A marginal structural model for normal tissue complication probability.

The goal of radiation therapy for cancer is to deliver prescribed radiation dose to the tumor while minimizing dose to the surrounding healthy tissues. To evaluate treatment plans, the dose distribution to healthy organs is commonly summarized as dose-volume histograms (DVHs). Normal tissue complication probability (NTCP) modeling has centered around making patient-level risk predictions with features extracted from the DVHs, but few have considered adapting a causal framework to evaluate the safety of alternative treatment plans. We propose causal estimands for NTCP based on deterministic and stochastic interventions, as well as propose estimators based on marginal structural models that impose bivariable monotonicity between dose, volume, and toxicity risk. The properties of these estimators are studied through simulations, and their use is illustrated in the context of radiotherapy treatment of anal canal cancer patients.

Molecular insights into the activation of Mre11-Rad50 endonuclease activity by Sae2/CtIP.

In Saccharomyces cerevisiae (S. cerevisiae), Mre11-Rad50-Xrs2 (MRX)-Sae2 nuclease activity is required for the resection of DNA breaks with secondary structures or protein blocks, while in humans, the MRE11-RAD50-NBS1 (MRN) homolog with CtIP is needed to initiate DNA end resection of all breaks. Phosphorylated Sae2/CtIP stimulates the endonuclease activity of MRX/N. Structural insights into the activation of the Mre11 nuclease are available only for organisms lacking Sae2/CtIP, so little is known about how Sae2/CtIP activates the nuclease ensemble. Here, we uncover the mechanism of Mre11 activation by Sae2 using a combination of AlphaFold2 structural modeling of biochemical and genetic assays. We show that Sae2 stabilizes the Mre11 nuclease in a conformation poised to cleave substrate DNA. Several designs of compensatory mutations establish how Sae2 activates MRX in vitro and in vivo, supporting the structural model. Finally, our study uncovers how human CtIP, despite considerable sequence divergence, employs a similar mechanism to activate MRN.

Evaluating the Effectiveness of Systemic Heparin During Arteriovenous Fistula Creation by Emulating a Target Trial.

Most of the 800,000 people living with end-stage kidney disease in the United States rely on a functioning vascular access to provide life-sustaining hemodialysis, yet one-third of arteriovenous fistulas experience early failures. Determining the safety and effectiveness of systemic heparin during fistula creation could improve the quality and quantity of life for these vulnerable patients. In this paper, a pragmatic randomized trial was emulated to assess the effect of systemic heparin administration (vs. none) during radiocephalic arteriovenous fistula creation on early bleeding and thrombosis using data from two international multicenter randomized trials performed between 2014 and 2019. Marginal risks were estimated using inverse probability weighted parametric survival analysis and confidence intervals were generated with bootstrapping. A total of 914 patients were enrolled and 61% received systemic heparin; median (IQR) age was 58 (49, 67) years and 45% were on hemodialysis at enrollment. No difference in the risk of bleeding events was observed, with a risk difference (95% CI) at 14 days of -0.1% (-1.6, 1.4). The risk of access thrombosis was lower in the heparin group, with a risk of 3.7% (2.6, 4.8) after heparin and 5.3% (3.4, 7.4) without heparin at 14 days (risk ratio 0.72, 95% CI 0.50, 0.98).

A Study of the Developmental Mechanisms of Inter-Team Conflict Processes Within Multi-Team Systems - An Exploratory Analysis Based on a Collaborative R&D Context.

