Reducing Bias in Observational Studies Using Subclassification on the Propensity Score

Evaluation of a program designed to prevent diabetic nephropathy aggravation: A retrospective cohort study using health checkups and claims data in Japanese municipalities

AIMS

Japan started the Diabetic Nephropathy Aggravation Prevention Program. Its early impact was assessed in this study.

METHODS

This study used the Kokuho Database of patients with type 2 diabetes from program-implementing and non-implementing municipalities (fiscal years [FYs] 2015-2021). Implementing municipalities facilitated clinic visits and provided education to eligible patients. Average treatment effects on the treated in FYs 2016 and 2018 were evaluated using the inverse probability of treatment weighting. Comparison included intervened vs. non-intervened patients in program-implementing municipalities (Comparison A), intervened patients in program-implementing vs. eligible patients in non-implementing municipalities (Comparison B), and eligible patients in implementing and non-implementing municipalities (Comparison C).

RESULTS

Overall, 89,611/89,685 patients from FY 2016/2018 were eligible. Among 68,125/68,170 patients in program-implementing municipalities, 1,470/1,819 were intervened. In Comparison A, the estimated effect of the program on ΔeGFR at 3 years were -0.4 (95 % confidence interval; -1.0, 0.2)/-0.4 (-0.9, 0.1) mL/min/1.73 m2 in FY 2016/2018. Comparisons B and C demonstrated similar tendency; distribution of %change in eGFR varied between municipalities.

CONCLUSIONS

Early in the program, renal function did not improve in the intervened patients or program-implementing municipalities. Diverse eGFR changes across municipalities highlighted diverse intervention outcomes, emphasizing the need of program refinement.

Assessment of targeted intervention programme under the National AIDS Control Program among men who have sex with men in India

INTRODUCTION

The population of men who have sex with men (MSM) in India is vulnerable to HIV/AIDS. India instituted a targeted intervention (TI) programme to reduce this vulnerability. We aimed to measure the assessment of the TI programme for MSM.

MATERIALS AND METHODS

The national Integrated Biological and Behavioural Survey (IBBS) was carried out in 2014-2015. We analysed MSM data from the IBBS and used bivariate and multivariate logistic regression to calculate the unadjusted and adjusted odds ratios with 95% confidence intervals. The use of a condom during their last sexual intercourse and consistent condom use during the previous month were considered indicators of programme effectiveness. The propensity score matching method was used to assess the effectiveness of the TI programme.

RESULTS

The matched-samples estimate (i.e., average treatment effect on treated) for the use of condoms during their last sexual intercourse increased by 10.0% (0.10; 95% confidence interval [CI] 0.08-0.12), and consistent condom use during the previous month increased by 9.0% (0.09; 95% CI 0.07-0.10) among those who had received condoms from the peer educator/outreach worker compared with those who had not received condoms.

CONCLUSIONS

The TI programme intervention among MSM was effective in reducing HIV risk behaviours, as evidenced by an increase in the use of condoms during their last sexual intercourse and consistent condom use during the last month.

An interdisciplinary integrated specialized one-stop outpatient clinic for idiopathic intracranial hypertension-a comprehensive assessment of clinical outcome

BACKGROUND AND PURPOSE

Management of idiopathic intracranial hypertension (IIH) is complex requiring multiple specialized disciplines. In practice, this creates considerable organizational and communicational challenges for healthcare professionals and patients. Thus, an interdisciplinary integrated outpatient clinic for IIH (comprising neurology, neuroophthalmology, neuroradiology, neurosurgery and endocrinology) was established with central coordination and a one-stop concept. Here, the aim was to evaluate the effects of this one-stop concept on objective clinical outcome.

METHODS

In a retrospective cohort study, the one-stop era with integrated care (IC) (1 July 2021 to 31 December 2022) was compared to a reference group receiving standard care (SC) (1 July 2018 to 31 December 2019) regarding visual impairment/worsening and headache improvement/freedom 6 months after diagnosis. Multivariate binary logistic regression models were used to adjust for confounders.

RESULTS

Baseline characteristics of the IC group (n = 85) and SC group (n = 81) were comparable (female 90.6% vs. 90.1%; mean age 33.6 vs. 32.8 years; median body mass index 31.8 vs. 33.0; median cerebrospinal fluid opening pressure 32 vs. 34 cmH2O; at diagnosis, visual impairment was present in 71.8% vs. 69.1% and chronic headache in 55.3% vs. 56.8% in IC vs. SC). IC was associated with a higher likelihood of achieving both headache improvement (odds ratio [OR] 2.24, 95% confidence interval [CI] 1.52-4.33, p < 0.001) and headache freedom (OR 1.75, 95% CI 1.11-3.09, p = 0.031). Regarding the risk of visual impairment and visual worsening IC was superior numerically but not statistically significantly (OR 0.87, 95% CI 0.69-1.16, p = 0.231, and OR 0.67, 95% CI 0.41-1.25, p = 0.354).

CONCLUSIONS

Interdisciplinary integrated care of IIH is favourably associated with headache outcomes and potentially also visual outcomes.

Efficacy of Combining Whole-body Vibration Training and Closed Kinetic Chain Exercises in Early Knee Osteoarthritis: A Preliminary Study

Objectives

We aimed to conduct a preliminary evaluation of the effectiveness of integrating whole-body vibration training (WBVT) into conventional closed kinetic chain (CKC) exercises as an intervention strategy for early knee osteoarthritis (KOA).

Methods

: This non-randomized comparative study conducted at an orthopedic clinic involved 53 patients (with Kellgren-Lawrence grades 1-2); 37 patients received only physical therapy (CKC group), and 16 patients received both physical therapy and WBVT (WBVT group). The primary outcome was the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) subscale score for pain, and the secondary outcomes were the WOMAC subscale score for physical function and muscle-strength assessments [isometric knee extension strength and the 30-second chair-stand test (CS-30) score]. Propensity score matching (PSM) was used to adjust for bias between the control and intervention groups.

Results

: After PSM adjustment, 13 patients were selected from each group. The WBVT group showed a significant improvement in the WOMAC pain score (d=1.16, P=0.007) and a significant increase in the CS-30 score (d=0.81, P=0.049). However, for the WOMAC physical function score, the between-group difference remained statistically insignificant (d=0.59, P=0.146).

Conclusions

: WBVT may be effective in reducing the pain of early KOA. WBVT is a non-invasive and convenient method, underscoring its potential as a novel therapeutic option.

Effectiveness of cladribine compared to fingolimod, natalizumab, ocrelizumab and alemtuzumab in relapsing-remitting multiple sclerosis

BACKGROUND

Comparisons between cladribine and other potent immunotherapies for multiple sclerosis (MS) are lacking.

OBJECTIVES

To compare the effectiveness of cladribine against fingolimod, natalizumab, ocrelizumab and alemtuzumab in relapsing-remitting MS.

METHODS

Patients with relapsing-remitting MS treated with cladribine, fingolimod, natalizumab, ocrelizumab or alemtuzumab were identified in the global MSBase cohort and two additional UK centres. Patients were followed for ⩾6/12 and had ⩾3 in-person disability assessments. Patients were matched using propensity score. Four pairwise analyses compared annualised relapse rates (ARRs) and disability outcomes.

RESULTS

The eligible cohorts consisted of 853 (fingolimod), 464 (natalizumab), 1131 (ocrelizumab), 123 (alemtuzumab) or 493 (cladribine) patients. Cladribine was associated with a lower ARR than fingolimod (0.07 vs. 0.12, p = 0.006) and a higher ARR than natalizumab (0.10 vs. 0.06, p = 0.03), ocrelizumab (0.09 vs. 0.05, p = 0.008) and alemtuzumab (0.17 vs. 0.04, p < 0.001). Compared to cladribine, the risk of disability worsening did not differ in patients treated with fingolimod (hazard ratio (HR) 1.08, 95% confidence interval (CI) 0.47-2.47) or alemtuzumab (HR 0.73, 95% CI 0.26-2.07), but was lower for patients treated with natalizumab (HR 0.35, 95% CI 0.13-0.94) and ocrelizumab (HR 0.45, 95% CI 0.26-0.78). There was no evidence for a difference in disability improvement.

CONCLUSION

Cladribine is an effective therapy that can be viewed as a step up in effectiveness from fingolimod, but is less effective than the most potent intravenous MS therapies.

On variance estimation of target population created by inverse probability weighting

Inverse probability weighting (IPW) is frequently used to reduce or minimize the observed confounding in observational studies. IPW creates a pseudo-sample by weighting each individual by the inverse of the conditional probability of receiving the treatment level that he/she has actually received. In the pseudo-sample there is no variation among the multiple individuals generated by weighting the same individual in the original sample. This would reduce the variability of the data and therefore bias the variance estimate in the target population. Conventional variance estimation methods for IPW estimators generally ignore this underestimation and tend to produce biased estimates of variance. We here propose a more reasonable method that incorporates this source of variability by using parametric bootstrapping based on intra-stratum variability estimates. This approach firstly uses propensity score stratification and intra-stratum standard deviation to approximate the variability among multiple individuals generated based on a single individual whose propensity score falls within the corresponding stratum. The parametric bootstrapping is then used to incorporate the target variability by re-generating outcomes after adding a random error term to the original data. The performance of the proposed method is compared with three existing methods including the naïve model-based variance estimator, the nonparametric bootstrap variance estimator, and the robust variance estimator in the simulation section. An example of patients with sarcopenia is used to illustrate the implementation of the proposed approach. According to the results, the proposed approach has desirable statistical properties and can be easily implemented using the provided R code.

