Most non-randomised controlled trials are unable to establish clear causal relationships in chronic obstructive pulmonary disease (COPD) due to the presence of confounding factors. This review summarises the evidence that the Mendelian randomisation method can be a powerful tool for performing causal inferences in COPD.

A non-systematic search of English-language scientific literature was performed on PubMed using the following keywords: 'Mendelian randomisation', 'COPD', 'lung function', and 'GWAS'. No date restrictions were applied. The types of articles selected included randomised controlled trials, cohort studies, observational studies, and reviews.

Mendelian randomisation is becoming an increasingly popular method for identifying the risk factors of COPD. Recent Mendelian randomisation studies have revealed some risk factors for COPD, such as club cell secretory protein-16, impaired kidney function, air pollutants, asthma, and depression. In addition, Mendelian randomisation results suggest that genetically predicted factors such as PM2.5, inflammatory cytokines, growth differentiation factor 15, docosahexaenoic acid, and testosterone may have causal relationships with lung function.

Mendelian randomisation is a robust method for performing causal inferences in COPD research as it reduces the impact of confounding factors.

Most subjects in osteoporosis clinical trials were women with postmenopausal osteoporosis and while bridging studies (BMD endpoint) provide an expectation that osteoporosis medications will reduce fracture risk in men. This real-world study shows direct evidence of fracture risk reduction among men with osteoporosis (36% of hip fracture reduction with denosumab).

Direct evidence for fracture risk reduction of medications used among men with osteoporosis is very limited. This study aims to evaluate the real-world effectiveness of denosumab in reducing fracture risk.

This study included 13,797 men aged ≥ 50 years with osteoporosis who had initiated denosumab in Taiwan. Taiwan's National Health Insurance Research Database includes all Taiwan residents' complete health claim data. We compared incidence rates of clinical fractures between patients on denosumab 60 mg subcutaneously every 6 months (on-treatment) and patients ending therapy after one administration (off-treatment). Propensity score (PS) analysis, adjusting for measured differences at baseline covariates, was used to estimate the adjusted hazard ratio using a Cox proportion hazards model.

During follow-up, 248 hip fracture events occurred. The crude incidence rates of hip fracture were 1.13 events and 1.73 events per 100 person-years in on-treatment and off-treatment cohorts, respectively. After PS inverse probability of treatment weighting, the cohorts achieved balance in all 59 covariates. The hip fracture event rate was lower in on-treatment cohort versus off-treatment cohort by 36% (hazard ratio, 0.64 [95% CI 0.50-0.83]). A similar magnitude of risk reduction was observed in clinical vertebral and nonvertebral fractures. A series of sensitivity analysis, including a validation analysis using a-million individual health records, demonstrated that unmeasured confounders were not suggested to impact study result interpretation.

In this large, real-world study evaluating denosumab treatment among men with osteoporosis, the observed fracture risk reductions were consistent with the available risk reductions demonstrated in clinical trials among women with postmenopausal osteoporosis.

The assumption of "no unmeasured confounders" is a critical but unverifiable assumption required for causal inference yet quantitative sensitivity analyses to assess robustness of real-world evidence remains under-utilized. The lack of use is likely in part due to complexity of implementation and often specific and restrictive data requirements for application of each method. With the advent of methods that are broadly applicable in that they do not require identification of a specific unmeasured confounder-along with publicly available code for implementation-roadblocks toward broader use of sensitivity analyses are decreasing. To spur greater application, here we offer a good practice guidance to address the potential for unmeasured confounding at both the design and analysis stages, including framing questions and an analytic toolbox for researchers. The questions at the design stage guide the researcher through steps evaluating the potential robustness of the design while encouraging gathering of additional data to reduce uncertainty due to potential confounding. At the analysis stage, the questions guide quantifying the robustness of the observed result and providing researchers with a clearer indication of the strength of their conclusions. We demonstrate the application of this guidance using simulated data based on an observational fibromyalgia study, applying multiple methods from our analytic toolbox for illustration purposes.

The objective of this study was to perform a meta-analysis of risk factors of conversion to total hip arthroplasty (THA) after operative fixation of acetabular fractures.

This systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Data sources included PubMed, MEDLINE, EMBASE, and Cochrane Library, which were screened from inception to 2024.

Inclusion criteria were studies comparing risk factors of conversion to THA following acetabular fracture (OTA/AO 62A, B, C) surgical fixation.

Studies were assessed by the risk of bias and methodologic quality of evidence tools designed by the Cochrane Methods Bias Group and Cochrane Statistical Methods Group.

Meta-analyses were conducted with a random-effects model using IBM SPSS Statistics Version 29.0.2.0. One-factor-at-a-time sensitivity analyses were conducted.

Twelve studies (1951 patients) were included. Based on the Judet and Letournel classification system, patients with associated fracture patterns were more likely to require conversion to THA than those with elementary patterns (risk ratio [RR] = 1.55, P = 0.013). Patients with posterior wall involvement (including posterior wall, posterior column with posterior wall, and transverse with posterior wall patterns) were more likely to require subsequent THA than those without posterior wall involvement (RR = 1.58, P < 0.001). Patients who presented with hip dislocation and acetabular dome impaction and comminution were at higher risk of THA (RR = 1.15 and 1.19, respectively; P < 0.001, both). Owing to heterogeneity in reported findings, there were insufficient data to assess the impact of the quality of reduction, restoration of the articular surface, time since acetabular fixation, and patient demographic factors on conversion to THA.

This study aids in the identification of patients who may require early THA for posttraumatic arthritis based on fracture and injury patterns at presentation. Acetabular fractures with posterior wall involvement and those with associated fracture patterns are associated with a higher rate of conversion to THA. Injuries with acetabular dome impaction and comminution and hip dislocation are also significantly associated with conversion to THA.

Level III. See Instructions for Authors for a complete description of levels of evidence.

To determine whether the use of glucagon-like peptide-1 (GLP-1) receptor agonists is associated with an increased risk of suicidal ideation, self-harm, and suicide among patients with type 2 diabetes compared with the use of dipeptidyl peptidase-4 (DPP-4) inhibitors or sodium-glucose cotransporter-2 (SGLT-2) inhibitors.

Active comparator, new user cohort study.

Primary care practices contributing data to the UK Clinical Practice Research Datalink linked to the Hospital Episodes Statistics Admitted Patient Care and Office for National Statistics Death Registration databases.

Patients with type 2 diabetes.

Two cohorts were assembled, with the first composed of patients who started and continued on GLP-1 receptor agonists or DPP-4 inhibitors between 1 January 2007 and 31 December 2020 and the second composed of patients who started and continued on GLP-1 receptor agonists or SGLT-2 inhibitors between 1 January 1 2013 and 31 December 2020. Both cohorts were followed until 29 March 2021.

