Severe hypoglycemia is a feared complication of diabetes treatment. While psychoeducational programs reduce severe hypoglycemia in type 1 diabetes, their effectiveness is unclear in type 2 diabetes (T2D). The Preventing Severe Hypoglycemia in Adults with Type 2 Diabetes (PHT2) randomized trial compared (a) proactive nurse care management (PC) and (b) PC augmented with my hypo compass for adults with T2D, a psychoeducational intervention (PC+). Adults with T2D on insulin or sulfonylurea and with a severe event in the prior 12 months or impaired awareness of hypoglycemia. Primary outcome was self-reported severe hypoglycemia over 12 months, assessed at 14 months. Ninety-two percent (n = 230) of 259 participants (67.2 ± 10.6 years; 61
BACKGROUND/AIMS: Evaluating heterogeneity of treatment effects (HTE) across subgroups is common in both randomized trials and observational studies. Although several statistical challenges of HTE analyses including low statistical power and multiple comparisons are widely acknowledged, issues specific to clustered data, including cluster randomized trials (CRTs), have received less attention. For testing interactions in linear mixed-effects models (LMM), Barr et al. (2013) suggested that: random slopes for interaction terms should be studied. In this paper, we explore the impact of model misspecification, including generalized LMM (GLMM) with or without random slopes, and provide recommendations for conducting inference for HTE across subgroups in CRTs. METHODS: We conducted a simulation study to evaluate the performance of common analytic approaches for testing the presence of HTE for continuous, binary, and count outcomes: generalized linear mixed models (GLMM) and generalized estimating equations (GEE) including interaction terms between treatment and subgroup. Several simulation scenarios covered broad range of scenarios in CRTs, for example, small to a large number of clusters, small to moderate cluster-specific random slopes for subgroup. The performance metric was the empirical type I error rate compared to a nominal level. We applied the analytical methods to a real-world CRT using the count outcome utilization of healthcare from the motivating Primary Care Opioid Use Disorder treatment (PROUD) trial. RESULTS: We found that standard GLMM analyses that assume a common correlation of participants within clusters can lead to severely elevated type 1 error rates of up to 47.2% compared to the 5% nominal level if the within-cluster correlation varies across subgroups. A maximal GLMM, which allows subgroup-specific within-cluster correlations, achieved the nominal type 1 error rate, as did GEE (though rates were slightly elevated even with as many as 50 clusters). Applying the methods to the real-world CRT, we found a large impact of the model specification on inference. CONCLUSIONS: We recommend that HTE analyses using the maximal GLMM account for within-subgroup correlation to avoid anti-conservative inference. For Wald t-testing of HTE in small sample clusters, appropriate small sample correction methods should be considered based on the outcome data type.
In a typical two-phase design, a random sample is drawn from the target population in phase 1, during which only a subset of variables is collected. In phase 2, a subsample of the phase-1 cohort is selected, and additional variables are measured. This setting induces a coarsened data structure on the data from the second phase. We assume coarsening at random, that is, the phase-2 sampling mechanism depends only on variables fully observed. We review existing estimators, including the generalized raking estimator and the inverse probability of censoring weighted targeted maximum likelihood estimation (IPCW-TMLE) along with its extensions that also target the phase-2 sampling mechanism to improve efficiency. We further introduce a new class of estimators constructed within the TMLE framework that are asymptotically equivalent.
Importance:Antihypertensive medications that stimulate angiotensin II type 2 or 4 receptors (angiotensin II-stimulating medications) may be associated with lower risk of dementia. Objective:To examine associations between cumulative exposure to angiotensin II-stimulating vs angiotensin II-inhibiting antihypertensive medications and neuropathology, accounting for blood pressure. Design, Setting, and Participants:This community-based autopsy cohort study from the Adult Changes in Thought cohort was conducted at Kaiser Permanente Washington between February 24, 1994, and November 25, 2022, among 756 participants who had blood pressure measurements and at least 1 person-year (PY) of angiotensin II-stimulating or -inhibiting antihypertensive medication exposure prior to death. Statistical analysis was performed between September 2024 and August 2025. Exposure:Angiotensin II-stimulating antihypertensive medications (angiotensin II receptor blockers, dihydropyridine calcium channel blockers, thiazides) and angiotensin II-inhibiting antihypertensive medications (angiotensin-converting enzyme inhibitors, β-blockers, nondihydropyridine calcium channel blockers) were ascertained from paper-based medical records (before 1977) and electronic prescription fill data (after 1977). The primary exposure was cumulative angiotensin II PYs, and the secondary exposure was long-term use (≥15 years). Main Outcomes and Measures:Neuropathology outcomes were classified as Alzheimer disease related, vascular brain injury, or other. Exploratory outcomes included quantitative measures of Aβ42 and phosphorylated tau. Data were analyzed using multivariable modified Poisson, proportional odds, and linear regression models and accounted for potential selection bias. Results:The sample included 756 participants (mean [SD] age at death, 89.2 [6.4] years; 440 women [58.2%]; mean [SD] follow-up, 22.2 [13.5] years). Compared with exposure to 5 additional PYs of angiotensin II-inhibiting antihypertensive medications, exposure to 5 additional PYs of angiotensin II-stimulating antihypertensive medications was associated with a 6% lower risk for arteriolosclerosis (relative risk [RR], 0.94; 95% CI, 0.89-0.99), with long-term use associated with a 24% lower risk (RR, 0.76; 95% CI, 0.63-0.91). For exploratory outcomes, PYs of angiotensin II-stimulating antihypertensive medications were associated with less quantitative phosphorylated tau burden in several brain regions (temporal lobe [adjusted ratio of geometric means, 0.79; 95% CI, 0.62-1.00], hippocampus [adjusted ratio of geometric means, 0.83; 95% CI, 0.71-0.97], cornu ammonis subfield 1 [adjusted ratio of geometric means, 0.86; 95% CI, 0.74-0.99], and transentorhinal cortex [adjusted ratio of geometric means, 0.83; 95% CI, 0.70-0.98]) but not with Aβ42 quantitative measures. Conclusions and Relevance:In this community-based autopsy cohort study, angiotensin II-stimulating antihypertensive medications were associated with lower risk of neuropathological burden, supporting findings from epidemiologic dementia studies. Additional mechanistic research examining the effects of individual antihypertensive classes on Alzheimer disease-related biomarkers is warranted.
