Consistency between the National Patient Register and the Swedish Cancer Register.

PURPOSE: The Swedish National Patient Register (NPR) is widely used as a data source in epidemiological studies, but the consistency of all cancer diagnoses compared to the Swedish Cancer Register (SCR) remains unclear. Using NPR supplementary for detecting safety signals is beneficial due to shorter data extraction delays compared to using SCR alone. This study aims to evaluate the consistency of NPR for cancer diagnoses compared to SCR and its potential use in pharmacoepidemiology. METHODS: Patients with a cancer diagnosis recorded in SCR during 2018-2020 were included. To measure the consistency of NPR diagnoses with SCR as the gold standard, positive predictive value (PPV), and sensitivity were calculated. As an empirical example showing differences in identification of cancer diagnoses in NPR and SCR, two nested case-control studies for the association between antidiabetic medications and pancreatic cancer were repeated using the two registers. Conditional logistic regression was performed and the 95% confidence intervals (CIs) for the odds ratios (ORs) were checked for overlaps. RESULTS: For breast, male genital organs, and oral cancers consistency was high (PPV: 87.5%-97.4%, sensitivity: 82.2%-91.0%), while for female genital organs, thyroid, and ill-defined, secondary, and unspecified sites cancers it was low (PPV: 8.8%-90.0%, sensitivity: 19.9%-32.3%). All the CIs for the ORs from the nested case-control studies overlapped when pancreatic cancer was identified in NPR or SCR. CONCLUSION: Consistency of cancer diagnoses in NPR when compared to SCR depends on cancer type with higher consistency for some cancers and lower for others. Differences in diagnostic processes for different cancer types and coding of cancer in the two registers may explain part of the inconsistent results.

Antibiotic use during pregnancy in Sweden: A nationwide utilization study covering 2007-2019.

INTRODUCTION: Antibiotics are often prescribed during pregnancy. Assessing the current state of prenatal antibiotic use is therefore imperative for optimizing prescribing and identifying emerging research priorities. The study aimed to describe recent trends and patterns in antibiotic use during pregnancy among women who gave birth in Sweden, including user characteristics. MATERIAL AND METHODS: Population-based descriptive study using linked nationwide registers. All pregnancies delivered in Sweden from 2007 to 2019 were included. Prevalence of use was defined as the percentage of pregnancies during which at least one prescription forantibiotics was filled. Temporal trends in the prevalence of antibiotic use by calendar year, trimester and weeks of gestation were assessed from time series graphs. RESULTS: Prescriptions for systemic antibiotics were filled in 20.7% of 1 434 431 pregnancies overall, decreasing from 24.7% in 2007 to 18.0% in 2019. Phenoxymethylpenicillin (8.5%), pivmecillinam (6.5%), nitrofurantoin (4.7%), amoxicillin (1.6%) and cefadroxil (1.5%) use were the most prevalent. Their use decreased over the 13-year period, except for pivmecillinam, which increased from 4.0% to 7.4%. Prevalence of use was highest in the second trimester (9.5%), with weekly trends peaking at 13 and 34 weeks of gestation. Compared with non-users, antibiotic users more often belonged to the youngest and oldest age strata, carried multipleton pregnancies, had delivered before, had attained a lower education level and smoked in early pregnancy. A higher body mass index, asthma, chronic renal disease and diabetes mellitus were more prevalent among antibiotic users than among non-users. CONCLUSIONS: Although outpatient antibiotic use during pregnancy in Sweden has been declining, one in five pregnancies was exposed to systemic antibiotics.

Model misspecification and bias for inverse probability weighting estimators of average causal effects.

Commonly used semiparametric estimators of causal effects specify parametric models for the propensity score (PS) and the conditional outcome. An example is an augmented inverse probability weighting (IPW) estimator, frequently referred to as a doubly robust estimator, because it is consistent if at least one of the two models is correctly specified. However, in many observational studies, the role of the parametric models is often not to provide a representation of the data-generating process but rather to facilitate the adjustment for confounding, making the assumption of at least one true model unlikely to hold. In this paper, we propose a crude analytical approach to study the large-sample bias of estimators when the models are assumed to be approximations of the data-generating process, namely, when all models are misspecified. We apply our approach to three prototypical estimators of the average causal effect, two IPW estimators, using a misspecified PS model, and an augmented IPW (AIPW) estimator, using misspecified models for the outcome regression (OR) and the PS. For the two IPW estimators, we show that normalization, in addition to having a smaller variance, also offers some protection against bias due to model misspecification. To analyze the question of when the use of two misspecified models is better than one we derive necessary and sufficient conditions for when the AIPW estimator has a smaller bias than a simple IPW estimator and when it has a smaller bias than an IPW estimator with normalized weights. If the misspecification of the outcome model is moderate, the comparisons of the biases of the IPW and AIPW estimators show that the AIPW estimator has a smaller bias than the IPW estimators. However, all biases include a scaling with the PS-model error and we suggest caution in modeling the PS whenever such a model is involved. For numerical and finite sample illustrations, we include three simulation studies and corresponding approximations of the large-sample biases. In a dataset from the National Health and Nutrition Examination Survey, we estimate the effect of smoking on blood lead levels.

