Antidepressant exposure and long-term dementia risk in a nationwide retrospective study on US veterans with midlife major depressive disorder.

INTRODUCTION: The use of antidepressants in major depressive disorder (MDD) has been reported to influence long-term risk of Alzheimer's disease (AD) and AD-related dementias (AD/ADRD), but studies are conflicting. METHODS: We used inverse probability weighted (IPW) Cox models with time-varying covariates in a retrospective cohort study among midlife veterans with MDD within the US Veterans Affairs healthcare system from January 1, 2000 to June 1, 2022. RESULTS: A total of 35,200 patients with MDD were identified. No associations were seen regarding the effect of being exposed to any antidepressant versus no exposure on AD/ADRD risk (events = 1,056, hazard ratio = 0.94, 95% confidence interval: 0.81 to 1.09) or the exposure to specific antidepressant classes versus no exposure. A risk reduction was observed for female patients in a stratified analysis; however, the number of cases was small. DISCUSSION: Our study suggests that antidepressant exposure has no effect on AD/ADRD risk. The association in female patients should be interpreted with caution and requires further attention. HIGHLIGHTS: We studied whether antidepressant use was associated with future dementia risk. We specifically focused on patients after their first-ever diagnosis of depression. We used IPW Cox models with time-varying covariates and a large observation window. Our study did not identify an effect of antidepressant use on dementia risk. A risk reduction was observed in female patients, but the number of cases was small.

Abiraterone or Enzalutamide for Patients With Metastatic Castration-Resistant Prostate Cancer.

Importance: Abiraterone acetate and enzalutamide are recommended as preferred treatments for metastatic castration-resistant prostate cancer (mCRPC), but differences in their relative efficacy are unclear due to a lack of head-to-head clinical trials. Clear guidance is needed for making informed mCRPC therapeutic choices. Objective: To compare clinical outcomes in patients with mCRPC treated with abiraterone acetate or enzalutamide. Design, Setting, and Participants: This retrospective, multicenter cohort study included patients with mCRPC in the US Department of Veterans Affairs health care system who initiated treatment with abiraterone acetate or enzalutamide between January 1, 2014, and October 30, 2022. Exposures: Abiraterone acetate or enzalutamide. Main Outcomes and Measures: The study used inverse probability of treatment weighting to balance baseline characteristics between patients initiating abiraterone acetate or enzalutamide and evaluated restricted mean survival time (RMST) differences in overall survival (OS), prostate cancer-specific survival (PCS), time to next treatment switching or death (TTS), and time to prostate-specific antigen (PSA) response (TTR) at different time points after treatment initiation. Results: The study included 5779 patients (median age, 74.42 years [IQR, 68.94-82.14 years]). Median follow-up was between 38 and 60 months. Patients initiating enzalutamide on average had longer OS than those initiating abiraterone acetate, with RMSTs of 24.29 months (95% CI, 23.58-24.99 months) and 23.38 months (95% CI, 22.85-23.92 months), respectively, and a difference in RMST of 0.90 months (95% CI, 0.02-1.79 months) at 4 years. Similarly, TTS and TTR were improved in patients initiating enzalutamide, with an RMST at 4 years of 1.95 months (95% CI, 0.92-2.99 months) longer for TTS and 3.57 months (95% CI, 1.76-5.38 months) shorter for TTR. For PCS, the RMST at 2 years was 0.48 months (95% CI, 0.01-0.95 months) longer. An examination of subgroups identified that enzalutamide initiation was associated with longer RMST in OS among patients without prior docetaxel treatment (1.14 months; 95% CI, 0.19-2.10 months) and in those with PSA doubling time of 3 months or longer (2.23 months; 95% CI, 0.81-3.66 months) but not among patients with prior docetaxel (-0.25 months; 95% CI, -2.59 to 2.09 months) or with PSA doubling time of less than 3 months (0.05 months; 95% CI, -1.05 to 1.15 months). Conclusions and Relevance: In this cohort study of patients with mCRPC, initiation of enzalutamide was associated with small but statistically significant improvements in OS, PCS, TTS, and TTR compared with initiation of abiraterone acetate. The improvements were more prominent in short-term outcomes, including TTS and TTR, and in patient subgroups without prior docetaxel or with PSA doubling time longer than 3 months.

Matching Patients to Accelerate Clinical Trials (MPACT): Enabling Technology for Oncology Clinical Trial Workflow.

Clinical trial enrollment is impeded by the significant time burden placed on research coordinators screening eligible patients. With 50,000 new cancer cases every year, the Veterans Health Administration (VHA) has made increased access for Veterans to high-quality clinical trials a priority. To aid in this effort, we worked with research coordinators to build the MPACT (Matching Patients to Accelerate Clinical Trials) platform with a goal of improving efficiency in the screening process. MPACT supports both a trial prescreening workflow and a screening workflow, employing Natural Language Processing and Data Science methods to produce reliable phenotypes of trial eligibility criteria. MPACT also has a functionality to track a patient's eligibility status over time. Qualitative feedback has been promising with users reporting a reduction in time spent on identifying eligible patients.

A big-data approach to understanding metabolic rate and response to obesity in laboratory mice.

Maintaining a healthy body weight requires an exquisite balance between energy intake and energy expenditure. To understand the genetic and environmental factors that contribute to the regulation of body weight, an important first step is to establish the normal range of metabolic values and primary sources contributing to variability. Energy metabolism is measured by powerful and sensitive indirect calorimetry devices. Analysis of nearly 10,000 wild-type mice from two large-scale experiments revealed that the largest variation in energy expenditure is due to body composition, ambient temperature, and institutional site of experimentation. We also analyze variation in 2329 knockout strains and establish a reference for the magnitude of metabolic changes. Based on these findings, we provide suggestions for how best to design and conduct energy balance experiments in rodents. These recommendations will move us closer to the goal of a centralized physiological repository to foster transparency, rigor and reproducibility in metabolic physiology experimentation.

Maintaining a healthy weight requires the body to balance energy intake and expenditure. The body converts food to energy through a process called energy metabolism. Genetic and environmental factors can affect energy metabolism and energy balance contributing to conditions like obesity. To better understand metabolism, scientists often study mice in laboratories, but mice from different laboratories appear to convert food to energy at different rates. This makes it hard to determine what is 'normal' for mouse metabolism. These discrepancies could be due to small differences between how mice are kept in different laboratories. For example, the temperatures of the mouse cages or how active the mice are might differ depending on the laboratory. Identifying the effects of such differences is essential, but it requires looking at data from hundreds of mice. Corrigan et al. examined data from more than 30,000 mice at laboratories around the world to show that room temperatures and the amount of muscle and fat in a mouse's body have the biggest influence on energy balance. These two factors affected the metabolism of both typical mice and mice with mutations that affect their energy balance. These results suggest that it is important for scientists to report factors like room temperatures, the body make-up of the mice, or the animals' activity levels in metabolism studies. This can help scientists compare results and repeat experiments, which could speed up research into mouse metabolism. Corrigan et al. also found that other unknown factors also affect mouse metabolism in different laboratories. Further studies are needed to identify these factors.