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Background There is little information on breast cancer screening (BCS) practices in women with multiple sclerosis (WwMS). Objective To assess and compare BCS rates in WwMS and in the general population and identify barriers and facilitators. Methods In a 2012–2020 cohort study, we identified 47,166 WwMS without a history of cancer and matched them (up to 1:4) to 184,124 controls from the French national medico‐administrative database. Mammography rates were compared according to age, city‐level socio‐economic status, period, and DMT use. We used logistic and negative binomial models to identify factors associated with BCS adherence in WwMS. We also carried out semistructured interviews with 20 WwMS and analyzed them using the empirically inductive method. Results Compared with controls, fewer WwMS underwent BCS at least once (69.9% vs. 76.7%, p < 0.001) and had a lower biennial mammography rate (0.55 vs. 0.63; p < 0.001). Rate differences increased with age. Once stratified on DMT, age‐standardized rates only differed in the non‐treated group (0.51 vs. 0.64; p < 0.001). Factors associated with lower mammography rates in WwMS were city‐level socio‐economic status (mostdeprived vs. least deprived; IRR 0.88 95% CI [0.86–0.91]), long MS duration (16–25 years: 0.91 [0.89–0.94]; ref: ≤ 5) and hospitalization (MS‐related: 0.85 [0.82–0.88]; non‐MS‐related: 0.92 [0.89–0.94]). However, DMT use was associated with higher mammography rates (high efficacy: 1.17 [1.14–1.21]; moderate efficacy: 1.18 [1.16–1.20]). Barriers were physical disability and feeling of excessive medicalization. Facilitators were disability‐accessible care and perception of BCS as a routine procedure. Conclusion BCS among WwMS is suboptimal, especially among those not treated by DMT, and needs to be improved.

The aim of this large retrospective cohort study was to use a quasi-exhaustive national medico-administrative database of deliveries in France to determine the risk of developing pancreatic cancer (PC) in women with a history of gestational diabetes mellitus (GDM). This nationwide population-based study included women aged 14–55 who gave birth between 1st January 2008 and 31 December 2009. The women were followed-up epidemiologically for eight years. Survival analyses using Cox regression models, adjusted for age, subsequent type 2 diabetes, and tobacco consumption, were performed on the time to occurrence of hospitalization for PC. The onset of GDM, tobacco consumption and subsequent type 2 diabetes were considered as time-dependent variables. Among 1,352,560 women included, 95,314 had a history of GDM (7.05%) and 126 women were hospitalized for PC (0.01%). Over the eight years of follow-up, GDM was significantly associated with a higher risk of hospitalization with PC in the first Cox regression model adjusted for age and subsequent type 2 diabetes (HR = 1.81 95% CI [1.06–3.10]). The second Cox regression model adjusted for the same covariates, plus tobacco consumption, showed that GDM was still significantly associated with a higher risk of hospitalization for PC with nearly the same estimated risk (HR = 1.77 95% CI [1.03–3.03]). Gestational diabetes was significantly associated with a greater risk of hospital admission for pancreatic cancer within eight years, regardless of subsequent type 2 diabetes.

Introduction Medico‐administrative databases are increasingly used to study the epidemiology of status epilepticus (SE), targeting hospitalizations with the SE G41 ICD‐10 code. However, the positive predictive value (PPV) of the G41 code, which measures the percentage of true cases among those identified by the code, is unknown. Methods We identified all hospitalizations with a primary or secondary diagnosis coded as G41 in five different hospitals. Medical reports for each hospitalization were reviewed to classify the stays as really related to SE or not, using two distinct approaches (sensitive and specific). The clinical characteristics of SE cases were also extracted. Results Among the 797 hospitalizations identified, the PPV ranged from 85.7% using the sensitive approach to 70.6% with the specific approach. Hospitalizations coded with G41 as the main diagnosis had the highest PPV, whereas codes G411 and G418 showed the lowest PPV. Of the 400 hospitalizations with a G410 (generalized convulsive SE) code, 72.7% were classified as generalized convulsive SE, while 76.5% of the 149 hospitalizations with a G412 (focal SE) code were classified as focal SE. Conclusion Our findings highlight that PPV varies by G41 subtype and diagnostic position. Studies requiring a higher PPV should exclude certain codes or hospitalizations with G41 code only as an associated diagnosis. Further studies are needed to estimate the sensitivity and specificity of G41 code. Sorbonne University Hospitals (5 hospitals, 1.1% of hospitalizations in France Extraction of all hospitalizations with a G41 discharge code (n = 797). Review of medical reports and labeling of hospitalizations using a sensitive and a specific approach. True positive (TP): hospitalization with a G41 code that corresponds to a hospitalization for Status Epilepticus. False positive (FP): hospitalization with a G41 code without Status Epilepticus Positive Predictive Value (PPV) : TP / (TP + FP). The Positive Predictive Value (PPV) of the G41 discharge code for Status Epilepticus ranges from 70.6% to 85.7%. The PPV is higher when the G41 code is the main diagnosis or when the patient is hospitalized in a neurology unit.