The primary outcome was suicidality, defined as a composite of suicidal ideation, self-harm, and suicide. Secondary outcomes were each of these events considered separately. Propensity score fine stratification weighted Cox proportional hazards models were fitted to estimate hazard ratios and 95% confidence intervals (CIs) to estimate the average treatment effect among the treated patients.

The first cohort included 36 082 GLP-1 receptor agonist users (median follow-up 1.3 years) and 234 028 DPP-4 inhibitor users (median follow-up 1.7 years). In crude analyses, GLP-1 receptor agonist use was associated with an increased incidence of suicidality compared with DPP-4 inhibitors (crude incidence rates 3.9 v 1.8 per 1000 person years, respectively; hazard ratio 2.08, 95% CI 1.83 to 2.36). This estimate decreased to a null value after confounding factors were accounted for (hazard ratio 1.02, 95% CI 0.85 to 1.23). The second cohort included 32 336 GLP-1 receptor agonist users (median follow-up 1.2 years) and 96 212 SGLT-2 inhibitor users (median follow-up 1.2 years). Similarly, GLP-1 receptor agonist use was associated with an increased risk of suicidality compared with SGLT-2 inhibitors in crude analyses (crude incidence rates 4.3 v 2.7 per 1000 person years; hazard ratio 1.60, 95% CI 1.37 to 1.87) but not after confounding factors were accounted for (0.91, 0.73 to 1.12). Similar findings were observed when suicidal ideation, self-harm, and suicide were analysed separately in both cohorts.

In this large cohort study, the use of GLP-1 receptor agonists was not associated with an increased risk of suicidality compared with the use of DPP-4 inhibitors or SGLT-2 inhibitors in patients with type 2 diabetes.

Understanding the potential for, and direction and magnitude of uncontrolled confounding is critical for generating informative real-world evidence. Many sensitivity analyses are available to assess robustness of study results to residual confounding, but it is unclear how researchers are using these methods. We conducted a systematic review of published active-comparator cohort studies of drugs or biologics to summarize use of sensitivity analyses aimed at assessing uncontrolled confounding from an unmeasured variable. We reviewed articles in 5 medical and 7 epidemiologic journals published between January 1, 2017, and June 30, 2022. We identified 158 active-comparator cohort studies: 76 from medical and 82 from epidemiologic journals. Residual, unmeasured, or uncontrolled confounding was noted as a potential concern in 93% of studies, but only 84 (53%) implemented at least 1 sensitivity analysis to assess uncontrolled confounding from an unmeasured variable. The most common analyses were E-values among medical journal articles (21%) and restriction on measured variables among epidemiologic journal articles (22%). Researchers must rigorously consider the role of residual confounding in their analyses and the best sensitivity analyses for assessing this potential bias. This article is part of a Special Collection on Pharmacoepidemiology.

Strabismus surgery, which is commonly performed in children, poses a high risk of postoperative vomiting. The current anesthesia guidelines for the prevention of postoperative vomiting in children are based on heterogeneous populations involving different types of surgery, and risk factors for postoperative vomiting in, specifically, the pediatric strabismus surgery population are unclear. Moreover, the effects of manipulating the deeply attached extraocular muscles and the oculocardiac reflex on this risk remain inconclusive.

To evaluate the associations among inferior oblique muscle manipulation, the oculocardiac reflex, and postoperative vomiting in children with retrospectively collected data.

The study had a multicenter retrospective cross-sectional design and was conducted at three institutions (two tertiary-care children's hospitals and one pediatric-adult mixed community hospital). It included children aged < 18 years and without major comorbidities undergoing strabismus surgery. The primary exposure was inferior oblique muscle manipulation during surgery. The outcome of interest was postoperative vomiting or antiemetic medication usage within 24 h postsurgery or by discharge.

Among 3152 children postoperative vomiting occurred in 108/795 (13.6%) children with and 227/2357 (9.6%) without inferior oblique muscle manipulation (unadjusted odds ratio, 1.57; 95% confidence interval, 1.21-2.05; p = 0.001). Multilevel logistic regression analysis, adjusting for potential confounders and surgeon-related variance, revealed that inferior oblique muscle manipulation (adjusted odds ratio, 1.58; 95% confidence interval, 1.15-2.18; p = 0.005), but not the oculocardiac reflex (adjusted odds ratio, 1.06; 95% confidence interval, 0.76-1.48; p = 0.73), was associated with postoperative vomiting after adjusting for confounders.

Stronger preventive measures against postoperative vomiting are recommended in healthy children undergoing strabismus surgery with inferior oblique muscle manipulation. Additionally, inferior oblique muscle manipulation should be considered a potential confounder in future related studies. However, the oculocardiac reflex was not associated with postoperative vomiting in pediatric strabismus surgery.

We propose a novel method to adjust for unmeasured time-stable confounding when the time between consecutive treatment administrations is fixed. We achieve this by focusing on a new-user cohort. Furthermore, we envisage that all time-stable confounding goes through the potential time on treatment as dictated by the disease condition at the initiation of treatment. Following this logic, we may eliminate all unmeasured time-stable confounding by adjusting for the potential time on treatment. A challenge with this approach is that right censoring of the potential time on treatment occurs when treatment is terminated at the time of the event of interest, for example, if the event of interest is death. We show how this challenge may be solved by means of the expectation-maximization algorithm without imposing any further assumptions on the distribution of the potential time on treatment. The usefulness of the methodology is illustrated in a simulation study. We also apply the methodology to investigate the effect of depression/anxiety drugs on subsequent poisoning by other medications in the Danish population by means of national registries. We find a protective effect of treatment with selective serotonin reuptake inhibitors on the risk of poisoning by various medications (1- year risk difference of approximately- 3 % $-3\%$ ) and a standard Cox model analysis shows a harming effect (1-year risk difference of approximately2 % $2\%$ ), which is consistent with what we would expect due to confounding by indication. Unmeasured time-stable confounding can be entirely adjusted for when the time between consecutive treatment administrations is fixed.

Causal inference enables machine learning methods to estimate treatment effects of medical interventions from electronic health records (EHRs). The prevalence of such observational data and the difficulty for randomized controlled trials (RCT) to cover all population/treatment relationships make these methods increasingly attractive for studying causal effects. However, researchers should be wary of many pitfalls. We propose and illustrate a framework for causal inference estimating the effect of albumin on mortality in sepsis using an Intensive Care database (MIMIC-IV) and comparing various sensitivity analyses to results from RCTs as gold-standard. The first step is study design, using the target trial concept and the PICOT framework: Population (patients with sepsis), Intervention (combination of crystalloids and albumin for fluid resuscitation), Control (crystalloids only), Outcome (28-day mortality), Time (intervention start within 24h of admission). We show that too large treatment-initiation times induce immortal time bias. The second step is selection of the confounding variables based on expert knowledge. Increasingly adding confounders enables to recover the RCT results from observational data. As the third step, we assess the influence of multiple models with varying assumptions, showing that a doubly robust estimator (AIPW) with random forests proved to be the most reliable estimator. Results show that these steps are all important for valid causal estimates. A valid causal model can then be used to individualize decision making: subgroup analyses showed that treatment efficacy of albumin was better for patients >60 years old, males, and patients with septic shock. Without causal thinking, machine learning is not enough for optimal clinical decision on an individual patient level. Our step-by-step analytic framework helps avoiding many pitfalls of applying machine learning to EHR data, building models that avoid shortcuts and extract the best decision-making evidence.