Purpose: The analysis of the pivotal determinants that impact the progression of inter-team conflict processes in multi-team systems, as well as their underlying mechanisms, serves to explicate the developmental framework of said conflict processes. Methodology: This study adopts a vantage point centered on the evolution of inter-team conflict in multi-team systems, with a specific focus on the sequential progression including "conflict latency → conflict perception → conflict management → conflict outcome → conflict feedback. Results: By transmuting qualitative data into quantitative data through the discernment of inter-conceptual relationships' directionality and quantity, this study distills the key chain of relationships between categories. Employing the explanatory structure model, the developmental mechanism of inter-team conflict processes in multi-team systems is unveiled. Notable sources of conflict include team goal identification, team role multiplicity, inter-team relationships, and team competence. Factors that exert a significant influence on conflict management comprise inter-team conflict types, inter-team relationships, team competence, inter-team heterogeneity, team affiliation, and system goals. Reviewing the genuine motivations underlying conflict management behavior, as well as adopting a lengthier temporal perspective, emerges as a crucial consideration when analyzing the implications of conflict management on both the system and the team for evaluative purposes. Inter-team communication emerges as a pivotal influence on the efficacy of conflict management, which, in turn, is influenced by boundary managers, inter-team heterogeneity, and the inter-team interactive memory system. Conclusion: Through an in-depth analysis of the hierarchical interrelationships among factors that influence conflicts within teams, we have established a model for the conflict development process. This model is instrumental in comprehensively understanding the dynamics of conflict evolution within teams. It serves as a reference point for formulating more precise and effective conflict management strategies. Moreover, this model not only offers practical guidance for resolving conflicts within a multi-team framework but also enhances inter-team collaboration. Therefore, it contributes significantly to achieving the objectives of the multi-team system.

Time-Varying Proteinuria and Progression of IgA Nephropathy: A Cohort Study.

RATIONALE & OBJECTIVE: Proteinuria is a surrogate end point for predicting long-term kidney outcomes in IgA nephropathy (IgAN) with levels<1g/day identified as a therapeutic target. However, this threshold has not been sufficiently studied. We quantified the associations of progression of IgAN with various levels of proteinuria. STUDY DESIGN: Observational cohort study. SETTING & PARTICIPANTS: 1,530 patients with IgAN and at least 12 months of follow-up at Peking University First Hospital. EXPOSURE: Proteinuria levels updated over time (time-varying proteinuria, TVP). OUTCOME: A composite kidney outcome of a 50% reduction in the estimated glomerular filtration rate or end-stage kidney disease. ANALYTICAL APPROACH: Marginal structural models. RESULTS: After a median follow-up period of 43.5 (IQR, 27.2-72.8) months, 254 patients (16.6%) developed the composite kidney outcome. A graded association was observed between TVP and composite kidney outcomes with higher risk among those with proteinuria of≥0.5g/day. Compared with TVP<0.3g/day, the HRs for proteinuria levels of 0.3 to<0.5g/day, 0.5 to<1.0g/day, 1.0 to<2.0g/day, and≥2.0g/day were 2.22 (95% CI, 0.88-5.58), 4.04 (95% CI, 1.93-8.46), 8.46 (95% CI, 3.80-18.83), and 38.00 (95% CI, 17.62-81.95), respectively. The trend was more pronounced in patients with baseline proteinuria of≥1.0g/day, among whom a higher risk was observed with TVP of 0.3 to<0.5g/day compared with TVP<0.3g/day (HR, 3.26 [95% CI, 1.07-9.92], P=0.04). However, in patients with baseline proteinuria levels of<1g/day, the risk of composite kidney outcome only began to increase when TVP was≥1.0g/day (HR, 3.25 [95% CI, 1.06-9.90]). LIMITATIONS: Single-center observational study, selection bias, and unmeasured confounders. CONCLUSIONS: This study showed that patients with IgAN and proteinuria levels of>0.5g/day, have an elevated risk of kidney failure especially among patients with proteinuria levels≥1.0g/day before initiating treatment. These data may serve to inform the selection of proteinuria targets in the treatment of IgAN. PLAIN-LANGUAGE SUMMARY: The presence of proteinuria has often been considered a surrogate end point and a possible therapeutic target in clinical trials in IgA nephropathy (IgAN). Some guidelines recommend a reduction in proteinuria to<1g/day as a treatment goal based on the results of previous longitudinal studies. However, these findings may have been biased because they did not properly adjust for time-dependent confounders. Using marginal structural models to appropriately account for these confounding influences, we observed that patients with IgAN and proteinuria levels≥0.5g/day have an elevated risk of kidney failure, especially among patients who had proteinuria levels of≥1.0g/day before initiating treatment. These data may serve to inform the selection of proteinuria targets in the treatment of IgAN.

Statistical methods for assessing drug interactions using observational data.

