Racial and ethnic differences in the risk of dementia diagnosis under hypothetical blood pressure-lowering interventions: The Multi-Ethnic Study of Atherosclerosis.

INTRODUCTION: Substantial racial and ethnic disparities in hypertension and dementia exist in the United States. We evaluated the effect of maintaining systolic blood pressure (SBP) below clinical thresholds on dementia incidence. METHODS: We included 6806 Multi-Ethnic Study of Atherosclerosis participants (44 to 84 years old). We implemented the parametric g-formula to simulate the hypothetical interventions to reduce SBP below 120 and 140 mmHg over time, accounting for time-varying confounding. We estimated risk ratios (RRs) and risk differences for dementia incidence at 19 years. RESULTS: The RRs (95% confidence intervals [CIs]) comparing an intervention reducing SBP below 120 mmHg to no intervention were 0.93 (0.87 to 0.99) for total sample, 0.95 (0.88 to 1.02) for White, 0.90 (0.79 to 1.02) for Black, 0.90 (0.78 to 1.05) for Latino, and 1.16 (0.83 to 1.55) for Chinese American participants. Results for lowering SBP below 140 mmHg and with death as competing event were attenuated. DISCUSSION: The reduction of SBP below 120 mmHg over time has modest effects on reducing dementia incidence. More work is needed to understand the heterogeneity across racial and ethnic groups. HIGHLIGHTS: There is a potential beneficial effect in lowering SBP to reduce the risk of dementia, which may vary by race and ethnicity. The percentage of participants who would need intervention on blood pressure to meet clinical thresholds is greater for Black and Latino communities. Results are sensitive to the way that death is specified in the research question and analysis.

Selection Bias in Health Research: Quantifying, Eliminating, or Exacerbating Health Disparities?

Purpose of review: To summarize recent literature on selection bias in disparities research addressing either descriptive or causal questions, with examples from dementia research. Recent findings: Defining a clear estimand, including the target population, is essential to assess whether generalizability bias or collider-stratification bias are threats to inferences. Selection bias in disparities research can result from sampling strategies, differential inclusion pipelines, loss to follow-up, and competing events. If competing events occur, several potentially relevant estimands can be estimated under different assumptions, with different interpretations. The apparent magnitude of a disparity can differ substantially based on the chosen estimand. Both randomized and observational studies may misrepresent health disparities or heterogeneity in treatment effects if they are not based on a known sampling scheme. Conclusion: Researchers have recently made substantial progress in conceptualization and methods related to selection bias. This progress will improve the relevance of both descriptive and causal health disparities research.

Towards a Clearer Causal Question Underlying the Association Between Cancer and Dementia.

BACKGROUND: Several observational studies have described an inverse association between cancer diagnosis and subsequent dementia risk. Multiple biologic mechanisms and potential biases have been proposed in attempts to explain this association. One proposed explanation is the opposite expression of Pin1 in cancer and dementia, and we use this explanation and potential drug target to illustrate the required assumptions and potential sources of bias for inferring an effect of Pin1 on dementia risk from analyses measuring cancer diagnosis as a proxy for Pin1 expression. METHODS: We used data from the Rotterdam Study, a population-based cohort. We estimate the association between cancer diagnosis (as a proxy for Pin1) and subsequent dementia diagnosis using two different proxy methods and with confounding and censoring for death addressed with inverse probability weights. We estimate and compare the complements of a weighted Kaplan-Meier survival estimator at 20 years of follow-up. RESULTS: Out of 3634 participants, 899 (25%) were diagnosed with cancer, of whom 53 (6%) had dementia, and 567 (63%) died. Among those without cancer, 15% (411) were diagnosed with dementia, and 667 (24%) died over follow-up. Depending on the confounding and selection bias control, and the way in which cancer was used as a time-varying proxy exposure, the risk ratio for dementia diagnosis ranged from 0.71 (95% confidence interval [CI] = 0.49, 0.95) to 1.1 (95% CI = 0.79, 1.3). CONCLUSION: Being explicit about the underlying mechanism of interest is key to maximizing what we can learn from this cancer-dementia association given available or readily collected data, and to defining, detecting, and preventing potential biases.

