Genetically-guided algorithm development and sample size optimization for age-related macular degeneration cases and controls in electronic health records from the VA Million Veteran Program.

Electronic health records (EHRs) linked to extensive biorepositories and supplemented with lifestyle, behavioral, and environmental exposure data, have enormous potential to contribute to genomic discovery, a necessary step in the pathway towards translational or precision medicine. A major bottleneck in incorporating EHRs into genomic studies is the extraction of research-grade variables for analysis, particularly when gold-standard measurements are not available or accessible. Here we develop algorithms for age-related macular degeneration (AMD), a common cause of blindness among the elderly, and controls free of AMD. These computable phenotypes were developed using billing codes (ICD-9-CM and ICD-10-CM) and Current Procedural Terminology (CPT) codes and evaluated in two study sites of the Veterans Affairs Million Veteran Program: Louis Stokes Cleveland VA Medical Center and the Providence VA Medical Center. After establishing a high overall positive and negative predictive values (93% and 95%, respectively) through manual chart review, the candidate algorithm was deployed in the full VA MVP dataset of >500,000 participants. The algorithm was then optimized in a data cube using a variety of approaches including adjusting inclusion age thresholds by examining previously-reported genetic associations for CFH (rs10801555, a proxy for rs1061170) and ARMS2 (rs10490924). The algorithm with the smallest p-values for the known genetic associations was selected for downstream and on-going AMD genomic discovery efforts. This two-phase approach to developing research-grade case/control variables for AMD genomic studies capitalizes on established genetic associations resulting in high precision and optimized sample sizes, an approach that can be applied to other large-scale biobanks linked to EHRs for precision medicine research.

Patient perspectives on an opioid overdose education and naloxone distribution program in the U.S. Department of Veterans Affairs.

BACKGROUND: In an effort to prevent opioid overdose mortality among Veterans, Department of Veterans Affairs (VA) facilities began implementing opioid overdose education and naloxone distribution (OEND) in 2013 and a national program began in 2014. VA is the first national health care system to implement OEND. The goal of this study is to examine patient perceptions of OEND training and naloxone kits. METHODS: Four focus groups were conducted between December 2014 and February 2015 with 21 patients trained in OEND. Participants were recruited from a VA residential facility in California with a substance use disorder treatment program (mandatory OEND training) and a homeless program (optional OEND training). Data were analyzed using matrices and open and closed coding approaches to identify participants' perspectives on OEND training including benefits, concerns, differing opinions, and suggestions for improvement. RESULTS: Veterans thought OEND training was interesting, novel, and empowering, and that naloxone kits will save lives. Some veterans expressed concern about using syringes in the kits. A few patients who never used opioids were not interested in receiving kits. Veterans had differing opinions about legal and liability issues, whether naloxone kits might contribute to relapse, and whether and how to involve family in training. Some veterans expressed uncertainty about the effects of naloxone. Suggested improvements included active learning approaches, enhanced training materials, and increased advertisement. CONCLUSIONS: OEND training was generally well received among study participants, including those with no indication for a naloxone kit. Patients described a need for OEND and believed it could save lives. Patient feedback on OEND training benefits, concerns, opinions, and suggestions provides important insights to inform future OEND training programs both within VA and in other health care settings. Training is critical to maximizing the potential for OEND to save lives, and this study includes specific suggestions for improving the effectiveness and acceptability of training.

Phenylpropanolamine appears not to promote weight loss in patients with schizophrenia who have gained weight during clozapine treatment.

BACKGROUND: Weight gain is a common side effect of clozapine treatment and may expose patients to obesity-associated health risks. We proposed that concomitant treatment with an appetite suppressant such as phenylpropanolamine (PPA) would lead to a decrease in appetite and therefore loss of weight. METHOD: This was a 12-week, double-blind, randomized, placebo-controlled trial of PPA, 75 mg/day, in outpatients with treatment-refractory schizophrenia (DSM-IV) who were stable on clozapine treatment for at least 4 months and had gained > 10% of their baseline body weight since starting clozapine. Patients were evaluated for adverse effects and weighed weekly. A Positive and Negative Syndrome Scale (PANSS) assessment, a short dietary quiz, and blood indices were completed monthly. RESULTS: Sixteen patients were equally randomly assigned to receive PPA or placebo. The groups did not differ in mean age, baseline weight, dose of clozapine, baseline PANSS scores, or the percent of weight gained since the start of clozapine. There was no significant effect of treatment on weight (t = 0.219, df = 10, p = .831). There was no significant change in either the total PANSS scores (t = -0.755, df = 10, p = .468), the positive or negative symptom cluster scores, or any of the remaining variables. CONCLUSION: Phenylpropanolamine 75 mg/day was well tolerated but was not effective in reversing established weight gain associated with clozapine treatment in stable outpatients with schizophrenia.