Retrospective analysis of a pilot pharmacist-led hospice deprescribing program initiative.

CONTEXT: Medication deprescribing in palliative care settings has been insufficiently studied. OBJECTIVE: To determine the feasibility of a deprescribing program in hospice patients with limited life expectancy. DESIGN: Pharmacist-led, single arm, single-centered, retrospective analysis of a pilot deprescribing program in an integrated healthcare delivery organization between 9/1/2018 to 1/31/2019. OUTCOME MEASURES: The primary outcome was the proportion of patients who achieved ≥50% reduction of the recommended medications to deprescribe. RESULTS: A total of 97 patients were included in the analysis. The average age was 77.5 ± 23.7 years, with 53.6% being women and 54.6% white. The most common primary diagnosis was cancer (58.8%), with cardiovascular disease the next most common (15.5%). The mean number of baseline comorbidities was 2.0 ± 1.6. Of 698 prescriptions at the start of hospice enrollment, 79.4% of patients achieved a ≥50% reduction in medications recommended for deprescribing. This success was seen mostly in cardiovascular and other nonspecific medications. We found that every 1-unit increase in the number of patient encounters with hospice pharmacists was associated with a 3.2-fold higher odds of achieving a ≥50% reduction in medications that were recommended for deprescribing. CONCLUSION: The findings from this pilot study revealed that a collaborative, pharmacist-led, collaborative medication deprescribing program initiative was associated with a 79% success in ≥50% medication reduction. More frequent patient encounters had higher odds of success. Future studies, utilizing a control group, should focus on determining the effectiveness of the program and the impact on quality of life.

Acute Blockade of PACAP-Dependent Activity in the Ventromedial Nucleus of the Hypothalamus Disrupts Leptin-Induced Behavioral and Molecular Changes in Rats.

Leptin signaling pathways, stemming primarily from the hypothalamus, are necessary for maintaining normal energy homeostasis and body weight. In both rodents and humans, dysregulation of leptin signaling leads to morbid obesity and diabetes. Since leptin resistance is considered a primary factor underlying obesity, understanding the regulation of leptin signaling could lead to therapeutic tools and provide insights into the causality of obesity. While leptin actions in some hypothalamic regions such as the arcuate nuclei have been characterized, less is known about leptin activity in the hypothalamic ventromedial nuclei (VMN). Recently, pituitary adenylate cyclase-activating polypeptide (PACAP) has been shown to reduce feeding behavior and alter metabolism when administered into the VMN in a pattern similar to that of leptin. In the current study, we examined whether leptin and PACAP actions in the VMN share overlapping pathways in the regulation of energy balance. Interestingly, PACAP administration into the VMN increased STAT3 phosphorylation and SOCS3 mRNA expression, both of which are hallmarks of leptin receptor activation. In addition, BDNF mRNA expression in the VMN was increased by both leptin and PACAP administration. Moreover, antagonizing PACAP receptors fully reversed the behavioral and cellular effects of leptin injections into the VMN. Electrophysiological studies further illustrated that leptin-induced effects on VMN neurons were blocked by antagonizing PACAP receptors. We conclude that leptin dependency on PACAP signaling in the VMN suggests a potential common signaling cascade, allowing a tonically and systemically secreted neuropeptide to be more precisely regulated by central neuropeptides.

Nine-year change in statistical design, profile, and success rates of Phase II oncology trials.

We investigated nine-year trends in statistical design and other features of Phase II oncology clinical trials published in 2005, 2010, and 2014 in five leading oncology journals: Cancer, Clinical Cancer Research, Journal of Clinical Oncology, Annals of Oncology, and Lancet Oncology. The features analyzed included cancer type, multicenter vs. single-institution, statistical design, primary endpoint, number of treatment arms, number of patients per treatment arm, whether or not statistical methods were well described, whether the drug was found effective based on rigorous statistical testing of the null hypothesis, and whether the drug was recommended for future studies.