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

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

Design and validation of algorithms to identify venous thromboembolism in the French National Healthcare Database.

PURPOSE: This paper aims to introduce an algorithm designed to identify Venous Thromboembolism (VTE) in the French National Healthcare Database (SNDS) and to estimate its positive predictive value. METHODS: A case-identifying algorithm was designed using SNDS inpatient and outpatient encounters, including hospital stays with discharge diagnoses, imaging procedures and drugs dispensed, of French patients aged at least 18 years old to whom baricitinib or Tumor Necrosis Factor Inhibitors (TNFi) were dispensed between September 1, 2017, and December 31, 2018. An intra-database validation study was then conducted, drawing 150 cases identified as VTE by the algorithm and requesting four vascular specialists to assess them. Patient profiles used to conduct the case adjudication were reconstituted from de-identified pooled and formatted SNDS data (i.e., reconstituted electronic health records-rEHR) with a 6-month look-back period prior to the supposed VTE onset and a 12-month follow-up period after. The positive predictive value (PPV) with its 95% confidence interval (95% CI) was calculated as the number of expert-confirmed VTE divided by the number of algorithm-identified VTE. The PPV and its 95% CI were then recomputed among the same patient set initially drawn, once the VTE-identifying algorithm was updated based on expert recommendation. RESULTS: For the 150 patients identified with the first VTE-identifying algorithm, the adjudication committee confirmed 92 cases, resulting in a PPV of 61% (95% CI = [54-69]). The final VTE-identifying algorithm including expert suggestions showed a PPV of 92% (95% CI = [86-98]) with a total of 87 algorithm-identified cases, including 80 retrieved from the 92 confirmed by experts. CONCLUSION: The identification of VTE in the SNDS is possible with a good PPV.

Frequency and timing of adverse reactions to COVID-19 vaccines; A multi-country cohort event monitoring study.

INTRODUCTION: During the COVID-19 pandemic, EMA set-up a large-scale cohort event monitoring (CEM) system to estimate incidence rates of patient-reported adverse drug reactions (ADRs) of different COVID-19 vaccines across the participating countries. This study aims to give an up to date and in-depth analysis of the frequency of patient-reported ADRs after the 1st, 2nd, and booster vaccination, to identify potential predictors in developing ADRs and to describe time-to-onset (TTO) and time-to-recovery (TTR) of ADRs. METHODS: A CEM study was rolled out in a period ranging from February 2021 to February 2023 across multiple European countries; The Netherlands, Belgium, France, the United Kingdom, Italy, Portugal, Romania, Slovakia and Spain. Analysis consisted of a descriptive analyses of frequencies of COVID-19 vaccine-related ADRs for 1st, 2nd and booster vaccination, analysis of potential predictors in developing ADRs with a generalized linear mixed-effects model, analysis of TTO and TTR of ADRs and a sensitivity analysis for loss to follow-up (L2FU). RESULTS: A total of 29,837 participants completed at least the baseline and the first follow-up questionnaire for 1st and 2nd vaccination and 7,250 participants for the booster. The percentage of participants who reported at least one ADR is 74.32% (95%CI 73.82-74.81). Solicited ADRs, including injection site reactions, are very common across vaccination moments. Potential predictors for these reactions are the brand of vaccine used, the patient's age, sex and prior SARS-CoV-2 infection. The percentage of serious ADRs in the study is low for 1st and 2nd vaccination (0.24%, 95%CI 0.19--0.31) and booster (0.26%, 95%CI 0.15, 0.41). The TTO was 14 h (median) for dose 1 and slightly longer for dose 2 and booster dose. TTR is generally also within a few days. The effect of L2FU on estimations of frequency is limited. CONCLUSION: Despite some limitations due to study design and study-roll out, CEM studies can allow prompt and almost real-time observations of the safety of medications directly from a patient-centered perspective, which can play a crucial role for regulatory bodies during an emergency setting such as the COVID-19 pandemic.

