Use of multiple sclerosis disease-modifying therapies during pregnancy in France: Nationwide study between 2010 and 2021.

BACKGROUND: Multiple sclerosis (MS) frequently affects women of childbearing age and pregnant women. OBJECTIVE: To assess the use of MS disease-modifying therapies (DMTs) during pregnancy in France over the last decade, marked by an increasing DMTs availability. METHODS: All pregnancies ended from April 2010 to December 2021 in women with MS were identified based on the nationwide Mother-Child Register EPI-MERES, built from the French National Health Data System (Système National des Données de Santé (SNDS)). RESULTS: Of a total of 20,567 pregnancies in women with MS, 7587 were exposed to DMT. The number of DMT-exposed pregnancies markedly increased from 1079 in 2010-2012 to 2413 in 2019-2021 (+124%), especially those exposed to glatiramer acetate, natalizumab, dimethyl fumarate, and anti-CD20. Among pregnancies of women on DMT 6 months before pregnancy, 78.0% underwent DMT discontinuation and 7.6% switched DMT, generally before (33.0% and 77.0%, respectively) or during the first trimester of pregnancy (58.3% and 17.8%, respectively). DMT discontinuation decreased from 84.0% in 2010-2012 to 72.4% in 2019-2021 and was less frequent among women aged ⩾35 years and those socioeconomically disadvantaged. CONCLUSION: Despite MS therapeutic management adaptations to pregnancy, exposure during pregnancy to treatments whose safety profile has not yet been clearly established has increased sharply over the last decade.

Trends in anti-infective use during pregnancy in France between 2010 and 2019: a nationwide population-based study.

AIMS: To describe the trends in anti-infective use during pregnancy between 2010 and 2019 and determine whether they were prescribed according to drug foetal safety international classification systems. METHODS: We conducted a population-based, nationwide study using the French national health data system including all pregnancies ended between 2010 and 2019. Anti-infective agents were considered according to their pharmacological group and potential harmful risk using the Australian and Swedish classification systems. Prevalence rate was estimated annually and by trimester. Average annual percent change (AAPC) and 95% confidence intervals (CIs) were calculated using Joinpoint regression. RESULTS: Among 7 571 035 pregnancies, 3 027 031 (40.0%) received ≥1 antibacterial. This proportion decreased significantly from 41.5% in 2010 to 36.1% in 2019 (AAPC = -1.7%, [95%CI, -2.5 to -1.0%]). Conversely, use of antiviral agents increased during the 10-year study period for anti-herpes simplex virus agents (AAPC = 4.4%, [3.7-5.2%]), influenza agents (AAPC = 25.4%, [6.2-48.1%]) and for HIV-antiretroviral agents (AAPC = 1.3%, [0.6-2.0%]). Use of influenza vaccine increased from 0.2% in 2010 to 4.2% in 2019 (AAPC = 49.7%, [39.3-60.9%]). Among all pregnancies, 0.9% had been exposed to a potentially harmful anti-infective agent increasing from 0.7% in 2010 to 1.2% in 2019 (AAPC = 6.4%, [4.4-8.5%]). CONCLUSION: Based on >7 million pregnancies identified from French nationwide data, this study showed that antibacterials are frequently prescribed during pregnancy although their use has decreased over the past 10 years. Our results suggest that anti-infective agents are generally prescribed in accordance with recommendations, although with a potential for improvement in influenza vaccination.

Epidemiology of granulomatosis with polyangiitis and microscopic polyangiitis in adults in France.