Propensity Weighted federated learning for treatment effect estimation in distributed imbalanced environments

Estimating treatment effects from observational data in medicine using causal inference is a very relevant task due to the abundance of observational data and the ethical and cost implications of conducting randomized experiments or experimental interventions. However, how could we estimate the effect of a treatment in a hospital that has very restricted access to treatment? In this paper, we want to address the problem of distributed causal inference, where hospitals not only have different distributions of patients, but also different treatment assignment criteria. Furthermore, it is necessary to take into account that due to privacy restrictions, personal patient data cannot be shared between hospitals. To address this problem, we propose an adaptation of the federated learning algorithm FederatedAveraging to one of the most advanced models for the prediction of treatment effects based on neural networks, TEDVAE. Our algorithm adaptation takes into account the shift in the treatment distribution between hospitals and is therefore called Propensity WeightedFederatedAveraging (PW FedAvg). As the distributions of the assignment of treatments become more unbalanced between the nodes, the estimation of causal effects becomes more challenging. The experiments show that PW FedAvg manages to reduce errors in the estimation of individual causal effects when imbalances are large, compared to VanillaFedAvg and other federated learning-based causal inference algorithms based on the application of federated learning to linear parametric models, Gaussian Processes and Random Fourier Features.

An interdisciplinary integrated specialized one-stop outpatient clinic for idiopathic intracranial hypertension - a comprehensive assessment of patient satisfaction

BACKGROUND

Management of idiopathic intracranial hypertension (IIH) is complex requiring contributions from multiple specialized disciplines. In practice, this creates considerable organizational and communicational challenges. To meet those challenges, we established an interdisciplinary integrated outpatient clinic for IIH with a central coordination and a one-stop concept. Here, we aimed to evaluate effects of this one-stop concept on subjective patient satisfaction and economic outcome in patients with IIH.

METHODS

In a retrospective cohort study, we compared the one-stop era with integrated care (IC, 1-JUL-2021 to 31-DEC-2022) to a reference group receiving standard care (SC, 1-JUL-2018 to 31-DEC-2019) regarding subjective patient satisfaction (assessed by the Vienna Patient Inventory). Multivariable binary linear regression models were used to adjust for confounders.

RESULTS

Baseline characteristics of the IC group (n = 85) and SC group (n = 81) were comparable (female: 90.6% vs. 90.1%; mean age: 33.6 vs. 32.8 years, educational level: ≥9 years of education 60.0% vs. 59.3%; located in Vienna 75.3% vs. 76.5%). Compared to SC, management within IC concept was associated with statistically significantly higher subjective patient satisfaction (beta = 0.93; p < 0.001) with the strongest effects observed in satisfaction with treatment accessibility and availability (beta = 2.05; p < 0.001). Subgroup analyses of patients with migration background and language barrier consistently indicated stronger effects of IC in these groups.

CONCLUSIONS

Interdisciplinary integrated management of IIH statistically significantly and clinically meaningfully improves patient satisfaction - particularly in socioeconomically underprivileged patient groups. Providing structured central coordination to facilitate and improve access to interdisciplinary management provides means to further improve outcome.

Traumatic Brain Injury, Seizures, and Cognitive Impairment Among Older Adults

Importance

Traumatic brain injury (TBI), seizures, and dementia increase with age. There is a gap in understanding the associations of TBI, seizures, and medications such as antiseizure and antipsychotics with the progression of cognitive impairment across racial and ethnic groups.

Objective

To investigate the association of TBI and seizures with the risk of cognitive impairment among cognitively normal older adults and the role of medications in moderating the association.

Design, Setting, and Participants

This multicenter cohort study was a secondary analysis of the Uniform Data Set collected between June 1, 2005, and June 30, 2020, from the National Alzheimer's Coordination Center. Statistical analysis was performed from February 1 to April 3, 2024. Data were collected from participants from 36 Alzheimer's Disease Research Centers in the US who were 65 years or older at baseline, cognitively normal at baseline (Clinical Dementia Rating of 0 and no impairment based on a presumptive etiologic diagnosis of AD), and had complete information on race and ethnicity, age, sex, educational level, and apolipoprotein E genotype.

Exposure

Health history of TBI, seizures, or both conditions.

Main Outcomes and Measures

Progression to cognitive impairment measured by a Clinical Dementia Rating greater than 0.

Results

Among the cohort of 7180 older adults (median age, 74 years [range, 65-102 years]; 4729 women [65.9%]), 1036 were African American or Black (14.4%), 21 were American Indian or Alaska Native (0.3%), 143 were Asian (2.0%), 332 were Hispanic (4.6%), and 5648 were non-Hispanic White (78.7%); the median educational level was 16.0 years (range, 1.0-29.0 years). After adjustment for selection basis using propensity score weighting, seizure was associated with a 40% higher risk of cognitive impairment (hazard ratio [HR], 1.40; 95% CI, 1.19-1.65), TBI with a 25% higher risk of cognitive impairment (HR, 1.25; 95% CI, 1.17-1.34), and both seizure and TBI were associated with a 57% higher risk (HR, 1.57; 95% CI, 1.23-2.01). The interaction models indicated that Hispanic participants with TBI and seizures had a higher risk of cognitive impairment compared with other racial and ethnic groups. The use of antiseizure medications (HR, 1.23; 95% CI, 0.99-1.53), antidepressants (HR, 1.32; 95% CI, 1.17-1.50), and antipsychotics (HR, 2.15; 95% CI, 1.18-3.89) was associated with a higher risk of cognitive impairment, while anxiolytic, sedative, or hypnotic use (HR, 0.88; 95% CI, 0.83-0.94) was associated with a lower risk.

Conclusions and Relevance

This study highlights the importance of addressing TBI and seizures as risk factors for cognitive impairment among older adults. Addressing the broader social determinants of health and bridging the health divide across various racial and ethnic groups are essential for the comprehensive management and prevention of dementia.

Up-front matching: an ongoing recruitment method for prospective observational studies that mimics randomization for selected baseline covariates

In a prospective observational study (POS) designed to assess the average causal effect of a treatment (e.g. Drug A) compared to a comparator (e.g. Drug B) in the treatment population, enrolling all patients who are assigned to the treatments of interest for follow-up has a potentially large negative impact on the statistical efficiency and bias of the analysis of the outcomes and on the cost of the study. "Up-front matching" is an innovative enrollment method for selecting patients for long-term follow-up among those who have already been assigned to treatment or comparator which uses frequency matching and hence avoids the restrictions of individual matching that other methods have used. To achieve potential statistical and logistical efficiencies in the POS, in up-front matching, a target population is defined based on a retrospective database which then enables selecting populations of patients for follow-up that have desirable statistical properties. In particular, the resulting populations of patients who are enrolled look like the population of treatment patients were randomized to treatment or comparator for the baseline covariates that are used to select patients for follow-up. The method is illustrated in detail for a study designed to assess the effect of injectable antipsychotics versus oral antipsychotics.

Despite Increased Disease Activity, Women who Attended a Dedicated Inflammatory Bowel Disease and Pregnancy Clinic Had Infants With Higher Apgar Scores: A Population-Based Study

BACKGROUND

Attendance at a subspecialty pregnancy clinic for women with inflammatory bowel disease (IBD) improves disease-specific pregnancy knowledge. We examined the impact of attendance at a dedicated IBD-pregnancy clinic on IBD and perinatal outcomes.

METHODS

Using linked administrative databases in Alberta, Canada (2012-2019), we identified 1061 pregnant women with IBD who delivered singleton liveborn infants in-hospital who did (n = 314) and did not attend (n = 747) the clinic. Propensity score weighted multivariable log-binomial and multinomial logistic regression models were used to determine the risk of IBD and perinatal outcomes.

RESULTS

The median number of clinic visits was 3 (Q1-Q3, 3-5), with 34.7% completing a preconception consultation. A greater proportion of women who attended lived near the clinic, were nulliparous, had a disease flare prior to pregnancy, and were on maintenance IBD medication (P < .05). Women who attended had increased risks of a disease flare during pregnancy (adjusted risk ratio [aRR], 2.02; 95% CI, 1.45-2.82), an IBD-related emergency department visit during pregnancy (aRR, 2.66; 95% CI, 1.92-3.68), and cesarean delivery (aRR, 1.78; 95% CI, 1.23-2.57). Despite this, clinic attendees had a decreased risk of delivering an infant with a low Apgar score at 1 minute (risk ratio [RR], 0.49; 95% CI, 0.32-0.76) and 5 minutes (RR, 0.32; 95% CI, 0.12-0.87).

CONCLUSIONS

Women who attended a dedicated IBD-pregnancy clinic were more likely to have a disease flare prior to pregnancy, reflecting a more severe disease phenotype, but had similar perinatal outcomes and infants with better Apgar scores at birth. Our study suggests the value of these subspecialty clinics in providing enhanced IBD-specific prenatal care.

Revisiting the Harm of Hate: A Quasi-Experimental Approach Using the National Crime Victimization Survey

Early legal challenges to the 1990 Hate Crime Statistics Act were originally excused on the argument that hate crimes "hurt more," but there remain some empirical gaps on this topic. Although many works have concluded that biased offenders cause greater harms to their victims relative to unbiased perpetrators, this effect tends to be sensitive to individual and situational factors like victim and offender characteristics, bias motivation, weapon use, or crime location. This type of confounding has the potential to introduce selection bias in the estimation of victimization harms among biased criminal incidents. With data from the National Crime Victimization Survey (2010-2020), I use propensity scores and inverse-probability weighting to show that, on average, victims of bias motivated offenses are more likely to report later physical and emotional harms despite not suffering greater initial injury in incidence. Findings also demonstrate that the harm of hate varies across different bias motivations, with such crimes directed toward those on the basis of disability, gender, and sexual orientation causing greater short- and long-term individual trauma and damage.

