities and challenges for text mining to aid in the complex process of drug discovery, testing, marketing and post-market surveillance. Stakeholders are eager to embrace natural language processing and AI tools to help in this process, provided that these tools can be demonstrated to add value to stakeholder workflows. This creates an opportunity for the BioCreative community to work in partnership with regulatory agencies, pharma and the text mining community to identify next steps for future challenge evaluations.

Prescribing Patterns of Codeine and Alternative Medicines in Children in Europe

Introduction

Concerns over serious respiratory depression in children led to two European Union (EU) referral procedures (in 2013 and 2015) to review the benefit–risk balance of codeine in this population when used for pain relief, cough or cold. Consequently, codeine should no longer be used in children aged < 12 years and restrictions were introduced for treatment in children ≥ 12 years.

Objective

This multinational collaborative study aimed to assess the effectiveness of these risk minimisation measures by evaluating changes in prescribing of codeine and alternative treatments.

Method

Children under 12 and 12–18 years old were followed between 2010 and 2017 to analyse quarterly trends in prescribing of codeine and alternative treatments in electronic health records from France, Germany, Norway, Spain and the United Kingdom using interrupted time series analysis.

Results

Overall prescribing of codeine in children decreased in all five countries, reaching near zero prevalence in children under 12 years of age. This was accompanied by an increase in use of other opioid analgesics in France (from 0.15 to 0.56 prevalence per 100 person-years immediately after the first referral), Norway (from 0.0006 to 0.0013 at the end of the study), the United Kingdom (from 0.018 to 0.05 at the end of the study), and an increase in non-opioid analgesics in Norway (from 0.045 to 0.075 at the end of the study) after the referral on pain relief indication. The referral on cough/cold indication led to a decrease in use of opioid and non-opioid antitussives in children aged < 12 years in France (from 10 to 7 and 20 to 16, respectively) and had no impact in other countries. Overall prescribing trends for codeine and alternatives were similar across both age groups within each country.

Conclusion

The decrease in use of codeine shows that healthcare professionals followed the adopted measures and switched prescribing practices for pain management in children aged < 18 years towards opioid or non-opioid analgesics depending on national clinical and reimbursement settings. Whist the magnitude of the first referral on pain differed between countries, the second referral on cough/cold had only a minimal impact on the use of codeine and antitussives.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40264-022-01214-y.

Advancing drug safety science by integrating molecular knowledge with post-marketing adverse event reports

Promising drug development efforts may frequently fail due to unintended adverse reactions. Several methods have been developed to analyze such data, aiming to improve pharmacovigilance and drug safety. In this work, we provide a brief review of key directions to quantitatively analyzing adverse events and explore the potential of augmenting these methods using additional molecular data descriptors. We argue that molecular expansion of adverse event data may provide a path to improving the insights gained through more traditional pharmacovigilance approaches. Examples include the ability to assess statistical relevance with respect to underlying biomolecular mechanisms, the ability to generate plausible causative hypotheses and/or confirmation where possible, the ability to computationally study potential clinical trial designs and/or results, as well as the further provision of advanced features incorporated in innovative methods, such as machine learning. In summary, molecular data expansion provides an elegant way to extend mechanistic modeling, systems pharmacology, and patient‐centered approaches for the assessment of drug safety. We anticipate that such advances in real‐world data informatics and outcome analytics will help to better inform public health, via the improved ability to prospectively understand and predict various types of drug‐induced molecular perturbations and adverse events.

Overview of the EU PAS register post-authorization studies performed in Europe from September 2010 to December 2018

BACKGROUND

The European post-authorisation study (EU PAS) register is a repository launched in 2010 by the European Medicines Agency (EMA). All EMA-requested PAS, commonly observational studies, must be recorded in this register. Multi-database studies (MDS) leveraging secondary data have become an important strategy to conduct PAS in recent years, as reflected by the type of studies registered in the EU PAS register.

OBJECTIVES

To analyse and describe PAS in the EU PAS register, with focus on MDS.

METHODS

Studies in the EU PAS register from inception to 31^st December 2018 were described concerning transparency, regulatory obligations, scope, study type (e.g. observational study, clinical trial, survey, systematic review/meta-analysis), study design, type of data collection and target population. MDS were defined as studies conducted through secondary use of >1 data source not linked at patient-level. Data extraction was carried out independently by 14 centres with expertise in pharmacoepidemiology, using publicly available information in the EU PAS register including study protocol, whenever available, using a standardised data collection form. For validation purposes, a second revision of key fields for a 15% random sample of studies was carried out by a different centre. The inter-rater reliability (IRR) was then calculated. Finally, to identify predictors of primary data collection-based studies /vs those based on secondary use of healthcare databases) or MDS (vs. non-MDS), odds ratios (OR) and 95% confidence intervals (CI) were calculated fitting univariate logistic regression models.