BACKGROUND: Granulomatosis with polyangiitis (GPA) and microscopic polyangiitis (MPA) are rare systemic necrotizing vasculitis. The national incidence and prevalence of GPA/MPA and patient mortality remain unknown in France. A real-life study using retrospective data from the French National Health Data System was set up to describe the epidemiology and demographic characteristics of hospitalized GPA and MPA patients, overall and by disease. METHODS: All adult patients (≥18 years of age) hospitalized for GPA (ICD-10 M31.3) or MPA (ICD-10 M31.7) between 01 and 01-2010 and 31-12-2017 and affiliated to the General health insurance Scheme (covering 76% of the French population) were included in this national retrospective observational study. Descriptive analyses, univariate and multivariable logistic models, Kaplan-Meier survival analysis, and Cox models were performed. RESULTS: The study involved 4445 prevalent GPA patients (including 1578 incident patients) and 1833 prevalent MPA patients (878 incident patients). Distinction between GPA and MPA diagnosis could not be made for 303 patients (149 incident patients). In people aged over 20 years, the age-standardized incidence rates of GPA and MPA were 0.5 and 0.3/100,000 person-years, respectively and the age-standardized prevalence rates were 10 and 4/100,000 person-years, respectively. The standardized mortality ratios in GPA and MPA patients aged over 20 years were 2.0 and 2.7, respectively, and remained constant. Renal failure, pulmonary and urinary tract infections, as well as coronary disease were more frequent among MPA than GPA patients. One-year survival rates among GPA and MPA patients were 96% (95%CI 94%-97%) and 94% (92%-95%), respectively. Five-year survival rates among GPA and MPA patients were 81% (95% CI 79%-83%) and 72% (68%-75%), respectively. After adjusting for comorbidities, the risk of death was still higher in MPA (hazard ratio 1.26 [95%CI 1.06-1.50]) than in GPA patients. CONCLUSIONS: Despite advances in the therapeutic management of patients, mortality rates are still high and stable over time, highlighting the need for improved management.

Risk of major adverse cardiovascular events in patients initiating biologics/apremilast for psoriatic arthritis: a nationwide cohort study.

OBJECTIVE: Several biological DMARDs (bDMARDs) have demonstrated anti-inflammatory effects in PsA. However, their comparative cardiovascular safety profiles remain unknown. We evaluated the risk of major adverse cardiovascular events (MACEs) in PsA patients on therapy with different classes of bDMARDs and apremilast. METHODS: This nationwide cohort study involved the administrative healthcare database of the French health insurance scheme linked to the hospital discharge database. All adults with PsA who were new users of bDMARDs/apremilast (neither in the year before the index date) during 2015-19 were included. Patients with previous cardiovascular diseases were excluded. End of follow-up was 31 December 2019. The primary endpoint was an occurrence of MACEs in a time-to-event analysis with propensity score-weighted Cox and Fine-Gray models. RESULTS: Between 2015 and 2019, we included 9510 bDMARD new users [mean age 48.5 (s.d. 12.7) years; 42% men], including 7289 starting a TNF inhibitor, 1058 an IL-12/23 inhibitor and 1163 an IL-17 inhibitor, with 1885 apremilast new users [mean age 54.0 (s.d. 12.5) years; 44% men]. MACEs occurred in 51 (0.4%) patients. After propensity score weighting, the risk of MACEs was significantly greater with IL-12/23 (weighted hazard ratio 2.0, 95% CI 1.3, 3.0) and IL-17 (weighted hazard ratio 1.9, 95% CI 1.2, 3.0) inhibitors than TNF inhibitors, with no significant increased risk with apremilast (weighted hazard ratio 1.3, 95% CI 0.8, 2.2). Similar results were observed with the Fine-Gray competing risks survival model. CONCLUSION: Analysis of a large database revealed a small overall number of MACEs, and the risk of MACEs was greater for PsA new users of IL-12/23 and IL-17 vs TNF inhibitors.

Identifying Protective Drugs for Parkinson's Disease in Health-Care Databases Using Machine Learning.

BACKGROUND: Available treatments for Parkinson's disease (PD) are only partially or transiently effective. Identifying existing molecules that may present a therapeutic or preventive benefit for PD (drug repositioning) is thus of utmost interest. OBJECTIVE: We aimed at detecting potentially protective associations between marketed drugs and PD through a large-scale automated screening strategy. METHODS: We implemented a machine learning (ML) algorithm combining subsampling and lasso logistic regression in a case-control study nested in the French national health data system. Our study population comprised 40,760 incident PD patients identified by a validated algorithm during 2016 to 2018 and 176,395 controls of similar age, sex, and region of residence, all followed since 2006. Drug exposure was defined at the chemical subgroup level, then at the substance level of the Anatomical Therapeutic Chemical (ATC) classification considering the frequency of prescriptions over a 2-year period starting 10 years before the index date to limit reverse causation bias. Sensitivity analyses were conducted using a more specific definition of PD status. RESULTS: Six drug subgroups were detected by our algorithm among the 374 screened. Sulfonamide diuretics (ATC-C03CA), in particular furosemide (C03CA01), showed the most robust signal. Other signals included adrenergics in combination with anticholinergics (R03AL) and insulins and analogues (A10AD). CONCLUSIONS: We identified several signals that deserve to be confirmed in large studies with appropriate consideration of the potential for reverse causation. Our results illustrate the value of ML-based signal detection algorithms for identifying drugs inversely associated with PD risk in health-care databases. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Effects of social deprivation and healthcare access on major amputation following a diabetic foot ulcer in a French administrative area: Analysis using the French claim data.