Pharmacological and epidemiological considerations while constructing treatment episodes using observational data: A simulation study.

BACKGROUND: The permissible gap method is an extensively used approach for defining episodes of continuous treatment use in pharmacoepidemiology. This method uses the amount of drug redeemed, when available, and researcher-defined temporal gaps to fill the interval between the calculated end of coverage of a redeemed prescription and the date of redemption of the next prescription in the same treatment episode. The final scope is defining periods of continuous use of medications. There are strong pharmacological and epidemiological arguments for adding the gap at the end of each treatment episode. However, the evidence is scarce on the impact that such a practice has on measures of association. This study aims to compare the impact of adding or not adding the researcher-defined gap time to the end of a treatment episode on the incidence of drug discontinuation and the incidence rate for a simulated outcome that occurred during an observational window. Additionally, the study aims at assessing the magnitude of misclassification of exposure time between the two methods. METHODS: A simulated dataset of 100 patients available in the R package AdhereR that contains 1080 redeemed prescriptions was used. A gap time of 90 days was used for constructing treatment episodes in an observational window of 365 days following the first redeemed prescription. Two approaches were used for defining treatment episodes that were named "gap+" and "gap-" and that respectively add and did not add the gap time at the end of a treatment episode. An outcome was simulated by using an exponential baseline hazard function with scale parameter λ = 0.5 and censoring at time t = 365 days. The incidence rate ratio for the simulated outcome between the two approaches was computed. RESULTS: The 100 patients were followed for a median time of 183 days (interquartile range, IQR 50-365 days) and a median time of 273 days (IQR 140-365 days), respectively using "gap-" and "gap+". During the first 100 days of the follow-up period, none of the patients was found to discontinue the treatment with the method "gap+" while 38 patients discontinued using the method "gap-". The approach "gap+" exerted a higher incidence rate for the simulated outcome among the exposed (0.98 events/person-years) when compared to the "gap-" (0.82 events/person-years) during defined periods of continuous treatment use. When comparing the two approaches and using the method "gap-" as the reference group, the incidence rate ratio for the simulated outcome was 1.20 (95% confidence interval: CI 0.72-2.02) among the exposed. CONCLUSIONS: This study showed that not adding the gap at the end of the treatment episodes leads to an overestimation of drug discontinuation, particularly at the beginning of the observational window, and an underestimation of the incidence rate of a hypothetical outcome during the period of exposure to the medication.

The use of uncertain exposure-A method to define switching and add-on in pharmacoepidemiology.

PURPOSE: When defining exposure to pharmacological treatments in pharmacoepidemiology, register data often do not provide information regarding if a pharmacological treatment is a switch or an add-on. This study aims to compare two methods defining switching and add-on therapies and their impact on exposure-outcome associations. Additionally, to guide bias reduction, it aims to describe how the methods relate to immortal time bias and selection bias. METHODS: Cohort study using Swedish population-based health registers to identify antidepressant (AD) prescriptions as exposures while hospitalizations for psychiatric reasons were used as an empirical outcome example. The first method for exposure definition used conditioning on future exposure (FE), the second used the concept of uncertain exposure (UE). To estimate associations between outcome and exposure categories "Use of one AD," "Use of two or more ADs", and "UE" compared to "Unexposed," hazard ratios (HRs) and 95% confidence intervals were estimated using Cox regression adjusted for age and sex. RESULTS: Using the UE method, 7.2% of time periods were classified as "UE" with a notable proportion of psychiatric hospitalizations (7.7%) occurring during this time, while when using the FE method these hospitalizations were distributed over unexposed time and AD use time. The FE method resulted in slightly higher associations than the UE method. The highest HR was found during "UE": HR (95% CI) 5.54 (5.06-6.07). CONCLUSIONS: This study suggests that to reduce the potential immortal time bias, selection bias, and exposure misclassification inherent to the FE method, the UE method could be used for identifying switching and add-on therapies. If not used as a main exposure definition, the UE method may be used to investigate the impact of UE time in a sensitivity analysis.