Clinical Characterization of Patients Diagnosed with Prostate Cancer and Undergoing Conservative Management: A PIONEER Analysis Based on Big Data.

BACKGROUND: Conservative management is an option for prostate cancer (PCa) patients either with the objective of delaying or even avoiding curative therapy, or to wait until palliative treatment is needed. PIONEER, funded by the European Commission Innovative Medicines Initiative, aims at improving PCa care across Europe through the application of big data analytics. OBJECTIVE: To describe the clinical characteristics and long-term outcomes of PCa patients on conservative management by using an international large network of real-world data. DESIGN, SETTING, AND PARTICIPANTS: From an initial cohort of >100 000 000 adult individuals included in eight databases evaluated during a virtual study-a-thon hosted by PIONEER, we identified newly diagnosed PCa cases (n = 527 311). Among those, we selected patients who did not receive curative or palliative treatment within 6 mo from diagnosis (n = 123 146). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Patient and disease characteristics were reported. The number of patients who experienced the main study outcomes was quantified for each stratum and the overall cohort. Kaplan-Meier analyses were used to estimate the distribution of time to event data. RESULTS AND LIMITATIONS: The most common comorbidities were hypertension (35-73%), obesity (9.2-54%), and type 2 diabetes (11-28%). The rate of PCa-related symptomatic progression ranged between 2.6% and 6.2%. Hospitalization (12-25%) and emergency department visits (10-14%) were common events during the 1st year of follow-up. The probability of being free from both palliative and curative treatments decreased during follow-up. Limitations include a lack of information on patients and disease characteristics and on treatment intent. CONCLUSIONS: Our results allow us to better understand the current landscape of patients with PCa managed with conservative treatment. PIONEER offers a unique opportunity to characterize the baseline features and outcomes of PCa patients managed conservatively using real-world data. PATIENT SUMMARY: Up to 25% of men with prostate cancer (PCa) managed conservatively experienced hospitalization and emergency department visits within the 1st year after diagnosis; 6% experienced PCa-related symptoms. The probability of receiving therapies for PCa decreased according to time elapsed after the diagnosis.

Clustering of prostate cancer healthcare pathways in the French National Healthcare database.

Background: Healthcare pathways of patients with prostate cancer are heterogeneous and complex to apprehend using traditional descriptive statistics. Clustering and visualization methods can enhance their characterization. Methods: Patients with prostate cancer in 2014 were identified in the French National Healthcare database (Système National des Données de Santé-SNDS) and their data were extracted with up to 5 years of history and 4 years of follow-up. Fifty-one-specific encounters constitutive of prostate cancer management were synthesized into four macro-variables using a clustering approach. Their values over patient follow-ups constituted healthcare pathways. Optimal matching was applied to calculate distances between pathways. Partitioning around medoids was then used to define consistent groups across four exclusive cohorts of incident prostate cancer patients: Hormone-sensitive (HSPC), metastatic hormone-sensitive (mHSPC), castration-resistant (CRPC), and metastatic castration-resistant (mCRPC). Index plots were used to represent pathways clusters. Results: The repartition of macro-variables values-surveillance, local treatment, androgenic deprivation, and advanced treatment-appeared to be consistent with prostate cancer status. Two to five clusters of healthcare pathways were observed in each of the different cohorts, corresponding for most of them to relevant clinical patterns, although some heterogeneity remained. For instance, clustering allowed to distinguish patients undergoing active surveillance, or treated according to cancer progression risk in HSPC, and patients receiving treatment for potentially curative or palliative purposes in mHSPC and mCRPC. Conclusion: Visualization methods combined with a clustering approach enabled the identification of clinically relevant patterns of prostate cancer management. Characterization of these care pathways is an essential element for the comprehension and the robust assessment of healthcare technology effectiveness.

Safety of COVID-19 Vaccines Among the Paediatric Population: Analysis of the European Surveillance Systems and Pivotal Clinical Trials.