AIM: The link between social deprivation and the development of diabetic foot ulcer (DFU) is still widely debated. The study objective was to evaluate the relationship between lower limb amputation, social deprivation level, and inequalities in access to care service among people with DFU. This regional pilot study was conducted at the living area level and based on the French National Health Data System (SNDS). METHODS: We conducted a retrospective cohort study using hospital and primary care claim data in the Languedoc-Roussillon region. DFUs were determined using an original algorithm of care consumption or hospital diagnosis. The primary end point was amputation at 1 year. Secondary end points were mortality at 1 year and impact of potential access to care on amputation. RESULTS: We included 15,507 people from 2015 to 2017. Amputation and mortality rates were 17.5 and 117 per 1000 person-years. The least precarious living areas showed better prognoses (relative risk = 0.46; 95% CI 0.27-0.66). Territorial accessibility to a private-practice nurse, unlike physician accessibility, was associated with better results on major outcomes (p = 0.004). CONCLUSION: This is the first study using SNDS to study the care pathway of DFU management within and outside the hospital. High social deprivation in a living areas seems to be associated with more major amputations after a DFU.

Epidemiologic study of patients with psoriatic arthritis in a real-world analysis: a cohort study of the French health insurance database.

OBJECTIVE: PsA is a chronic inflammatory arthritis with heterogeneous disease manifestations. Data on the prevalence of PsA in adults differ widely depending on the study and the country. This study aimed to estimate the prevalence and incidence of PsA in France, characterize comorbidities associated to PsA and identify prescribed treatments. METHODS: This nationwide cohort study involved the administrative healthcare database (Système National des Données de Santé) of the French health insurance scheme linked to the national hospital discharge database. All adults with PsA registered in the database and identified with a specific International Classification of Diseases, 10th revision code (M07) were included between 1 January 2015 and 31 December 2018. RESULTS: A total of 63 598 patients were identified as having PsA [55.9 years (s.d. 14.4), 45.6% males]. The prevalence of PsA was estimated at 0.1% and the incidence at 8.4 per 100 000 person-years in the general population. The most common comorbidities were hypertension, diabetes, chronic obstructive pulmonary disease and dyslipidaemia. The prevalence of treatment with conventional synthetic DMARDs (csDMARDs), biological or biosimilar DMARDs (b/bsDMARDs) and apremilast for PsA was 25.9% (16 453), 30.4% (19 325) and 3.5% (2231), respectively. Overall, 8966 (14.1%) patients were new users of csDMARDs, 8311 (13.1%) were new users of b/bsDMARDs and 1529 (7.4%) were new users of apremilast. The most common first-line csDMARD was methotrexate (70.9%) and the most frequent first-line b/bsDMARD was adalimumab (30.8%). CONCLUSION: Our results lead to a better understanding of PsA. Results were similar to those from other published studies using other data sources, which highlights the reliability of insurance databases for studies.

Value of a national administrative database to guide public decisions: From the système national d'information interrégimes de l'Assurance Maladie (SNIIRAM) to the système national des données de santé (SNDS) in France.