Considering Questions Before Methods in Dementia Research With Competing Events and Causal Goals.

Studying causal exposure effects on dementia is challenging when death is a competing event. Researchers often interpret death as a potential source of bias, although bias cannot be defined or assessed if the causal question is not explicitly specified. Here we discuss 2 possible notions of a causal effect on dementia risk: the "controlled direct effect" and the "total effect." We provide definitions and discuss the "censoring" assumptions needed for identification in either case and their link to familiar statistical methods. We illustrate concepts in a hypothetical randomized trial on smoking cessation in late midlife, and emulate such a trial using observational data from the Rotterdam Study, the Netherlands, 1990-2015. We estimated a total effect of smoking cessation (compared with continued smoking) on 20-year dementia risk of 2.1 (95% confidence interval: -0.1, 4.2) percentage points and a controlled direct effect of smoking cessation on 20-year dementia risk had death been prevented of -2.7 (95% confidence interval: -6.1, 0.8) percentage points. Our study highlights how analyses corresponding to different causal questions can have different results, here with point estimates on opposite sides of the null. Having a clear causal question in view of the competing event and transparent and explicit assumptions are essential to interpreting results and potential bias.

Limiting Dynamic Driving Pressure in Patients Requiring Mechanical Ventilation.

OBJECTIVES: Previous studies reported an association between higher driving pressure (∆P) and increased mortality for different groups of mechanically ventilated patients. However, it remained unclear if sustained intervention on ∆P, in addition to traditional lung-protective ventilation, improves outcomes. We investigated if ventilation strategies limiting daily static or dynamic ∆P reduce mortality compared with usual care in adult patients requiring greater than or equal to 24 hours of mechanical ventilation. DESIGN: For this comparative effectiveness study, we emulated pragmatic clinical trials using data from the Toronto Intensive Care Observational Registry recorded between April 2014 and August 2021. The per-protocol effect of the interventions was estimated using the parametric g-formula, a method that controls for baseline and time-varying confounding, as well as for competing events in the analysis of longitudinal exposures. SETTING: Nine ICUs from seven University of Toronto-affiliated hospitals. PATIENTS: Adult patients (≥18 yr) requiring greater than or equal to 24 hours of mechanical ventilation. INTERVENTIONS: Receipt of a ventilation strategy that limited either daily static or dynamic ∆P less than or equal to 15 cm H 2 O compared with usual care. MEASUREMENTS AND MAIN RESULTS: Among the 12,865 eligible patients, 4,468 of (35%) were ventilated with dynamic ∆P greater than 15 cm H 2 O at baseline. Mortality under usual care was 20.1% (95% CI, 19.4-20.9%). Limiting daily dynamic ∆P less than or equal to 15 cm H 2 O in addition to traditional lung-protective ventilation reduced adherence-adjusted mortality to 18.1% (95% CI, 17.5-18.9%) (risk ratio, 0.90; 95% CI, 0.89-0.92). In further analyses, this effect was most pronounced for early and sustained interventions. Static ∆P at baseline were recorded in only 2,473 patients but similar effects were observed. Conversely, strict interventions on tidal volumes or peak inspiratory pressures, irrespective of ∆P, did not reduce mortality compared with usual care. CONCLUSIONS: Limiting either static or dynamic ∆P can further reduce the mortality of patients requiring mechanical ventilation.

Invited Commentary: Conducting and Emulating Trials to Study Effects of Social Interventions.