Contemporary Prestroke Dual Antiplatelet Use and Symptomatic Intracerebral Hemorrhage Risk After Thrombolysis

Importance

Intravenous alteplase (IV-tPA) can be administered to patients with acute ischemic stroke but is associated with symptomatic intracerebral hemorrhage (sICH). It is unclear if patients taking prestroke dual antiplatelet therapy (DAPT) are at higher risk of sICH.

Objective

To determine the associated risk of sICH in patients taking prestroke dual antiplatelet therapy receiving alteplase for acute ischemic stroke using propensity score matching analysis.

Design, Setting, and Participants

This cohort study used data from the American Heart Association and American Stroke Association Get With The Guidelines-Stroke (GWTG-Stroke) registry between 2013 and 2021. Data were obtained from hospitals in the GWTG-Stroke registry. This study included patients hospitalized with acute ischemic stroke and treated with IV-tPA. Data were analyzed from January 2013 to December 2021.

Exposures

Prestroke DAPT before treatment with IV-tPA for acute ischemic stroke.

Main Outcome Measures

sICH, In-hospital death, discharge modified Rankin scale score, and other life-threatening systemic hemorrhages.

Results

Of 409 673 participants, 321 819 patients (mean [SD] age, 68.6 [15.1] years; 164 587 female [51.1%]) who were hospitalized with acute ischemic stroke and treated with IV-tPA were included in the analysis. The rate of sICH was 2.9% (5200 of 182 344), 3.8% (4457 of 117 670), and 4.1% (893 of 21 805) among patients treated with no antiplatelet therapy, single antiplatelet therapy (SAPT), and DAPT, respectively (P < .001). In adjusted analyses after propensity score subclassification, both SAPT (odds ratio [OR], 1.13; 95% CI, 1.07-1.19) and DAPT (OR, 1.28; 95% CI, 1.14-1.42) were associated with increased risks of sICH. Prestroke antiplatelet medications were associated with lower odds of discharge mRS score of 2 or less compared with no medication (SAPT OR, 0.92; 95% CI, 0.90-0.95; DAPT OR, 0.94; 95% CI, 0.88-0.98). Results of a subgroup analysis of patients taking DAPT exposed to aspirin-clopidogrel vs aspirin-ticagrelor combination therapy were not significant (OR, 1.35; 95% CI, 0.84-1.86).

Conclusions and Relevance

Prestroke DAPT was associated with a significantly elevated risk of sICH among patients with ischemic stroke who were treated with thrombolysis; however, the absolute increase in risk was small. Patients exposed to antiplatelet medications did not have excess sICH compared with landmark trials, which demonstrated overall clinical benefit of thrombolysis therapy for acute ischemic stroke.

Tackling Challenges in Assessing the Economic Value of Tumor-Agnostic Therapies: A Cost-Effectiveness Analysis of Pembrolizumab as a Case Study

OBJECTIVES

Assessing the value of tumor-agnostic drugs (TAD) is challenging given the potential variability in treatment effects, trials with small sample sizes, different standards of care (SoC), and lack of comparative data from single-arm basket trials. Our study developed and applied novel methods to assess the value of pembrolizumab compared with SoC to inform coverage decisions.

METHODS

We developed a partitioned survival model to evaluate the cost-utility of pembrolizumab for previously treated patients with 8 advanced or metastatic microsatellite instability-high or mismatch repair-deficient cancers from a US commercial payer perspective. Efficacy of pembrolizumab was based on data from trials directly or with adjustment using Bayesian hierarchical models. Eight chemotherapy-based external control arms were constructed from the TriNetX electronic health record databases. Tumor-specific health-state utility values were applied. All costs were adjusted to 2022 US dollars.

RESULTS

At a lifetime horizon, pembrolizumab was associated with increased effectiveness compared with chemotherapies in colorectal (quality-adjusted life years [QALYs]: +0.64, life years [LYs]: +0.64), endometrial (QALYs: +3.79, LYs: +5.47), and small intestine cancers (QALYs: +1.73, LYs: +2.48), but not for patients with metastatic gastric, cholangiocarcinoma, pancreatic, ovarian, and brain cancers. Incremental cost-effectiveness ratios varied substantially across tumor types. Pembrolizumab was found to be cost-effective in treating colorectal and endometrial cancers (incremental cost-effectiveness ratios: $121 967 and $139 257, respectively), and not cost-effective for other assessed cancers at a $150 000 willingness-to-pay/QALY threshold, compared with SoC chemotherapies.

CONCLUSIONS

The cost-effectiveness of TADs can vary by cancers. Using analytic tools such as external controls and Bayesian hierarchical models can tackle several challenges in assessing the value of TADs and uncertainties from basket trials.

Improving Inverse Probability Weighting by Post-calibrating Its Propensity Scores

Theoretical guarantees for causal inference using propensity scores are partially based on the scores behaving like conditional probabilities. However, prediction scores between zero and one do not necessarily behave like probabilities, especially when output by flexible statistical estimators. We perform a simulation study to assess the error in estimating the average treatment effect before and after applying a simple and well-established postprocessing method to calibrate the propensity scores. We observe that postcalibration reduces the error in effect estimation and that larger improvements in calibration result in larger improvements in effect estimation. Specifically, we find that expressive tree-based estimators, which are often less calibrated than logistic regression-based models initially, tend to show larger improvements relative to logistic regression-based models. Given the improvement in effect estimation and that postcalibration is computationally cheap, we recommend its adoption when modeling propensity scores with expressive models.

On variance estimation of the inverse probability-of-treatment weighting estimator: A tutorial for different types of propensity score weights

Propensity score methods, such as inverse probability-of-treatment weighting (IPTW), have been increasingly used for covariate balancing in both observational studies and randomized trials, allowing the control of both systematic and chance imbalances. Approaches using IPTW are based on two steps: (i) estimation of the individual propensity scores (PS), and (ii) estimation of the treatment effect by applying PS weights. Thus, a variance estimator that accounts for both steps is crucial for correct inference. Using a variance estimator which ignores the first step leads to overestimated variance when the estimand is the average treatment effect (ATE), and to under or overestimated estimates when targeting the average treatment effect on the treated (ATT). In this article, we emphasize the importance of using an IPTW variance estimator that correctly considers the uncertainty in PS estimation. We present a comprehensive tutorial to obtain unbiased variance estimates, by proposing and applying a unifying formula for different types of PS weights (ATE, ATT, matching and overlap weights). This can be derived either via the linearization approach or M-estimation. Extensive R code is provided along with the corresponding large-sample theory. We perform simulation studies to illustrate the behavior of the estimators under different treatment and outcome prevalences and demonstrate appropriate behavior of the analytical variance estimator. We also use a reproducible analysis of observational lung cancer data as an illustrative example, estimating the effect of receiving a PET-CT scan on the receipt of surgery.

Identifying Veterans Who Benefit From Nirmatrelvir-Ritonavir: A Target Trial Emulation

BACKGROUND

Nirmatrelvir-ritonavir is recommended for persons at risk for severe coronavirus disease 2019 (COVID-19) but remains underutilized. Information on which eligible groups are likely to benefit from treatment is needed.

METHODS

We conducted a target trial emulation study in the Veterans Health Administration comparing nirmatrelvir-ritonavir treated versus matched untreated veterans at risk for severe COVID-19 who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from April 2022 through March 2023. We measured incidence of any hospitalization or all-cause mortality at 30 days. Outcomes were measured for the entire cohort, as well as among subgroups defined by 30-day risk of death or hospitalization, estimated using an ensemble risk prediction model.

RESULTS

Participants were 87% male with median age 66 years and 16% unvaccinated. Compared with matched untreated participants, those treated with nirmatrelvir-ritonavir (n = 24 205) had a lower 30-day risk for hospitalization (1.80% vs 2.30%; risk difference [RD], -0.50% points [95% confidence interval {CI}: -.69 to -.35]) and death (0.11% vs 0.30%; RD, -0.20 [95% CI: -.24 to -.13]). The greatest reductions in combined hospitalization or death were observed in the highest risk quartile (RD -2.85 [95% CI: -3.94 to -1.76]), immunocompromised persons (RD -1.91 [95% CI: -3.09 to -.74]), and persons aged ≥75 years (RD -1.16 [95% CI: -1.73 to -.59]). No reductions were observed in the 2 lowest risk quartiles or persons younger than 65 years.

CONCLUSIONS

Nirmatrelvir-ritonavir was effective in reducing 30-day hospitalization and death in older veterans, those at highest predicted risk for severe outcomes, and immunocompromised groups. Benefit was not observed in younger veterans or groups at lower predicted risk for hospitalization and death.

Causal Inference About the Effects of Interventions From Observational Studies in Medical Journals

Importance

Many medical journals, including JAMA, restrict the use of causal language to the reporting of randomized clinical trials. Although well-conducted randomized clinical trials remain the preferred approach for answering causal questions, methods for observational studies have advanced such that causal interpretations of the results of well-conducted observational studies may be possible when strong assumptions hold. Furthermore, observational studies may be the only practical source of information for answering some questions about the causal effects of medical or policy interventions, can support the study of interventions in populations and settings that reflect practice, and can help identify interventions for further experimental investigation. Identifying opportunities for the appropriate use of causal language when describing observational studies is important for communication in medical journals.