Epidemiological research aims to investigate how multiple exposures affect health outcomes of interest, but observational studies often suffer from biases caused by unmeasured confounders. In this study, we develop a novel sensitivity model to investigate the effect of correlated multiple exposures on the continuous health outcomes of interest. The proposed sensitivity analysis is model-agnostic and can be applied to any machine learning algorithm. The interval of single- or joint-exposure effects is efficiently obtained by solving a linear programming problem with a quadratic constraint. Some strategies for reducing the input burden in the sensitivity analysis are discussed. We demonstrate the usefulness of sensitivity analysis via numerical studies and real data application.

We test the robustness of the self-controlled risk interval (SCRI) design in a setting where time between doses may introduce time-varying confounding, using both negative control outcomes (NCOs) and quantitative bias analysis (QBA). All vaccinated cases identified from 5 European databases between September 1, 2020, and end of data availability were included. Exposures were doses 1-3 of the Pfizer, Moderna, AstraZeneca, and Janssen COVID-19 vaccines; outcomes were myocarditis and, as the NCO, otitis externa. The SCRI used a 60-day control window and dose-specific 28-day risk windows, stratified by vaccine brand and adjusted for calendar time. The QBA included two scenarios: (1) baseline probability of the confounder was higher in the control window and (2) vice versa. The NCO was not associated with any of the COVID-19 vaccine types or doses except Moderna dose 1 (IRR = 1.09; 95% CI 1.01-1.09). The QBA suggested that even the strongest literature-reported confounder (COVID-19; RR for myocarditis = 18.3) could only explain away part of the observed effect, from IRR = 3 to IRR = 1.40. The SCRI seems robust to unmeasured confounding in the COVID-19 setting, although a strong unmeasured confounder could bias the observed effect upward. Replication of our findings for other safety signals would strengthen this conclusion. This article is part of a Special Collection on Pharmacoepidemiology.

Anti-tumor necrosis factor (anti-TNF) therapy may improve insulin sensitivity, and its impact during pregnancy remains unclear. We aimed to assess the risk of gestational diabetes mellitus (GDM) associated with anti-TNF treatment among pregnant women with inflammatory bowel disease (IBD).

This nationwide cohort study included patients with IBD in Korea from 2010 to 2021. Anti-TNF exposure was identified from the last menstrual period (LMP) to LMP + 140 days. The development of GDM was assessed from LMP + 141 days to delivery. We performed overlap weighting to balance the covariates and used a generalized linear mixed model to measure the risk ratio (RR) and 95% confidence intervals (CIs). The anti-TNF group was compared with the unexposed group, as well as with the immunosuppressant, 5-aminosalicylate, and untreated groups.

A total of 3,695 pregnancies in women with IBD were identified, of which 338 (9.2%) were exposed to anti-TNFs. GDM was found in 7.1% of the pregnancies exposed to anti-TNFs as compared with 11.0% of those unexposed. The crude and weighted RRs for GDM risk were 0.64 (95% CI 0.43-0.96) and 0.68 (95% CI 0.55-0.84), respectively. The weighted RR when compared with the immunosuppressant, 5-aminosalicylate, and untreated groups was 0.70 (95% CI 0.41-1.18), 0.71 (95% CI 0.52-0.95), and 0.85 (95% CI 0.59-1.24), respectively.

This nationwide cohort reported a decreased risk of GDM among patients who used anti-TNFs during early pregnancy compared with those unexposed. GDM risk may become a consideration in the decision-making process when choosing treatment options for pregnant women with a risk factor for GDM.

Idiopathic intracranial hypertension (IIH) is known to elevate cardiovascular disease (CVD) risk, but the extent to which obesity and IIH-specific factors contribute to this risk is not well understood. WE aim to separate the effects of obesity from IIH-specific factors on the risk of stroke and CVD, building on previous findings that indicate a two-fold increase in cardiovascular events in women with IIH compared to BMI-matched controls.

An obesity-adjusted risk analysis was conducted using Indirect Standardization based on data from a cohort study by Adderley et al., which included 2,760 women with IIH and 27,125 matched healthy controls from The Health Improvement Network (THIN). Advanced statistical models were employed to adjust for confounding effects of obesity and determine the risk contributions of IIH to ischemic stroke and CVD, independent of obesity. Four distinct models explored the interactions between IIH, obesity, and CVD risk.

The analysis showed that IIH independently contributes to increased cardiovascular risk beyond obesity alone. Risk ratios for cardiovascular outcomes were significantly higher in IIH patients compared to controls within similar obesity categories. Notably, a synergistic effect was observed in obese IIH patients, with a composite CVD risk ratio of 6.19 (95% CI: 4.58-8.36, p<0.001) compared to non-obese controls.

This study underscores a significant, independent cardiovascular risk from IIH beyond obesity. The findings advocate for a shift in managing IIH to include comprehensive cardiovascular risk assessment and mitigation. Further research is required to understand the mechanisms and develop specific interventions for this group.

In September 2023 the Food and Drug Administration (FDA) approved an updated mRNA COVID-19 vaccine targeting the XBB.1.5 sublineage. This study evaluates the effectiveness of mRNA-1273.815, a 2023-2024 Omicron XBB.1.5-containing mRNA COVID-19 vaccine in preventing COVID-19-related hospitalizations and medically attended COVID-19 in US adults aged ≥ 18 years.

This observational, matched cohort study used medical and pharmacy claims data from HealthVerity. Adults vaccinated with mRNA-1273.815 between September 12, 2023, and December 31, 2023, were followed through January 26, 2024. Vaccinated individuals were matched with individuals unvaccinated with any 2023-2024 COVID-19 vaccine on demographic and clinical characteristics. The primary and secondary outcomes were COVID-19 hospitalization and medically attended COVID-19, respectively. Inverse probability of treatment weighting and Cox proportional hazards regression were utilized to estimate vaccine effectiveness (VE).

The study included 1,272,161 vaccinated individuals matched 1:1 with unvaccinated individuals, with a maximum follow-up of 128 (median 84) days. The VE against COVID-19 hospitalization was 51% (95% confidence interval [CI]: 48-54%). Subgroup analyses showed a VE of 56% (95% CI 51-61%) among adults ≥ 65 years and 46% (95% CI 39-52%) in immunocompromised adults. For medically attended COVID-19, the VE was 25% (95% CI 24-27%). Time-varying analyses showed that while VE declined over time, VE remained significant.