Background Antibiotic resistance is increasing among urinary pathogens, resulting in worse clinical and economic outcomes. We analysed factors associated with antibiotic-resistant bacteria (ARB) in patients hospitalized for urinary tract infection, using the comprehensive French national claims database. Methods Hospitalized urinary tract infections were identified from 2015 to 2017. Cases (due to ARB) were matched to controls (without ARB) according to year, age, sex, infection, and bacterium. Healthcare-associated (HCAI) and community-acquired (CAI) infections were analysed separately; logistic regressions were stratified by sex. Results From 9460 cases identified, 6468 CAIs and 2855 HCAIs were matched with controls. Over a 12-months window, the risk increased when exposure occurred within the last 3 months. The following risk factors were identified: antibiotic exposure, with an OR reaching 3.6 [2.8–4.5] for men with CAI, mostly associated with broad-spectrum antibiotics; surgical procedure on urinary tract (OR 2.0 [1.5–2.6] for women with HCAI and 1.3 [1.1–1.6] for men with CAI); stay in intensive care unit > 7 days (OR 1.7 [1.2–2.6] for men with HCAI). Studied co-morbidities had no impact on ARB. Conclusions This study points out the critical window of 3 months for antibiotic exposure, confirms the impact of broad-spectrum antibiotic consumption on ARB, and supports the importance of prevention during urological procedures, and long intensive care unit stays.

Background Chronic heart failure (CHF) is one of the most common causes of mortality in industrialized countries despite regular therapeutic advances. Numerous factors influence mortality in CHF patients, including nutritional status. It is known that malnutrition is a risk factor for mortality, whereas obesity may play a protective role, a phenomenon dubbed the “obesity paradox”. However, the effect of the obesity-malnutrition association on mortality has not been previously studied for CHF. Our aim was to study the effect of nutritional status on overall mortality in CHF patients. Methods This retrospective, multicenter study was based on a French nationwide database (PMSI). We included all CHF patients aged ≥18 years admitted to all public and private hospitals between 2012 and 2016 and performed a survival analysis over 1 to 4 years of follow-up. Results Malnutrition led to a significant decrease in life expectancy in CHF patients when compared with normal nutritional status (aHR=1.16 [1.14-1.18] at one year and aHR=1.04 [1.004-1.08] at four years), obese, and obese-malnutrition groups. In contrast, obesity led to a significant increase in life expectancy compared with normal nutritional status (aHR=0.75 [0.73-0.78] at one year and aHR=0.85 [0.81-0.90] at four years), malnutrition, and obese-malnutrition groups. The mortality rate was similar in patients presenting both malnutrition and obesity and patients with normal nutritional status. Conclusions Our results indicate that the protective effect on mortality observed in obese CHF patients seems to be linked to fat massincrease. Furthermore, malnourished obese and normal nutritional status patients had similar mortality rates. Further studies should be conducted to confirm our results and to explore the physiopathological mechanisms behind these effects.