BACKGROUND AND OBJECTIVES: The European Medicine Agency extended the use of Comirnaty, Spikevax, and Nuvaxovid in paediatrics; thus, these vaccines require additional real-world safety evidence. Herein, we aimed to monitor the safety of COVID-19 vaccines through Covid-19 Vaccine Monitor (CVM) and EudraVigilance surveillance systems and the published pivotal clinical trials. METHODS: In a prospective cohort of vaccinees aged between 5 and 17 years, we measured the frequency of commonly reported (local/systemic solicited) and serious adverse drug events (ADRs) following the first and second doses of COVID-19 vaccines in Europe using data from the CVM cohort until April 2022. The results of previous pivotal clinical trials and data in the EudraVigilance were also analysed. RESULTS: The CVM study enrolled 658 first-dose vaccinees (children aged 5-11 years; n = 250 and adolescents aged 12-17 years; n = 408). Local/systemic solicited ADRs were common, whereas serious ADRs were uncommon. Among Comirnaty first and second dose recipients, 28.8% and 17.1% of children and 54.2% and 52.2% of adolescents experienced at least one ADR, respectively; injection-site pain (29.2% and 20.7%), fatigue (16.1% and 12.8%), and headache (22.1% and 19.3%) were the most frequent local and systemic ADRs. Results were consistent but slightly lower than in pivotal clinical trials. Reporting rates in Eudravigilance were lower by a factor of 1000. CONCLUSIONS: The CVM study showed high frequencies of local solicited reactions after vaccination but lower rates than in pivotal clinical trials. Injection-site pain, fatigue, and headache were the most commonly reported ADRs for clinical trials, but higher than spontaneously reported data.

Cohort Event Monitoring of Adverse Reactions to COVID-19 Vaccines in Seven European Countries: Pooled Results on First Dose.

INTRODUCTION: COVID-19 vaccines were rapidly authorised, thus requiring intense post-marketing re-evaluation of their benefit-risk profile. A multi-national European collaboration was established with the aim to prospectively monitor safety of the COVID-19 vaccines through web-based survey of vaccinees. METHODS: A prospective cohort event monitoring study was conducted with primary consented data collection in seven European countries. Through the web applications, participants received and completed baseline and up to six follow-up questionnaires on self-reported adverse reactions for at least 6 months following the first dose of COVID-19 vaccine (Netherlands, France, Belgium, UK, Italy) and baseline and up to ten follow-up questionnaires for one year in Germany and Croatia. Rates of adverse reactions have been described by type (solicited, non-solicited; serious/non-serious; and adverse events of special interest) and stratified by vaccine brand. We calculated the frequency of adverse reaction after dose 1 and prior to dose 2 among all vaccinees who completed at least one follow-up questionnaire. RESULTS: Overall, 117,791 participants were included and completed the first questionnaire in addition to the baseline: 88,196 (74.9%) from Germany, 27,588 (23.4%) from Netherlands, 984 (0.8%) from France, 570 (0.5%) from Italy, 326 (0.3%) from Croatia, 89 (0.1%) from the UK and 38 (0.03%) from Belgium. There were 89,377 (75.9%) respondents who had received AstraZeneca vaccines, 14,658 (12.4%) BioNTech/Pfizer, 11,266 (9.6%) Moderna and 2490 (2.1%) Janssen vaccines as a first dose. Median age category was 40-49 years for all vaccines except for Pfizer where median age was 70-79 years. Most vaccinees were female with a female-to-male ratio of 1.34, 1.96 and 2.50 for AstraZeneca, Moderna and Janssen, respectively. BioNtech/Pfizer had slightly more men with a ratio of 0.82. Fatigue and headache were the most commonly reported solicited systemic adverse reactions and injection-site pain was the most common solicited local reaction. The rates of adverse events of special interest (AESIs) were 0.1-0.2% across all vaccine brands. CONCLUSION: This large-scale prospective study of COVID-19 vaccine recipients showed, for all the studied vaccines, a high frequency of systemic reactions, related to the immunogenic response, and local reactions at the injection site, while serious reactions or AESIs were uncommon, consistent with those reported on product labels. This study demonstrated the feasibility of setting up and conducting cohort event monitoring across multiple European countries to collect safety data on novel vaccines that are rolled out at scale in populations which may not have been included in pivotal trials.