In 1999, French legislators asked health insurance funds to develop a système national d'information interrégimes de l'Assurance Maladie (SNIIRAM) [national health insurance information system] in order to more precisely determine and evaluate health care utilization and health care expenditure of beneficiaries. These data, based on almost 66 million inhabitants in 2015, have already been the subject of numerous international publications on various topics: prevalence and incidence of diseases, patient care pathways, health status and health care utilization of specific populations, real-life use of drugs, assessment of adverse effects of drugs or other health care procedures, monitoring of national health insurance expenditure, etc. SNIIRAM comprises individual information on the sociodemographic and medical characteristics of beneficiaries and all hospital care and office medicine reimbursements, coded according to various systems. Access to data is controlled by permissions dependent on the type of data requested or used, their temporality and the researcher's status. In general, data can be analyzed by accredited agencies over a period covering the last three years plus the current year, and specific requests can be submitted to extract data over longer periods. A 1/97th random sample of SNIIRAM, the échantillon généraliste des bénéficiaires (EGB), representative of the national population of health insurance beneficiaries, was composed in 2005 to allow 20-year follow-up with facilitated access for medical research. The EGB is an open cohort, which includes new beneficiaries and newborn infants. SNIIRAM has continued to grow and extend to become, in 2016, the cornerstone of the future système national des données de santé (SNDS) [national health data system], which will gradually integrate new information (causes of death, social and medical data and complementary health insurance). In parallel, the modalities of data access and protection systems have also evolved. This article describes the SNIIRAM data warehouse and its transformation into SNDS, the data collected, the tools developed in order to facilitate data analysis, the limitations encountered, and changing access permissions.

18F-FDG PET can effectively rule out conversion to dementia and the presence of CSF biomarker of neurodegeneration: a real-world data analysis.

BACKGROUND: Precisely defining the delay in onset of dementia is a particular challenge for early diagnosis. Brain [18F] fluoro-2-deoxy-2-D-glucose (18F-FDG) Positron Emission Tomography (PET) is a particularly interesting tool for the early diagnosis of neurodegenerative diseases, through the measurement of the cerebral glucose metabolic rate. There is currently a lack of longitudinal studies under real-life conditions, with sufficient patients, to accurately evaluate the predictive values of brain 18F-FDG PET scans. Here, we aimed to estimate the value of brain 18F-FDG PET for predicting the risk of dementia conversion and the risk of occurrence of a neurodegenerative pathology. METHODS: Longitudinal data for a cohort of patients with no diagnosis of dementia at the time of recruitment referred by a tertiary memory clinic for brain 18F-FDG PET were matched with (Prince M, Wimo A, Guerchet Maëlenn, Ali G-C, Wu Y-T et al. World Alzheimer Report 2015. The Global Impact of Dementia: An analysis of prevalence, incidence, cost and trends. [Research Report] Alzheimer's Disease International. 2015. 2015.) data from the French National Health Data System (NHDS), (Jack CR, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimers Dement. 2018;14(4):535-62.) data from the National Alzheimer Bank (NAB), and (Davis M, O`Connell T, Johnson S, Cline S, Merikle E, Martenyi F, et al. Estimating Alzheimer's Disease Progression Rates from Normal Cognition Through Mild Cognitive Impairment and Stages of Dementia. CAR. 2018;15(8):777-88.) lumbar puncture (LP) biomarker data. The criteria for dementia conversion were the designation, within the three years after the brain 18F-FDG PET scan, of a long-term condition for dementia in the NHDS and a dementia stage of cognitive impairment in the NAB. The criterion for the identification of a neurodegenerative disease in the medical records was the determination of LP biomarker levels. RESULTS: Among the 403 patients (69.9 ± 11.4 years old, 177 women) from the initial cohort with data matched with the NHDS data, 137 were matched with the NAB data, and 61 were matched with LP biomarker data. Within three years of the scan, a 18F-FDG PET had negative predictive values of 85% for dementia conversion (according to the NHDS and NAB datasets) and 95% for the presence of LP neurodegeneration biomarkers. CONCLUSION: A normal brain 18F-FDG PET scan can help rule out the risk of dementia conversion and the presence of cerebrospinal fluid (CSF) biomarker of neurodegeneration early with high certainty, allowing modifications to patient management regimens in the short term. TRIAL REGISTRATION: Clinical Trials database (NCT04804722). March 18, 2021. Retrospectively registered.

Maternal, prenatal and postnatal risk factors for early child physical abuse: a French nationwide cohort study.