With advances in medicine, many drugs and treatments become available. On the one hand, polydrug use (i.e. using more than one drug at a time) has been used to treat patients with multiple morbid conditions, and polydrug use may cause severe side effects. On the other hand, combination treatments have been successfully developed to treat severe diseases such as cancer and chronic diseases. Observational data, such as electronic health record data, may provide useful information for assessing drug interactions. In this article, we propose using marginal structural models to assess the average treatment effect and causal interaction of two drugs by controlling confounding variables. The causal effect and the interaction of two drugs are assessed using the weighted likelihood approach, with weights being the inverse probability of the treatment assigned. Simulation studies were conducted to examine the performance of the proposed method, which showed that the proposed method was able to estimate the causal parameters consistently. Case studies were conducted to examine the joint effect of metformin and glyburide use on reducing the hospital readmission for type 2 diabetic patients, and to examine the joint effect of antecedent statins and opioids use on the immune and inflammatory biomarkers for COVID-19 hospitalized patients.

On the Elusive Crystallography of Lithium-Rich Layered Oxides: Novel Structural Models.

Lithium-rich layered oxides (LRLOs) are one of the most attractive families among future positive electrode materials for the so-called fourth generation of lithium-ion batteries (LIBs). Their electrochemical performance is enabled by the unique ambiguous crystal structure that is still not well understood despite decades of research. In the literature, a clear structural model able to describe their crystallographic features is missing thereby hindering a clear rationalization of the interplay between synthesis, structure, and functional properties. Here, the structure of a specific LRLO, Li1.28 Mn0.54 Ni0.13 Co0.02 Al0.03 O2 , using synchrotron X-ray diffraction (XRD), neutron diffraction (ND), and High-Resolution Transmission Electron Microscopy (HR-TEM), is analyzed. A systematic approach is applied to model diffraction patterns of Li1.28 Mn0.54 Ni0.13 Co0.02 Al0.03 O2 by using the Rietveld refinement method considering the R 3 ¯ $\bar{3}$ m and C2/m unit cells as the prototype structures. Here, the relative ability of a variety of structural models is compared to match the experimental diffraction pattern evaluating the impact of defects and supercells derived from the R 3 ¯ $\bar{3}$ m structure. To summarize, two possible models able to reconcile the description of experimental data are proposed here for the structure of Li1.28 Mn0.54 Ni0.13 Co0.02 Al0.03 O2 : namely a monoclinic C2/m defective lattice (prototype Li2 MnO3 ) and a monoclinic defective supercell derived from the rhombohedral R 3 ¯ $\bar{3}$ m unit cell (prototype LiCoO2 ).

Effect of cytomegalovirus infection on post-transplant hospitalization days among children undergoing allogeneic hematopoietic cell transplantation: A marginal structural model approach.

BACKGROUND: Cytomegalovirus (CMV) commonly reactivates after allogeneic hematopoietic cell transplant (HCT), potentially leading to CMV disease and significant morbidity and mortality. To reduce morbidity and mortality, many centers conduct weekly CMV blood polymerase chain reaction (PCR) surveillance testing with subsequent initiation of antiviral therapy upon CMV DNAemia detection. However, the impact of CMV DNAemia on subsequent hospitalization risk has not been assessed using models accounting for the time-varying nature of the exposure, outcome, and confounders. METHODS: All allogeneic HCTs at the Children's Hospital of Philadelphia from January 2004-April 2017 were considered for inclusion. Patients were monitored with CMV surveillance via PCR testing for up to 105 days after HCT receipt. We estimated the association between CMV DNAemia and rate of hospitalization using marginal structural models (MSM). RESULTS: There were 343 allogeneic HCT episodes in 330 with CMV surveillance; median age was 9.0 (range: 0.1-26.2) and 46.5% were female. And 24.1% of HCT patients had at least one positive CMV blood PCR during the follow-up period. Median time to CMV DNAemia detection was 19 days (range: 4-97). The MSM estimated the incidence rate ratios for an association of CMV DNAemia with hospitalization to be 1.24, (95% confidence interval: 1.04-1.47). CONCLUSIONS: CMV DNAemia was associated with an increased hospitalization in the post-HCT period. The MSM accounted for time-varying nature of the outcome, exposure and confounders. The findings support prevention of CMV DNAemia in this population. We recommend further investigation into the effectiveness and safety of prophylaxis versus pre-emptive CMV prevention approaches.