RESULTS

Overall, 1,426 studies were identified. Clinical trials (N=30; 2%), systematic reviews/meta-analyses (N=16; 1%) and miscellaneous study designs (N=46; 3%) were much less common than observational studies (N=1,227; 86%). The protocol was available for 63% (N=360) of 572 observational studies requested by a competent authority. Overall, 36% (N=446) of observational studies were based fully or partially on primary data collection. Of 757 observational studies based on secondary use of data alone, 282 (37%) were MDS. Drug utilisation was significantly more common as a study scope in MDS compared to non-MDS studies. The overall percentage agreement among collaborating centres that collected the data concerning study variables was highest for study type (93.5%) and lowest for type of secondary data (67.8%).

CONCLUSIONS

Observational studies were the most common type of studies in the EU PAS register, but 30% used primary data, which is more resource-intensive. Almost half of observational studies using secondary data were MDS. Data recording in the EU PAS register may be improved further, including more widespread availability of study protocols to improve transparency.

From Inception to ConcePTION: Genesis of a Network to Support Better Monitoring and Communication of Medication Safety During Pregnancy and Breastfeeding

In 2019, the Innovative Medicines Initiative (IMI) funded the ConcePTION project-Building an ecosystem for better monitoring and communicating safety of medicines use in pregnancy and breastfeeding: validated and regulatory endorsed workflows for fast, optimised evidence generation-with the vision that there is a societal obligation to rapidly reduce uncertainty about the safety of medication use in pregnancy and breastfeeding. The present paper introduces the set of concepts used to describe the European data sources involved in the ConcePTION project and illustrates the ConcePTION Common Data Model (CDM), which serves as the keystone of the federated ConcePTION network. Based on data availability and content analysis of 21 European data sources, the ConcePTION CDM has been structured with six tables designed to capture data from routine healthcare, three tables for data from public health surveillance activities, three curated tables for derived data on population (e.g., observation time and mother-child linkage), plus four metadata tables. By its first anniversary, the ConcePTION CDM has enabled 13 data sources to run common scripts to contribute to major European projects, demonstrating its capacity to facilitate effective and transparent deployment of distributed analytics, and its potential to address questions about utilization, effectiveness, and safety of medicines in special populations, including during pregnancy and breastfeeding, and, more broadly, in the general population.

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

BACKGROUND

Biological drugs have improved the management of immune-mediated inflammatory diseases (IMIDs) despite being associated with important safety issues such as immunogenicity, infections, and malignancies in real-world settings.

OBJECTIVE

The aim of this study was to explore the potential of a large Italian multi-database distributed network for use in the postmarketing surveillance of biological drugs, including biosimilars, in patients with IMID.

METHODS

A retrospective cohort study was conducted using 13 Italian regional claims databases during 2010-2019. A tailor-made R-based tool developed for distributed analysis of claims data using a study-specific common data model was customized for this study. We measured the yearly prevalence of biological drug users and the frequency of switches between originator and biosimilars for infliximab, etanercept, and adalimumab separately and stratified them by calendar year and region. We then calculated the cumulative number of users and person-years (PYs) of exposure to individual biological drugs approved for IMIDs. For a number of safety outcomes (e.g., severe acute respiratory syndrome coronavirus 2 [SARS-COV-2] infection), we conducted a sample power calculation to estimate the PYs of exposure required to investigate their association with individual biological drugs approved for IMIDs, considering different strengths of association.

RESULTS

From a total underlying population of almost 50 million inhabitants from 13 Italian regions, we identified 143,602 (0.3%) biological drug users, with a cumulative exposure of 507,745 PYs during the entire follow-up. The mean age ± standard deviation of biological drug users was 49.3 ± 16.3, with a female-to-male ratio of 1.2. The age-adjusted yearly prevalence of biological drug users increased threefold from 0.7 per 1000 in 2010 to 2.1 per 1000 in 2019. Overall, we identified 40,996 users of biosimilars of tumor necrosis factor (TNF)-α inhibitors (i.e., etanercept, adalimumab, and infliximab) in the years 2015-2019. Of these, 46% (N = 18,845) switched at any time between originator and biosimilars or vice versa. To investigate a moderate association (incidence rate ratio 2) between biological drugs approved for IMIDs and safety events of interest, such as optic neuritis (lowest background incidence rate 10.4/100,000 PYs) or severe infection (highest background incidence rate 4312/100,000 PYs), a total of 43,311 PYs and 104 PYs of exposure to individual biological drugs, respectively, would be required. As such, using this network, of 15 individual biological drugs approved for IMIDs, the association with those adverse events could be investigated for four (27%) and 14 (93%), respectively.