During the 2023-2024 respiratory season, the mRNA-1273.815 vaccine significantly protected against COVID-19-related hospitalizations and medically attended COVID-19 across diverse adult populations and demonstrated durability of the effect. These results support the continued use of updated COVID-19 vaccines to mitigate severe outcomes and maintain public health safety.

To compare the effectiveness and safety of budesonide-glycopyrrolate-formoterol, a twice daily metered dose inhaler, and fluticasone-umeclidinium-vilanterol, a once daily dry powder inhaler, in patients with chronic obstructive pulmonary disease (COPD) treated in routine clinical practice.

New user cohort study.

Longitudinal commercial US claims data.

New initiators of budesonide-glycopyrrolate-formoterol or fluticasone-umeclidinium-vilanterol between 1 January 2021 and 30 September 2023 who had a diagnosis of COPD and were aged 40 years or older.

In this 1:1 propensity score matched study, the main outcome measures were first moderate or severe COPD exacerbation (effectiveness) and first admission to hospital with pneumonia (safety) while on treatment. Potential confounders were measured in the 365 days before cohort entry and included in propensity scores. Hazard ratios and 95% confidence intervals (CIs) were estimated using a Cox proportional hazards regression model.

The study cohort included 20 388 propensity score matched pairs of new users initiating single inhaler triple therapy. Patients who received budesonide-glycopyrrolate-formoterol had a 9% higher incidence of first moderate or severe COPD exacerbation (hazard ratio 1.09 (95% CI 1.04 to 1.14); number needed to harm 38) compared with patients receiving fluticasone-umeclidinium-vilanterol and an identical incidence of first admission to hospital with pneumonia (1.00 (0.91 to 1.10)). The hazard of first moderate COPD exacerbation was 7% higher (1.07 (1.02 to 1.12); number needed to harm 54) and the hazard of first severe COPD exacerbation 29% higher (1.29 (1.12 to 1.48); number needed to harm 97) among those receiving budesonide-glycopyrrolate-formoterol compared to fluticasone-umeclidinium-vilanterol. Prespecified sensitivity analyses yielded similar findings to the primary analysis.

Budesonide-glycopyrrolate-formoterol was not associated with improved clinical outcomes compared with fluticasone-umeclidinium-vilanterol. Given the added climate impact of metered dose inhalers, health systems seeking to decrease use of these products may consider steps to promote further prescribing of fluticasone-umeclidinium-vilanterol compared with budesonide-glycopyrrolate-formoterol in people with COPD.

Center for Open Science Real World Evidence Registry (https://osf.io/6gdyp/).

Unmeasured confounding is often raised as a source of potential bias during the design of nonrandomized studies, but quantifying such concerns is challenging. We developed a simulation-based approach to assess the potential impact of unmeasured confounding during the study design stage. The approach involved generation of hypothetical individual-level cohorts using realistic parameters, including a binary treatment (prevalence 25%), a time-to-event outcome (incidence 5%), 13 measured covariates, a binary unmeasured confounder (u1; 10%), and a binary measured "proxy" variable (p1) correlated with u1. Strengths of unmeasured confounding and correlations between u1 and p1 were varied in simulation scenarios. Treatment effects were estimated with (1) no adjustment, (2) adjustment for measured confounders (level 1), and (3) adjustment for measured confounders and their proxy (level 2). We computed absolute standardized mean differences in u1 and p1 and relative bias with each level of adjustment. Across all scenarios, level 2 adjustment led to improvement in the balance of u1, but this improvement was highly dependent on the correlation between u1 and p1. Level 2 adjustments also had lower relative bias than level 1 adjustments (in strong u1 scenarios: relative bias of 9.2%, 12.2%, and 13.5% at correlations of 0.7, 0.5, and 0.3, respectively, vs 16.4%, 15.8%, and 15.0% for level 1). An approach using simulated individual-level data is useful to explicitly convey the potential for bias due to unmeasured confounding while designing nonrandomized studies, and can be helpful in informing design choices. This article is part of a Special Collection on Pharmacoepidemiology.

Rationale: Although recent evidence suggested that glucagon-like peptide 1 receptor agonists (GLP1RAs) might reduce the risk of asthma exacerbations, it remains unclear which subpopulations might derive the most benefit from GLP1RA treatment. Objectives: To identify characteristics of patients with asthma that predict who might benefit the most from GLP1RA treatment using real-world data. Methods: We implemented an active-comparator, new-user design analysis using commercially ensured patients 18-65 years of age from MarketScan data for 2007-2019 and identified two cohorts: GLP1RAs versus thiazolidinediones and GLP1RAs versus sulfonylureas. The outcome was acute exacerbation of asthma (hospital admission or emergency department visit for asthma) within 180 days after initiation. We applied iterative causal forest, a novel causal machine learning subgrouping algorithm, to assess heterogeneous treatment effects. In identified subgroups, we predicted propensity score, conducted propensity score trimming, and then estimated adjusted risk differences for the effect of GLP1RAs relative to comparators on asthma exacerbation using inverse probability treatment weighting in the propensity score-trimmed subpopulation. Results: Among 10,989 patients initiating GLP1RAs or thiazolidinediones and 17,088 patients initiating GLP1RAs versus sulfonylurea, GLP1RA initiators had fewer exacerbations, with adjusted risk differences of -0.5% (95% confidence interval [CI], -1.1% to 0.1%) and -1.6% (95% CI, -2.2% to -1.1%), respectively. In the GLP1RA versus sulfonylurea cohort, in which we observed a beneficial effect, our iterative causal forest analysis identified five subgroups with different treatment effects, defined by the number of emergency department visits, the number of prescriptions for short-acting β2-agonists, the number of prescriptions for inhaled steroids and long-acting β-agonists (either combination therapy or concurrent use), and age ≥ 50 years. Among these, patients with two or more emergency department visits during the 12-month baseline period had the largest absolute exacerbation risk reduction, with a decrease of 2.8% for GLP1RAs (95% CI, -4.8% to -0.9%). Conclusions: GLP1RAs demonstrated a beneficial effect on reducing asthma exacerbation relative to sulfonylureas. Patients with asthma with two or more emergency department visits (a proxy for disease severity) benefit most from GLP1RAs. Emergency department visit frequency, the number of maintenance and reliever inhalers, and age might help individualize prediction of the short-term benefit of GLP1RAs on asthma exacerbation.

This study used real-world observational data to compare profiles of patients receiving different first-line treatment for hormone receptor positive (ER+), HER2 negative, metastatic breast cancer (MBC): CDK4/6 inhibitors (CDK4/6i) in combination with endocrine therapy (ET) versus ET alone.