Investigating the association between prenatal exposure to folic acid and risk of neonatal diabetes/hyperglycemia and type 1 diabetes: A Norwegian register-based study.

BACKGROUND: Experimental animal studies suggest a novel role for the folate receptor 1 in ß-cell differentiation in the pancreas, with potential implications for glycemic control. We tested the hypothesis of a protective association between prenatal folic acid use and neonatal diabetes or hyperglycemia and type 1 diabetes in an observational cohort study using data from the national population health registers in Norway. METHODS: All singleton pregnancies resulting in live births from 2005 to 2018 were identified. Prenatal exposure to folic acid was determined based on maternal report at antenatal care in early pregnancy. Diagnoses of neonatal diabetes, hyperglycemia, and type 1 diabetes for the children were identified. Associations were estimated with logistic regression or Cox proportional hazard model and included crude and adjusted estimates. RESULTS: Among 781,567 children, 69% had prenatal exposure to folic acid, 264 were diagnosed with neonatal diabetes or hyperglycemia, and 1390 with type 1 diabetes. Compared to children with no prenatal exposure to folic acid, children with prenatal exposure to folic acid had similar odds of having a neonatal diabetes or hyperglycemia diagnosis (adjusted odds ratio 0.95, 95% confidence interval [CI] 0.72, 1.25) and similar risk of being diagnosed with type 1 diabetes (adjusted hazard ratio 1.05, 95% CI 0.93, 1.18). CONCLUSIONS: No association between prenatal folic acid exposure and neonatal diabetes/hyperglycemia or type 1 diabetes was found. These findings do not rule out a translational effect of the experimental results and future studies with longer follow-up and more precise information on the window of prenatal exposure are needed.

Methods for constructing treatment episodes and impact on exposure-outcome associations.

PURPOSE: To assess the impact on exposure time and outcome misclassifications, and consequent impact on exposure-outcome associations from treatment episode construction. We investigated the dosage assumptions of 1 unit per day, and 1 DDD per day, versus actual prescribed dosage under different handling of gaps and overlaps of prescriptions. METHODS: Data on mirtazapine and citalopram exposure (years 2006-2014) from the Swedish Prescribed Drug register were used. Via a within individuals design we compared method A, based on actual dosage, with methods B and C based on 1 unit of drug per day and 1 DDD per day assumptions, respectively, including consideration of gaps and overlaps. Four outcomes were used, hospitalizations and outpatient visits for all and for psychiatric causes. RESULTS: Relative to method A, both alternative methods lead to misclassification of exposure time. With regard to outcome misclassifications, method B overestimates the effect of the exposure on the outcome in 77% and 100% of exposure definition comparisons for mirtazapine and citalopram respectively, while 23% of the comparisons for mirtazapine results in underestimation of exposure-outcome associations. Conversely, treatment episodes based on DDD (method C) result in underestimation of the exposure-outcome association in 100% and 87.5% of exposure definition comparisons for mirtazapine and citalopram respectively, while 12.5% of the comparisons for citalopram results in overestimation of the exposure-outcome associations. CONCLUSIONS: The study provides results that have consistent clinical relevance. We have showed that a non-accurate construction of exposure time may lead to errors on outcome detection during exposed time, and consequently affect conclusions on safety or efficacy profile of a treatment.

Methods for time-varying exposure related problems in pharmacoepidemiology: An overview.

PURPOSE: Lack of control for time-varying exposures can lead to substantial bias in estimates of treatment effects. The aim of this study is to provide an overview and guidance on some of the available methodologies used to address problems related to time-varying exposure and confounding in pharmacoepidemiology and other observational studies. The methods are explored from a conceptual rather than an analytical perspective. METHODS: The methods described in this study have been identified exploring the literature concerning to the time-varying exposure concept and basing the search on four fundamental pharmacoepidemiological problems, construction of treatment episodes, time-varying confounders, cumulative exposure and latency, and treatment switching. RESULTS: A correct treatment episodes construction is fundamental to avoid bias in treatment effect estimates. Several methods exist to address time-varying covariates, but the complexity of the most advanced approaches-eg, marginal structural models or structural nested failure time models-and the lack of user-friendly statistical packages have prevented broader adoption of these methods. Consequently, simpler methods are most commonly used, including, for example, methods without any adjustment strategy and models with time-varying covariates. The magnitude of exposure needs to be considered and properly modelled. CONCLUSIONS: Further research on the application and implementation of the most complex methods is needed. Because different methods can lead to substantial differences in the treatment effect estimates, the application of several methods and comparison of the results is recommended. Treatment episodes estimation and exposure quantification are key parts in the estimation of treatment effects or associations of interest.