CONCLUSION

The VALORE project multi-database network has access to data on more than 140,000 biological drug users (and > 0.5 million PYs) from 13 Italian regions during the years 2010-2019, which will be further expanded with the inclusion of data from other regions and more recent calendar years. Overall, the cumulated amount of person-time of exposure to biological drugs approved for IMIDs provides enough statistical power to investigate weak/moderate associations of almost all individual compounds and the most relevant safety outcomes. Moreover, this network may offer the opportunity to investigate the interchangeability of originator and biosimilars of several TNFα inhibitors in different therapeutic areas in real-world settings.

Renoprotective effect of SGLT-2 inhibitors among type 2 diabetes patients with different baseline kidney function: a multi-center study

Background

To assess the effect of sodium glucose cotransporter-2 inhibitors (SGLT-2is) for type 2 diabetes on kidney outcomes stratified by patient baseline estimated glomerular filtration rate (eGFR) levels (i.e., eGFR ≤ 60, 60 < eGFR ≤ 90, and eGFR > 90 mL/min/1.73 m²).

Methods

Patients from three large healthcare delivery systems in Taiwan who had initiated SGLT-2is or other glucose-lowering drugs (oGLDs) between May 2016 and December 2017 were included. Main outcomes were the times to 30%, 40%, and 50% eGFR reduction after treatment initiation. One-to-one propensity score matching in the overall study cohort and in each eGFR subgroup between SGLT-2i and oGLD users was applied to ensure between-group comparability in baseline characteristics.

Results

There were 13,666 matched pairs of SGLT-2is and oGLD users in the overall cohort. While a sustained eGFR decline was revealed in oGLD-treated patients (mean values [standard errors] from 85.61 [0.43] to 82.49 [0.44] mL/min/1.73 m² during the 12 months after treatment initiation), the mean eGFR values of SGLT-2i users decreased in the first 3 months (85.68 [0.37] to 79.71 [0.41] mL/min/1.73 m²) but then improved and sustained until the end of follow-up. There were 2300, 5705, and 5509 matched SGLT-2i and oGLD users in the eGFR ≤ 60, 60 < eGFR ≤ 90, and eGFR > 90 subgroups, respectively. Using SGLT-2is versus oGLDs was significantly associated with slower eGFR declines; hazard ratios (HRs) were 0.51 (95% CI 0.37–0.69), 0.51 (0.37–0.70), and 0.47 (0.31–0.71) for 40% eGFR reduction in the eGFR ≤ 60, 60 < eGFR ≤ 90, and eGFR > 90 subgroups, respectively. The renoprotective effect of SGLT-2is versus oGLDs was confirmed in the outcomes of 30% and 50% eGFR reduction across the three eGFR subgroups.

Conclusions

This study supports the renoprotective benefit of real-world SGLT-2i use irrespective of patient baseline kidney function.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01396-2.

Desloratadine Exposure and Incidence of Seizure: A Nordic Post-authorization Safety Study Using a New-User Cohort Study Design, 2001-2015

Introduction

A small number of adverse events of seizure in patients using desloratadine (DL) have been reported. The European Medicines Agency requested a post-authorization safety study to investigate whether there is an association between DL exposure and seizure.

Objective

The aim was to study the association between DL exposure and incidence of first seizure.

Methods

A new-user cohort study of individuals redeeming a first-ever prescription of DL in Denmark, Finland, Norway, and Sweden in 2001–2015 was conducted. DL exposure was defined as days’ supply plus a 4-week grace period. DL unexposed periods were initiated 27 weeks after DL prescription redemption. Poisson regression was used to estimate the adjusted incidence rate and adjusted incidence rate ratio (aIRR) of incident seizure.

Results

A total of 1,807,347 first-ever DL users were included in the study, with 49.3% male and a mean age of 29.5 years at inclusion; 20.3% were children aged 0–5 years. The adjusted incidence rates of seizure were 21.7 and 31.6 per 100,000 person-years during DL unexposed and exposed periods, respectively. A 46% increased incidence rate of seizure was found during DL exposed periods (aIRR = 1.46, 95% confidence interval [CI] 1.34–1.59). The aIRR ranged from 1.85 (95% CI 1.65–2.08) in children aged 0–5 years to 1.01 in adults aged 20 years or more (95% CI 0.85–1.19).

Conclusion

This study found an increased incidence rate of seizure during DL exposed periods as compared to unexposed periods among individuals younger than 20 years. No difference in incidence rate of seizure was observed in adults between DL exposed and unexposed.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40264-021-01106-7.