From a nationwide electronic health record-derived Flatiron Health de-identified database including 280 US cancer clinics, we identified patients with hormone receptor positive, HER2 negative, metastatic breast cancer receiving 1st -line therapy with ET alone or CDK4/6i plus ET between February 2015 and November 2021. Patient sociodemographic status, MBC treatment regimen and outcomes were the focus of this analysis. Patient characteristics were compared using t-tests and chi-square tests. Logistic regression analysis was performed to examine the association of patient characteristics with the likelihood of receiving 1st -line CDK4/6i plus ET vs. ET alone. Kaplan-Meier method and Cox proportional hazards were used to test the impact of 1st -line treatment regimen on real-world progression-free survival (PFS) and overall survival (OS). Baseline characteristics were balanced using inverse probability weighting (IPW).

The study population included 3,917 patients receiving CDK4/6i plus ET (n = 2170) and ET alone (n = 1747) for their MBC. Compared to patients receiving ET alone, those receiving CDK4/6i plus ET were younger (mean age 66.8 vs. 68.6, p < 0.001), more likely to present with de novo MBC (p < 0.001), had better performance status (50.2% vs. 40.5% patients with ECOG value 0, p = 0.001) and lower number of comorbidities (29.7% vs. 26.6% ≥ 1 comorbidity, p < 0.001). Logistic regression revealed increased odds of CDK4/6i plus ET in individuals aged 50-64 (OR: 3.42, 95% CI [2.41, 4.86]) and 65-74 (OR: 3.18, 95% CI [1.68, 6.02]) versus those aged 18-49 years of age. Black individuals had lower odds of CDK4/6i plus ET (OR: 0.76, 95% CI [0.58, 1.00]) compared to White individuals. Other characteristics associated with lower odds of CDK4/6i plus ET included patients with stage III disease (OR: 0.69, 95% CI [0.52, 0.92]), lower performance status (OR: 0.50, 95% CI [0.40, 0.62]), and Medicare insurance (OR: 0.73, 95% CI [0.30, 1.78]) compared to those with commercial and Medicaid insurance. After IPW adjustment, use of CDK4/6i plus ET as 1st -line treatment was associated with significantly longer median PFS compared to ET alone (27 vs. 17 months; hazard ratio [HR] = 0.61, p < 0.001). Median OS was 52 months in the CDK4/6i plus ET group and was 42 months with ET alone (HR = 0.74, p < 0.001).

In this real-world database, disparities in receiving 1st -line CDK4/6 inhibitors were seen by age, diagnosis stage, baseline performance status, comorbidity, and insurance status. In adjusted analysis, the use of 1st -line CDK4/6i plus ET yielded better PFS and OS rates than ET alone. Further efforts are essential to enhance equitable use of and access to this crucial drug class.

Non-alcoholic fatty liver diseases (NAFLDs)/non-alcoholic steatohepatitis (NASH) are the most common liver disorders among patients with type 2 diabetes. Newer classes of glucose-lowering agents (GLAs), such as glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose cotransporter 2 inhibitors (SGLT2is), have been shown to improve liver-related biomarkers. However, their effects on the development of NAFLD/NASH remain inconclusive.

A nested case-control study was conducted using Taiwan's National Health Insurance Research Database for 2011-2018. Patients aged ≥ 40 years, diagnosed with type 2 diabetes, having stable non-insulin GLA use, and without NAFLD/NASH history were included. Patients with incident NAFLD/NASH were matched up to 10 randomly sampled controls based on individual's age, gender, cohort entry date, type 2 diabetes diagnosis date, and disease risk score. Conditional logistic regression analyses were employed to estimate the association between liver risk and treatment exposure. Dose-response analysis was also performed.

There were 621,438 study patients included for analysis. During 1.8 years of median follow-up, the incidence of NAFLD/NASH was 2.7 per 1000 person-years. After matching, 5,730 incident NAFLD cases (mean age: 57.6 years, male: 53.2%) and 45,070 controls (57.7 years, 52.7%) were identified. Using GLP-1RAs or SGLT2is was associated with an insignificantly lower NAFLD/NASH risk (i.e., odds ratios [95% CIs]: 0.84 [0.46-1.52] and 0.85 [0.63-1.14], respectively) and increased cumulative SGLT2i doses were significantly associated with a reduced NAFLD/NASH risk (0.61 [0.38-0.97]).

GLP-1RA and SGLT2i therapies in type 2 diabetes patients might prevent NAFLD/NASH development, with a significantly lower risk related to greater treatment exposure.

Non-randomized studies on bariatric surgery have reported large reductions in mortality within 6-12 months after surgery compared with non-surgical patients. It is unclear whether these findings are the result of bias.

We searched PubMed to identify all non-randomized studies investigating the effect of bariatric surgery on all-cause mortality compared with non-surgical patients. We assessed these studies for potential confounding and time-related biases. We conducted bias analyses to quantify the effect of these biases.

We identified 21 cohort studies that met our inclusion criteria. Among those, 11 were affected by immortal time bias resulting from the misclassification or exclusion of relevant follow-up time. Five studies were subject to potential confounding bias because of a lack of adjustment for body mass index (BMI). All studies used an inadequate comparator group that lacked indications for bariatric surgery. Bias analyses to correct for potential confounding from BMI shifted the effect estimates towards the null [reported hazard ratio (HR): 0.78 vs. bias-adjusted HR: 0.92]. Bias analyses to correct for the presence of immortal time also shifted the effect estimates towards the null (adjustment for 2-year wait time: reported HR: 0.57 vs. bias-adjusted HR: 0.81).

Several important sources of bias were identified in non-randomized studies of the effectiveness of bariatric surgery versus non-surgical comparators on mortality. Future studies should ensure that confounding by BMI is accounted for, considering the choice of the comparator group, and that the design or analysis avoids immortal time bias from the misclassification or exclusion.

Pharmacoepidemiological studies provide important information on the safety and effectiveness of medications, but the validity of study findings can be threatened by residual bias. Ideally, biases would be minimized through appropriate study design and statistical analysis methods. However, residual biases can remain, for example, due to unmeasured confounders, measurement error, or selection into the study. A group of sensitivity analysis methods, termed quantitative bias analyses, are available to assess, quantitatively and transparently, the robustness of study results to these residual biases. These approaches include methods to quantify how the estimated effect would be altered under specified assumptions about the potential bias, and methods to calculate bounds on effect estimates. This article introduces quantitative bias analyses for unmeasured confounding, misclassification, and selection bias, with a focus on their relevance and application to pharmacoepidemiological studies.