Safety of GLP-1 Receptor Agonists and Other Second-Line Antidiabetics in Early Pregnancy.

Importance: Increasing use of second-line noninsulin antidiabetic medication (ADM) in pregnant individuals with type 2 diabetes (T2D) may result in fetal exposure, but their teratogenic risk is unknown. Objective: To evaluate periconceptional use of second-line noninsulin ADMs and whether it is associated with increased risk of major congenital malformations (MCMs) in the infant. Design, Setting, and Participants: This observational population-based cohort study used data from 4 Nordic countries (2009-2020), the US MarketScan Database (2012-2021), and the Israeli Maccabi Health Services database (2009-2020). Pregnant women with T2D were identified and their live-born infants were followed until up to 1 year after birth. Exposure: Periconceptional exposure was defined as 1 or more prescription fill of sulfonylureas, dipeptidyl peptidase 4 (DPP-4) inhibitors, glucagon-like peptide 1 (GLP-1) receptor agonists, and sodium-glucose cotransporter 2 (SGLT2) inhibitors, or insulin (active comparator) from 90 days before pregnancy to end of first trimester. Main Outcomes and Measures: Relative risks (RRs) and 95% CIs for MCMs were estimated using log-binomial regression models, adjusting for key confounders in each cohort and meta-analyzed. Results: Periconceptional exposure to second-line noninsulin ADMs differed between countries (32, 295, and 73 per 100 000 pregnancies in the Nordics, US, and Israel, respectively), and increased over the study period, especially in the US. The standardized prevalence of MCMs was 3.7% in all infants (n = 3 514 865), 5.3% in the infants born to women with T2D (n = 51 826), and among infants exposed to sulfonylureas was 9.7% (n = 1362); DPP-4 inhibitors, 6.1% (n = 687); GLP-1 receptor agonists, 8.3% (n = 938); SGLT2 inhibitors, 7.0% (n = 335); and insulin, 7.8% (n = 5078). Compared with insulin, adjusted RRs for MCMs were 1.18 (95% CI, 0.94-1.48), 0.83 (95% CI, 0.64-1.06), 0.95 (95% CI, 0.72-1.26), and 0.98 (95% CI, 0.65-1.46) for infants exposed to sulfonylureas, DPP-4 inhibitors, GLP-1 receptor agonists, and SGLT2 inhibitors, respectively. Conclusions and Relevance: Use of second-line noninsulin ADMs is rapidly increasing for treatment of T2D and other indications, resulting in an increasing number of exposed pregnancies. Although some estimates were imprecise, results did not indicate a large increased risk of MCMs above the risk conferred by maternal T2D requiring second-line treatment. Although reassuring, confirmation from other studies is needed, and continuous monitoring will provide more precise estimates as data accumulate.

A global systematic overview of socioeconomic factors associated with antidiabetic medication adherence in individuals with type 2 diabetes.

BACKGROUND: Antidiabetic medication adherence is a key aspect for successful control of type 2 diabetes mellitus (T2DM). This systematic review aims to provide an overview of the associations between socioeconomic factors and antidiabetic medication adherence in individuals with T2DM. METHODS: A study protocol was established using the PRISMA checklist. A primary literature search was conducted during March 2022, searching PubMed, Embase, Web of Science, as well as WorldCat and the Bielefeld Academic Search Engine. Studies were included if published between 1990 and 2022 and included individuals with T2DM. During primary screening, one reviewer screened titles and abstracts for eligibility, while in the secondary screening, two reviewers worked independently to extract the relevant data from the full-text articles. RESULTS: A total of 15,128 studies were found in the primary search, and 102 were finally included in the review. Most studies found were cross-sectional (72) and many investigated multiple socioeconomic factors. Four subcategories of socioeconomic factors were identified: economic (70), social (74), ethnical/racial (19) and geographical (18). The majority of studies found an association with antidiabetic medication adherence for two specific factors, namely individuals' insurance status (10) and ethnicity or race (18). Other important factors were income and education. CONCLUSIONS: A large heterogeneity between studies was observed, with many studies relying on subjective data from interviewed individuals with a potential for recall bias. Several socioeconomic groups influencing medication adherence were identified, suggesting potential areas of intervention for the improvement of diabetes treatment adherence and individuals' long-term well-being.

