Propensity Score Model Research Articles

Targeted learning with an undersmoothed LASSO propensity score model for large-scale covariate adjustment in health-care database studies.

Least absolute shrinkage and selection operator (LASSO) regression is widely used for large-scale propensity score (PS) estimation in health-care database studies. In these settings, previous work has shown that undersmoothing (overfitting) LASSO PS models can improve confounding control, but it can also cause problems of nonoverlap in covariate distributions. It remains unclear how to select the degree of undersmoothing when fitting large-scale LASSO PS models to improve confounding control while avoiding issues that can result from reduced covariate overlap. Here, we used simulations to evaluate the performance of using collaborative-controlled targeted learning to data-adaptively select the degree of undersmoothing when fitting large-scale PS models within both singly and doubly robust frameworks to reduce bias in causal estimators. Simulations showed that collaborative learning can data-adaptively select the degree of undersmoothing to reduce bias in estimated treatment effects. Results further showed that when fitting undersmoothed LASSO PS models, the use of cross-fitting was important for avoiding nonoverlap in covariate distributions and reducing bias in causal estimates.

Community groups as an enabler for access to livelihood capitals, deprivation of which contributes to multidimensional poverty in rural Uganda

Using the 2016/2017 and 2019/2020 Uganda National Household Survey (UNHS), this study analyses the effect of saving and credit community groups, both cooperatives and associations, on multidimensional poverty. Access to livelihood capitals reduces poverty. Poverty being a rural phenomenon in Uganda, this study assesses whether households in rural Uganda with community group members have access to livelihood capitals. The study also examined the effect of non-membership in a community group on multidimensional poverty and whether being multidimensionally poor affects membership in community groups. The Alkire-Foster method is applied to calculate the Adjusted Headcount Ratio (M0), which is used in the propensity score model to establish the effect of membership in a community group on household multidimensional poverty. Analysis of how the estimated multidimensional poverty varies with the estimated propensity score is achieved using the estimated Average Treatment Effect of the Treated (ATET) obtained with four matching methods (nearest neighbour, radius, kernel, and stratification). Findings reveal that community groups enable rural dwellers to access livelihood capitals, hence enabling them to overcome their multiple deprivations and reducing their likelihood of being multidimensionally poor. Membership in community groups is robustly linked to a decreased probability of being multidimensionally poor by over 3 percentage points.

Matching-Adjusted Indirect Comparison of Brexucabtagene Autoleucel (ZUMA-2) and Pirtobrutinib (BRUIN) in Patients with Relapsed/Refractory Mantle Cell Lymphoma Previously Treated with a Covalent Bruton Tyrosine KinaseInhibitor.

Patients with relapsed/refractory (R/R) mantle cell lymphoma (MCL) often require multiple lines of treatment and have a poor prognosis, particularly after failing covalent Bruton tyrosine kinase inhibitor (cBTKi) therapy. Newer treatments such as brexucabtagene autoleucel (brexu-cel, chimeric antigen receptor Tcell therapy) and pirtobrutinib (non-covalent BTKi) show promise in improving outcomes. Without direct comparative evidence, an unanchored matching-adjusted indirect comparison was conducted to estimate the relative treatment effects of brexu-cel and pirtobrutinib for post-cBTKi R/R MCL. Using logistic propensity score models, individual patient-level data from ZUMA-2 brexu-cel-infused population (N = 68) were weighted to match pre-specified clinically relevant prognostic factors based on study-level data from the BRUIN cBTKi pre-treated cohort (N = 90). The base-case model incorporated the five most pertinent factors reported in ≥ 50% of both trial populations: morphology, MCL International Prognostic Index, number of prior lines of therapy, disease stage, and prior autologous stem cell transplant. A sensitivity analysis additionally incorporated TP53 mutation and Ki-67 proliferation. Relative treatment effects were expressed as odds ratios (ORs) or hazard ratios (HRs) with 95% confidence intervals (CIs). In the base-case model, brexu-cel was associated with higher rates of objective response (OR 10.39 [95%CI 2.81-38.46]) and complete response (OR 10.11 [95%CI 4.26-24.00]), and improved progression-free survival (HR0.44 [95%CI 0.25-0.75]), compared to pirtobrutinib. Overall survival and duration of response favored brexu-cel over pirtobrutinib but the differences crossed the bounds for statistical significance. Findings were consistent across the adjusted and unadjusted analyses. Findings suggest that brexu-cel may offer clinically and statistically significant benefits regarding objective response, complete response, and progression-free survival compared to pirtobrutinib among patients with R/R MCL after prior cBTKi therapy. Given the short follow-up and high degree of censoring in BRUIN, an analysis incorporating updated BRUIN data may provide more definitive overall survival results.