The inability to correctly account for unmeasured confounding can lead to bias in parameter estimates, invalid uncertainty assessments, and erroneous conclusions. Sensitivity analysis is an approach to investigate the impact of unmeasured confounding in observational studies. However, the adoption of this approach has been slow given the lack of accessible software. An extensive review of available R packages to account for unmeasured confounding list deterministic sensitivity analysis methods, but no R packages were listed for probabilistic sensitivity analysis. The R package unmconf implements the first available package for probabilistic sensitivity analysis through a Bayesian unmeasured confounding model. The package allows for normal, binary, Poisson, or gamma responses, accounting for one or two unmeasured confounders from the normal or binomial distribution. The goal of unmconf is to implement a user friendly package that performs Bayesian modeling in the presence of unmeasured confounders, with simple commands on the front end while performing more intensive computation on the back end. We investigate the applicability of this package through novel simulation studies. The results indicate that credible intervals will have near nominal coverage probability and smaller bias when modeling the unmeasured confounder(s) for varying levels of internal/external validation data across various combinations of response-unmeasured confounder distributional families.

The conditions required for health record data sources to accurately assess treatment effectiveness remain unclear. Emulation of randomized clinical trials (RCTs) with health record data and subsequent calibration of the results can help elucidate this.

To pilot an emulation of the KEYNOTE-189 RCT using a commercially available electronic health record (EHR) data source.

This retrospective cohort study used an EHR database spanning from April 2007 to February 2023. Follow-up began on treatment initiation and proceeded until an outcome event, loss to follow-up, end of data, or end of study period (640 days). The population-based cohort was ascertained from EHRs provided by 52 health systems across the US. Eligibility criteria were defined as closely as possible to the benchmark RCT. Patients with non-small cell lung cancer initiating first-line treatment for metastatic disease were included. Patients with evidence of squamous non-small cell lung cancer, primary nonlung malignant neoplasms, or identified EGFR/ALK variations were excluded. Data were analyzed from June to October 2023.

Initiation of first-line pembrolizumab and chemotherapy and chemotherapy alone. Chemotherapy in both groups was defined as a combination of pemetrexed and platinum-based (carboplatin or cisplatin) therapy.

Outcomes of interest were 12-month survival probability and mortality hazard ratio (HR).

A total of 1854 patients (mean [SD] age, 63.7 [9.6] years; 971 [52.4%] men) were eligible, including 589 patients who initiated pembrolizumab and chemotherapy and 1265 patients who initiated chemotherapy only. The cohort included 364 Black patients (19.6%) and 1445 White patients (77.9%). The 12-month survival probabilities were 0.60 (95% CI, 0.54-0.65) in the pembrolizumab group and 0.58 (95% CI, 0.55-0.62) in the chemotherapy-only group, compared with 0.69 (95% CI, 0.64-0.74) in the KEYNOTE-189 pembrolizumab group and 0.49 (95% CI, 0.42-0.56) in the KEYNOTE-189 chemotherapy-only group. The mortality HR was 0.95 (95% CI, 0.78-1.16), compared with 0.49 (95% CI, 0.38-0.64) in the KEYNOTE-189 RCT.

In this cohort study piloting an RCT emulation, results were incongruous with the benchmark trial. Differences in patient treatment and data capture between the RCT and EHR populations, confounding by indication, treatment crossover, and accuracy of captured diagnoses may explain these findings. Future feasibility assessments will require data sources to have important oncology-specific measures curated.

There is insufficient evidence that angiotensin-converting enzyme inhibitors (ACEIs) can reduce pneumonia by inducing a dry cough that confers a protective effect on the airway. To increase the evidence base on the clinical use of ACEIs for pneumonia prevention, this retrospective cohort study aimed to comparatively examine the risk of pneumonia-related hospitalization between ACEI initiators and angiotensin II receptor blocker (ARB) initiators using claims data from two Japanese municipalities. We identified persons who were newly prescribed any ACEI or ARB as their first antihypertensive agent between April 2016 and March 2020. The Fine-Gray method was applied to a Cox proportional hazards model to estimate the subdistribution hazard ratio (HR) of ACEI use (reference: ARB use) for pneumonia-related hospitalization, with death treated as a competing risk. Sex, age, comorbidities, medications, and pneumococcal immunization were included as covariates. The analysis was conducted on 1421 ACEI initiators and 9040 ARB initiators, and the adjusted subdistribution HR of ACEI use was estimated to be 1.21 (95% confidence interval: 0.89-1.65; P = 0.22). ACEI initiation did not demonstrate any significant preventive effect against pneumonia-related hospitalization relative to ARB initiation. There remains a lack of strong evidence on the protective effects of ACEIs, and further research is needed to ascertain the benefits of their use in preventing pneumonia. We conducted a large-scale retrospective cohort study using real-world healthcare data from a Japanese population. In this study, ACEI initiation did not indicate a significant preventive effect against pneumonia-related hospitalization.

It is unclear whether renal transplant recipients treated with mycophenolic acid (MPA) who carry the reduced-function allele at polymorphism SLCO1B1 c.521T>C differ from their wild-type peers regarding renal outcomes and tolerability. We aimed to estimate the effect of this polymorphism on the graft function (estimated glomerular filtration rate, eGFR) over the first 12 post-transplant months in patients on MPA-based maintenance immunosuppression.

In a 12-month observational cohort study, consecutive adult patients were repeatedly assessed for eGFR. The SLCO1B1 c.521C>T variant allele carriers (exposed) and wild-type subjects (controls) were balanced on a range of demographic, medical, and genetic variables at baseline, and eGFR trajectory was estimated with further adjustment for time-varying covariates. A subset of patients were assessed for exposure to MPA 5-7 days after the transplantation.

The adjusted eGFR slopes from day 1 to day 28 (daily), and from day 28 to day 365 (monthly) were practically identical in exposed (n = 86) and control (n = 168) patients [geometric means ratios (GMR) = 0.99, 95% confidence interval (CI) = 0.92-1.06 and GMR = 0.98, 0.94-1.01, respectively]. The rates of adverse renal outcomes and possible MPA-related adverse effects were low, and similar in exposed and controls [rate ratios (RR) = 0.94, 0.49-1.84 and RR = 1.08, 0.74-1.58, respectively]. The pharmacokinetic analysis did not signal meaningful differences regarding exposure to MPA, overall (exposed n = 23, control n = 45), if cotreated with cyclosporine (n = 17 vs. n = 26) or with tacrolimus (n = 8 vs. n = 17).

In patients treated with MPA, variant allele SLCO1B1 c.521T>C appears of no practical relevance regarding the 12-month renal graft function, MPA safety and exposure to MPA at early steady-state.

Multimorbidity is common in hospitalised adults who are at increased risk of inappropriate prescribing including drug-disease interactions. These interactions occur when a medicine being used to treat one condition exacerbates a concurrent medical condition and may lead to adverse health outcomes. The aim of this review was to examine the association between drug-disease interactions and the risk of mortality and readmission in hospitalised middle-aged and older adults.