Strong instrumental variables biased propensity scores in comparative effectiveness research: A case study in oncology.

BACKGROUND AND OBJECTIVES: Some medications require specific medical procedures in the weeks before their start. Such procedures may meet the definition of instrumental variables (IVs). We examined how they may influence treatment effect estimation in propensity score (PS)-adjusted comparative studies, and how to remedy. STUDY DESIGN AND SETTING: Different covariate assessment periods (CAPs) did and did not include the month preceding treatment start were used to compute PS in the French claims database (Sytème National des Données de Santé-SNDS), and 1:1 match patients with metastatic castration resistant prostate cancer initiating abiraterone acetate or docetaxel. The 36-month survival was assessed. RESULTS: Among 1, 213 docetaxel and 2, 442 abiraterone initiators, the PS distribution resulting from the CAP [-12; 0 months] distinctly separated populations (c = 0.93; 273 matched pairs). The CAPs [-12;-1 months] identified 765 pairs (c = 0.81). Strong docetaxel treatment predictors during the month before treatment start were implantable delivery systems (1% vs. 59%), which fulfilled IV conditions. The 36-month survival was not meaningfully different under the [-12; 0 months] CAP but differed by 10% points (38% vs. 28%) after excluding month -1. CONCLUSION: In the setting of highly predictive pretreatment procedures, excluding the immediate pre-exposure time from the CAP will reduce the risk of including potential IVs in PS models and may reduce bias.

Evaluation of VTE, MACE, and Serious Infections Among Patients with RA Treated with Baricitinib Compared to TNFi: A Multi-Database Study of Patients in Routine Care Using Disease Registries and Claims Databases.

INTRODUCTION: The aim of this work is to evaluate baricitinib safety with respect to venous thromboembolism (VTE), major adverse cardiovascular events (MACE), and serious infection relative to tumor necrosis factor inhibitors (TNFi) in patients with rheumatoid arthritis (RA). METHODS: Patients with RA from 14 real-world data sources (three disease registries, eight commercial and three government health insurance claims databases) in the United States (n = 9), Europe (n = 3), and Japan (n = 2) were analyzed using a new user active comparator design. Propensity score matching (1:1) controlled for potential confounding. Meta-analysis of incidence rate ratios (IRR) and incidence rate differences (IRD) for each outcome, from each data source was executed using modified Poisson regression and Cochran-Mantel-Haenszel analysis. RESULTS: Of 9013 eligible baricitinib-treated patients, 7606 were propensity score-matched with TNFi-treated patients, contributing 5879 and 6512 person-years of baricitinib and TNFi exposure, respectively. Across data sources, 97 patients (56 baricitinib) experienced VTE during follow-up, 93 experienced MACE (54 baricitinib), and 321 experienced serious infection (176 baricitinib). Overall IRRs comparing baricitinib with TNFi treatment were 1.51 (95% CI 1.10, 2.08) for VTE, 1.54 (95% CI 0.93, 2.54) for MACE, and 1.36 (95% CI 0.86, 2.13) for serious infection. IRDs for VTE, MACE, and serious infection, respectively, were 0.26 (95% CI -0.04, 0.57), 0.22 (95% CI -0.07, 0.52), and 0.57 (95% CI -0.07, 1.21) per 100 person-years greater for baricitinib than TNFi. CONCLUSIONS: Overall results suggest increased risk of VTE with baricitinib versus TNFi, with consistent point estimates from the two largest data sources. A numerically greater risk was observed for MACE and serious infection when comparing baricitinib versus TNFi, with different point estimates from the two largest data sources. Findings from this study and their impact on clinical practice should be considered in context of limitations and other evidence regarding the safety and efficacy of baricitinib and other Janus kinase inhibitors. TRIAL REGISTRATION: EU PAS Register ( http://encepp.eu ), identifier #32271.