In-utero antibiotic exposure and subsequent infections in infancy: a register-based cohort study with sibling analysis.

BACKGROUND: Prenatal antibiotic use, the ensuing maternal dysbiosis, and subsequent acquisition of altered microbiota in early life have been linked to the offspring's increased susceptibility to childhood infections. However, infection risks during the first year of life associated with in-utero antibiotic exposure have not been comprehensively explored. OBJECTIVE: To investigate the associations between exposure to antibiotics in utero and subsequent infections during infancy and whether such associations differ by antibiotic class. STUDY DESIGN: All data were retrieved from Swedish population-based registers. Singletons live-born between 2006 and 2018 were followed up from birth to their first birthday. Exposure was maternal filling of at least 1 antibiotic prescription between the last menstrual period and delivery. Outcomes were the infants' antimicrobial prescription fills, incident infections diagnosed in specialist care, and deaths with infections indicated as underlying or contributing causes ("infection-related deaths"). Birth year, birth season, maternal age, place of residence, parity, comorbidity indicator, body mass index, proxies for general health status, education level, and smoking status were considered covariates. Poisson regression was used to estimate crude and adjusted incidence rate ratios with 95% confidence intervals for the number of antimicrobial prescriptions filled to the infant. Cox regression was used to estimate crude and adjusted hazard ratios with 95% confidence intervals for incident infections diagnosed in specialist care and at death. Sibling analyses were used to account for shared familial factors. Sensitivity of the results to exposure definition and perinatal factors prognostic for the outcomes were assessed in supplementary analyses. RESULTS: Of 1,347,018 infants in the full cohort, 294,657 (21.9%) were exposed to antibiotics in utero. There were 677,430 antimicrobial prescriptions filled (1.380 per 1000 person-days), 423,705 incident infections diagnosed in specialist care (0.870 per 1000 person-days), and 2800 infection-related deaths (0.006 deaths per 1000 person-days) during follow-up. Compared to unexposed, infants exposed to antibiotics in utero had higher rates of antimicrobial prescription fills (adjusted incidence rate ratio, 1.34; 95% confidence interval, 1.33-1.34), incident infections diagnosed in specialist care (adjusted hazard ratio, 1.28; 95% confidence interval, 1.27-1.29), and infection-related mortality (adjusted hazard ratio, 1.15; 95% confidence interval, 1.05-1.25). For antimicrobial prescriptions and infections diagnosed in specialist care, associations were consistent across most antibiotic classes but were attenuated in the sibling analyses: adjusted incidence rate ratio of 1.05 (95% confidence interval, 1.04-1.06) and adjusted hazard ratio of 1.05 (95% confidence interval, 1.03-1.07), respectively. No association with infant mortality was found in the sibling cohort (adjusted hazard ratio, 0.93; 95% confidence interval, 0.81-1.08). CONCLUSION: The minor associations between exposure to antibiotics in utero and infections during infancy were partly explained by shared familial factors and did not differ across frequently used antibiotic classes.

Metformin Versus Insulin and Risk of Major Congenital Malformations in Pregnancies With Type 2 Diabetes: A Nordic Register-Based Cohort Study.

OBJECTIVE: To assess the risk of major congenital malformations with metformin versus insulin in pregnancies with type 2 diabetes. RESEARCH DESIGN AND METHODS: This cohort study used four Nordic countries' nationwide registers of live and stillborn infants exposed to metformin or insulin during first trimester organogenesis. Main exclusion criteria were type 1 diabetes, polycystic ovary syndrome, fertility treatment, and exposure to other diabetes drugs. Adjusted risk ratios (RRs) and 95% CIs were estimated for any and cardiac malformations. RESULTS: Of 3,734,125 infants in the source population, 25,956 were exposed to metformin or insulin in the first trimester, and 4,023 singleton infants were included. A malformation was diagnosed in 147 (4.7%) of 3,145 infants with exposure to any metformin (alone or in addition to insulin) and 50 (5.7%) of 878 infants with exposure to insulin alone (RR 0.84, 95% CI 0.46-1.54). Among 2,852 infants exposed to metformin alone and 293 infants exposed to metformin in addition to insulin 127 (4.4%) and 20 (6.8%), respectively, had a malformation. The adjusted risk was not increased for either metformin alone (0.83, 0.44-1.58) or both metformin and insulin (0.98, 0.56-1.69) versus insulin alone. Corresponding RRs for cardiac malformations were 1.01 (0.55-1.84) for any metformin, 0.92 (0.47-1.81) for metformin alone, and 1.72 (0.76-3.91) for both metformin and insulin. CONCLUSIONS: No evidence of an increased malformation risk with metformin versus insulin in the first trimester was found. Results should be interpreted with caution since information on glycemic control was missing.