A systematic review was conducted on drug-disease interactions in hospitalised middle-aged (45-64 years) and older adults (≥65 years). The study protocol was prospectively registered with PROSPERO (Registration Number: CRD42022341998). Drug-disease interactions were defined as a medicine being used to treat one condition with the potential to exacerbate a concurrent medical condition or that were inappropriate based on a comorbid medical condition. Both observational and interventional studies were included. The outcomes of interest were mortality and readmissions. The databases searched included MEDLINE, CINAHL, EMBASE, Web of Science, SCOPUS and the Cochrane Library from inception to 12 July, 2022. A meta-analysis was performed to pool risk estimates using the random-effects model.

A total of 563 studies were identified and four met the inclusion criteria. All were observational studies in older adults, with no studies identified in middle-aged adults. Most of the studies were at risk of bias because of an inadequate adjustment for covariates and a lack of clarity around individuals lost to follow-up. There were various definitions of drug-disease interactions within these four studies. Two studies assessed drugs that were contraindicated based on renal function, one assessed an individual drug-disease combination, and one was based on the clinical judgement of a pharmacist. There were two studies that showed an association between drug-disease interactions and the outcomes of interest. One reported that the use of diltiazem in patients with heart failure was associated with an increased risk of readmissions. The second reported that the use of medicines contraindicated according to renal function were associated with increased risk of all-cause mortality and a composite of mortality and readmission. Three of the studies (total study population = 5705) were amenable to a meta-analysis, which showed no significant association between drug-disease interactions and readmissions (odds ratio = 1.0, 95% confidence interval 0.80-1.38).

Few studies were identified examining the risk of drug-disease interactions and mortality and readmission in hospitalised adults. Most of the identified studies were at risk of bias. There is no universal accepted definition of drug-disease interactions in the literature. Further studies are needed to develop a standardised and accepted definition of these interactions to guide further research in this area.

Disease latency is defined as the time from disease initiation to disease diagnosis. Disease latency bias (DLB) can arise in epidemiological studies that examine latent outcomes, since the exact timing of the disease inception is unknown and might occur before exposure initiation, potentially leading to bias. Although DLB can affect epidemiological studies that examine different types of chronic disease (e.g. Alzheimer's disease, cancer etc), the manner by which DLB can introduce bias into these studies has not been previously elucidated. Information on the specific types of bias, and their structure, that can arise secondary to DLB is critical for researchers, to enable better understanding and control for DLB.

Here we describe four scenarios by which DLB can introduce bias (through different structures) into epidemiological studies that address latent outcomes, using directed acyclic graphs (DAGs). We also discuss potential strategies to better understand, examine and control for DLB in these studies.

Using causal diagrams, we show that disease latency bias can affect results of epidemiological studies through: (i) unmeasured confounding; (ii) reverse causality; (iii) selection bias; (iv) bias through a mediator.

Disease latency bias is an important bias that can affect a number of epidemiological studies that address latent outcomes. Causal diagrams can assist researchers better identify and control for this bias.

Childhood-onset type 1 diabetes (T1D) is associated with substantial psychiatric morbidity in later life, but it remains unknown whether these associations are due to common underlying biological mechanisms or the impacts of living with the condition and its treatment. Here, using Czech national register data, we identified children with T1D aged ≤14 years between 1994 and 2007 and estimated the risk of psychiatric disorders up to 24 years later. We found that children diagnosed with T1D had an elevated risk of developing substance use, mood, anxiety and personality disorders, and behavioral syndromes. Conversely, we found that children with T1D had a lower risk of developing psychotic disorders. In Mendelian randomization analysis, we found an association with schizophrenia, which, however, did not persist following multiple testing adjustment. The combined observational and Mendelian randomization evidence suggests that T1D diagnosis in childhood predisposes to far-reaching, extensive psychiatric morbidity, which is unlikely to be explicable by common underlying biological mechanisms. The findings of this study highlight that monitoring and addressing the mental health needs of children with T1D is imperative, whereas glucose dysregulation and/or inflammation implicated in schizophrenia pathogenesis warrants future research.

The objective of this review is to summarize and appraise the research methodology, emerging findings, and future directions in pharmacoepidemiologic studies assessing the benefits and harms of pharmacotherapies in older adults with different levels of frailty. Older adults living with frailty are at elevated risk for poor health outcomes and adverse effects from pharmacotherapy. However, current evidence is limited due to the under-enrollment of frail older adults and the lack of validated frailty assessments in clinical trials. Recent advancements in measuring frailty in administrative claims and electronic health records (database-derived frailty scores) have enabled researchers to identify patients with frailty and to evaluate the heterogeneity of treatment effects by patients' frailty levels using routine health care data. When selecting a database-derived frailty score, researchers must consider the type of data (e.g., different coding systems), the length of the predictor assessment period, the extent of validation against clinically validated frailty measures, and the possibility of surveillance bias arising from unequal access to care. We reviewed 13 pharmacoepidemiologic studies published on PubMed from 2013 to 2023 that evaluated the benefits and harms of cardiovascular medications, diabetes medications, anti-neoplastic agents, antipsychotic medications, and vaccines by frailty levels. These studies suggest that, while greater frailty is positively associated with adverse treatment outcomes, older adults with frailty can still benefit from pharmacotherapy. Therefore, we recommend routine frailty subgroup analyses in pharmacoepidemiologic studies. Despite data and design limitations, the findings from such studies may be informative to tailor pharmacotherapy for older adults across the frailty spectrum.

Limited evidence exists on the comparative safety and effectiveness of empagliflozin against alternative glucose-lowering medications in individuals with type 2 diabetes with the broad spectrum of cardiovascular risk. The EMPagliflozin compaRative effectIveness and SafEty (EMPRISE) cohort study was designed to monitor the safety and effectiveness of empagliflozin periodically for a period of 5 years with data collection from electronic healthcare databases.

We identified individuals ≥18 years old with type 2 diabetes who initiated empagliflozin or dipeptidyl peptidase-4 inhibitors (DPP-4i) from 2014 to 2019 using US Medicare and commercial claims databases. After 1:1 propensity score matching using 143 baseline characteristics, we identified four a priori-defined effectiveness outcomes: (1) myocardial infarction (MI) or stroke; (2) hospitalisation for heart failure (HHF); (3) major adverse cardiovascular events (MACE); and (4) cardiovascular mortality or HHF. Safety outcomes included lower-limb amputations, non-vertebral fractures, diabetic ketoacidosis (DKA), acute kidney injury (AKI), severe hypoglycaemia, retinopathy progression, and short-term kidney and bladder cancers. We estimated HRs and rate differences (RDs) per 1000 person-years, overall and stratified by age, sex, baseline atherosclerotic cardiovascular disease (ASCVD) and heart failure.