Enhanced doubly robust estimation with concave link functions for estimands in clinical trials

ABSTRACT For observational studies or clinical trials not fully randomised, the baseline covariates are often not balanced between the treatment and control groups. In this case, the traditional estimates of treatment effects are biased, and causal inference method is needed to get unbiased estimate. The doubly robust estimator (DRE) is a recent popular development in casual inference. However, the unbiasedness of DRE relies on the correct specification of either propensity score or outcome models, which is hardly guaranteed. To overcome this issue, Yuan et al. [(2021), ‘Enhanced Doubly Robust Procedure for Causal Inference’, Statistics in Bioscience, 13(3), 454–478. https://doi.org/10.1007/s12561-021-09300-y.] proposed an enhanced doubly robust estimator which utilises semiparametric models and nonparametric monotone link functions for both propensity score and outcome models. In this article, we further develop an enhanced doubly robust estimator with concave link functions for both propensity score and outcome models. The asymptotic properties of the enhanced doubly robust estimator are studied. Simulation studies are conducted to evaluate the proposed method. A clinical trial data analysis is used to illustrate the method.

Non-femoral focused transaxillary access in TAVI: GARY data analysis and future trends.

In patients not suitable for transfemoral transcatheter aortic valve implantation (TAVI), several access strategies can be chosen. To evaluate the use and patient outcomes of transaxillary (TAx), transapical (TA), and transaortic (TAo) as alternative access for TAVI in Germany; to further evaluate surgical cutdown vs. percutaneous TAx access. All patients entered the German Aortic Valve Registry (GARY) between 2011 and 2019 who underwent non-transfemoral TAVI were included in this analysis. Patients with TA, TAo, or TAx TAVI were compared using a weighted propensity score model. Furthermore, a subgroup analysis was performed for TAx regarding the percutaneous or surgical cutdown approach. Overall, 9686 patients received a non-transfemoral access. A total of 8918 patients (92.1%) underwent TA, 398 (4.1%) TAo, and 370 (3.8%) TAx approaches. Within the TAx subgroup, 141 patients (38.1%) received subclavian cutdown, while 200 (54.1%) underwent a percutaneous approach. The TA patients had a significantly lower 30-day survival than TAx patients (TA 90.92% vs. TAx 95.59%, p = 0.006; TAo 92.22% vs. TAx 95.59%, p = 0.102). Comparing percutaneous and cutdown TAx approaches, no significant differences were seen. However, more vascular complications occurred (TA 1.8%, TAo 2.4%, TAx 12.2%; p < .001), and the hospital length of stay was shorter (TA 12.9days, TAo 14.1days, TAx 12days; p < .001) after TAx access. It may be reasonable to consider TAx access first in patients not suitable for TF-TAVI, because the 30-day survival was higher compared with TA access and the 1-year survival was higher compared with TAo access. It remains important for the heart teams to offer alternative access modalities for patients not amenable to the standard TF-TAVI approaches.

Doubly robust estimation of multivariate fractional outcome means with multivalued treatments

. This article suggests a doubly robust method of estimating potential outcome means for multivariate fractional outcomes when the treatment of interest is unconfounded and can take more than two values. The method involves maximizing a propensity score weighted multinomial quasi-log-likelihood function with a multinomial logit conditional mean. We show that this estimator, which we call weighted multivariate fractional logit (wmflogit), consistently estimates the potential outcome means if either the propensity score model or the conditional mean model is misspecified. Our simulations demonstrate this double robustness property for the case of shares generated using a Dirichlet distribution. Finally, we advocate for the use of wmflogit by applying it to estimate time-use shares of women participating in the Mexican conditional cash transfer program, Progresa, using Stata’s fmlogit command developed by Buis.