The Italian Network for Monitoring Medication Use During Pregnancy (MoM-Net): Experience and Perspectives

There is an acute need for research to acquire high-quality information on the use of medicines in pregnancy, both in terms of appropriateness and safety. For this purpose, the Italian Medicines Agency established a Network for Monitoring Medication use in pregnancy (MoM-Net) through the conduction of population-based studies using administrative data available at regional level. This paper aimed to describe the experiences and challenges within the network. MoM-Net currently involves eight regions and several experts from public and academic institutions. The first study conducted aimed to identify drug use before, during and after pregnancy investigating specific therapeutic categories, analysing regional variability and monitoring drug use in specific subpopulations (i.e. foreign women/multiple pregnancies). Aggregated demographic, clinical, and prescription data were analysed using a distributed network approach based on common data model. The study population included all women delivering during 2016–2018 in the participating regions (n = 449,012), and corresponding to 59% of deliveries in Italy. Seventy-three per cent of the cohort had at least one drug prescription during pregnancy, compared to 57% before and 59% after pregnancy. In general, a good adherence to guidelines for pregnant women was found although some drug categories at risk of inappropriateness, such as progestins and antibiotics, were prescribed. A strong variability in the use of drugs among regions and in specific subpopulations was observed. The MoM-Net represents a valuable surveillance system on the use of medicines in pregnancy, available to monitor drug categories at high risk of inappropriateness and to investigate health needs in specific regions or subpopulations.

A systematic review of how missing data are handled and reported in multi-database pharmacoepidemiologic studies

Purpose

Pharmacoepidemiologic multi‐database studies (MDBS) provide opportunities to better evaluate the safety and effectiveness of medicines. However, the issue of missing data is often exacerbated in MDBS, potentially resulting in bias and precision loss. We sought to measure how missing data are being recorded and addressed in pharmacoepidemiologic MDBS.

Methods

We conducted a systematic literature search in PubMed for pharmacoepidemiologic MDBS published between 1st January 2018 and 31st December 2019. Included studies were those that used ≥2 distinct databases to assess the same safety/effectiveness outcome associated with a drug exposure. Outcome variables extracted from the studies included strategies to execute a MDBS, reporting of missing data (type, bias evaluation) and the methods used to account for missing data.

Results

Two thousand seven hundred and twenty‐six articles were identified, and 62 studies were included: using data from either North America (56%), Europe (31%), multiple regions (11%) or East‐Asia (2%). Thirty‐five (56%) articles reported missing data: 11 of these studies reported that this could have introduced bias and 19 studies reported a method to address missing data. Thirteen (68%) carried out a complete case analysis, 2 (11%) applied multiple imputation, 2 (11%) used both methods, 1 (5%) used mean imputation and 1 (5%) substituted information from a similar variable.

Conclusions

Just over half of the recent pharmacoepidemiologic MDBS reported missing data and two‐thirds of these studies reported how they accounted for it. We should increase our vigilance for database completeness in MDBS by reporting and addressing the missing data that could introduce bias.

Drug safety in thalassemia: lessons from the present and directions for the future

Introduction: Beta-thalassemia is an autosomal recessive hereditary anemia characterized by reduced or absent β-globin chain synthesis, affecting about 60,000 people peryear. Management for β-thalassemia major includes regular blood transfusions followed by iron chelating therapy and drug targeting ineffective erythropoiesis.Areas covered: The safety of licensed drugs for the management of β-thalassemia is reviewed, using evidence from clinical trials and observational research. Such drugs include the iron chelators and the erythrocyte maturation agent luspatercept. The safety of emerging treatment, such as hydroxyurea and thalidomide is also reviewed.Expert opinion: Beta-thalassemia is arare disease, and is not surprising that there are limited studies investigating the safety of drugs used in this disease. Indeed, although observational studies are the main source of drug safety information in areal-world setting, only eleven studies were identified for iron-chelators and none of these estimated the risk of agiven safety outcome. Future work should aim to better leverage existing sources of real-world datato investigate drug safety in thalassemia.

Challenges for Drug Repurposing in the COVID-19 Pandemic Era

The coronavirus disease (COVID-19) pandemic has affected an estimated 16 million persons and caused 0.6 million deaths worldwide by September 2020. The pandemic has led to a rush to repurpose existing drugs, although the underlying evidence base is of variable quality. The improving knowledge of the virology and clinical presentation of COVID-19 is leading to a broadening pool of potential pharmacological targets. The aim of this review is to describe regulatory and pharmacological aspects of drug repurposing and to identify drugs proposed for repurposing in COVID-19 based on registered clinical trials, discussing the evidence to support their use in the treatment of this disease. The challenges of the correct interpretation of existing pre-clinical/clinical evidence as well as the generation of new evidence concerning drug repurposing in COVID-19 will also be discussed. Clinical Trial Registration: https://clinicaltrials.gov, identifier NCT04321174, NCT04342663, NCT04280705, NCT04244591, NCT04359329, NCT04348695, NCT04304313, NCT043505931.