All else being equal, if we had 1 causal effect we wished to estimate, we would conduct a randomized trial with a protocol that mapped onto that causal question, or we would attempt to emulate that target trial with observational data. However, studying the social determinants of health often means there are not just 1 but several causal contrasts of simultaneous interest and importance, and each of these related but distinct causal questions may have varying degrees of feasibility in conducting trials. With this in mind, we discuss challenges and opportunities that arise when conducting and emulating such trials. We describe designing trials with the simultaneous goals of estimating the intention-to-treat effect, the per-protocol effect, effects of alternative protocols or joint interventions, effects within subgroups, and effects under interference, and we describe ways to make the most of all feasible randomized trials and emulated trials using observational data. Our comments are grounded in the study results of Courtin et al. (Am J Epidemiol. 2022;191(8):1444-1452).

Emulating a target trial of statin use and risk of dementia using cohort data.

OBJECTIVE: Observational data can be used to attempt to emulate a target trial of statin use and estimate analogues of intention-to-treat and per protocol effects on dementia risk. METHODS: Using data from a prospective cohort study in the Netherlands, we conceptualized a sequence of "trials" in which eligible individuals ages 55-80 years were classified as statin initiators or noninitiators for every consecutive month between 1993 and 2007 and were followed until diagnosis of dementia, death, loss to follow-up, or the end of follow-up. We estimated 2 types of effects of statin use on dementia and a combined endpoint of dementia or death: the effect of initiation vs no initiation and the effect of sustained use vs no use. We estimated risk by statin treatment strategy over time via pooled logistic regression. We used inverse-probability weighting to account for treatment-confounder feedback in estimation of per-protocol effects. RESULTS: Of 233,526 eligible person-trials (6,373 individuals), there were 622 initiators and 232,904 noninitiators. Comparing statin initiation with no initiation, the 10-year risk differences (95% confidence interval) were -0.1% (-2.3% to 1.8%) for dementia and 0.3% (-2.7% to 3.3%) for dementia or death. Comparing sustained statin use vs no use, the 10-year risk differences were -2.2% (-5.2% to 1.6%) for dementia and -5.1% (-10.5% to -1.1%) for dementia or death. CONCLUSIONS: Individuals with sustained statin use, but not statin initiation alone, had reduced 10-year risks of dementia and dementia or death. Our results should be interpreted with caution due to the small number of initiators and events and potential for residual confounding.

Unspecified Strokes: Time Trends, Determinants, and Long-Term Prognosis in the General Population.

INTRODUCTION: In the absence of neuroimaging, a stroke is typically labelled as unspecified. While the majority of clinic-based stroke research focuses on hemorrhagic or ischemic stroke, in the general population, a substantial proportion of strokes remains unspecified. OBJECTIVE: To investigate time trends in the occurrence and determinants of unspecified strokes and differences in patient characteristics and survival compared to ischemic or hemorrhagic stroke. METHODS: We included 1,546 participants from the population-based Rotterdam Study who suffered a first-ever stroke during follow-up (1990-2016). We calculated the proportion of unspecified strokes per year and compared their characteristics between 3 time periods (1990-1999, 2000-2009, and 2010-2016) using a chi-square test, and furthermore investigated differences between unspecified, ischemic, and hemorrhagic stroke in patient characteristics and survival using age- and sex-adjusted survival curves. RESULTS: The occurrence of unspecified stroke among all strokes decreased from 75% in 1990 to 16% in 2016. Compared to the first time period (1991-1999), diagnosis of unspecified strokes was more often done by nursing home physicians (13 vs. 40%) and unspecified stroke patients had more often dementia (30 vs. 43%) in the last time period (2010-2016). Compared to patients with ischemic or hemorrhagic stroke, patients with unspecified stroke were on average older (84.3 vs. 78.5 years) and had more often physical impairments and dementia. Furthermore, patients with unspecified stroke had a lower survival probability up to 10 years after stroke than those with ischemic stroke. CONCLUSIONS: The proportion of unspecified strokes decreased drastically from 75 to 16% in the last decades. Patients who do not undergo neuroimaging and therefore are classified as unspecified stroke represent an older, more frail patient group that suffers more often from multimorbidities and poor long-term prognosis than those who do undergo neuroimaging and are thus classified as ischemic or hemorrhagic stroke.