Relation between metacognitive strategies, motivation to think, and critical thinking skills.

Critical thinking is a complex reasoning skill, and even though it is hard to reach a consensus on its definition, there is agreement on it being an eminently cognitive skill. It is strongly related with reflective and metacognitive skills, as well as attitudinal or motivational aspects, although no model has yet been able to integrate these three elements. We present herein the preliminary results of a study seeking to establish these relations, in a sample of Chilean university students. 435 students from three universities participated, of which 88 were men, 333 were women, and 14 did not indicate their gender. Their ages ranges between 18 and 51 years old (M = 21, SD = 3.09). Three instruments were applied, one to measure metacognitive strategies, one to measure motivation to critical thinking, and a third to measure critical thinking skills. The relation was analyzed via structural equations. The results show a positive, strong, and significant relation between metacognition and motivation to think. However, only a weak significant relation was observed between motivation to think and critical thinking, and no direct relation was found between metacognition and critical thinking. We hypothesize a significant but moderate relation between the variables, where metacognition influences motivation to think, which in turn influences critical thinking skills. Factors are discussed which could negatively affect the studied relations, as well as the importance of generating integrated models between the three variables, as they would show a theoretical and empirical link.

Marginal structural models with latent class growth analysis of treatment trajectories: Statins for primary prevention among older adults.

Latent class growth analysis is increasingly proposed as a solution to summarize the observed longitudinal treatment into a few distinct groups. When latent class growth analysis is combined with standard approaches like Cox proportional hazards models, confounding bias is not properly addressed because of time-varying covariates that have a double role of confounders and mediators. We propose to use latent class growth analysis to classify individuals into a few latent classes based on their medication adherence pattern, then choose a working marginal structural model that relates the outcome to these groups. The parameter of interest is defined as a projection of the true marginal structural model onto the chosen working model. Simulation studies are used to illustrate our approach and compare it with unadjusted, baseline covariates adjusted, time-varying covariates adjusted, and inverse probability of trajectory groups weighted adjusted models. Our proposed approach yielded estimators with little or no bias and appropriate coverage of confidence intervals in these simulations. We applied our latent class growth analysis and marginal structural model approach to a database comprising information on 52,790 individuals from the province of Quebec, Canada, aged more than 65 and who were statin initiators to estimate the effect of statin-usage trajectories on a first cardiovascular event.

Research Progress on the Application of Triboelectric Nanogenerators for Wind Energy Collection.

The escalating global energy demand necessitates the exploration of renewable energy sources, with wind energy emerging as a crucial and widely available resource. With wind energy exhibiting a vast potential of approximately 1010 kw/a per year, about ten times that of global hydroelectric power generation, its efficient conversion and utilization hold the promise of mitigating the pressing energy crisis and replacing the dominant reliance on fossil fuels. In recent years, Triboelectric Nanogenerators (TENGs) have emerged as novel and efficient means of capturing wind energy. This paper provides a comprehensive summary of the fundamental principles governing four basic working modes of TENGs, elucidating the structures and operational mechanisms of various models employed in wind energy harvesting. Furthermore, it highlights the significance of two major TENG configurations, namely, the vertical touch-separation pattern structure and the independent layer pattern for wind energy collection, emphasizing their respective advantages. Furthermore, the study briefly discusses the current strengths of nano-friction power generation in wind energy harvesting while acknowledging the existing challenges pertaining to device design, durability, operation, and maintenance. The review concludes by presenting potential research directions and prospects for triboelectric nanogenerators generation in the realm of wind energy, offering valuable insights for researchers and scholars in the field.

Association between coffee and incident heart failure: A prospective cohort study from the UK Biobank.