Observations

A structured approach to whether and how causal language may be used when describing observational studies would enhance the communication of research goals, support the assessment of assumptions and design and analytic choices, and allow for more clear and accurate interpretation of results. Building on the extensive literature on causal inference across diverse disciplines, we suggest a framework for observational studies that aim to provide evidence about the causal effects of interventions based on 6 core questions: what is the causal question; what quantity would, if known, answer the causal question; what is the study design; what causal assumptions are being made; how can the observed data be used to answer the causal question in principle and in practice; and is a causal interpretation of the analyses tenable?

Conclusions and Relevance

Adoption of the proposed framework to identify when causal interpretation is appropriate in observational studies promises to facilitate better communication between authors, reviewers, editors, and readers. Practical implementation will require cooperation between editors, authors, and reviewers to operationalize the framework and evaluate its effect on the reporting of empirical research.

High-dimensional mediation analysis for continuous outcome with confounders using overlap weighting method in observational epigenetic study

BACKGROUND

Mediation analysis is a powerful tool to identify factors mediating the causal pathway of exposure to health outcomes. Mediation analysis has been extended to study a large number of potential mediators in high-dimensional data settings. The presence of confounding in observational studies is inevitable. Hence, it's an essential part of high-dimensional mediation analysis (HDMA) to adjust for the potential confounders. Although the propensity score (PS) related method such as propensity score regression adjustment (PSR) and inverse probability weighting (IPW) has been proposed to tackle this problem, the characteristics with extreme propensity score distribution of the PS-based method would result in the biased estimation.

METHODS

In this article, we integrated the overlapping weighting (OW) technique into HDMA workflow and proposed a concise and powerful high-dimensional mediation analysis procedure consisting of OW confounding adjustment, sure independence screening (SIS), de-biased Lasso penalization, and joint-significance testing underlying the mixture null distribution. We compared the proposed method with the existing method consisting of PS-based confounding adjustment, SIS, minimax concave penalty (MCP) variable selection, and classical joint-significance testing.

RESULTS

Simulation studies demonstrate the proposed procedure has the best performance in mediator selection and estimation. The proposed procedure yielded the highest true positive rate, acceptable false discovery proportion level, and lower mean square error. In the empirical study based on the GSE117859 dataset in the Gene Expression Omnibus database using the proposed method, we found that smoking history may lead to the estimated natural killer (NK) cell level reduction through the mediation effect of some methylation markers, mainly including methylation sites cg13917614 in CNP gene and cg16893868 in LILRA2 gene.

CONCLUSIONS

The proposed method has higher power, sufficient false discovery rate control, and precise mediation effect estimation. Meanwhile, it is feasible to be implemented with the presence of confounders. Hence, our method is worth considering in HDMA studies.

Comparison of two propensity score-based methods for balancing covariates: the overlap weighting and fine stratification methods in real-world claims data

BACKGROUND

Two propensity score (PS) based balancing covariate methods, the overlap weighting method (OW) and the fine stratification method (FS), produce superb covariate balance. OW has been compared with various weighting methods while FS has been compared with the traditional stratification method and various matching methods. However, no study has yet compared OW and FS. In addition, OW has not yet been evaluated in large claims data with low prevalence exposure and with low frequency outcomes, a context in which optimal use of balancing methods is critical. In the study, we aimed to compare OW and FS using real-world data and simulations with low prevalence exposure and with low frequency outcomes.

METHODS

We used the Texas State Medicaid claims data on adult beneficiaries with diabetes in 2012 as an empirical example (N = 42,628). Based on its real-world research question, we estimated an average treatment effect of health center vs. non-health center attendance in the total population. We also performed simulations to evaluate their relative performance. To preserve associations between covariates, we used the plasmode approach to simulate outcomes and/or exposures with N = 4,000. We simulated both homogeneous and heterogeneous treatment effects with various outcome risks (1-30% or observed: 27.75%) and/or exposure prevalence (2.5-30% or observed:10.55%). We used a weighted generalized linear model to estimate the exposure effect and the cluster-robust standard error (SE) method to estimate its SE.

RESULTS

In the empirical example, we found that OW had smaller standardized mean differences in all covariates (range: OW: 0.0-0.02 vs. FS: 0.22-3.26) and Mahalanobis balance distance (MB) (< 0.001 vs. > 0.049) than FS. In simulations, OW also achieved smaller MB (homogeneity: <0.04 vs. > 0.04; heterogeneity: 0.0-0.11 vs. 0.07-0.29), relative bias (homogeneity: 4.04-56.20 vs. 20-61.63; heterogeneity: 7.85-57.6 vs. 15.0-60.4), square root of mean squared error (homogeneity: 0.332-1.308 vs. 0.385-1.365; heterogeneity: 0.263-0.526 vs 0.313-0.620), and coverage probability (homogeneity: 0.0-80.4% vs. 0.0-69.8%; heterogeneity: 0.0-97.6% vs. 0.0-92.8%), than FS, in most cases.

CONCLUSIONS

These findings suggest that OW can yield nearly perfect covariate balance and therefore enhance the accuracy of average treatment effect estimation in the total population.

Migration, Gender, and Families: The Effects of Spousal Migration on Women's Empowerment

Labor migration has a profound effect on families, but evidence documenting the impact of migration on women left behind is still lacking. Utilizing the Matlab Health and Socioeconomic Surveys, we examined the roles of migration and families in four domains of empowerment for women in Bangladesh. We found that women with international migrant spouses saw significant improvements in economic empowerment, mobility, and decision-making relative to women with coresident spouses (p < .0001). However, women who lived in multigenerational households with their parents or in-laws experienced significant reductions in empowerment across these three domains. Both having a migrant spouse and living in a multigenerational household had negative effects on beliefs about gender equivalence and reduced joint decision-making for women. Results, which were robust to migration selection controls (including propensity approaches), indicate that the benefits of migration for women left behind might be diluted by family structures that perpetuate unequal gender dynamics.

Win Statistics in Observational Cancer Research: Integrating Clinical and Quality-of-Life Outcomes

Background: Quality-of-life metrics are increasingly important for oncological patients alongside traditional endpoints like mortality and disease progression. Statistical tools such as Win Ratio, Win Odds, and Net Benefit prioritize clinically significant outcomes using composite endpoints. In randomized trials, Win Statistics provide fair comparisons between treatment and control groups. However, their use in observational studies is complicated by confounding variables. Propensity score (PS) matching mitigates confounding variables but may reduce the sample size, affecting the power of win statistics analyses. Alternatively, PS matching can stratify samples, preserving the sample size. This study aims to assess the long-term impact of these methods on decision making, particularly in colorectal cancer patients. Methods: A motivating example involves a cohort of patients from the ReSARCh observational study (2016-2021) with locally advanced adenocarcinoma of the rectum, situated up to 12 cm from the anal verge. These patients underwent either a watch-and-wait approach (WW) or trans-anal local excision (LE). Win statistics compared the effects of WW and LE on a composite outcome (overall survival, recurrence, presence of ostomy, and rectum excision). For matched win statistics, we used robust inference techniques proposed by Matsouaka et al. (2022), and for stratified win statistics, we applied the method proposed by Dong et al. (2018). A simulation study assessed the coverage probability of matched and stratified win statistics in balanced and unbalanced groups, calculating how often the confidence intervals included the true values of WR, NB, and WO across 1000 simulations. Results: The results suggest a better efficacy of the LE approach when considering efficacy outcomes alone (WR: 0.47 (0.01 to 1.14); NB: -0.16 (-0.34 to 0.02); and WO: 0.73 (0.5 to 1.05)). However, when QoL outcomes are included in the analyses, the estimates are closer to 1 (WR: 0.87 (0.06 to 2.06); WO: 0.93 (0.61 to 1.4)) and to 0 (NB: -0.04 (-0.25 to 0.17)), indicating a negative impact of the treatment effect of LE regarding the presence of ostomy and the excision of the rectum. Moreover, based on the simulation study, our findings underscore the superior performance of matched compared to stratified win statistics in terms of coverage probability (matched WR: 97% vs. stratified WR: 33.3% in a high-imbalance setting; matched WR: 98% vs. stratified WR: 34.4% in a medium-imbalance setting; and matched WR: 99.2% vs. stratified WR: 37.4% in a low-imbalance setting). Conclusions: In conclusion, our study sheds light on the interpretation of the results of win statistics in terms of statistical significance, providing insights into the application of pairwise comparison in observational settings, promoting its use to improve outcomes for cancer patients.

An interdisciplinary integrated specialized one-stop outpatient clinic for idiopathic intracranial hypertension - an assessment of sick leave, presenteeism, and health care utilization

BACKGROUND

Management of idiopathic intracranial hypertension (IIH) is complex requiring contributions from multiple specialized disciplines. In practice, this creates considerable organizational and communicational challenges. To meet those challenges, we established an interdisciplinary integrated outpatient clinic for IIH with a central coordination and a one-stop- concept. Here, we aimed to evaluate effects of this concept on sick leave, presenteeism, and health care utilization.

METHODS

In a retrospective cohort study, we compared the one-stop era with integrated care (IC, 1-JUL-2021 to 31-DEC-2022) to a reference group receiving standard care (SC, 1-JUL-2018 to 31-DEC-2019) regarding economic outcome parameters assessed over 6 months. Multivariate binary logistic regression models were used to adjust for confounders.

RESULTS

Baseline characteristics of the IC group (n = 85) and SC group (n = 81) were comparable (female: 90.6% vs. 90.1%; mean age: 33.6 vs. 32.8 years, educational level: ≥9 years of education 60.0% vs. 59.3%; located in Vienna 75.3% vs. 76.5%). Compared to SC, the IC group showed significantly fewer days with sick leave or presenteeism (-5 days/month), fewer unscheduled contacts for IIH-specific problems (-2.3/month), and fewer physician or hospital contacts in general (-4.1 contacts/month). Subgroup analyses of patients with migration background and language barrier consistently indicated stronger effects of the IC concept in these groups.