Treatment effect estimation using the propensity score in clinical trials with historical control

BackgroundClinical trials assessing new treatment effects require a control group to compare the pure treatment effects. However, in clinical trials on regenerative medicine, rare diseases, and intractable diseases, it may be ethically difficult to assign participants to the control group. In recent years, the use of historical control data has attracted attention as a method for supplementing the number of participants in the control group. When combining historical control data with new randomized controlled trial (RCT) data, the assessment of heterogeneity using outcome data is not sufficient. Therefore, several statistical methods that consider participant outcomes and baseline characteristics, including the propensity score (PS) method have been proposed.MethodsWe propose a new method considering “information on whether the data are RCT data or not” in the PS model when combining the RCT and historical control data. The performance of the proposed method in estimating the treatment effect is evaluated using simulation data.ResultsWhen the distribution of covariates is similar between the RCT and historical control data, not much difference in performance is found between the proposed and conventional methods to estimate the treatment effect. On the other hand, when the distribution of covariates is not similar between the two kinds of data, the proposed method shows higher performance.ConclusionsEven when it is not known whether RCT and historical control data are similar, the proposed PS model is useful to estimate the treatment effect appropriately in RCTs using historical control data.

Real-Time Machine Learning Alerts to Prevent Escalation of Care: A Nonrandomized Clustered Pragmatic Clinical Trial.

Machine learning algorithms can outperform older methods in predicting clinical deterioration, but rigorous prospective data on their real-world efficacy are limited. We hypothesized that real-time machine learning generated alerts sent directly to front-line providers would reduce escalations. Single-center prospective pragmatic nonrandomized clustered clinical trial. Academic tertiary care medical center. Adult patients admitted to four medical-surgical units. Assignment to intervention or control arms was determined by initial unit admission. Real-time alerts stratified according to predicted likelihood of deterioration sent either to the primary team or directly to the rapid response team (RRT). Clinical care and interventions were at the providers' discretion. For the control units, alerts were generated but not sent, and standard RRT activation criteria were used. The primary outcome was the rate of escalation per 1000 patient bed days. Secondary outcomes included the frequency of orders for fluids, medications, and diagnostic tests, and combined in-hospital and 30-day mortality. Propensity score modeling with stabilized inverse probability of treatment weight (IPTW) was used to account for differences between groups. Data from 2740 patients enrolled between July 2019 and March 2020 were analyzed (1488 intervention, 1252 control). Average age was 66.3 years and 1428 participants (52%) were female. The rate of escalation was 12.3 vs. 11.3 per 1000 patient bed days (difference, 1.0; 95% CI, -2.8 to 4.7) and IPTW adjusted incidence rate ratio 1.43 (95% CI, 1.16-1.78; p < 0.001). Patients in the intervention group were more likely to receive cardiovascular medication orders (16.1% vs. 11.3%; 4.7%; 95% CI, 2.1-7.4%) and IPTW adjusted relative risk (RR) (1.74; 95% CI, 1.39-2.18; p < 0.001). Combined in-hospital and 30-day-mortality was lower in the intervention group (7% vs. 9.3%; -2.4%; 95% CI, -4.5% to -0.2%) and IPTW adjusted RR (0.76; 95% CI, 0.58-0.99; p = 0.045). Real-time machine learning alerts do not reduce the rate of escalation but may reduce mortality.

