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.

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.

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.

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.

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.

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.

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.

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.