CONCLUSIONS

Interdisciplinary integrated management significantly improves the burden of IIH in terms of sick leave, presenteeism and healthcare consultations - particularly in socioeconomically underprivileged patient groups.

Contrast-specific propensity scores for causal inference with multiple interventions

Existing methods that use propensity scores for heterogeneous treatment effect estimation on non-experimental data do not readily extend to the case of more than two treatment options. In this work, we develop a new propensity score-based method for heterogeneous treatment effect estimation when there are three or more treatment options, and prove that it generates unbiased estimates. We demonstrate our method on a real patient registry of patients in Singapore with diabetic dyslipidemia. On this dataset, our method generates heterogeneous treatment recommendations for patients among three options: Statins, fibrates, and non-pharmacological treatment to control patients' lipid ratios (total cholesterol divided by high-density lipoprotein level). In our numerical study, our proposed method generated more stable estimates compared to a benchmark method based on a multi-dimensional propensity score.

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.

Accelerating drug development at Bristol Myers Squibb through innovation

This paper focuses on the use of novel technologies and innovative trial designs to accelerate evidence generation and increase pharmaceutical Research and Development (R&D) productivity, at Bristol Myers Squibb. We summarize learnings with case examples, on how we prepared and continuously evolved to address the increasing cost, complexities, and external pressures in drug development, to bring innovative medicines to patients much faster. These learnings were based on review of internal efforts toward accelerating R&D focusing on four key areas: adopting innovative trial designs, optimizing trial designs, leveraging external control data, and implementing novel methods using artificial intelligence and machine learning.

The Next Horizon of Drug Development: External Control Arms and Innovative Tools to Enrich Clinical Trial Data

Conducting clinical trials (CTs) has become increasingly costly and complex in terms of designing and operationalizing. These challenges exist in running CTs on novel therapies, particularly in oncology and rare diseases, where CTs increasingly target narrower patient groups. In this study, we describe external control arms (ECA) and other relevant tools, such as virtualization and decentralized clinical trials (DCTs), and the ability to follow the clinical trial subjects in the real world using tokenization. ECAs are typically constructed by identifying appropriate external sources of data, then by cleaning and standardizing it to create an analysis-ready data file, and finally, by matching subjects in the external data with the subjects in the CT of interest. In addition, ECA tools also include subject-level meta-analysis and simulated subjects' data for analyses. By implementing the recent advances in digital health technologies and devices, virtualization, and DCTs, realigning of CTs from site-centric designs to virtual, decentralized, and patient-centric designs can be done, which reduces the patient burden to participate in the CTs and encourages diversity. Tokenization technology allows linking the CT data with real-world data (RWD), creating more comprehensive and longitudinal outcome measures. These tools provide robust ways to enrich the CT data for informed decision-making, reduce the burden on subjects and costs of trial operations, and augment the insights gained for the CT data.

Updated Trends in the Utilization of Brachytherapy in Cervical Cancer in the United States: A Surveillance, Epidemiology, and End-Results Study

PURPOSE

Our previous Surveillance, Epidemiology, and End Results (SEER) study revealed a concerning decline in brachytherapy utilization in the United States between 1988 and 2009. This study evaluates recent trends in brachytherapy utilization in cervical cancer and identifies factors and survival benefit associated with the use of brachytherapy treatment.

METHODS AND MATERIALS

Using SEER data, 8500 patients with International Federation of Gynecologists and Obstetricians 2009 stage IB2-IVA cervical cancer treated with external beam radiation therapy (EBRT) between 2000 and 2020 were identified. Logistic regression analysis was performed on potential factors associated with brachytherapy use: age, marital status, race, ethnicity, income, metropolitan status, year of diagnosis, SEER region, histology, grade, and stage. To adjust for differences between patients who received brachytherapy and those who did not, propensity-score matching was used. Multivariable Cox regression analysis assessed the association of brachytherapy use with cervical cancer-specific mortality (CSM) and all-cause mortality (ACM) in the matched cohort.

RESULTS

Sixty-four percent of the 8500 women received brachytherapy in combination with EBRT; 36% received EBRT alone. The brachytherapy utilization rate declined sharply in 2003/2004 (lowest rate 44% in 2003) and then gradually improved especially in 2018 to 2020 (76%). Factors associated with higher odds of brachytherapy use included younger age, married (vs single), later years of diagnosis, certain SEER regions, and earlier stage. In the propensity-score matched cohort, brachytherapy treatment was associated with lower 4-year cumulative incidence of cancer death (32.1% vs 43.4%; P < .001) and better overall survival (64.0% vs 51.4%; P < .001). Brachytherapy treatment was independently associated with lower CSM (hazard ratio, 0.70; 95% CI, 0.64-0.76; P < .001) and ACM (hazard ratio, 0.72; 95% CI, 0.67-0.78; P < .001).

CONCLUSIONS

Brachytherapy utilization among SEER regions has improved since 2004 in patients with stage IB2-IVA cervical cancer. Brachytherapy use remains independently associated with significantly lower CSM and ACM and is an essential component of treatment for patients with locally advanced cervical cancer.

Beyond the Surface: Intimate Partner Violence Typology and Recent Depression

Depression and intimate partner violence (IPV) are highly related. However, it is unclear what drives this relationship: the form of violence (psychological, physical, or sexual) or its severity. In this study, we first identify patterns of combined forms and severity of violence and then estimate the effects of IPV on depression. We use the DHS and focus on Peru, a country with high IPV rates. Five classes of IPV were identified. The more intense the IPV class, the higher the effect on recent depression. However, the effect on depression tends to be smaller when levels of depression are higher.

Impact assessment of mandatory safety device installation for gas stoves

Numerous fire accidents have occurred in Japan owing to food overheating when cooking on gas stoves because users left the cooking area unattended. In response, authorities enacted a legal revision mandating temperature sensor installation on gas stove burners. Nevertheless, the actual effectiveness of this measure remains uncertain. Furthermore, prior studies have raised concerns about the efficacy of specific safety standards for consumer products owing to insufficient evidence of reduction in accidents. Consequently, this study seeks to assess the impact of the standards revision implemented in 2008, requiring the placement of safety devices on all gas stove burners. Through a comprehensive analysis, it was aimed to ascertain how these measures have precisely influenced safety outcomes in cooking-related incidents. The data in this study were subdivided to mitigate potential bias from user attributes during data collection. The analysis employed the difference-in-differences method, specifically utilizing one-burner gas stoves unaffected by the standards revision. The data used in this study include accidents associated with gas stoves, spanning the period 2007-2019. To estimate the likelihood of overheating accidents, a binomial distribution model that utilized the Markov chain Monte Carlo methods was applied. For gas stoves with two or more burners, which were affected by the standards revision, the estimated probability of overheating accidents decreased by approximately 80%. In contrast, no decreasing trend was observed for one-burner gas stoves. The analysis suggests that the mandatory installation of safety devices on gas stoves has indeed resulted in a significant reduction in overheating accidents.

Effectiveness of targeted intervention program under the national AIDS control program among Hijra and transgender population: Evidence from Integrated Biological and Behavioral Surveillance, 2014-15

INTRODUCTION

The hijra and transgender (H/TG) population in India is vulnerable to HIV/AIDS. India had instituted a targeted intervention (TI) program to reduce this vulnerability. We aimed to measure the effectiveness of the TI program for H/TG.

MATERIALS AND METHODS

The National Integrated Behavioral and Biological Survey (IBBS) was carried out in 2014-15. H/TG data from IBBS was analyzed. Bivariate and multivariate logistic regression were used to calculate the unadjusted and adjusted odds ratios with 95% confidence interval. Condom use during the last sexual intercourse, and the consistent condom use in the last one month were considered as indicators of program effectiveness. The Propensity Score Matching (PSM) method was used to assess the effectiveness.

RESULTS

We found that the participants who had received condoms from peer educator/outreach worker were 1.74 and 1.40 times more likely to use condoms in the last sexual intercourse (aOR: 1.74, CI: 1.35 - 2.26) and consistent condom use in the last one month (aOR: 1.40, CI: 1.12 - 1.74) respectively compared to the participants who did not receive the condom. The matched-samples estimate (i.e., average treatment effect on treated) for the condom use during the last sexual intercourse increased by 13.0%, i.e., 0.13 (CI; 0.08 - 0.18) and consistent condom use in the last one month increased by 5.0%, i.e., 0.05 (CI; 0.00 - 0.10) among those who had received condoms from the peer educator/outreach worker compared with those who had not received condom, respectively.

CONCLUSIONS

The TI program intervention for H/TG was effective in reducing HIV risk behavior as evidenced by increase in use of condom during last sexual intercourse, and consistent condom use in the last one month.