BACKGROUND AND AIMS: The relationship between coffee consumption and heart failure (HF) incidence is inconclusive. This study aimed to explore the association between time-varying coffee consumption and incident HF using a longitudinal study design. METHODS AND RESULTS: Data were obtained from the UK Biobank, comprising 497,503 adults (age, 56.5 ± 8.1 years; 54.6% women) who were free from HF at baseline in 2006-2010. The median follow-up time for the HF incidence was 11.9 years. Marginal structural models (MSM) were employed to adjust for potential time-varying confounders and account for bias caused by loss of follow-up. Furthermore, we used a restricted cubic spline to test and describe the nonlinear relationship between coffee consumption and HF risk. At baseline, 70.5% of participants reported drinking ≥1 cups/d coffee and 2.7% participants developed HF. After adjusting for potential confounders, we identified a nonlinear J-shaped association between coffee consumption and HF risk (P < 0.001). Compared with drinking coffee <1 cups/d, 1-2 cups/d (HR = 0.878; 95% CI: 0.838-0.920), 3-4 cups/d (HR = 0.920; 95% CI: 0.869-0.974) may be associated with a reduced risk of HF, while >6 cups/d (HR = 1.209; 95% CI: 1.056-1.385) may be associated with a higher risk of HF. However, sensitive analyses stratified by gender and smoking status indicated that >6 cups/d does not significantly increase the risk of HF. Additionally, the type of coffee was found to significant impact on the incidence of HF (P < 0.05). CONCLUSION: In this large cohort of UK adults, moderate coffee consumption may reduce risk of HF incidence.

Causal inference for recurrent events via aggregated marginal odds ratio.

Researchers often work with treatments and outcomes that vary over time. For example, psychologists are interested in the curative effect of cognitive behavior therapies on patients' recurrent depression symptoms. While there are various causal effect measures designed for one-time treatment, the causal effect measures for time-varying treatment and recurrent events are relatively under-developed. In this article, a new causal measure is proposed to quantify the causal effect of time-varying treatments on recurrent events. We suggest estimators with robust standard errors that are based on various weight models for both conventional causal measures and the proposed measure in different time settings. We outline the approaches and describe how using some stabilized inverse probability weight models are more advantageous than others. We demonstrate that the proposed causal estimand can be consistently estimated for study periods of moderate length, and the estimation results are compared under different treatment settings with various weight models. We also find that the proposed method is suitable for both absorbing and nonabsorbing treatments. The methods are applied to the 1997 National Longitudinal Study of Youth as an illustrative example.

Is cognition integral to psychopathology? A population-based cohort study.

BACKGROUND: Lower cognitive functioning has been documented across psychiatric disorders and hypothesized to be a core deficit of mental disorders. Situating psychopathology and cognition as part of a unitary construct is therefore important to understanding the etiology of psychiatric disorders. The current study aims to test competing structural models of psychopathology and cognition in a large national cohort of adolescents. METHODS: The analytic sample consisted of 1189 participants aged 16-17 years, screened by the Israeli Draft Board. Psychopathology was assessed using a modified version of the Brief Symptom Inventory, and cognition was assessed based on four standardized test scores ((1) mathematical reasoning, concentration, and concept manipulation; (2) visual-spatial problem-solving skills and nonverbal abstract reasoning; (3) verbal understanding; (4) categorization and verbal abstraction). Confirmatory factor analysis was implemented to compare competing structural models of psychopathology with and without cognition. Sensitivity analyses examined the models in different subpopulations. RESULTS: Confirmatory factor analysis indicated a better model fit of psychopathological symptoms without cognition (RMSEA = 0.037; TLI = 0.991; CFI = 0.992) than with cognition (RMSEA = 0.04-0.042; TLI = 0.987-0.988; CFI = 0.988-0.989). Sensitivity analyses supported the robustness of these results with a single exception. Among participants with low cognitive abilities (N = 139), models that integrated psychopathological symptoms with cognition had a better fit compared to models of psychopathology without cognition. CONCLUSIONS: The current study suggests that cognition and psychopathology are, generally, independent constructs. However, within low cognitive abilities, cognition was integral to the structure of psychopathology. Our results point toward an increased vulnerability to psychopathology in individuals with low cognitive abilities and may provide valuable information for clinicians.

A Review of Pectin-Based Material for Applications in Water Treatment.