Associations between physical activity and subcategories of mental health: A propensity score analysis among a global sample of 341,956 adults

BackgroundEvidence indicates that physical activity (PA) can be a clinically useful and low-cost option for preventing and managing many mental health problems. Further investigation into which specific aspects of mental health are most influenced by PA can help to elucidate the differential effects that PA may confer. PurposeThis study used cross-sectional data from the Global Mind Project to investigate the association of PA on overall mental well-being and various subcategories of mental health across different adult age groups. MethodsParticipants completed the 47-item Mental Health Quotient (MHQ) and reported how frequently they engaged in daily bouts of PA for 30 min or more. Weighted propensity score models were used to estimate the Average Treatment effect on the Control (ATC) of PA engagement on overall mental well-being as well as six subcategories of mental health. ResultsAn estimated ATC of 17.41 was found for overall MHQ, corresponding to a standardized mean difference (SMD) of 0.25. Among the mental health subcategories, PA engagement was estimated to have the largest ATC for Mind-Body Connection (ATC = 18.90; SMD = 0.30), followed by Adaptability and Resilience (ATC = 17.09; SMD = 0.26), Core Cognition (ATC = 16.00; SMD = 0.24), Drive and Motivation (ATC = 15.43; SMD = 0.24), Mood and Outlook (ATC = 14.81; SMD = 0.21), and Social Self (ATC = 12.53; SMD = 0.17). ConclusionOur findings support the existing literature demonstrating an association of PA engagement on overall mental well-being, and builds on this work by revealing consistent effects that exist across various mental health subcategories and the adult lifespan.

Multiply robust generalized estimating equations for cluster randomized trials with missing outcomes.

Generalized estimating equations (GEEs) provide a useful framework for estimating marginal regression parameters based on data from cluster randomized trials (CRTs), but they can result in inaccurate parameter estimates when some outcomes are informatively missing. Existing techniques to handle missing outcomes in CRTs rely on correct specification of a propensity score model, a covariate-conditional mean outcome model, or require at least one of these two models to be correct, which can be challenging in practice. In this article, we develop new weighted GEEs to simultaneously estimate the marginal mean, scale, and correlation parameters in CRTs with missing outcomes, allowing for multiple propensity score models and multiple covariate-conditional mean models to be specified. The resulting estimators are consistent provided that any one of these models is correct. An iterative algorithm is provided for implementing this more robust estimator and practical considerations for specifying multiple models are discussed. We evaluate the performance of the proposed method through Monte Carlo simulations and apply the proposed multiply robust estimator to analyze the Botswana Combination Prevention Project, a large HIV prevention CRT designed to evaluate whether a combination of HIV-prevention measures can reduce HIV incidence.

Association between red blood cell distribution width-to-platelet ratio and post-discharge readmission rate in patients with heart failure: A retrospective cohort study

BackgroundTo date, no studies have investigated the association between red blood cell distribution width (RDW)-to-platelet ratio (RPR) and readmission rates among patients with heart failure (HF). As such, the present study aimed to examine the relationship between RPR and readmission rates in patients with HF. MethodsData for this study were obtained from the Fourth People's Hospital (Zigong, Sichuan Province, China). Patients were diagnosed with HF in accordance with European Society of Cardiology criteria. The primary outcome was the 28-day readmission rate. Various logistic regression models were constructed to explore the association between RPR and the 28-day readmission rate. ResultsThe study comprised 1978 patients with HF, with a 28-day readmission rate of 6.98%. RPR emerged as an independent risk factor for 28-day readmission, evidenced by consistent results across the various regression-adjusted models. The covariate-adjusted propensity score model demonstrated that every 0.1 increase in RPR was associated with an 8.2% increase in 28-day readmission rate (odds ratio [OR] 1.082 [95% confidence interval (CI) 1.012–1.158]; P = 0.0212). Similarly, each 0.1 change in RPR was associated with a 9.8% (OR 1.098 [95% CI 1.014–1.188]) and 7.3% (OR 1.073 [95% CI 0.991–1.161]) increase in 3- and 6-month readmission rates, respectively. However, RPR was not statistically associated with the 6-month readmission rate. Curve fit plots illustrated a nonlinear positive correlation between RPR and 28-day, and 3- and 6-month readmissions. Moreover, the effects of RPR on 28-day, and 3- and 6-month readmission rates remained robust across subgroup variables in stratified analysis. Finally, the effect sizes of pooled multiply imputed data were consistent with the original data, suggesting robust results. ConclusionRPR was an independent risk factor for 28-day readmission among patients with HF and also demonstrated modest predictive value for readmissions at 3 and 6 months, despite being non-significant for the 6-month readmission rate. Early identification of patients with HF with elevated RPR would facilitate management and may confer favorable effects on prognosis.