Dysphagia and Functional Limitations Among Adults in the United States: Findings from the 2022 National Health Interview Survey

Dysphagia or swallowing dysfunction is associated with reduced quality of life and poor long term outcomes. While standard dysphagia treatment focuses on improving swallowing function, it is not clear if people with dysphagia also have difficulties performing daily tasks. This study aimed to determine if individuals with dysphagia had difficulties with participating in daily tasks requiring physical function, as compared to those with no dysphagia. We conducted a secondary data analysis using the responses of 24,107 adults aged 18 years or older who completed the 2022 National Health Interview Survey. The independent variable was report of swallowing problem during the past 12 months, and the dependent variables were report of difficulty in physical function tasks (e.g., self-care, mobility, working, social participation). We utilized propensity score methods to balance demographic and clinical variables between groups, and examined if individuals with dysphagia had more difficulties with the physical function tasks. The propensity score methods balanced the demographic and clinical variables (absolute standardized differences < 0.1). People with dysphagia had significantly higher odds ratios (ranged from 1.23 to 1.70, all p < 0.05) of having difficulties in physical function tasks than those without dysphagia. The findings revealed an association between experiencing dysphagia and encountering difficulties in self-care, mobility, working, and social participation in the general adult population in the US. Results of our study indicate that during the course of rehabilitation, healthcare professionals should consider the potential impact of dysphagia symptoms on clients' ability to partake in independent activities in their community settings.

Meta-analysis on studies with heterogeneous and partially observed covariates

Individual participant data meta-analysis is a commonly used alternative to the traditional aggregate data meta-analysis. It is popular because it avoids relying on published results and enables direct adjustment for relevant covariates. However, a practical challenge is that the studies being combined often vary in terms of the potential confounders that were measured. Furthermore, it will inevitably be the case that some individuals have missing values for some of those covariates. In this paper, we demonstrate how these challenges can be resolved using a propensity score approach, combined with multiple imputation, as a strategy to adjust for covariates in the context of individual participant data meta-analysis. To illustrate, we analyze data from the Bill and Melinda Gates Foundation-funded Healthy Birth, Growth, and Development Knowledge Integration project to investigate the relationship between physical growth rate in the first year of life and cognition measured later during childhood. We found that the overall effect of average growth velocity on cognitive outcome is slightly, but significantly, positive with an estimated effect size of 0.36 (95% CI 0.18, 0.55).

Propensity score stratified MAP prior and posterior inference for incorporating information across multiple potentially heterogeneous data sources

Incorporation of external information is becoming increasingly common when designing clinical trials. Availability of multiple sources of information has inspired the development of methodologies that account for potential heterogeneity not only between the prospective trial and the pooled external data sources but also between the different external data sources themselves. Our approach proposes an intuitive way of handling such a scenario for the continuous outcomes setting by using propensity score-based stratification and then utilizing robust meta-analytic predictive priors for each stratum to incorporate the prior data to distinguish among different external data sources in each stratum. Through extensive simulations, our approach proves to be more efficient and less biased than the currently available methods. A real case study using clinical trials that study schizophrenia from multiple different sources is also included.

Propensity score-incorporated adaptive design approaches when incorporating real-world data

The propensity score-integrated composite likelihood (PSCL) method is one method that can be utilized to design and analyze an application when real-world data (RWD) are leveraged to augment a prospectively designed clinical study. In the PSCL, strata are formed based on propensity scores (PS) such that similar subjects in terms of the baseline covariates from both the current study and RWD sources are placed in the same stratum, and then composite likelihood method is applied to down-weight the information from the RWD. While PSCL was originally proposed for a fixed design, it can be extended to be applied under an adaptive design framework with the purpose to either potentially claim an early success or to re-estimate the sample size. In this paper, a general strategy is proposed due to the feature of PSCL. For the possibility of claiming early success, Fisher's combination test is utilized. When the purpose is to re-estimate the sample size, the proposed procedure is based on the test proposed by Cui, Hung, and Wang. The implementation of these two procedures is demonstrated via an example.

Development of a comorbidity index for patients undergoing abdominal aortic aneurysm repair

BACKGROUND

Endovascular aneurysm repair (EVAR) and open surgical repair (OSR) are two modalities to treat patients with abdominal aortic aneurysm (AAA). Alternative to individual comorbidity adjustment, a summary comorbidity index is a weighted composite score of all comorbidities that can be used as standard metric to control for comorbidity burden in clinical studies. This study aimed to develop summary comorbidity indices for patients who underwent AAA repair.

METHODS

Patients who went under EVAR or OSR were identified in National Inpatient Sample (NIS) between the last quarter of 2015 to 2020. In each group, patients were randomly sampled into experimental (2/3) and validation (1/3) groups. The weights of Elixhauser comorbidities were determined from a multivariable logistic regression and single comorbidity indices were developed for EVAR and OAR groups, respectively.

RESULTS

There were 34,668 patients underwent EVAR (2.19% mortality) and 4792 underwent OSR (10.98% mortality). Both comorbidity indices had moderate discriminative power (EVAR c-statistic, 0.641; 95% confidence interval [CI], 0.616-0.665; OSR c-statistic, 0.600; 95% CI, 0.563-0.630) and good calibration (EVAR Brier score, 0.021; OSR Brier score, 0.096). The indices had significantly better discriminative power (DeLong P <.001) than the Elixhauser Comorbidity Index (ECI) (EVAR c-statistic, 0.572; 95% CI, 0.546-0.597; OSR c-statistic, 0.502; 95% CI, 0.472-0.533). For internal validation, both indices had similar performance compared with individual comorbidity adjustment (EVAR DeLong P = .650; OSR DeLong P = .431). These indices demonstrated good external validation, exhibiting comparable performance to their respective validation groups (EVAR DeLong P = .891; OSR DeLong P = .757).

CONCLUSIONS

ECI, the comorbidity index formulated for the general population, exhibited suboptimal performance in patients who underwent AAA repair. In response, we developed summary comorbidity indices for both EVAR and OSR for AAA repair, which were internally and externally validated. The EVAR and OSR comorbidity indices outperformed the ECI in discriminating in-hospital mortality rates. They can standardize comorbidity measurement for clinical studies in AAA repair, especially for studies with small samples such as single-institute data sources to facilitate replication and comparison of results across studies.

Laparoscopic and open minor liver resection for hepatocellular carcinoma with clinically significant portal hypertension: a multicenter study using inverse probability weighting approach

BACKGROUND

Liver resection offers substantial advantages over open liver resection (OLR) for patients with hepatocellular carcinoma (HCC) in terms of reduced intraoperative blood loss and morbidity. However, there is limited evidence comparing the indications and perioperative outcomes with the open versus laparoscopic approach for resection. This study aimed to compare postoperative outcomes between patients undergoing laparoscopic liver resection (LLR) and OLR for HCC with clinically significant portal hypertension (CSPH).

METHODS

A total of 316 HCC patients with CSPH (the presence of gastroesophageal varices or platelet count < 100,000/ml and spleen diameter > 12 cm) undergoing minor liver resection at eight centers were included in this study. To adjust for confounding factors between the LLR and OLR groups, an inverse probability weighting method analysis was performed.

RESULTS

Overall, 193 patients underwent LLR and 123 underwent OLR. After weighting, LLR was associated with a lower volume of intraoperative blood loss and the incidence of postoperative complications (including pulmonary complications, incisional surgical site infection, and paralytic ileus) compared to the OLR group. The 3-, 5-, and 7-year postoperative recurrence-free survival rates were 39%, 26%, and 22% in the LLR group and 49%, 18%, and 18% in the OLR group, respectively (p = 0.18). And, the 3-, 5-, and 7-year postoperative overall survival rates were 71%, 56%, and 44% in the LLR group and 76%, 51%, 44% in the OLR group, respectively (p = 0.87).

CONCLUSIONS

LLR for HCC patients with CSPH is clinically advantageous by lowering the volume of intraoperative blood loss and incidence of postoperative complications, thereby offering feasible long-term survival.

Cost-effectiveness of ChloraSolv in treating hard-to-heal venous leg ulcers

OBJECTIVE

To estimate whether the topical, amino acid-buffered hypochlorite debriding gel ChloraSolv (RLS Global AB, Sweden) could potentially afford the UK's health services a cost-effective intervention for hard-to-heal venous leg ulcers (VLUs).

METHOD

A Markov model representing the management of hard-to-heal VLUs with ChloraSolv plus standard care (SC) or SC alone was populated with inputs from an indirect comparison of two propensity score-matched cohorts. The model estimated the relative cost-effectiveness of ChloraSolv in terms of the incremental cost per quality-adjusted life year (QALY) gained at 2021/2022 prices.

RESULTS

Addition of ChloraSolv to an SC protocol was found to increase the probability of healing by 36% (from 0.14 to 0.19) after 12 weeks, and by 79% (from 0.24 to 0.43) after 24 weeks. This led to a marginal increase in health-related quality of life. Treatment with ChloraSolv plus SC instead of SC alone reduced the total cost of wound management by 8% (£189 per VLU) at 12 weeks and by 18% (£796 per VLU) at 24 weeks. Use of ChloraSolv was estimated to improve health outcomes at reduced cost. Sensitivity analysis showed that use of ChloraSolv plus SC remained a cost-effective treatment with plausible variations in costs and effectiveness.

CONCLUSION

Within the limitations of the study, the addition of ChloraSolv to an SC protocol potentially affords a cost-effective treatment to the UK's health services for managing hard-to-heal VLUs.

Evaluating hybrid controls methodology in early-phase oncology trials: A simulation study based on the MORPHEUS-UC trial

Phase Ib/II oncology trials, despite their small sample sizes, aim to provide information for optimal internal company decision-making concerning novel drug development. Hybrid controls (a combination of the current control arm and controls from one or more sources of historical trial data [HTD]) can be used to increase statistical precision. Here we assess combining two sources of Roche HTD to construct a hybrid control in targeted therapy for decision-making via an extensive simulation study. Our simulations are based on the real data of one of the experimental arms and the control arm of the MORPHEUS-UC Phase Ib/II study and two Roche HTD for atezolizumab monotherapy. We consider potential complications such as model misspecification, unmeasured confounding, different sample sizes of current treatment groups, and heterogeneity among the three trials. We evaluate two frequentist methods (with both Cox and Weibull accelerated failure time [AFT] models) and three different commensurate priors in Bayesian dynamic borrowing (with a Weibull AFT model), and modifications within each of those, when estimating the effect of treatment on survival outcomes and measures of effect such as marginal hazard ratios. We assess the performance of these methods in different settings and the potential of generalizations to supplement decisions in early-phase oncology trials. The results show that the proposed joint frequentist methods and noninformative priors within Bayesian dynamic borrowing with no adjustment on covariates are preferred, especially when treatment effects across the three trials are heterogeneous. For generalization of hybrid control methods in such settings, we recommend more simulation studies.