Association of In Utero Antipsychotic Medication Exposure With Risk of Congenital Malformations in Nordic Countries and the US.

Importance: Psychiatric disorders are common among female individuals of reproductive age. While antipsychotic medication use is increasing, the safety of such medications in pregnancy is an area with large evidence gaps. Objective: To evaluate the risk of first-trimester antipsychotic exposure with respect to congenital malformations, focusing on individual drugs and specific malformation subtypes. Design, Setting, and Participants: This cohort study used data from nationwide health registers from the 5 Nordic countries and the US and spanned 1996 to 2018. The Nordic cohort included all pregnancies resulting in singleton live-born infants, and the US cohort consisted of publicly insured mothers linked to their live-born infants nested in the nationwide Medicaid Analytic eXtract. Data were analyzed from November 2020 to April 2022. Exposures: One or more first-trimester dispensing of any atypical, any typical, and individual antipsychotic drugs. Main Outcomes and Measures: Any major congenital malformation and specific malformation subtypes previously suggested to be associated with antipsychotic exposure in utero: cardiovascular malformations, oral clefts, neural tube defects, hip dysplasia, limb reduction defects, anorectal atresia/stenosis, gastroschisis, hydrocephalus, other specific brain anomalies, and esophageal disorders. Propensity score stratification was used to control for potential confounders. Pooled adjusted estimates were calculated using indirect standardization. Results: A total of 6 455 324 unexposed mothers (mean maternal age range across countries: 24-31 years), 21 751 mothers exposed to atypical antipsychotic drugs (mean age range, 26-31 years), and 6371 mothers exposed to typical antipsychotic drugs (mean age range, 27-32 years) were included in the study cohort. Prevalence of any major malformation was 2.7% (95% CI, 2.7%-2.8%) in unexposed infants, 4.3% (95% CI, 4.1%-4.6%) in infants with atypical antipsychotic drug exposure, and 3.1% (95% CI, 2.7%-3.5%) in infants with typical antipsychotic drug exposure in utero. Among the most prevalent exposure-outcome combinations, adjusted relative risks (aRR) were generally close to the null. One exception was olanzapine exposure and oral cleft (aRR, 2.1 [95% CI, 1.1-4.3]); however, estimates varied across sensitivity analyses. Among moderately prevalent combinations, increased risks were observed for gastroschisis and other specific brain anomalies after atypical antipsychotic exposure (aRR, 1.5 [95% CI, 0.8-2.6] and 1.9 [95% CI, 1.1-3.0]) and for cardiac malformations after chlorprothixene exposure (aRR, 1.6 [95% CI, 1.0-2.7]). While the association direction was consistent across sensitivity analyses, confidence intervals were wide, prohibiting firm conclusions. Conclusions and Relevance: In this study, considering the evidence from primary and sensitivity analyses and inevitable statistical noise for very rare exposure-outcome combinations, in utero antipsychotic exposure generally was not meaningfully associated with an increased risk of malformations. The observed increased risks of oral clefts associated with olanzapine, gastroschisis, and other specific brain anomalies with atypical antipsychotics and cardiac malformations with chlorprothixene requires confirmation as evidence continues to accumulate.

Rationale and performances of a data-driven method for computing the duration of pharmacological prescriptions using secondary data sources.

The assessment of the duration of pharmacological prescriptions is an important phase in pharmacoepidemiologic studies aiming to investigate persistence, effectiveness or safety of treatments. The Sessa Empirical Estimator (SEE) is a new data-driven method which uses k-means algorithm for computing the duration of pharmacological prescriptions in secondary data sources when this information is missing or incomplete. The SEE was used to compute durations of exposure to pharmacological treatments where simulated and real-world data were used to assess its properties comparing the exposure status extrapolated with the method with the "true" exposure status available in the simulated and real-world data. Finally, the SEE was also compared to a Researcher-Defined Duration (RDD) method. When using simulated data, the SEE showed accuracy of 96% and sensitivity of 96%, while when using real-world data, the method showed sensitivity ranging from 78.0 (nortriptyline) to 95.1% (propafenone). When compared to the RDD, the method had a lower median sensitivity of 2.29% (interquartile range 1.21-4.11%). The SEE showed good properties and may represent a promising tool to assess exposure status when information on treatment duration is not available.

