Citations

Introduction: Accurately balancing risks of interventional treatment and intracranial hemorrhage (ICH) in the untreated course of unruptured brain arteriovenous malformation (uBAVM) patients is critical for optimal management. Observational studies of uBAVM afford an opportunity to address important gaps and previous criticisms of randomized data to help guide treatment decisions and assess long-term risk/benefit ratio. We previously published an individual patient data meta-analysis (IPDMA) in 4 MARS cohorts and identified ICH presentation and increasing age as significant predictors of ICH during follow-up, but was not powered to detect predictors in those with uBAVM. Thus, the goals of this project are to identify risk factors for ICH in uBAVMs, to estimate the risk with precision, and to create personalized, risk-prediction models. Methods: MARS is an international, multi-center study of 11 cohorts with target enrollment of 4,500 uBAVM patients ascertained through population-based or referral-based studies. We are harmonizing both retrospective and prospective data, including clinical, lifestyle, imaging, and angiographic factors. Treatments, complications, and functional outcomes (physician and patient-reported) will be updated annually between 2018-2022. We propose to: 1) identify predictors of outcome in uBAVMs using IPDMA; 2) test whether long-term outcomes differ by treatment using statistical approaches for causal inference and unbiased estimates; 3) compare treatment outcomes in randomized and non-randomized data to address generalizability; and 4) validate models and provide a novel tool for calculating individualized risks. Eligible sites have: a) prior BAVM publications; b) data from a minimum of 100 uBAVM patients; c) agree to random outcome adjudication; and d) agree to MARS data sharing policy. Discussion: The NIH-funded MARS consortium will provide important and comprehensive characterization of the untreated and treated course of uBAVMs, using large observational datasets and sophisticated epidemiological approaches. The data and models generated will be a useful resource for decision-making. We welcome participation from eligible sites with longitudinal data on uBAVM patients

AbstractThe purpose of this study was to estimate the extent of potential antidepressant overprescribing in a geographically defined U.S. population, and to determine the indications and factors that account for it. We conducted a cohort study of new antidepressant prescriptions for elderly residents of Olmsted County, Minnesota, 2005‐2012, using the Rochester Epidemiology Project medical records‐linkage system. Indications for antidepressants were abstracted from health records for all cohort members. Potential antidepressant overprescribing was defined based on regulatory approval, the level of evidence identified from a standardized drug information database, and multidisciplinary expert review. Predictors of potential antidepressant overprescribing were investigated using logistic regression models, stratified by general antidepressant indication (general medical indication, specific psychiatric diagnosis, and non‐specific psychiatric symptoms). Potential antidepressant overprescribing occurred in 24% of 3199 incident antidepressant prescriptions during the study period, and involved primarily newer antidepressants that were prescribed for non‐specific psychiatric symptoms and subthreshold diagnoses. Potential antidepressant overprescribing was associated with nursing home residence, having a higher number of comorbid medical conditions and outpatient prescribers, taking more concomitant medications, having greater use of urgent or acute care services in the year preceding the index antidepressant prescription, and being prescribed antidepressants via telephone, e‐mail, or patient portal. In conclusion, potential antidepressant overprescribing occurred in elderly persons and involved mainly newer antidepressants used for non‐specific psychiatric symptoms and subthreshold diagnoses, and was associated with indicators of higher clinical complexity or severity and with prescribing without face‐to‐face patient contact.

BACKGROUND Patient-reported outcomes are critical to research directed at maximizing patient benefit. The outcomes patients consider most relevant in the treatment of skin cancer have not been directly investigated. OBJECTIVE To develop a ranked list of outcomes deemed most important by patients with skin cancer through a proctored Delphi process. METHODS Twenty-one patients with a history of skin cancer volunteered to participate in the patient summit. The patient members participated in a guided discussion to generate a long list of potentially relevant outcomes. The list was then condensed and ranked through 2 rounds of a proctored Delphi process. RESULTS Patients were diverse in their skin cancer histories and complexities, ages, and states of residence. Twelve themes were rated as highly important by 70% or more of participants. Most of these themes related to patient education and the collaborative nature of the physician–patient relationship. Fear of recurrence and cosmetic outcome were also highly rated. Limitations include a preponderance of older patients and patients from the midwest and northeast. CONCLUSION Patients with skin cancer overwhelmingly prioritize a shared decision-making process, in which they are actively engaged and value detailed education regarding their disease. This should inform future research directed at skin cancer treatment and current physician–patient interactions.

BACKGROUND Few reports describe squamous cell carcinoma (SCC) arising in hidradenitis suppurativa (HS). OBJECTIVE The 2 objectives were (1) to describe the clinical characteristics, pathologic findings, and postoperative outcomes of SCC in HS and (2) to assess whether human papillomavirus (HPV) is involved in the pathogenesis. MATERIALS AND METHODS Cases of SCC in HS were identified through institutional medical records (1976–2013) and the Rochester Epidemiology Project. Tumor specimens were assessed for HPV DNA/RNA with in situ hybridization. RESULTS Twelve patients were identified (11 Caucasians and 9 men). All SCCs involved gluteal, perianal, or perineal skin; 1 patient had, in addition, involvement of the vagina. Surgical excision was performed on all 12 patients, 4 of whom had a colostomy. Mean duration of HS before SCC development was 28.5 years (range, 15–53 years). Mean follow-up was 4.3 years after surgical excision. Seven of 12 patients followed had postoperative SCC recurrence. Squamous cell carcinoma caused death despite wide surgical excision in these 7 patients. Of the remaining 5 patients, 4 are unknown and 1 who did not recur had an in situ SCC (Bowen disease carcinoma). Squamous cell carcinoma was not associated with high-risk or low-risk HPV. CONCLUSION Invasive SCC arising in HS carries a high risk of death.

Background: Proteomic approaches allow measurement of thousands of proteins in a single specimen, which can accelerate biomarker discovery. However, applying these technologies to massive biobanks is not currently feasible because of the practical barriers and costs of implementing such assays at scale. To overcome these challenges, we used a “virtual proteomic” approach, linking genetically predicted protein levels to clinical diagnoses in >40 000 individuals. Methods: We used genome-wide association data from the Framingham Heart Study (n=759) to construct genetic predictors for 1129 plasma protein levels. We validated the genetic predictors for 268 proteins and used them to compute predicted protein levels in 41 288 genotyped individuals in the Electronic Medical Records and Genomics (eMERGE) cohort. We tested associations for each predicted protein with 1128 clinical phenotypes. Lead associations were validated with directly measured protein levels and either low-density lipoprotein cholesterol or subclinical atherosclerosis in the MDCS (Malmö Diet and Cancer Study; n=651). Results: In the virtual proteomic analysis in eMERGE, 55 proteins were associated with 89 distinct diagnoses at a false discovery rate q<0.1. Among these, 13 associations involved lipid (n=7) or atherosclerosis (n=6) phenotypes. We tested each association for validation in MDCS using directly measured protein levels. At Bonferroni-adjusted significance thresholds, levels of apolipoprotein E isoforms were associated with hyperlipidemia, and circulating C-type lectin domain family 1 member B and platelet-derived growth factor receptor-β predicted subclinical atherosclerosis. Odds ratios for carotid atherosclerosis were 1.31 (95% CI, 1.08–1.58; P =0.006) per 1-SD increment in C-type lectin domain family 1 member B and 0.79 (0.66–0.94; P =0.008) per 1-SD increment in platelet-derived growth factor receptor-β. Conclusions: We demonstrate a biomarker discovery paradigm to identify candidate biomarkers of cardiovascular and other diseases.