Comparative analysis of outcomes of neoadjuvant and adjuvant systemic therapy in non-metastatic renal cell carcinoma: A propensity score-matched analysis from the INMARC registry.

414 Background: Receipt of adjuvant therapy has become a standard of care for management of high risk localized renal cell carcinoma (RCC), with emerging literature demonstrating longer disease-free survival. Neoadjuvant approaches have been utilized investigationally to facilitate complete surgical resections in high risk and complex renal masses. We sought to evaluate outcomes of patients treated with neoadjuvant or adjuvant therapy in non-metastatic RCC utilizing a propensity score model. Methods: We queried the INMARC database for patients with localized surgically treated RCC who underwent systemic neoadjuvant or adjuvant therapy. Neoadjuvant therapy was defined as presurgical therapy given in the setting of localized disease and adjuvant therapy as systemic therapy given postoperatively in the absence of documented metastases. Patients with metastases at time of diagnosis were excluded from the analysis. A propensity score match (PSM) model in a 1:3 ratio was conducted within a caliper width of 0.1 including: age, sex, hypertension, Charlson Comorbidity Index, tumor size, tumor necrosis, stage, surgical margin, tumor grade and type of surgery [radical vs. partial nephrectomy]. Primary outcome was all-cause mortality (ACM), and secondary outcome was cancer-specific mortality (CSM). Multivariable analysis (MVA) via Cox regression was fitted for the outcomes of interest. Kaplan-Meier analysis (KMA) for overall (OS), cancer specific survival (CSS) was conducted for 5-year survival assessment. Results: After PSM 293 patients were analyzed [adjuvant n=203, (69.2%), 109 targeted therapy (TT) vs. 94 immunotherapy; neoadjuvant n=90, (30.7%), 59 TT vs. 31 immunotherapy]; median follow up was 50 (IQR 20-76) months from surgery . MVA revealed adjuvant vs. neoadjuvant (HR 1.98, p=0.007) and positive margin (HR 2.01, p=0.046) to be associated with increased risk of ACM; immunotherapy vs. TT (HR 0.47, p=0.001) was associated with a decreased risk. MVA for CSM revealed that adjuvant vs. neoadjuvant (HR 2.18, p=0.016) and positive margin (HR 2.41, p=0.028) were associated with increased risk of CSM, while immunotherapy vs. TT (HR 0.35, p&lt;0.001) was associated with decreased risk. KMA comparing neoadjuvant vs. adjuvant 5-year OS was 80.4% vs. 64.8% (p=0.04), while CSS was 88.1% vs. 76.2% (p=0.03). Conclusions: In a comparison of patients with localized RCC who underwent adjuvant or neoadjuvant systemic therapy, receipt of neoadjuvant therapy was associated with superior survival outcomes. These findings are hypothesis generating and call for consideration for a clinical trial to compare outcomes of adjuvant vs. neoadjuvant therapy in high-risk localized RCC.

Propensity Score Weighting with Missing Data on Covariates and Clustered Data Structure

Propensity score (PS) analyses are increasingly popular in behavioral sciences. Two issues often add complexities to PS analyses, including missing data in observed covariates and clustered data structure. In previous research, methods for conducting PS analyses with considering either issue alone were examined. In practice, the two issues often co-occur; but the performance of methods for PS analyses in the presence of both issues has not been evaluated previously. In this study, we consider PS weighting analysis when data are clustered and observed covariates have missing values. A simulation study is conducted to evaluate the performance of different missing data handling methods (complete-case, single-level imputation, or multilevel imputation) combined with different multilevel PS weighting methods (fixed- or random-effects PS models, inverse-propensity-weighting or the clustered weighting, weighted single-level or multilevel outcome models). The results suggest that the bias in average treatment effect estimation can be reduced, by better accounting for clustering in both the missing data handling stage (such as with the multilevel imputation) and the PS analysis stage (such as with the fixed-effects PS model, clustered weighting, and weighted multilevel outcome model). A real-data example is provided for illustration.