Towards an Interoperable Ecosystem of Research Cohort and Real-world Data Catalogues Enabling Multi-center Studies.

OBJECTIVES: Existing individual-level human data cover large populations on many dimensions such as lifestyle, demography, laboratory measures, clinical parameters, etc. Recent years have seen large investments in data catalogues to FAIRify data descriptions to capitalise on this great promise, i.e. make catalogue contents more Findable, Accessible, Interoperable and Reusable. However, their valuable diversity also created heterogeneity, which poses challenges to optimally exploit their richness. METHODS: In this opinion review, we analyse catalogues for human subject research ranging from cohort studies to surveillance, administrative and healthcare records. RESULTS: We observe that while these catalogues are heterogeneous, have various scopes, and use different terminologies, still the underlying concepts seem potentially harmonizable. We propose a unified framework to enable catalogue data sharing, with catalogues of multi-center cohorts nested as a special case in catalogues of real-world data sources. Moreover, we list recommendations to create an integrated community of metadata catalogues and an open catalogue ecosystem to sustain these efforts and maximise impact. CONCLUSIONS: We propose to embrace the autonomy of motivated catalogue teams and invest in their collaboration via minimal standardisation efforts such as clear data licensing, persistent identifiers for linking same records between catalogues, minimal metadata 'common data elements' using shared ontologies, symmetric architectures for data sharing (push/pull) with clear provenance tracks to process updates and acknowledge original contributors. And most importantly, we encourage the creation of environments for collaboration and resource sharing between catalogue developers, building on international networks such as OpenAIRE and research data alliance, as well as domain specific ESFRIs such as BBMRI and ELIXIR.

Abiraterone acetate versus docetaxel for metastatic castration-resistant prostate cancer: a cohort study within the French nationwide claims database.

OBJECTIVES: To conduct the direct comparison of abiraterone acetate and docetaxel for first-line treatment of metastatic castration-resistant prostate cancer (mCRPC) in real-life settings. METHODS: Data were extracted from the French nationwide claims database (SNDS) on all men aged ≥40 years starting first-line treatment with abiraterone acetate or docetaxel for mCRPC in 2014. A high-dimensional propensity score including 100 baseline characteristics was used to match patients of both groups and form two comparative cohorts. Three-year overall survival and treatment discontinuation-free survival were determined using Kaplan-Meier analysis. RESULTS: In 2014, 2,444 patients started abiraterone for treatment of mCRPC and 1,214 started docetaxel. After trimming and matching, 716 patients were available in each group. Median overall survival tended to be longer in the abiraterone acetate cohort (23.8 months, 95% confidence interval = [21.5; 26.0]) than in the docetaxel cohort (20.3 [18.4; 21.6] months). Survival at 36 months was 34.6% for abiraterone acetate and 27.9% for docetaxel (p = 0.0027). Treatment discontinuation-free median was longer in the abiraterone acetate cohort compared to the docetaxel cohort (10.8 [10.1; 11.7] versus 7.4 [7.0; 8.0] months). CONCLUSION: The findings underline the interest of oral abiraterone acetate over intravenous docetaxel as the first-line treatment option in mCRPC.

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.

Intra-database validation of case-identifying algorithms using reconstituted electronic health records from healthcare claims data.