Comparative analysis of tabelecleucel and current treatment in patients with Epstein-Barr virus-positive post-transplant lymphoproliferative disease following hematopoietic cell transplant or solid organ transplant

AIMS

With recent European Union marketing authorization, tabelecleucel is the first off-the-shelf, allogeneic Epstein-Barr virus (EBV)-specific T-cell immunotherapy approved for the treatment of relapsed/refractory EBV-positive post-transplant lymphoproliferative disease (EBV+ PTLD). In the absence of a control arm, real-world evidence can provide a comparative benchmark for single-arm studies in ultra-rare populations. This study assessed the treatment effect of tabelecleucel in the single-arm phase 3 ALLELE study (NCT03394365) versus a treatment group from a multinational, multicenter retrospective chart review study (RS002) of patients with EBV+ PTLD.

METHODS

In ALLELE, patients had disease relapsed/refractory to rituximab ± chemotherapy and received tabelecleucel 2x106 cells/kg on days 1, 8, and 15 in 35-day cycles. Patients in RS002 had disease relapsed/refractory to rituximab ± chemotherapy and received next line of systemic therapy between January 2000 and December 2018. Propensity score-based standardized mortality/morbidity ratio weighting was used to achieve balance between treatment and comparator arms. Kaplan-Meier estimators and Cox regression models were used to compare overall survival (OS) in the re-weighted sample.

RESULTS

30 patients (n = 14 hematopoietic cell transplant [HCT], n = 16 solid organ transplant [SOT]) from ALLELE (data cutoff: November 2021) and 84 patients (n = 36 HCT, n = 48 SOT) from RS002 (data lock: January 2021) were included. Median time from diagnosis to first tabelecleucel dose (ALLELE) or start date of next line of systemic therapy (RS002) was 3.6 months. Tabelecleucel was associated with a substantial OS benefit compared with current treatment, with an unadjusted HR of 0.47 (95% confidence interval [CI] 0.25-0.88) and adjusted HR of 0.37 (95% CI 0.20-0.71) when using the start date of the next line of therapy as the index date. Sensitivity analyses yielded consistent results.

CONCLUSIONS

In this study of real-world data, tabelecleucel was associated with an OS benefit among patients with R/R EBV+ PTLD for whom there is high unmet need.

Impact of Perioperative Systemic Chemotherapy on Survival for Patients Who have Diffuse Malignant Peritoneal Mesothelioma Treated with CRS-HIPEC

BACKGROUND

The available data on the role of perioperative systemic chemotherapy (SC) for diffuse malignant peritoneal mesothelioma (DMPM) patients undergoing (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) is heterogeneous and unstandardized. This study aimed to evaluate the impact of SC on the survival outcomes of DMPM patients undergoing CRS-HIPEC and to identify prognostic factors that affect the decision to administer SC.

METHODS

Patients who underwent CRS-HIPEC in the National Cancer Institute Milan (1995-2020) were retrospectively analyzed using propensity score-matching of known covariates. The patients were grouped into three groups: group A (neoadjuvant chemotherapy [NACT] and no-SC), group B (no-SC and adjuvant chemotherapy [ACT]), and group C (NACT and ACT). Overall survival (OS) and progression-free survival (PFS) were calculated using the Kaplan-Meir method, and prognostic factors were calculated using the Cox-regression method.

RESULTS

After a median follow-up period of 45 months (95% confidence interval [CI], 6.348-83.652 months) for group A, 115 months (95% CI, 44.379-185.621 months) for group B, and 88 months (95% CI, 3.296-172.704 months) for group C, the study analyzed 154 DMPM patients consisting of matched group A (NACT: 60 + no-SC: 52 = 112), group B (ACT: 38 + no-SC: 38 = 76), and group C (NACT: 31 + ACT: 31 = 62). The patients undergoing ACT had better 5-year OS and PFS than the patients undergoing NACT. In the multivariate analysis, ACT was significantly associated with improved OS by 48% (hazard ratio [HR], 0.52; 95% CI, 0.280-0.965, p = 0.038). For PFS, the association of ACT did not reach statistical significance (HR, 0.531; 95% CI, 0.266-1.058; p = 0.072).

CONCLUSION

The optimum treatment sequence for DMPM is CRS-HIPEC followed by adjuvant chemotherapy for high-risk patients. Upfront surgery appears preferable to NACT for patients amenable to complete CRS.

Analysis of survival data with nonproportional hazards: A comparison of propensity-score-weighted methods

One of the most common ways researchers compare cancer survival outcomes across treatments from observational data is using Cox regression. This model depends on its underlying assumption of proportional hazards, but in some real-world cases, such as when comparing different classes of cancer therapies, substantial violations may occur. In this situation, researchers have several alternative methods to choose from, including Cox models with time-varying hazard ratios; parametric accelerated failure time models; Kaplan-Meier curves; and pseudo-observations. It is unclear which of these models are likely to perform best in practice. To fill this gap in the literature, we perform a neutral comparison study of candidate approaches. We examine clinically meaningful outcome measures that can be computed and directly compared across each method, namely, survival probability at time T, median survival, and restricted mean survival. To adjust for differences between treatment groups, we use inverse probability of treatment weighting based on the propensity score. We conduct simulation studies under a range of scenarios, and determine the biases, coverages, and standard errors of the average treatment effects for each method. We then demonstrate the use of these approaches using two published observational studies of survival after cancer treatment. The first examines chemotherapy in sarcoma, which has a late treatment effect (i.e., similar survival initially, but after 2 years the chemotherapy group shows a benefit). The other study is a comparison of surgical techniques for kidney cancer, where survival differences are attenuated over time.

The Impact of Raising Children with Barth Syndrome on Parental Health-Related Quality of Life and Family Functioning: Preliminary Reliability and Validity of the PedsQL™ Family Impact Module

Objective

This study examined the preliminary reliability and validity of the PedsQL™ Family Impact Module (PedsQL FIM) in families of children with Barth syndrome (BTHS).

Method

A total of 72 parents with children or youth between the ages of 5 and 19 participated in this study. Thirty-three parents of children with BTHS and 39 parents of unaffected children completed the PedsQL FIM and a demographic information form. Internal consistency reliability and item-total correlations were calculated to test the reliability of the PedsQL FIM. Construct validity was examined using the known-groups method. We estimated the mean score differences of the PedsQL FIM between the two groups using three different models, including unadjusted, multivariate regression, and propensity score matching with inverse probability of treatment weighting (PS-IPTW) models.

Results

The Cronbach's alpha coefficients were greater than 0.70 for all scales of the PedsQL FIM, except for the communication scale. The item-total correlations were significant for all scales with moderate to high correlations (p < .05). In construct validity, the mean scores of the PedsQL FIM between the two groups were significantly different (p < .05) for all scales and total score in the unadjusted and PS-IPTW models. However, in the multivariate regression model, the family relationships scale was not significant between the two groups.

Conclusion

The PedsQL FIM demonstrated adequate measurement properties of preliminary reliability and validity in assessing the impact of children with BTHS on parental health-related quality of life (HRQoL) and family functioning. Further research needs to be conducted to examine the psychometric properties of the PedsQL FIM with a large sample of BTHS and with other pediatric rare diseases.

Bayesian causal inference for observational studies with missingness in covariates and outcomes

Missing data are a pervasive issue in observational studies using electronic health records or patient registries. It presents unique challenges for statistical inference, especially causal inference. Inappropriately handling missing data in causal inference could potentially bias causal estimation. Besides missing data problems, observational health data structures typically have mixed-type variables - continuous and categorical covariates - whose joint distribution is often too complex to be modeled by simple parametric models. The existence of missing values in covariates and outcomes makes the causal inference even more challenging, while most standard causal inference approaches assume fully observed data or start their works after imputing missing values in a separate preprocessing stage. To address these problems, we introduce a Bayesian nonparametric causal model to estimate causal effects with missing data. The proposed approach can simultaneously impute missing values, account for multiple outcomes, and estimate causal effects under the potential outcomes framework. We provide three simulation studies to show the performance of our proposed method under complicated data settings whose features are similar to our case studies. For example, Simulation Study 3 assumes the case where missing values exist in both outcomes and covariates. Two case studies were conducted applying our method to evaluate the comparative effectiveness of treatments for chronic disease management in juvenile idiopathic arthritis and cystic fibrosis.

Optimizing treatment allocation in randomized clinical trials by leveraging baseline covariates

We consider the problem of optimizing treatment allocation for statistical efficiency in randomized clinical trials. Optimal allocation has been studied previously for simple treatment effect estimators such as the sample mean difference, which are not fully efficient in the presence of baseline covariates. More efficient estimators can be obtained by incorporating covariate information, and modern machine learning methods make it increasingly feasible to approach full efficiency. Accordingly, we derive the optimal allocation ratio by maximizing the design efficiency of a randomized trial, assuming that an efficient estimator will be used for analysis. We then expand the scope of optimization by considering covariate-dependent randomization (CDR), which has some flavor of an observational study but provides the same level of scientific rigor as a standard randomized trial. We describe treatment effect estimators that are consistent, asymptotically normal, and (nearly) efficient under CDR, and derive the optimal propensity score by maximizing the design efficiency of a CDR trial (under the assumption that an efficient estimator will be used for analysis). Our optimality results translate into optimal designs that improve upon standard practice. Real-world examples and simulation results demonstrate that the proposed designs can produce substantial efficiency improvements in realistic settings.