Climate change and water are inseparably connected. Extreme weather events cause water to become more scarce, polluted, and erratic than ever. Therefore, we urgently need to develop solutions to reduce water contamination. This review intends to demonstrate that pectin-based materials are an excellent route to detect and mitigate pollutants from water, with several benefits. Pectin is a biodegradable polymer, extractable from vegetables, and contains several hydroxyl and carboxyl groups that can easily interact with the contaminant ions. In addition, pectin-based materials can be prepared in different forms (films, hydrogels, or beads) and cross-linked with several agents to change their molecular structure. Consequently, the pectin-based adsorbents can be tuned to remove diverse pollutants. Here, we will summarize the existing water remediation technologies highlighting adsorption as the ideal method. Then, the focus will be on the chemical structure of pectin and, from a historical perspective, on its structure after applying different cross-linking methods. Finally, we will review the application of pectin as an adsorbent of water pollutants considering the pectin of low degree methoxylation.

CM2D3: Furnishing the Human Interactome with Structural Models of Protein Complexes Derived by Comparative Modeling and Docking.

The human interactome is composed of around half a million interactions according to recent estimations and it is only for a small fraction of those that three-dimensional structural information is available. Indeed, the structural coverage of the human interactome is very low and given the complexity and time-consuming requirements of solving protein structures this problem will remain for the foreseeable future. Structural models, or predictions, of protein complexes can provide valuable information when the experimentally determined 3D structures are not available. Here we present CM2D3, a relational database containing structural models of the whole human interactome derived both from comparative modeling and data-driven docking. Starting from a consensus interactome derived from integrating several interactomics databases, a strategy was devised to derive structural models by computational means. Currently, CM2D3 includes 33338 structural models of which 5121 derived from comparative modeling and the remaining from docking. Of the latter, the structures of 14554 complexes were derived from monomers modeled by M4T while the rest were modeled with structures as predicted by AlphaFold2. Lastly, CM2D3 complements existing resources by focusing on models derived from both free-docking, as opposed to template-based docking, and hence expanding the available structural information on protein complexes to the scientific community. Database URL:http://www.bioinsilico.org/CM2D3.

Maternal and neonatal outcomes associated with treating hypertension in pregnancy at different thresholds.

INTRODUCTION: In the United States, there has been controversy over whether treatment of mild-to-moderate hypertension during pregnancy conveys more benefit than risk. OBJECTIVE: The objective of the study was to compare risks and benefits of treatment of mild-to-moderate hypertension during pregnancy. METHODS: This retrospective cohort study included 11,871 pregnant women with mild-to-moderate hypertension as defined by blood pressure (BP) values from three Kaiser Permanente regions between 2005 and 2014. Data were extracted from electronic health records. Dynamic marginal structural models with inverse probability weighting and informative censoring were used to compare risks of adverse outcomes when beginning antihypertensive medication treatment at four BP thresholds (≥155/105, ≥150/100, ≥145/95, ≥140/90 mm Hg) compared with the recommended threshold in the United States at that time, ≥160/110 mm Hg. Outcomes included preeclampsia, preterm birth, small-for-gestational-age (SGA), Neonatal Intensive Care Unit (NICU) care, and stillbirth. Primary analyses allowed 2 weeks for medication initiation after an elevated BP. Several sensitivity and subgroup (i.e., race/ethnicity and pre-pregnancy body mass index) analyses were also conducted. RESULTS: In primary analyses, medication initiation at lower BP thresholds was associated with greater risk of most outcomes. Comparing the lowest (≥140/90 mm Hg) to the highest BP threshold (≥160/110 mm Hg), we found an excess risk of preeclampsia (adjusted Risk Difference (aRD) 38.6 per 100 births, 95% Confidence Interval (CI): 30.6, 46.6), SGA (aRD: 10.2 per 100 births, 95% CI: 2.6, 17.8), NICU admission (aRD: 20.2 per 100 births, 95% CI: 12.6, 27.9), and stillbirth (1.18 per 100 births, 95% CI: 0.27, 2.09). The findings did not reach statistical significance for preterm birth (aRD: 2.5 per 100 births, 95% CI: -0.4, 5.3). These relationships were attenuated and did not always reach statistically significance when comparing higher BP treatment thresholds to the highest threshold (i.e., ≥160/110 mm Hg). Sensitivity and subgroup analyses produced similar results. CONCLUSIONS: Initiation of antihypertensive medication at mild-to-moderate BP thresholds (140-155/90-105 mm Hg; with the largest risk consistently associated with treatment at 140/90 mm Hg) may be associated with adverse maternal and neonatal outcomes. Limitations include inability to measure medication adherence.