BACKGROUND: Diagnosis performances of case-identifying algorithms developed in healthcare database are usually assessed by comparing identified cases with an external data source. When this is not feasible, intra-database validation can present an appropriate alternative. OBJECTIVES: To illustrate through two practical examples how to perform intra-database validations of case-identifying algorithms using reconstituted Electronic Health Records (rEHRs). METHODS: Patients with 1) multiple sclerosis (MS) relapses and 2) metastatic castration-resistant prostate cancer (mCRPC) were identified in the French nationwide healthcare database (SNDS) using two case-identifying algorithms. A validation study was then conducted to estimate diagnostic performances of these algorithms through the calculation of their positive predictive value (PPV) and negative predictive value (NPV). To that end, anonymized rEHRs were generated based on the overall information captured in the SNDS over time (e.g. procedure, hospital stays, drug dispensing, medical visits) for a random selection of patients identified as cases or non-cases according to the predefined algorithms. For each disease, an independent validation committee reviewed the rEHRs of 100 cases and 100 non-cases in order to adjudicate on the status of the selected patients (true case/ true non-case), blinded with respect to the result of the corresponding algorithm. RESULTS: Algorithm for relapses identification in MS showed a 95% PPV and 100% NPV. Algorithm for mCRPC identification showed a 97% PPV and 99% NPV. CONCLUSION: The use of rEHRs to conduct an intra-database validation appears to be a valuable tool to estimate the performances of a case-identifying algorithm and assess its validity, in the absence of alternative.

Empirical assessment of case-based methods for identification of drugs associated with acute liver injury in the French National Healthcare System database (SNDS).

PURPOSES: Drug induced acute liver injury (ALI) is a frequent cause of liver failure. Case-based designs were empirically assessed and calibrated in the French National claims database (SNDS), aiming to identify the optimum design for drug safety alert generation associated with ALI. METHODS: All cases of ALI were extracted from SNDS (2009-2014) using specific and sensitive definitions. Positive and negative drug controls were used to compare 196 self-controlled case series (SCCS), case-control (CC), and case-population (CP) design variants, using area under the receiver operating curve (AUC), mean square error (MSE) and coverage probability. Parameters that had major impacts on results were identified through logistic regression. RESULTS: Using a specific ALI definition, AUCs ranged from 0.78 to 0.94, 0.64 to 0.92 and 0.48 to 0.85, for SCCS, CC and CP, respectively. MSE ranged from 0.12 to 0.40, 0.22 to 0.39 and 1.03 to 5.29, respectively. Variants adjusting for multiple drug use had higher coverage probabilities. Univariate regressions showed that high AUCs were achieved with SCCS using exposed time as the risk window. The top SCCS variant yielded an AUC = 0.93 and MSE = 0.22 and coverage = 86%, with 1/7 negative and 13/18 positive controls presenting significant estimates. CONCLUSIONS: SCCS adjusting for multiple drugs and using exposed time as the risk window performed best in generating ALI-related drug safety alert and providing estimates of the magnitude of the risk. This approach may be useful for ad-hoc pharmacoepidemiology studies to support regulatory actions.

Epidemiology of metastatic castration-resistant prostate cancer: A first estimate of incidence and prevalence using the French nationwide healthcare database.

BACKGROUND: There is a lack of information about the burden of metastatic castration-resistant prostate cancer (mCRPC). The present work aims to estimate the incidence and prevalence of mCRPC in 2014 using the French nationwide healthcare database (SNDS). METHODS: Prevalence and incidence were estimated based on an SNDS extraction of men covered by the general healthcare insurance (86 % of the French population), and aged ≥40. Patients with mCRPC were identified amongst prostate cancer cases using an algorithm estimating a date of first metastasis management and a date of castration resistance. This algorithm was validated by clinical experts through a blind review of 200 anonymized medical charts from SNDS data. Prevalence and incidence were standardized on the European Standard Population (2013 edition). RESULTS: Prevalence and incidence of mCRPC were estimated as, respectively, 62 and 21 cases per 100 000 men in 2014. Less than one mCRPC case per 100 000 was observed in men aged 40-49. Maximum mCRPC incidence was in men aged 80-89 (175 per 100 000). The algorithm used for mCRPC identification had 97 % positive and 99 % negative predictive values. CONCLUSION: The good performances of the algorithm for mCRPC identification and the consistency of the generated results with the existing data highlight the robustness of these first estimates of mCRPC prevalence and incidence. Future updates will call for algorithm adjustment as practices evolve over time. These first real-life data will serve for future follow-up of the impact of changes in the management of prostate cancer.

