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)

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.</p

Pull vs. Wet:Diagnostic performance and sample quality of eus-guided fna in solid lesions of pancreas

Differential diagnosis of pancreatic masses is challenging. The endoscopic ultrasound-guided fine-needle aspiration method with the highest diagnostic yield has not been esta-blished. It was realized a prospective, randomized, double-blind study of the endoscopic ultrasound-guided fine-needle aspiration in solid lesions of the pancreas to compare and evaluate diagnostic yield and aspirate quality between wet and pull technique. Forty-one patients were enrolled. The wet technique presented a sensitivity, a specificity, a positive and negative predictive value, and a diagnostic accuracy of 58.3%, 100%, 100%, 25% and 63.4%, respectively. In the capillary technique they were: 75%, 100%, 100%, 35.7% and 78.1%, respectively. Comparing the diagnostic yield between both techniques, there was no statistically significant difference (McNemar's test p = 0.388). Regarding the cellularity of the specimen, both in cytology and the cell block samples, no significant difference was observed between the techniques (p = 0.84 and 0.61, respectively). With res-pect to contaminating blood in the specimen, there was no difference in cytology samples (p = 0.89) and no difference in cell block samples (p = 0.08). The suitability of cytology samples for diagnosis was similar in both techniques (wet = 57.5% and capillary = 56.7%, p = 0.94) and there was no difference in cell block samples (wet = 75% and capillary = 66.1%, p = 0.38). In this study we did not observe differences in diagnostic yield or sample quality. Since both techniques are effective, we suggest the simultaneous and alternate use of both methods.</p

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

Hypothetical blood-pressure-lowering interventions and risk of stroke and dementia

We aimed to study the effects of hypothetical interventions on systolic blood pressure (SBP) and smoking on risk of stroke and dementia using data from 15 years of follow-up in the Rotterdam Study. We used data from 4930 individuals, aged 55–80 years, with no prior history of stroke, dementia or cognitive impairment, followed for 15 years within the Rotterdam Study, a population-based cohort. We defined the following sustained interventions on SBP: (1) maintaining SBP below 120 mmHg, (2) maintaining SBP below 140 mmHg, (3) reducing SBP by 10% if above 140 mmHg, (4) reducing SBP by 20% if above 140 mmHg, and a combined intervention of quitting smoking with each of these SBP-lowering strategies. We considered incident stroke and incident dementia diagnoses as outcomes. We applied the parametric g-formula to adjust for baseline and time-varying confounding. The observed 15-year risk for stroke was 10.7%. Compared to no specified intervention (i.e., the “natural course”), all interventions that involved reducing SBP were associated with a stroke risk reduction of about 10% (e.g., reducing SBP by 20% if above 140 mmHg risk ratio: 0.89; 95% CI 0.76, 1). Jointly

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.</p