Estimating causal effects in observational studies for survival data with a cure fraction using propensity score adjustment

In observational studies, covariates are often confounding factors for treatment assignment. Such covariates need to be adjusted to estimate the causal treatment effect. For observational studies with survival outcomes, it is usually more challenging to adjust for the confounding covariates for causal effect estimation because of censoring. The challenge becomes even thornier when there exists a nonignorable cure fraction in the population. In this paper, we propose a causal effect estimation approach in observational studies for survival data with a cure fraction. We extend the absolute treatment effects on survival outcomes-including the restricted average causal effect and SPCE-to survival outcomes with cure fractions, and construct the corresponding causal effect estimators based on propensity score stratification. We prove the asymptotic properties of the proposed estimators and conduct simulation studies to evaluate their performances. As an illustration, the method is applied to a stomach cancer study.

A novel approach to risk exposure and epigenetics-the use of multidimensional context to gain insights into the early origins of cardiometabolic and neurocognitive health

BACKGROUND

Each mother-child dyad represents a unique combination of genetic and environmental factors. This constellation of variables impacts the expression of countless genes. Numerous studies have uncovered changes in DNA methylation (DNAm), a form of epigenetic regulation, in offspring related to maternal risk factors. How these changes work together to link maternal-child risks to childhood cardiometabolic and neurocognitive traits remains unknown. This question is a key research priority as such traits predispose to future non-communicable diseases (NCDs). We propose viewing risk and the genome through a multidimensional lens to identify common DNAm patterns shared among diverse risk profiles.

METHODS

We identified multifactorial Maternal Risk Profiles (MRPs) generated from population-based data (n = 15,454, Avon Longitudinal Study of Parents and Children (ALSPAC)). Using cord blood HumanMethylation450 BeadChip data, we identified genome-wide patterns of DNAm that co-vary with these MRPs. We tested the prospective relation of these DNAm patterns (n = 914) to future outcomes using decision tree analysis. We then tested the reproducibility of these patterns in (1) DNAm data at age 7 and 17 years within the same cohort (n = 973 and 974, respectively) and (2) cord DNAm in an independent cohort, the Generation R Study (n = 686).

RESULTS

We identified twenty MRP-related DNAm patterns at birth in ALSPAC. Four were prospectively related to cardiometabolic and/or neurocognitive childhood outcomes. These patterns were replicated in DNAm data from blood collected at later ages. Three of these patterns were externally validated in cord DNAm data in Generation R. Compared to previous literature, DNAm patterns exhibited novel spatial distribution across the genome that intersects with chromatin functional and tissue-specific signatures.

CONCLUSIONS

To our knowledge, we are the first to leverage multifactorial population-wide data to detect patterns of variability in DNAm. This context-based approach decreases biases stemming from overreliance on specific samples or variables. We discovered molecular patterns demonstrating prospective and replicable relations to complex traits. Moreover, results suggest that patterns harbour a genome-wide organisation specific to chromatin regulation and target tissues. These preliminary findings warrant further investigation to better reflect the reality of human context in molecular studies of NCDs.

Integrated analysis of randomized controlled trials evaluating bortezomib + lenalidomide + dexamethasone or bortezomib + thalidomide + dexamethasone induction in transplant-eligible newly diagnosed multiple myeloma

Objective

Providing the most efficacious frontline treatment for newly diagnosed multiple myeloma (NDMM) is critical for patient outcomes. No direct comparisons have been made between bortezomib + lenalidomide + dexamethasone (VRD) and bortezomib + thalidomide + dexamethasone (VTD) induction regimens in transplant-eligible NDMM.

Methods

An integrated analysis was performed using patient data from four trials meeting prespecified eligibility criteria: two using VRD (PETHEMA GEM2012 and IFM 2009) and two using VTD (PETHEMA GEM2005 and IFM 2013-04).

Results

The primary endpoint was met, with VRD demonstrating a noninferior rate of at least very good partial response (≥ VGPR) after induction vs VTD. GEM comparison demonstrated improvement in the ≥ VGPR rate after induction for VRD vs VTD (66.3% vs 51.2%; P = .00281) that increased after transplant (74.4% vs 53.5%). Undetectable minimal residual disease rates post induction (46.7% vs 34.9%) and post transplant (62.4% vs 47.3%) support the benefit of VRD vs VTD. Treatment-emergent adverse events leading to study and/or treatment discontinuation were less frequent with VRD (3%, GEM2012; 6%, IFM 2009) vs VTD (11%, IFM 2013-04).

Conclusion

These results supported the benefit of VRD over VTD for induction in transplant-eligible patients with NDMM. The trials included are registered with ClinicalTrials.gov (NCT01916252, NCT01191060, NCT00461747, and NCT01971658).

Age at Diagnosis of Atrial Fibrillation and Incident Dementia

Importance

Epidemiological evidence regarding the association between atrial fibrillation (AF) onset age and risk of incident dementia remains unexplored.

Objective

To examine whether age at AF diagnosis is associated with risk of incident dementia and its subtypes.

Design, Setting, and Participants

This prospective, population-based cohort study used data from UK Biobank, a public, open-access database in the UK with baseline information collected from 2006 to 2010. A total of 433 746 participants were included in the main analysis after excluding participants with a diagnosis of dementia or AF at baseline, missing data on covariates, or having dementia before AF onset during a median follow-up of 12.6 years. Data were analyzed from October to December 2022.

Exposures

AF diagnosis and age at AF diagnosis according to age groups (<65 years, 65-74 years, or ≥75 years).

Main Outcomes and Measures

Incident dementia, ascertained through linkage from multiple databases until December 31, 2021. Cox proportional hazards models and the propensity score matching method were adopted to estimate the association between AF onset age and incident dementia.

Results

Of 433 746 included participants, 236 253 (54.5%) were female, the mean (SD) age was 56.9 (8.1) years, and 409 990 (94.5%) were White. Compared with individuals without AF, 30 601 individuals with AF had a higher risk of developing all-cause dementia (adjusted hazard ratio [HR], 1.42; 95% CI, 1.32-1.52) and vascular dementia (VD; adjusted HR, 2.06; 95% CI, 1.80-2.36), but not Alzheimer disease (AD; adjusted HR, 1.08; 95% CI, 0.96-1.21). Among participants with AF, younger age at AF onset was associated with higher risks of developing all-cause dementia (adjusted HR per 10-year decrease, 1.23; 95% CI, 1.16-1.32), AD (adjusted HR per 10-year decrease, 1.27; 95% CI, 1.13-1.42), and VD (adjusted HR per 10-year decrease, 1.35; 95% CI, 1.20-1.51). After propensity score matching, individuals with AF diagnosed before age 65 years had the highest HR of developing all-cause dementia (adjusted HR, 1.82; 95% CI, 1.54-2.15), followed by AF diagnosed at age 65 to 74 years (adjusted HR, 1.47; 95% CI, 1.31-1.65) and diagnosed at age 75 years or older (adjusted HR, 1.11; 95% CI, 0.96-1.28). Similar results can be seen in AD and VD.

Conclusions and Relevance

In this prospective cohort study, earlier onset of AF was associated with an elevated risk of subsequent all-cause dementia, AD, and VD, highlighting the importance of monitoring cognitive function among patients with AF, especially those younger than 65 years at diagnosis.

Therapeutic plasma exchange for anti-glomerular basement membrane disease with dialysis-dependent kidney failure without diffuse alveolar hemorrhage

BACKGROUND

Anti-glomerular basement membrane (anti-GBM) disease is treated with immunosuppressive medications and plasma exchange. However, whether plasma exchange, in addition to pulse glucocorticoid therapy, would benefit patients with anti-GBM disease with dialysis-dependent kidney failure without diffuse alveolar hemorrhage remains unclear.

METHODS

Using the Japanese Diagnosis Procedure Combination database, we identified patients diagnosed with anti-GBM disease with dialysis-dependent kidney failure and without diffuse alveolar hemorrhage from July 2010 to March 2020. We compared in-hospital mortality within 10 days of hospitalization between patients who received therapeutic plasma exchange in addition to pulse glucocorticoid therapy and those who received pulse glucocorticoid therapy alone. Overlap weighting based on propensity score was performed to adjust for potential confounders.

RESULTS

We identified 207 eligible patients; 168 patients received therapeutic plasma exchange plus pulse glucocorticoid therapy, while 39 patients received pulse glucocorticoid therapy alone. The mean dose of therapeutic plasma exchange was 52.2 ml/kg/day of albumin and/or fresh frozen plasma. Therapeutic plasma exchange in addition to pulse glucocorticoid therapy was associated with a lower in-hospital mortality risk in the unweighted (10.7% versus 28.2%; risk difference, 17.5%; 95% confidence interval, 2.6-32.4%; P = 0.02) and weighted analyses (11.5% versus 28.4%; risk difference, 17.0%; 95% confidence interval, 1.5-32.5%; P = 0.03) than pulse glucocorticoid therapy alone.

CONCLUSIONS

This retrospective cohort study using a national database suggests that therapeutic plasma exchange may improve the in-hospital prognosis of anti-GBM disease with dialysis-dependent kidney failure and without diffuse alveolar hemorrhage.