P782 Comparison of accelerated and standard infliximab induction regimens in Acute Severe Ulcerative Colitis using propensity score: A retrospective multicenter study in a Chinese cohort

Abstract Background The optimal regimen of infliximab salvage in acute severe ulcerative colitis (ASUC) patients remains controversial. This retrospective multicenter study aimed to compare accelerated and standard infliximab induction in a Chinese cohort of ASUC patients, and to explore risk factors associated with poor prognosis. Methods Data were collected retrospectively from steroid-refractory ASUC patients who received infliximab induction as rescue therapy at seven tertiary centers across China. Accelerated infliximab induction was defined as receiving two doses of infliximab on or before day 13 and/or receiving intensified doses of ≥ 7.5 mg/kg. Outcomes including colectomy and clinical remission (Mayo score ≤ 2 and every subscore ≤ 1 at day 14) rates were compared using propensity score adjustment for potential confounders. The variables in propensity score model was determined by logistic regression analysis for accelerated induction. Results A total of 76 patients were included: 29 received standard induction and 47 received accelerated induction. The overall disease severity was significantly higher in patients of accelerated group (Table). The 30-day colectomy rates did not differ between two groups (4.3% vs. 0%, P=0.522). However, the accelerated group had a higher 90-day colectomy rate (17.8% vs. 0%, P=0.019) and lower clinical remission rate (27.7% vs. 65.5%, P=0.001). (Figure. A) After adjusting with propensity score and institution, there was no significant difference in colectomy (P=0.20) or no clinical remission (P=0.48) hazards. Dose-effect curves plotted by restricted cubic splines (adjusted for propensity score and institution) showed decreased colectomy hazard with higher cumulative infliximab dosage within 5 days, while no improvement was observed for increasing cumulative infliximab dosage within 28 days. (Figure. B) Multivariate logistic regression analyses revealed female gender (OR=7.69, 95%CI: 1.96-33.33) and C-reactive protein (CRP) &amp;gt;10 mg/L at infliximab initiation (OR=5.00, 95%CI: 1.27-24.34) as independent risk factors for no clinical remission. (Figure. C) Conclusion After adjusting for confounders, there were no significant differences in colectomy or clinical remission rates between accelerated and standard infliximab induction among steroid-refractory ASUC patients. Elevated CRP at infliximab initiation indicated more intensive treatment or earlier surgery to be considered. And it would be better to give early intensified dosage within 5 days if needed.

Pediatric patients on veno-arterial extracorporeal membrane oxygenation undergoing cardiac rehabilitation have better outcomes

BackgroundThe importance of physical rehabilitation in optimizing outcomes in critically ill patients is recognized. However, the frequency and benefit of mobilization in pediatric patients undergoing veno-arterial (VA) extracorporeal membrane oxygenation (ECMO) is unclear. This study evaluates a cohort of pediatric VA-ECMO patients to characterize the spectrum of mobility and evaluate associations of mobilization with clinical outcomes. MethodsWe analyzed 688 patients (8-18yrs) who underwent primary ECMO runs and had mobilization data collected in the Extracorporeal Life Support Organization (ELSO) Registry. Demographics, pre-ECMO support, location and duration of support, and outcomes including survival to hospital discharge, heart transplant, and ECMO related complications were collected. Propensity score modeling was performed with entropy weighting to compare outcomes between mobile and non-mobile patients. ResultsOf the 688 patients included, 10% achieved some degree of mobility (69/688); the majority of those exercised in bed. After propensity score matching, mobility was associated with an increased likelihood of being discharged alive (OR 1.16, 95% CI 1.04, 1.30) and receiving a heart transplant (OR 1.15, 95% CI 1.02, 1.29), and a lower likelihood of dying on ECMO (OR 0.90, 95% CI 0.81, 1.00). There was no association between mobility and ECMO being discontinued due to complication (OR, 1.03 95% CI 0.97, 1.10). ConclusionMobilization in a pediatric VA-ECMO cohort was achieved by 1/10 patients, is associated with heart transplant and survival to hospital discharge and is not associated with ECMO related adverse events. Mobility in certain pediatric VA-ECMO patients is feasible and may represent an opportunity to improve outcomes.

