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Purpose: Management of schizophrenia among Blacks in the United States is affected by persistent disparities. This review explored response to atypical antipsychotics among Blacks compared with other groups to assess systematic variation that may contribute to disparities., Methods: We conducted a quasi-systematic review of studies reporting response to atypical antipsychotics among Blacks compared with other groups, including effects of genetic variation., Results: Of 48 identified research articles, 29 assessed differences in outcomes without inclusion of genetic variation and 20 explored effects of genetic variation; of note: one article included both types of data. Analysis of the 29 papers with clinical outcomes only suggests that while data on efficacy and risk of movement disorders were heterogeneous, findings indicate increased risk of metabolic effects and neutropenia among Blacks. Of the 20 articles exploring effects of genetic variation, allelic or genotypic variations involving several genes were associated with altered efficacy or safety among Blacks but not Whites, including risk of decreased response involving variation in DRD4 and DRD1 , and improved efficacy associated with variants in DRD2 , COMT , and RGS4 . Others showed significant improvement in treatment response only among Whites, including variation in DTNBP1 , DRD4 , and GNB3 ., Conclusions: The current analysis can help tailor management among Blacks using an atypical antipsychotic. Heterogeneity in genetic variation effects and response allele frequency suggests that pharmacogenetics approaches for atypical antipsychotics will need to explicitly incorporate race and ethnicity., Competing Interests: Competing Interests: None declared., (Copyright © 2020, Ethnicity & Disease, Inc.)

Background: The All of Us Research Program is building a national longitudinal cohort and collecting data from multiple information sources (e.g., biospecimens, electronic health records, and mobile/wearable technologies) to advance precision medicine. Participant-provided information, collected via surveys, will complement and augment these information sources. We report the process used to develop and refine the initial three surveys for this program., Methods: The All of Us survey development process included: (1) prioritization of domains for scientific needs, (2) examination of existing validated instruments, (3) content creation, (4) evaluation and refinement via cognitive interviews and online testing, (5) content review by key stakeholders, and (6) launch in the All of Us electronic participant portal. All content was translated into Spanish., Results: We conducted cognitive interviews in English and Spanish with 169 participants, and 573 individuals completed online testing. Feedback led to over 40 item content changes. Lessons learned included: (1) validated survey instruments performed well in diverse populations reflective of All of Us; (2) parallel evaluation of multiple languages can ensure optimal survey deployment; (3) recruitment challenges in diverse populations required multiple strategies; and (4) key stakeholders improved integration of surveys into larger Program context., Conclusions: This efficient, iterative process led to successful testing, refinement, and launch of three All of Us surveys. Reuse of All of Us surveys, available at http://researchallofus.org, may facilitate large consortia targeting diverse populations in English and Spanish to capture participant-provided information to supplement other data, such as genetic, physical measurements, or data from electronic health records.

When clinical trial enrollment is not an option for seriously ill patients whose illnesses have not responded to approved treatment options, those patients and their physicians may consider gaining access to investigational therapies through a pathway established by the Food and Drug Administration (FDA) called expanded access. However, recent events have highlighted the challenging dynamics involved in accessing investigational therapies through expanded access that include a complex interplay of factors involving the patient, physician, drug company, FDA, and, increasingly, social media. The authors offer several potential strategies to streamline what is otherwise an arduous process for all involved. (1) The drug company should prospectively determine whether it will establish an expanded access program for specific drugs. (2) A central clearinghouse for companies should support registration of expanded access drugs for suitable patients. (3) The determination of whether a patient fits criteria would be made by an independent review board of clinicians. (4) An independent coordinating center is needed; academic health centers are ideally suited for that role. (5) Adequate financing of the costs of therapy need to be in place to make expanded access a reality, given frequent lack of payer coverage for therapies. (6) Further enhancement of regulatory pathways, approaches, or rules would promote expanded access. (7) Patients should explicitly acknowledge the limited data available. (8) There should be a shared, secure, technical platform to facilitate expanded access. All the authors' strategies present important prospects for improving treatment options for the most seriously ill patients.

This report provides an overview of methods used to conduct systematic reviews for the US Food and Drug Administration (FDA) Mini-Sentinel project, which is designed to inform the development of safety monitoring tools for FDA-regulated products including vaccines. The objective of these reviews was to summarize the literature describing algorithms (e.g., diagnosis or procedure codes) to identify health outcomes in administrative and claims data. A particular focus was the validity of the algorithms when compared to reference standards such as diagnoses in medical records. The overarching goal was to identify algorithms that can accurately identify the health outcomes for safety surveillance. We searched the MEDLINE database via PubMed and required dual review of full text articles and of data extracted from studies. We also extracted data on each study's methods for case validation. We reviewed over 5600 abstracts/full text studies across 15 health outcomes of interest. Nearly 260 studies met our initial criteria (conducted in the US or Canada, used an administrative database, reported case-finding algorithm). Few studies (N=45), however, reported validation of case-finding algorithms (sensitivity, specificity, positive or negative predictive value). Among these, the most common approach to validation was to calculate positive predictive values, based on a review of medical records as the reference standard. Of the studies reporting validation, the ease with which a given clinical condition could be identified in administrative records varied substantially, both by the clinical condition and by other factors such as the clinical setting, which relates to the disease prevalence., (Copyright © 2013 Elsevier Ltd. All rights reserved.)