Background: Identifying risk factors for early child physical abuse (CPA) is crucial for understanding its mechanisms and defining effective preventive interventions. We aimed to identify maternal, prenatal and postnatal factors associated with early CPA. Methods: This cohort study was based on comprehensive data from the Mother-Child EPI-MERES nationwide register and included all infants born alive in France between 2010 and 2019. Factors associated with early CPA (before age 1) were identified with a multilevel Cox regression model with random intercepts at the regional level. Findings: Among the 6,897,384 included infants, 2994 (40/100,000) had a diagnosis of early CPA, at a median age of 4 months. Independent factors most strongly associated with early CPA were maternal low financial resources (adjusted hazard ratio [aHR] 1.91; 95% confidence interval [95% CI] 1.67-2.18), maternal age <20 years versus 35-40 years (aHR 7.06; 95% CI 6.00-8.31), maternal alcohol use disorder (aHR 1.85; 95% CI 1.48-2.31), opioid use disorder (aHR 1.90; 95% CI 1.41-2.56), intimate partner violence (aHR 3.33; 95% CI 2.76-4.01), diagnosis of a chronic mental disorder (aHR 1.50; 95% CI 1.14-1.97) or somatic disorder (aHR 1.55; 95% CI 1.32-1.83), hospitalisation for a mental disorder (aHR 1.88; 95% CI 1.49-2.36), very preterm birth (aHR 2.15; 95% CI 1.68-2.75), and diagnosis of a chronic severe neurocognitive disorder in the infant (aHR 14.37; 95% CI 11.85-17.44). Interpretation: Independent risk factors of early CPA identified at the national level in France may help in understanding CPA mechanisms and developing effective prevention programs including risk-stratification tools to optimise the allocation of parenting interventions to parents who could most benefit from them. Funding: Ile-de-France regional council, L'Oréal-UNESCO For Women In Science France Young Talent Award, French National Observatory for Child Protection [ONPE], French Association of Ambulatory Paediatrics [AFPA], HUGO university hospitals network, Mustela Foundation and Sauver la Vie prizes.

Performing pharmacoepidemiological studies using the French health insurance data warehouse (SNDS): How to translate guidelines into practice.

The French health insurance data warehouse named SNDS is one of the largest medico-administrative in the world allowing for powerful pharmacoepidemiological studies, based on real-life data collected prospectively. In addition to the absolute necessity of a strong pharmacological rationale, recommendations have been thought to improve the quality of pharmacoepidemiological studies. These guidelines emphasize the importance of an accurate definition of the study population, outcome and exposure, especially for studies performed on medico-administrative databases. Compliance with certain guidelines, particularly those concerning the identification of a specific population or an outcome and the definition of risk periods or exposure periods, may be difficult when performing studies on the SNDS because of its structure and the nature of the data recorded. The objective of this article is to provide advice for the conduct of pharmacoepidemiological studies according to the recommendations when using the SNDS, given its specificities. The performing of reliable studies from this rich but complex data warehouse requires the expertise of researchers with deep knowledge both in the SNDS and in pharmacological reasoning.

Global healthcare pathway of people living with diabetes prior to wounding is associated with a decreased risk of amputation.

AIMS: Diabetic foot ulcer (DFU) has a poor prognosis and high amputation rate. We previously used the French National Health Data System (Système National des Données de Santé: SNDS) to analyze the impact of deprivation and healthcare access on DFU prognosis. The purpose of this ancillary study was to explore the relationship between the global care pathway (care consumption) the year before and after DFU and the risk of amputation. METHODS: We conducted a study based on a cohort from the SNDS. The data came from a region of France and subjects living with a complication of DFU. We looked at care consumption one year before and one year after wound onset. Risk of amputation was calculated one year after DFU onset. RESULTS: Data were extracted for 6,642 patients. Subjects with DFU had a better prognosis regarding amputation risk when they are taking cardiovascular, antibiotic, neurological, drugs. A consultation with an ophthalmologist was also linked to a better prognosis: HR = 0.71 IC95 (0.499-0.995) (p = 0.04). CONCLUSION: People with the best diabetes follow-up, even with several comorbidities, appear to have a better prognosis for their DFU. This highlights the importance of global healthcare and the care pathway in this chronic disease.

Prevalence, mortality, and treatment of patients with rheumatoid arthritis: A cohort study of the French National Health Data System, 2010-2019.