Difference in the physical and mental health of informal caregivers pre- and post-COVID-19 National Emergency Declaration in the United States.

BackgroundThe burden of informal caregiving represents a chronic stressor for the informal caregivers (ICs). The study investigates differences in the physical and mental health of ICs and that of non-informal caregivers before and during COVID-19. MethodsWe used data from the 2019/2020 Behavioral Risk Factor Surveillance System (BRFSS) to investigate differences in the rates of days of poor physical and mental health among ICs compared to non-informal caregivers before and after the COVID-19 National Emergency Declaration (NED). A propensity score model simulated a pseudo experimental design, comparing ICs (“treated”) with non-informal caregivers (“control”). A difference-in-difference regression model estimated the incidence rate ratios for days of poor physical and mental health as a function of IC status and time of care provision. ResultsA total of 44,583 respondents were identified with valid responses on informal caregiving status and key sociodemographic characteristics. Of those, 6.24% (n = 3073) were ICs, matched against 15,365 non-informal caregivers. In the matched sample (n = 18,848), the incidence rate for days of poor physical health among ICs was 17% (p = 0.003) higher compared to non-informal caregivers. The incidence rate for days of poor physical health was 23% (p < 0.001) lower in the post-NED compared to the pre-NED periods. The incidence rate for days of poor mental health was 44% (p < 0.001) higher among ICs compared to non-informal caregivers and 22% higher among respondents who took the survey post-NED compared to those who answered during the pre-NED period. No statistically significant differences were found between the two groups in their incidence rates for days of poor physical and mental health from the pre-to the post-NED period. ConclusionThese findings suggest a need to balance between the benefits conferred by public health restrictions versus the mental health burden that may result among certain groups, including ICs, who experience higher negative mental health outcomes.

Similar rate of venous thromboembolism (VTE) and failure of non-operative management for early versus delayed VTE chemoprophylaxis in adolescent blunt solid organ injuries: a propensity-matched analysis

BackgroundEarly initiation of venous thromboembolism (VTE) chemoprophylaxis in adults with blunt solid organ injury (BSOI) has been demonstrated to be safe but this is controversial in adolescents. We hypothesized that adolescent patients with BSOI undergoing non-operative management (NOM) and receiving early VTE chemoprophylaxis (eVTEP) (≤ 48 h) have a decreased rate of VTE and similar rate of failure of NOM, compared to similarly matched adolescents receiving delayed VTE chemoprophylaxis (dVTEP) (> 48 h).MethodsThe 2017–2019 Trauma Quality Improvement Program database was queried for adolescents (12–17 years of age) with BSOI (liver, kidney, and/or spleen) undergoing NOM. We compared eVTEP versus dVTEP using a 1:1 propensity score model, matching for age, comorbidities, BSOI grade, injury severity score, hypotension on arrival, and need for transfusions. We performed subset analyses in patients with isolated spleen, kidney, and liver injury.ResultsFrom 1022 cases, 417 (40.8%) adolescents received eVTEP. After matching, there was no difference in matched variables (all p > 0.05). Both groups had a similar rate of VTE (dVTEP 0.6% vs. eVTEP 1.7%, p = 0.16), mortality (dVTEP 0.3% vs. eVTEP 0%, p = 0.32), and failure of NOM (eVTEP 6.7% vs. dVTEP 7.3%, p = 0.77). These findings remained true in all subset analyses of isolated solid organ injury (all p > 0.05).ConclusionsThe rate of VTE with adolescent BSOI is exceedingly rare. Early VTE chemoprophylaxis in adolescent BSOI does not increase the rate of failing NOM. However, unlike adult trauma patients, adolescent patients with BSOI receiving eVTEP had a similar rate of VTE and death, compared to adolescents receiving dVTEP.