Background In the French population-based colorectal cancer screening program (CRCSP), the fact that the medical-exclusion rate was estimated only after a collection of voluntary statements from subjects could compromise an exhaustive collection of potential cases of medical-exclusion. The health insurance medico-administrative database (SNDS) that contains medical and healthcare consumption information have to date never been used to refine the target population of the CRCSP. Objective To identify in the SNDS, from published and disparate algorithms, the computational definitions of morbid situations that could justify medical exclusion from the CRCSP. Methods The non-systematic review of the literature synthetised an exhaustive list of algorithms targeting in SNDS, the morbid situations (CCR, colorectal adenoma/polyp, chronic inflammatory bowel disease, familial adenomatous polyposis, or Lynch syndrome colonoscopy, coloscanner, polypectomy) which may justify temporary or permanent medical exclusion from the CRCSP campaigns. Secondly, the discovered codes of morbid situations were searched on statistical reports to estimate their frequencies of use in SNDS (in 2021), and their interest in the computational phenotypes’ algorithm. Results The analysis of the literature (28 articles/studies) highlights the existence of diagnostic or therapeutic codes that can define in the SNDS database, the morbid situations justifying medical exclusion from the CRCSP. Except for personal or family history of CRC classifiable in the Z85.0 or Z80.0 codes of the ICD-10, almost all the morbid situations have a requestable definition in the SNDS. The target favoured by the search algorithms was the ICD-10 code (i.e., C18-C20, K50, K51). The definition codes listed were frequently used in SNDS in 2021, except for a few codes (D12.6 + 6, M07.5). From this definition of morbid situations by the only codes of the ICD-10 or the procedure codes emerges a feasibility and a decision-making algorithm for the choice of the person to be excluded from CRCSP campaign, using the SNDS. Age is the first discriminating variable in this decision-making algorithm because the CRCSP targeted people aged 50 to 74 years old and a restriction on age was made in several included SNDS’s studies. The second discrimination based on diagnostic evidence derives its relevance from the quasi-systematic search for ICD-10 diagnostic codes in SNDS’s studies. Conclusion In addition to being widely used in the context of medico-economic and epidemiological studies, the SNDS currently contains almost all the data essential for estimating the rate of medical-exclusion during colorectal cancer screening campaigns. While initiating the answer to the question of the choice of the most appropriate algorithm in each context, this review of the literature also emphasizes the need for validation studies because the quality of the algorithms used conditions the quality of the studies carried out in the medico-administrative databases. Summary points What was already known on the topic: • In the French population-based colorectal cancer screening program, the medical exclusion rate was estimated only after a collection of voluntary statements from subjects and GPs, which compromises an exhaustive collection of potential cases of medical exclusion. • The French medico-administrative database contains medical, and healthcare information have to date never been used to refine the target population of the screening program. What this study added to our knowledge: • This review showed that there was no unique algorithm that can identify in the French database, all morbid situations that can justify medical exclusion from CRCSP campaigns. • The use of a single phenotype model and the lack of validation of research phenotypes of the chronic colorectal diseases in the French database. • The French medico-administrative database currently contains almost all the data essential for estimating the rate of medical exclusion during screening campaigns.

Background: Colorectal cancer (CRC) screening in average-risk populations requires filtering a target population based on medical information in population-based CRC screening programs (CRCSP). This study describes the level of consensus in medical exclusion practice and the role of the medico-administrative databases (MADB) in accurately targeting the eligible individuals for CRCSP screening campaigns. Design: The descriptive study combined a cross-sectional survey and a non-systematic literature review. Methods: A cross-sectional survey was conducted among CRCSPs worldwide. Information was collected on the use of MADB for identifying consensus-based exclusion criteria (applied by >50% of CRCSPs). When a MADB was used, the study assessed whether the definition (code lists, medical terminologies) of the exclusion criteria was available. These definitions were compared between programs to evaluate the degree of consensus. Results: In all, 20 out of the 31 CRCSPs (Australia, England, Manitoba, Ontario, Washington State, 26 European countries) participating in the survey implemented medical exclusions. Five consensus-based exclusion criteria were identified (personal history of CRC, inflammatory bowel disease, adenoma, recent colonoscopy, genetic risk). However, these criteria were not uniformly defined in MADBs (i.e., CRC phenotype includes ICD-10 codes C18–C21 in Catalonia, while the C21 code was excluded elsewhere). Furthermore, although the MADBs exist and contain relevant information, they remain inaccessible to screening management structures in some countries (e.g., in France). Conclusion: The number of consensus-based criteria was limited, and they were the least nuanced, likely because they are easier to collect using the current CRCSPs management resources. These consensual criteria can be queried in most MADBs. However, the use of MADBs was not standardized across programs for various reasons (absence of a database, unavailability of information in the database when it exists, inaccessibility of the database when it exists), limiting comparability between them. Standardizing the five consensus criteria across all programs would only be effective if the disparity caused by systemic failures in the organization of each program was controlled.

Background The use of national medico-administrative databases for epidemiological studies has increased in the last decades. In France, the Healthcare Expenditures and Conditions Mapping (HECM) algorithm has been developed to analyse and monitor the morbidity and economic burden of 58 diseases. We aimed to assess the performance of the HECM in identifying different conditions in patients with end-stage kidney disease (ESKD) using data from the REIN registry (the French National Registry for patients with ESKD). Methods We included all patients over 18 years of age who started renal replacement therapy in France in 2018. Five conditions with a similar definition in both databases were included (ESKD, diabetes, human immunodeficiency virus [HIV], coronary insufficiency, and cancer). The performance of each SNDS algorithm was assessed using sensitivity, specificity, positive predictive values (PPVs), negative predictive values (NPVs), and Cohen’s kappa coefficient. Results In total 5,971 patients were included. Among them, 81% were identified as having ESKD in both databases. Diabetes was the condition with the best performance, with a sensitivity, specificity, PPV, NPV, and Kappa coefficient all over 80%. Cancer had the lowest level of agreement with a Kappa coefficient of 51% and a high specificity and high NPV (94% and 95%). The conditions for which the definition in the HECM included disease-specific medications performed better in our study. Conclusion The HECM showed good to very good concordance with the REIN database information overall, with the exception of cancer. Further validation of the HECM tool in other populations should be performed.