Database development and survival analysis in a clinical and historical cohort of dogs affected by myxomatous mitral valve disease treated or not with pimobendan using causal inference techniques.

The aim of this work was to retrospectively evaluate the influence of pimobendan on the survival time (ST) of dogs with myxomatous mitral valve disease at different stages using an Inverse Probability Weighting (IPW) analysis. An IPW method was used to minimize confounding and IPW weighted time-repeated logistic model was used to approximate survival curves (SCs) and calculate survival differences. Subjects were allocated into exposed (E) and unexposed (U). Dogs in the American College of Veterinary Internal Medicine (ACVIM) B2 class treated with pimobendan (± ACE-inhibitors) were selected for the E group, as well as symptomatic patients (ACVIM class C) treated with triple (furosemide, ACE-inhibitor, pimobendan) or quadruple (furosemide, ACE-inhibitor, pimobendan and spironolactone) therapy. The U group included ACVIM class B2 dogs not treated with any medication and ACVIM C dogs treated with a combination of furosemide and ACE-inhibitor/spironolactone without pimobendan. The survival curve (SC) of the E group crossed the U group at 1634 days. The difference between the two SCs at the time of maximum survival difference in favor of the U group was 11.3% (CI 1.7%-20.9%) (significant), in favor of the E group was 3.9% (CI -8.6%-16.4%) (not significant) and at the mean ST was 3.6% (CI -8.5%-15.7%) (not significant) in favor of the E group. For times greater than 1634 days the survival was in favor of the E group, but there were no statistically significant differences in survival in favor of the E group in this clinical population.

Increased antidepressant use during the COVID-19 pandemic: Findings from the Friuli Venezia Giulia region, Italy, 2015-2020.

BACKGROUND: Few studies investigated the impact of the pandemic on antidepressant (AD) use. METHODS: The Social and Health Information System of Friuli Venezia Giulia region, Italy, provided data on AD use. Sex, age, AD class and month used the amount of AD prescriptions, measured by defined daily doses (DDD) per 1000 inhabitants per day, to compare AD use in 2020 with the period 2015-2019. A linear trend model predicted AD use for 2020, based on years 2015-2019. RESULTS: AD use was on average 20% higher in each month of 2020 when compared with the same month for the period 2015-2019, with an increase of more than 30% in the first four and in the last two months of 2020. The observed AD use in 2020 was higher than predicted, particularly in men, and in the 30-59 years age group. LIMITATIONS: Descriptive study of AD use without analysis of data at the individual level. No information on psychiatric diagnoses of AD users. CONCLUSION: AD use was higher in the first year of the COVID-19 pandemic. Further research is warranted to understand if this may be related to a rise in mental disorders in the general population during the COVID-19 pandemic.

Association between folic acid use during pregnancy and gestational diabetes mellitus: Two population-based Nordic cohort studies.

INTRODUCTION: Inconsistent results have been reported on the association between folic acid use in pregnancy and risk of GDM. The aim of this study was to estimate the association between folic acid use and GDM in two population-based Nordic cohorts. MATERIAL AND METHODS: Two cohort studies were conducted using data from the national population registers in Norway (2005-2018, n = 791,709) and Sweden (2006-2016, n = 1,112,817). Logistic regression was used to estimate the associations between GDM and self-reported folic acid use and prescribed folic acid use, compared to non-users, adjusting for covariates. To quantify how potential unmeasured confounders may affect the estimates, E-values were reported. An exposure misclassification bias analysis was also performed. RESULTS: In Norwegian and Swedish cohorts, adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for maternal self-reported folic acid use were 1.10 (1.06-1.14) and 0.89 (0.85-0.93), with E-values of 1.43 (1.31) and 1.50 (1.36), respectively. For prescribed folic acid use, ORs were 1.33 (1.15-1.53) and 1.56 (1.41-1.74), with E-values of 1.99 (1.57) and 2.49 (2.17), in Norway and Sweden respectively. CONCLUSIONS: The slightly higher or lower odds for GDM in self-reported users of folic acid in Norway and Sweden respectively, are likely not of clinical relevance and recommendations for folic acid use in pregnancy should remain unchanged. The two Nordic cohorts showed different directions of the association between self-reported folic acid use and GDM, but based on bias analysis, exposure misclassification is an unlikely explanation since there may still be differences in prevalence of use and residual confounding. Prescribed folic acid is used by women with specific comorbidities and co-medications, which likely underlies the higher odds for GDM.