COVID-19 Pandemic Impact on the Trajectories of Cognitive Decline and Depression Symptoms in Long-Term Care Facility Residents

ObjectivesTo compare the longitudinal rates of change in cognition and depressive symptoms between 2019 (pre–COVID-19 pandemic) and 2020 (COVID-19 pandemic) among long-term care facility (LTCF) residents in Iowa, which ranked among the top 10 US states that suffered from extreme nursing staff shortages during this crisis. DesignA longitudinal cohort study analyzing the Long-Term Care Minimum Data Set (MDS) version 3.0 between January 1, 2019, and December 31, 2020. Setting and ParticipantsLTCF residents from the state of Iowa, with a first assessment before March 10 for each year (2019 and 2020), LTCF stay period >60 days, and at least 2 documented assessments with a minimum of 45 days in between. LTCF residents with a Brief Interview for Mental Status score (BIMS) <3 were excluded. MethodsWe computed doubly robust estimators by combining regression and propensity score models for BIMS (cognitive decline) and Nine-item Patient Health Questionnaire (PHQ-9; depression symptoms) monthly scores for 2020 vs 2019. ResultsA total of 24,025 residents from 436 LTCFs were included. Our research revealed a marginally accelerated monthly decline in BIMS scores during 2020 as opposed to 2019, with a rate of −0.012 per month (95% CI −0.022, −0.002; P = .016). Simultaneously, we observed a monthly increment of 0.016 in the PHQ-9 scores among LTCF residents in 2020 (95% CI 0.006, 0.028; P = .003). Conclusions and ImplicationsOur study identified a notable yet modest increase in cognitive decline and depressive symptoms among NH residents in Iowa during the COVID-19 pandemic. Although statistically significant, the changes were small and may not have clinical relevance over 1 year. Further research is needed to examine risk factors for cognitive decline during pandemic scenarios such as social isolation, loneliness, inappropriate patient-centered care, and the relationship with staff shortage and facility resources.

Treatment Comparisons in Adaptive Platform Trials Adjusting for Temporal Drift

An adaptive platform trial (APT) is a multi-arm trial in the context of a single disease where treatment arms are allowed to enter or leave the trial based on some decision rule. If a treatment enters the trial later than the control arm, there exist nonconcurrent controls who were not randomized between the two arms under comparison. As APTs typically take long periods of time to conduct, temporal drift may occur, which requires the treatment comparisons to be adjusted for this temporal change. Under the causal inference framework, we propose two approaches for treatment comparisons in APTs that account for temporal drift, both based on propensity score weighting. In particular, to address unmeasured confounders, one approach is doubly robust in the sense that it remains valid so long as either the propensity score model is correctly specified or the time effect model is correctly specified. Simulation study shows that our proposed approaches have desirable operating characteristics with well controlled Type I error rates and high power with or without unmeasured confounders.

Simple and robust estimation of average treatment effects for the overlap population using model averaging

The propensity score plays a central role in estimating causal effects in observational studies. Recently, considerable research has been conducted on specific causal estimands that represent the target population for causal effect estimation. In this manuscript, our focus is on the average treatment effects for the overlap population (ATO), where the estimand relies on the ‘true’ propensity score. Consequently, any misspecification of the propensity score model can introduce significant bias to the estimation of the causal effect. To address this issue, we present a novel approach for estimating propensity scores using a model-averaging method that ensures more robust causal effect estimators than a single propensity score model even with the misspecification of some propensity score models. The proposed procedure is user-friendly, as it only involves the use of generalized linear models in freely available software packages, such as ‘glm’ in R and the ‘GENMOD’ procedure in SAS, among others. Also, we propose a novel augmented inverse probability weighting estimator for the ATO that has boundedness; the estimator has the same support as the interested outcome. Through extensive simulation and real data analysis, we demonstrated that the proposed method yields stable and efficient causal estimators for the ATO estimand.