OBJECTIVES: Rheumatoid arthritis (RA) is a chronic inflammatory disease mostly affecting the joints. Data on the prevalence of RA differ widely, depending on the study and country. Our objectives were to estimate the prevalence of RA in France and the mortality rate, characterise the causes of death, and identify prescribed treatments. METHODS: This nationwide cohort study was based on data of the French National Health Data System (SNDS) which covers 99% of the French population. All patients identified with RA based on specific ICD-10 codes (M05 and M06, except M06.1) between 2010 and 2019 were included. RESULTS: We identified 385,919 RA cases between 2010 and 2019, 318,243 of which were followed in 2019 (65.8±16.8 years, 72% women). The overall crude prevalence rate in 2019 was 0.47%: 0.66% for women and 0.28% for men. The crude annual mortality rate was 3.1%. The overall standardised mortality ratio (SMR) of RA patients relative to the French general population decreased over time, reaching 1.21 in 2019. Cause-specific mortality was increased in RA patients for cardiovascular (SMR 1.40, 95% confidence interval 1.36-1.43), respiratory system (1.80, 1.73-1.87), digestive system (1.73, 1.59-1.88), and urogenital system (1.73, 1.59-1.88) diseases and infections (1.91, 1.76-2.06). We found no excess mortality due to tumours. The prevalence of treatment with conventional synthetic and biological/targeted synthetic disease-modifying antirheumatic drugs for RA in 2019 was 41.9% (n=133,477) and 18.7% (n=59,409), respectively. CONCLUSION: Our results may provide a better understanding of RA and its care in France.

Contribution of real-life studies in France during the COVID-19 pandemic and for the national pharmaco-epidemiological surveillance of COVID-19 vaccines.

During the COVID-19 pandemic, EPI-PHARE, a scientific group in pharmaco-epidemiology created by the French National Agency for the Safety of Medicines and Health Products (ANSM) and the French National Health Insurance (Cnam), has reoriented its work program to enlighten health authorities in this health crisis. By exploiting massive and complex data of the French Health Data System (SNDS) from the beginning of the first lockdown in France in March 2020, we were able to publish numerous results on the use, benefits and risks of medicines, on the risk factors of COVID-19 before and after vaccination, and on the benefits and risks of COVID-19 vaccines. Our results were widely taken into account by the French health authorities and allowed them to take informed decision in this pandemic situation in order to ensure the health of the population.

[Performing pharmacoepidemiological studies using the French health insurance data warehouse (SNDS): How to translate guidelines into practice]. / Réalisation d'études pharmacoépidémiologiques à partir du système national des données de santé (SNDS) : application des recommandations dans la pratique.

The French health insurance data warehouse named SNDS is one of the largest medico-administrative in the world allowing for powerful pharmacoepidemiological studies, based on real-life data collected prospectively. In addition to the absolute necessity of a strong pharmacological rationale, recommendations have been thought to improve the quality of pharmacoepidemiological studies. These guidelines emphasize the importance of an accurate definition of the study population, outcome and exposure, especially for studies performed on medico-administrative databases. Compliance with certain guidelines, particularly those concerning the identification of a specific population or an outcome and the definition of risk periods or exposure periods, may be difficult when performing studies on the SNDS because of its structure and the nature of the data recorded. The objective of this article is to provide advice for the conduct of pharmacoepidemiological studies according to the recommendationswhen using the SNDS, given its specificities. The performing of reliable studies from this rich but complex data warehouse requires the expertise of researchers with deep knowledge both in the SNDS and in pharmacological reasoning.

Opportunities and Obstacles to the Development of Health Data Warehouses in Hospitals in France: The Recent Experience of Comprehensive Cancer Centers.