Background Considering the growing body of evidence suggesting a potential implication of herpesviruses in the development of dementia, several authors have questioned a protective effect of antiherpetic drugs (AHDs) which may represent a new means of prevention, well tolerated and easily accessible. Subsequently, several epidemiological studies have shown a reduction in the risk of dementia in subjects treated with AHDs, but the biological plausibility of this association and the impact of potential methodological biases need to be discussed in more depth. Methods Using a French medico-administrative database, we assessed the association between the intake of systemic AHDs and the incidence of (i) dementia, (ii) Alzheimer’s disease (AD), and (iii) vascular dementia in 68,291 subjects over 65 who were followed between 2009 and 2017. Regarding potential methodological biases, Cox models were adjusted for numerous potential confounding factors (including proxies of sociodemographic status, comorbidities, and use of healthcare) and sensitivity analyses were performed in an attempt to limit the risk of indication and reverse causality biases. Results 9.7% of subjects ( n =6642) had at least one intake of systemic AHD, and 8883 incident cases of dementia were identified. Intake of at least one systemic AHD during follow-up was significantly associated with a decreased risk of AD (aHR 0.85 95% confidence interval [0.75–0.96], p =0.009) and, to a lesser extent with respect to p values, to both dementia from any cause and vascular dementia. The association with AD remained significant in sensitivity analyses. The number of subjects with a regular intake was low and prevented us from studying its association with dementia. Conclusions Taking at least one systemic AHD during follow-up was significantly associated with a 15% reduced risk of developing AD, even after taking into account several potential methodological biases. Nevertheless, the low frequency of subjects with a regular intake questions the biological plausibility of this association and highlights the limits of epidemiological data to evaluate a potential protective effect of a regular treatment by systemic AHDs on the incidence of dementia

Context Real-life data consist of exhaustive data which are not subject to selection bias. These data enable to study drug-safety profiles but are underused because of their temporality, necessitating complex models (i.e., safety depends on the dose, timing, and duration of treatment). We aimed to create a data-driven pipeline strategy that manages the complex temporality of real-life data to highlight the safety profile of a given drug. Methods We proposed to apply the weighted cumulative exposure (WCE) statistical model to all health events occurring after a drug introduction (in this paper HCQ) and performed bootstrap to select relevant diagnoses, drugs and interventions which could reflect an adverse drug reactions (ADRs). We applied this data-driven pipeline on a French national medico-administrative database to extract the safety profile of hydroxychloroquine (HCQ) from a cohort of 2,010 patients. Results The proposed method selected eight drugs (metopimazine, anethole trithione, tropicamide, alendronic acid & colecalciferol, hydrocortisone, chlormadinone, valsartan and tixocortol), twelve procedures (six ophthalmic procedures, two dental procedures, two skin lesions procedures and osteodensitometry procedure) and two medical diagnoses (systemic lupus erythematous, unspecified and discoid lupus erythematous) to be significantly associated with HCQ exposure. Conclusion We provide a method extracting the broad spectrum of diagnoses, drugs and interventions associated to any given drug, potentially highlighting ADRs. Applied to hydroxychloroquine, this method extracted among others already known ADRs. Highlights • The challenge of drug-safety signal detection methods is to handle four types of difficulties: ○ The data source, the study of long-term adverse drug reactions or effects not suspected by healthcare professionals, requires the use of a real-life data source. ○ The consideration of a broad spectrum of potential adverse drug reactions (ADRs), and not only candidate ADRs. ○ The temporal impact (meaning that safety depends on the dose, date and duration of treatment). ○ The difference between true ADRs and disease natural course. • We aimed to create a data-driven pipeline strategy, without any assumption of any ADRs, which take into account the complex temporality of real-life data to provide the safety profile of a given drug. • Our pipeline used three sources of real-life data to establish a safety profile of a given drug: drug prescriptions, procedures and medical diagnoses. • We successfully applied our data-driven pipeline strategy to hydroxychloroquine (HCQ). Our pipeline enabled us to find diagnoses, drugs and interventions related to HCQ and which could reflect an ADR due to HCQ or the disease itself. • This data-driven pipeline strategy may be of interest to other experts involved in the pharmacovigilance discipline.