The association between family structure and children's BMI over time-the mediating role of income.

PURPOSE: Although both family structure and income have previously been indicated as being associated with body mass index (BMI), the extent to which the effect of family structure on BMI is mediated through income is incompletely understood. Taking the case of the United Kingdom, this study aims to investigate the association between family structure, defined in this study as whether children live in a one- or two-adult household, and childhood BMI, and whether this varies by child sex and with increased age. Second, the study aims to examine whether family equivalised income, as a proxy for socioeconomic status, mediates the association between family structure and childhood BMI. METHODS: This study uses data from the Millennium Cohort Study. Data from 7478 children born between 2000 and 2001 in the UK at the ages of 3, 5, 7, 11, and 14 were used. Mediation analysis was used to consider, at each age, the extent to which the association between living in a one- or two-adult household and BMI was mediated through income overall and stratified by sex. To assess the robustness of the mediation analysis estimates, we used both E-values and multiple confounder adjustment. RESULTS: At ages 3 and 5, there was no direct or indirect effect of family structure mediated by income on BMI. Between the ages of 7 and 11, the overall proportion of the association mediated vastly increased, from 19.70% at age 7 up to 42.70% at the age of 11. The E-values show that substantial unmeasured confounder associations would be needed to fully explain away the conclusions from the mediation analysis. Results remained significant when models were additionally adjusted for geographic region, the main respondent's (usually the mother's) highest educational attainment, and ethnicity. CONCLUSIONS: An increasing proportion of the association between family structure and BMI is mediated by income as children grow older. The study focuses on the mediating role of income between family structure and BMI using the available data as an empirical application of the potential impact of income as mediator in the causal pathway.

Influence of Morphometry on Echocardiographic Measurements in Cavalier King Charles Spaniels: An Inverse Probability Weighting Analysis.

The development and progression of myxomatous mitral valve disease (MMVD) in Cavalier King Charles Spaniels (CKCS) are difficult to predict. Thus, the identification of dogs with a morphotype associated with more severe mitral disease at a young age is desirable. The aims of this study were to: (1) describe the physical, morphometric, and echocardiographic features of class B1 MMVD-affected Cavalier King Charles Spaniels (CKCS) according to the American College of Veterinary Internal Medicine (ACVIM) guidelines; (2) evaluate the influence of morphometric physical measurements on murmur intensity, mitral valve prolapse (MVP), regurgitant jet size, and indexed mitral valve and annulus measurements. Fifty-two MMVD-affected CKCS were included in the ACVIM class B1. This is a prospective clinical cross-sectional study. Morphometric measurements, which included the body, thorax, and head sizes of each dog, were investigated to establish the association with heart murmur intensity, valvular and annular echocardiographic measurements, MVP, and regurgitant jet size, using inverse probability weighting (IPW) analyses to adjust for confounding. The IPW analyses showed that when the head length and nose length decreased, dogs had a more severe regurgitant jet size. Furthermore, subjects with a more pronounced head stop angle had thicker anterior mitral valve leaflets. A brachycephalic morphotype, as seen in dogs similar to the King Charles Spaniel breed in terms of cephalic morphology, is associated with a more severe regurgitant jet size and with valvular characteristics that are related to the most severe forms of MMVD.

Reinforcing one-carbon metabolism via folic acid/Folr1 promotes ß-cell differentiation.

Diabetes can be caused by an insufficiency in ß-cell mass. Here, we performed a genetic screen in a zebrafish model of ß-cell loss to identify pathways promoting ß-cell regeneration. We found that both folate receptor 1 (folr1) overexpression and treatment with folinic acid, stimulated ß-cell differentiation in zebrafish. Treatment with folinic acid also stimulated ß-cell differentiation in cultures of neonatal pig islets, showing that the effect could be translated to a mammalian system. In both zebrafish and neonatal pig islets, the increased ß-cell differentiation originated from ductal cells. Mechanistically, comparative metabolomic analysis of zebrafish with/without ß-cell ablation and with/without folinic acid treatment indicated ß-cell regeneration could be attributed to changes in the pyrimidine, carnitine, and serine pathways. Overall, our results suggest evolutionarily conserved and previously unknown roles for folic acid and one-carbon metabolism in the generation of ß-cells.