Valid and efficient subgroup analyses using nested case-control data

Neuropathological findings in Down syndrome, Alzheimer's disease and control patients with and without SARS-COV-2: preliminary findings

The SARS-CoV-2 virus that led to COVID-19 is associated with significant and long-lasting neurologic symptoms in many patients, with an increased mortality risk for people with Alzheimer's disease (AD) and/or Down syndrome (DS). However, few studies have evaluated the neuropathological and inflammatory sequelae in postmortem brain tissue obtained from AD and people with DS with severe SARS-CoV-2 infections. We examined tau, beta-amyloid (Aβ), inflammatory markers and SARS-CoV-2 nucleoprotein in DS, AD, and healthy non-demented controls with COVID-19 and compared with non-infected brain tissue from each disease group (total n = 24). A nested ANOVA was used to determine regional effects of the COVID-19 infection on arborization of astrocytes (Sholl analysis) and percent-stained area of Iba-1 and TMEM 119. SARS-CoV-2 antibodies labeled neurons and glial cells in the frontal cortex of all subjects with COVID-19, and in the hippocampus of two of the three DS COVID-19 cases. SARS-CoV-2-related alterations were observed in peri-vascular astrocytes and microglial cells in the gray matter of the frontal cortex, hippocampus, and para-hippocampal gyrus. Bright field microscopy revealed scattered intracellular and diffuse extracellular Aβ deposits in the hippocampus of controls with confirmed SARS-CoV-2 infections. Overall, the present preliminary findings suggest that SARS-CoV-2 infections induce abnormal inflammatory responses in Down syndrome.

Associations between systemic medications and development of wet age-related macular degeneration

PURPOSE

To examine whether systemic medications are associated with the subsequent development of wet age-related macular degeneration (AMD).

METHODS

A retrospective study of 259 562 individuals based on registry data, from January 1, 2001, to December 31, 2017. End-point event was the International Classification of Diseases (ICD)-10 diagnosis for wet AMD. Association between use of systemic medication covering 85 generic drugs categorized according to Anatomical Therapeutic Chemical (ATC) codes and the incidence of wet AMD was evaluated using multivariate Poisson regression model (adjusted for age, sex, diabetes, cancer and socioeconomic group) and nested case-control design.

RESULTS

The mean length of follow-up was 9.84 years. The number of cases with wet AMD was 2947 and incidence rate was 1.15 per 1000 person-years. After adjustment, we observed an increased risk for the development of wet AMD for patients exposed to amlodipine (IRR 1.33, 95% CI 1.16-1.53), or felodipine (1.24, 95% CI 1.02-1.50). Similarly, an increased risk of wet AMD was associated with the use of bicalutamide (2.14, 95% CI 1.14-4.02), estradiol (1.20, 95% CI 1.03-1.40) and atorvastatin (1.22, 95% CI 1.05-1.43). Of note, digoxin (0.72, 95% CI 0.57-0.91), and ramipril (0.80, 95% CI 0.65-0.99) users had a lower incidence of wet AMD.

CONCLUSIONS

Our findings suggest that the use of second-generation calcium channel blockers could be associated with an increased risk for wet AMD development. Of note, the incidence of wet AMD seemed to be lower in patients using ramipril and digoxin. More studies are needed to elucidate the associations further.

Sampling strategies to evaluate the prognostic value of a new biomarker on a time-to-event end-point

BACKGROUND

The availability of large epidemiological or clinical data storing biological samples allow to study the prognostic value of novel biomarkers, but efficient designs are needed to select a subsample on which to measure them, for parsimony and economical reasons. Two-phase stratified sampling is a flexible approach to perform such sub-sampling, but literature on stratification variables to be used in the sampling and power evaluation is lacking especially for survival data.

METHODS

We compared the performance of different sampling designs to assess the prognostic value of a new biomarker on a time-to-event endpoint, applying a Cox model weighted by the inverse of the empirical inclusion probability.

RESULTS

Our simulation results suggest that case-control stratified (or post stratified) by a surrogate variable of the marker can yield higher performances than simple random, probability proportional to size, and case-control sampling. In the presence of high censoring rate, results showed an advantage of nested case-control and counter-matching designs in term of design effect, although the use of a fixed ratio between cases and controls might be disadvantageous. On real data on childhood acute lymphoblastic leukemia, we found that optimal sampling using pilot data is greatly efficient.

CONCLUSIONS

Our study suggests that, in our sample, case-control stratified by surrogate and nested case-control yield estimates and power comparable to estimates obtained in the full cohort while strongly decreasing the number of patients required. We recommend to plan the sample size and using sampling designs for exploration of novel biomarker in clinical cohort data.

Prognostic Value of Combined C-Reactive Protein, Body Mass Index, and Left Ventricular Ejection Fraction in Predicting Cardiovascular Events in Patients ≥80 Years of Age With Acute Myocardial Infarction

Elevated high-sensitivity C-reactive protein (hsCRP) and low body mass index (BMI) are linked to increased mortality in the elderly population. However, the combined value for predicting adverse cardiovascular events in the oldest-old (≥80 years old) with acute myocardial infarction (AMI) remains undetermined. A total of 463 AMI patients, who were ≥80 years old, were enrolled in this study between January 2012 and June 2017. A nested case-control study was implemented in 106 deaths and 212 controls, who were matched for age, gender, time of inclusion, and myocardial infarction type. Furthermore, the individual and additive values of hsCRP, BMI, and left ventricular ejection fraction (LVEF) were assessed using adjusted hazard ratio, unadjusted Kaplan-Meier analysis, and receiver-operating characteristic curve models. The median follow-up time was 19.15 months, and there were 106 deaths (33.3%). Furthermore, HsCRP, BMI, and LVEF were significantly associated with all-cause mortality (p <0.05, respectively). In addition, a negative correlation between BMI and LVEF, and the positive association of hsCRP with all-cause mortality in the fully adjusted Cox proportional hazards model were detected. The combination of hsCRP, BMI, and LVEF was found to exhibit an enhanced predictive value for all-cause mortality (0.733 in jointly vs 0.623 in cardiovascular risk factors, p = 0.0007) in these oldest-old AMI patients. HsCRP, BMI, and LVEF are the independent risk factors for all-cause mortality for the oldest-old patients with AMI, and this combination offers more appreciable and reliable predictive value for all-cause mortality.