Big Data and Artificial Intelligence can profoundly transform medical practices, particularly in oncology. Comprehensive Cancer Centers have a major role to play in this revolution. With the purpose of advancing our knowledge and accelerating cancer research, it is urgent to make this pool of data usable through the development of robust and effective data warehouses. Through the recent experience of Comprehensive Cancer Centers in France, this article shows that, while the use of hospital data warehouses can be a source of progress by taking into account multisource, multidomain and multiscale data for the benefit of knowledge and patients, it nevertheless raises technical, organizational and legal issues that still need to be addressed. The objectives of this article are threefold: 1. to provide insight on public health stakes of development in Comprehensive Cancer Centers to manage cancer patients comprehensively; 2. to set out a challenge of structuring the data from within them; 3. to outline the legal issues of implementation to carry out real-world evidence studies. To meet objective 1, this article firstly proposed a discussion on the relevance of an integrated approach to manage cancer and the formidable tool that data warehouses represent to achieve this. To address objective 2, we carried out a literature review to screen the articles published in PubMed and Google Scholar through the end of 2022 on the use of data warehouses in French Comprehensive Cancer Centers. Seven publications dealing specifically with the issue of data structuring were selected. To achieve objective 3, we presented and commented on the main aspects of French and European legislation and regulations in the field of health data, hospital data warehouses and real-world evidence.

The French Early Breast Cancer Cohort (FRESH): A Resource for Breast Cancer Research and Evaluations of Oncology Practices Based on the French National Healthcare System Database (SNDS).

BACKGROUND: Breast cancer (BC) is the most frequent cancer and the leading cause of cancer-related death in women. The French National Cancer Institute has created a national cancer cohort to promote cancer research and improve our understanding of cancer using the National Health Data System (SNDS) and amalgamating all cancer sites. So far, no detailed separate data are available for early BC. OBJECTIVES: To describe the creation of the French Early Breast Cancer Cohort (FRESH). METHODS: All French women aged 18 years or over, with early-stage BC newly diagnosed between 1 January 2011 and 31 December 2017, treated by surgery, and registered in the general health insurance coverage plan were included in the cohort. Patients with suspected locoregional or distant metastases at diagnosis were excluded. BC treatments (surgery, chemotherapy, targeted therapy, radiotherapy, and endocrine therapy), and diagnostic procedures (biopsy, cytology, and imaging) were extracted from hospital discharge reports, outpatient care notes, or pharmacy drug delivery data. The BC subtype was inferred from the treatments received. RESULTS: We included 235,368 patients with early BC in the cohort (median age: 60 years). The BC subtype distribution was as follows: luminal (80.2%), triple-negative (TNBC, 9.5%); HER2+ (10.3%), or unidentifiable (n = 44,388, 18.9% of the cohort). Most patients underwent radiotherapy (n = 200,685, 85.3%) and endocrine therapy (n = 165,655, 70.4%), and 38.3% (n = 90,252) received chemotherapy. Treatments and care pathways are described. CONCLUSIONS: The FRESH Cohort is an unprecedented population-based resource facilitating future large-scale real-life studies aiming to improve care pathways and quality of care for BC patients.

Is the type 2 diabetes epidemic plateauing in France? A nationwide population-based study.

AIM: Nationwide data on the evolution of diabetes incidence and prevalence are scarce in France. For this reason, our objectives were to determine type 2 diabetes prevalence and incidence rates between 2010 and 2017, stratified by gender, age and region, and to assess annual time trends over the study period in adults aged≥45 years. METHODS: Diabetes cases in the National Health Data System (SNDS), which covers the entire French population (66 million people), were identified through a validated algorithm. Gender- and age-specific prevalence and incidence rates were estimated. Negative binomial models, adjusted for gender, age and region, were used to assess annual time trends for prevalence and incidence throughout the study period. RESULTS: During 2017, 3,144,225 diabetes cases aged≥45 years were identified. Over the study period, prevalence increased slightly (men from 11.5% to 12.1%, women from 7.9% to 8.4%) whereas incidence decreased (men from 11 to 9.7, women from 7.2 to 6.2 per 1000 person-years). In only four groups did prevalence rates decrease: men aged 45-65 years; women aged 45-60 years; women in Reunion; and women in Martinique. An increasing annual time trend was observed for prevalence (men: +0.9% [95% CI: +0.7%, +1%]; women: +0.4% [95% CI: +0.2%, +0.6%]) with a decreasing annual time trend for incidence in both genders (men: -2.6% [95% CI: -3.1%, -2.0%]; women: -3.9% [95% CI: -4.5%, -3.4%]). CONCLUSION: Further efforts towards diabetes prevention are required to ensure that incidence rates in France continue to diminish, as the disorder continues to represent an important public-health burden.