Empirical assessment of case-based methods for identification of drugs associated with upper gastrointestinal bleeding in the French National Healthcare System database (SNDS).

PURPOSE: Upper gastrointestinal bleeding (UGIB) is a severe and frequent drug-related event. In order to enable efficient drug safety alert generation in the French National Healthcare System database (SNDS), we assessed and calibrated empirically case-based designs to identify drug associated with UGIB risk. METHODS: All cases of UGIB were extracted from SNDS (2009-2014) using two definitions. Positive and negative drug controls were used to compare 196 self-controlled case series (SCCS), case-control (CC) and case-population (CP) design variants. Each variant was evaluated in a 1/10th population sample using area under the receiver operating curve (AUC) and mean square error (MSE). Parameters that had major impacts on results were identified through logistic regression. Optimal designs were replicated in the unsampled population. RESULTS: Using a specific UGIB definition, AUCs ranged from 0.64 to 0.80, 0.44 to 0.61 and 0.50 to 0.67, for SCCS, CC and CP, respectively. MSE ranged from 0.07 to 0.39, 0.83 to 1.33 and 1.96 to 4.6, respectively. Univariate regressions showed that high AUCs were achieved with SCCS with multiple drug adjustment and a 30-day risk window starting at exposure. The top-performing SCCS variant in the unsampled population yielded an AUC = 0.84 and MSE = 0.14, with 10/36 negative controls presenting significant estimates. CONCLUSIONS: SCCS adjusting for multiple drugs and using a 30-day risk window has the potential to generate UGIB-related alerts in the SNDS and hypotheses on its potential population impact. Negative control implementation highlighted that low systematic error was generated but that protopathic bias and confounding by indication remained unaddressed issues.

Empirical assessment of case-based methods for drug safety alert identification in the French National Healthcare System database (SNDS): Methodology of the ALCAPONE project.

OBJECTIVES: To introduce the methodology of the ALCAPONE project. BACKGROUND: The French National Healthcare System Database (SNDS), covering 99% of the French population, provides a potentially valuable opportunity for drug safety alert generation. ALCAPONE aimed to assess empirically in the SNDS case-based designs for alert generation related to four health outcomes of interest. METHODS: ALCAPONE used a reference set adapted from observational medical outcomes partnership (OMOP) and Exploring and Understanding Adverse Drug Reactions (EU-ADR) project, with four outcomes-acute liver injury (ALI), myocardial infarction (MI), acute kidney injury (AKI), and upper gastrointestinal bleeding (UGIB)-and positive and negative drug controls. ALCAPONE consisted of four main phases: (1) data preparation to fit the OMOP Common Data Model and select the drug controls; (2) detection of the selected controls via three case-based designs: case-population, case-control, and self-controlled case series, including design variants (varying risk window, adjustment strategy, etc.); (3) comparison of design variant performance (area under the ROC curve, mean square error, etc.); and (4) selection of the optimal design variants and their calibration for each outcome. RESULTS: Over 2009-2014, 5225 cases of ALI, 354 109 MI, 12 633 AKI, and 156 057 UGIB were identified using specific definitions. The number of detectable drugs ranged from 61 for MI to 25 for ALI. Design variants generated more than 50 000 points estimates. Results by outcome will be published in forthcoming papers. CONCLUSIONS: ALCAPONE has shown the interest of the empirical assessment of pharmacoepidemiological approaches for drug safety alert generation and may encourage other researchers to do the same in other databases.