We identified 115,116 matched pairs. Compared with DPP-4i, empagliflozin was associated with lower risks of MI/stroke (HR 0.88 [95% CI 0.81, 0.96]; RD -2.08 [95% CI (-3.26, -0.90]), HHF (HR 0.50 [0.44, 0.56]; RD -5.35 [-6.22, -4.49]), MACE (HR 0.73 [0.62, 0.86]; RD -6.37 [-8.98, -3.77]) and cardiovascular mortality/HHF (HR 0.57 [0.47, 0.69]; RD -10.36 [-12.63, -8.12]). Absolute benefits were larger in older individuals and in those with ASCVD/heart failure. Empagliflozin was associated with an increased risk of DKA (HR 1.78 [1.44, 2.19]; RD 1.59 [1.08, 2.09]); decreased risks of AKI (HR 0.62 [0.54, 0.72]; RD -2.39 [-3.08, -1.71]), hypoglycaemia (HR 0.75 [0.67, 0.84]; RD -2.46 [-3.32, -1.60]) and retinopathy progression (HR 0.78 [0.63, 0.96)]; RD -9.49 [-16.97, -2.10]); and similar risks of other safety events.

Empagliflozin relative to DPP-4i was associated with risk reductions of MI or stroke, HHF, MACE and the composite of cardiovascular mortality or HHF. Absolute risk reductions were larger in older individuals and in those who had history of ASCVD or heart failure. Regarding the safety outcomes, empagliflozin was associated with an increased risk of DKA and lower risks of AKI, hypoglycaemia and progression to proliferative retinopathy, with no difference in the short-term risks of lower-extremity amputation, non-vertebral fractures, kidney and renal pelvis cancer, and bladder cancer.

Takotsubo syndrome (TS) is a heart condition mimicking acute myocardial infarction. TS is characterized by a sudden weakening of the heart muscle, usually triggered by physical or emotional stress. In this study, we aimed to investigate the effect of pharmacological interventions on short- and long-term mortality in patients with TS.

We analysed data from the SWEDEHEART (the Swedish Web System for Enhancement and Development of Evidence-based care in Heart disease Evaluated According to Recommended Therapies) registry, which included patients who underwent coronary angiography between 2009 and 2016. In total, we identified 1724 patients with TS among 228 263 individuals in the registry. The average age was 66 ± 14 years, and 77% were female. Nearly half of the TS patients (49.4%) presented with non-ST-elevation acute coronary syndrome, and a quarter (25.9%) presented with ST-elevation myocardial infarction. Most patients (79.1%) had non-obstructive coronary artery disease on angiography, while 11.7% had a single-vessel disease and 9.2% had a multivessel disease. All patients received at least one pharmacological intervention; most of them used beta-blockers (77.8% orally and 8.3% intravenously) or antiplatelet agents [aspirin (66.7%) and P2Y12 inhibitors (43.6%)]. According to the Kaplan-Meier estimator, the probability of all-cause mortality was 2.5% after 30 days and 16.6% after 6 years. The median follow-up time was 877 days. Intravenous use of inotropes and diuretics was associated with increased 30 day mortality in TS [hazard ratio (HR) = 9.92 (P < 0.001) and HR = 3.22 (P = 0.001), respectively], while angiotensin-converting enzyme inhibitors and statins were associated with decreased long-term mortality [HR = 0.60 (P = 0.025) and HR = 0.62 (P = 0.040), respectively]. Unfractionated and low-molecular-weight heparins were associated with reduced 30 day mortality [HR = 0.63 (P = 0.01)]. Angiotensin receptor blockers, oral anticoagulants, P2Y12 antagonists, aspirin, and beta-blockers did not statistically correlate with mortality.

Our findings suggest that some medications commonly used to treat TS are associated with higher mortality, while others have lower mortality. These results could inform clinical decision-making and improve patient outcomes in TS. Further research is warranted to validate these findings and to identify optimal pharmacological interventions for patients with TS.

Lifestyles are associated with all-cause mortality, yet limited research has explored the association in the elderly population with multimorbidity. We aim to investigate the impact of adopting a healthy lifestyle on reducing the risk of all-cause mortality in older individuals with or without multimorbidity in both China and UK. This prospective study included 29,451 and 173,503 older adults aged 60 and over from Chinese Longitudinal Healthy Longevity Survey (CLHLS) and UK Biobank. Lifestyles and multimorbidity were categorized into three groups, respectively. Cox proportional hazards regression was used to estimate the Hazard Ratios (HRs), 95% confidence intervals (95% CIs), and dose-response for all-cause mortality in relation to lifestyles and multimorbidity, as well as the combination of both factors. During a mean follow-up period of 4.7 years in CLHLS and 12.14 years in UK Biobank, we observed 21,540 and 20,720 deaths, respectively. For participants with two or more conditions, compared to those with an unhealthy lifestyle, adopting a healthy lifestyle was associated with a 27%-41% and 22%-42% reduction in mortality risk in the CLHLS and UK Biobank, respectively; Similarly, for individuals without multimorbidity, this reduction ranged from 18% to 41%. Among participants with multimorbidity, individuals with an unhealthy lifestyle had a higher mortality risk compared to those maintaining a healthy lifestyle, with HRs of 1.15 (95% CI: 1.00, 1.32) and 1.27 (95% CI: 1.16, 1.39) for two conditions, and 1.24 (95% CI: 1.06, 1.45) and 1.73 (95% CI: 1.56, 1.91) for three or more conditions in CLHLS and UK Biobank, respectively. Adherence to a healthy lifestyle can yield comparable mortality benefits for older individuals, regardless of their multimorbidity status. Furthermore, maintaining a healthy lifestyle can alleviate the mortality risks linked to a higher number of diseases.

Variant allele at the inosine monophosphate dehydrogenase type 2 polymorphism IMPDH2 3757T>C has been associated with increased enzyme activity and reduced susceptibility to mycophenolic acid (MPA) in vitro. It has been suggested associated with an increased risk of acute rejection in renal transplant recipients on MPA-based immunosuppression, but not unambiguously. We assessed one-year evolution of the estimated glomerular filtration rate (eGFR) in transplanted variant allele carriers and wild-type subjects, while controlling for a number of demographic, pharmacogenetic, (co)morbidity, and treatment baseline and time-varying covariates. The eGFR slopes to day 28 (GMR = 1.01, 95% CI 0.93-1.09), and between days 28 and 365 (GMR = 1.01, 95% CI 0.99-1.02) were practically identical in 52 variant carriers and 202 wild-type controls. The estimates (95%CIs) remained within the limits of ±20% difference even after adjustment for a strong hypothetical effect of unmeasured confounders. Polymorphism IMPDH2 3757T>C does not affect the renal graft function over the 1st year after transplantation.