Glucocorticoid exposure and the risk of serious infections in rheumatoid arthritis: a marginal structural model application.

OBJECTIVE: Observational studies have reported an increased risk of infections associated with glucocorticoids in RA, not supported by evidence from randomized controlled trials. Inappropriately accommodating time-varying exposure and confounding in observational studies might explain the conflicting results. Therefore, we compared the incidence of serious infections between different oral glucocorticoid dose patterns over three years in a prospective inception cohort, adjusting for time-varying confounders in marginal structural models. METHODS: We included 9654 newly diagnosed RA patients from the Swedish Rheumatology Quality Register between 2007-2018 and followed them for three years after the first rheumatology visit. Follow-up was divided into 90-day periods. A mean oral prednisone daily dose was calculated for each period and categorized into 'no use', 'low' (≤10 mg/day) and 'high' (>10 mg/day) doses. The incidence of serious infections (hospitalization for infection) over follow-up periods was modelled by pooled logistic regression allowing separate effects for recent and past exposure. RESULTS: An increased incidence of serious infections was associated with higher compared with lower doses and with more recent compared with past glucocorticoid exposure. Over 3 years of follow-up, the marginal structural models predicted one additional serious infection for every 83 individuals treated with low GC doses for the first 6 months, and for every 125 individuals treated with high GC doses for the first 3 months, compared with no GC use. CONCLUSION: Our results broadly agree with previous observational studies showing a dose dependent increased risk of infection associated with (recent) use of oral glucocorticoids.

Marginal structural models with monotonicity constraints: A case study in out-of-hospital cardiac arrest patients.

This paper deals with estimating the probability of a binary counterfactual outcome as a function of a continuous covariate under monotonicity constraints. We are motivated by the study of out-of-hospital cardiac arrest patients which aims to estimate the counterfactual 30-day survival probability if either all patients had received, or if none of the patients had received bystander cardiopulmonary resuscitation (CPR), as a function of the ambulance response time. It is natural to assume that the counterfactual 30-day survival probability cannot increase with increasing ambulance response time. We model the monotone relationship with a marginal structural model and B-splines. We then derive an estimating equation for the parameters of interest which however further relies on an auxiliary regression model for the observed 30-day survival probabilities. The predictions of the observed 30-day survival probabilities are used as pseudo-values for the unobserved counterfactual 30-day survival status. The methods are illustrated and contrasted with an unconstrained modeling approach in large-scale Danish registry data.

Estimation of marginal structural models under irregular visits and unmeasured confounder: calibrated inverse probability weights.

Clinical information collected in electronic health records (EHRs) is becoming an essential source to emulate randomized experiments. Since patients do not interact with the healthcare system at random, the longitudinal information in large observational databases must account for irregular visits. Moreover, we need to also account for subject-specific unmeasured confounders which may act as a common cause for treatment assignment mechanism (e.g. glucose-lowering medications) while also influencing the outcome (e.g. Hemoglobin A1c). We used the calibration of longitudinal weights to improve the finite sample properties and to account for subject-specific unmeasured confounders. A Monte Carlo simulation study is conducted to evaluate the performance of calibrated inverse probability estimators using time-dependent treatment assignment and irregular visits with subject-specific unmeasured confounders. The simulation study showed that the longitudinal weights with calibrated restrictions improved the finite sample bias when compared to the stabilized weights. The application of the calibrated weights is demonstrated using the exposure of glucose lowering medications and the longitudinal outcome of Hemoglobin A1c. Our results support the effectiveness of glucose lowering medications in reducing Hemoglobin A1c among type II diabetes patients with elevated glycemic index ([Formula: see text]) using stabilized and calibrated weights.