Recommendations of Common Data Elements to Advance the Science of Selfâ Management of Chronic Conditions

PurposeCommon data elements (CDEs) are increasingly being used by researchers to promote data sharing across studies. The purposes of this article are to (a) describe the theoretical, conceptual, and definition issues in the development of a set of CDEs for research addressing selfâ management of chronic conditions; (b) propose an initial set of CDEs and their measures to advance the science of selfâ management; and (c) recommend implications for future research and dissemination.Design and MethodsBetween July 2014 and December 2015 the directors of the National Institute of Nursing Research (NINR)â funded P20 and P30 centers of excellence and NINR staff met in a series of telephone calls and a faceâ toâ face NINRâ sponsored meeting to select a set of recommended CDEs to be used in selfâ management research. A list of potential CDEs was developed from examination of common constructs in current selfâ management frameworks, as well as identification of variables frequently used in studies conducted in the centers of excellence.FindingsThe recommended CDEs include measures of three selfâ management processes: activation, selfâ regulation, and selfâ efficacy for managing chronic conditions, and one measure of a selfâ management outcome, global health.ConclusionsThe selfâ management of chronic conditions, which encompasses a considerable number of processes, behaviors, and outcomes across a broad range of chronic conditions, presents several challenges in the identification of a parsimonious set of CDEs. This initial list of recommended CDEs for use in selfâ management research is provisional in that it is expected that over time it will be refined. Comment and recommended revisions are sought from the research and practice communities.Clinical RelevanceThe use of CDEs can facilitate generalizability of research findings across diverse population and interventions.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134268/1/jnu12233_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134268/2/jnu12233.pd

The Use of Technology to Support Precision Health in Nursing Science

PurposeThis article outlines how current nursing research can utilize technology to advance symptom and self‐management science for precision health and provides a roadmap for the development and use of technologies designed for this purpose.ApproachAt the 2018 annual conference of the National Institute of Nursing Research (NINR) Research Centers, nursing and interdisciplinary scientists discussed the use of technology to support precision health in nursing research projects and programs of study. Key themes derived from the presentations and discussion were summarized to create a proposed roadmap for advancement of technologies to support health and well‐being.ConclusionsTechnology to support precision health must be centered on the user and designed to be desirable, feasible, and viable. The proposed roadmap is composed of five iterative steps for the development, testing, and implementation of technology‐based/enhanced self‐management interventions. These steps are (a) contextual inquiry, focused on the relationships among humans, and the tools and equipment used in day‐to‐day life; (b) value specification, translating end‐user values into end‐user requirements; (c) design, verifying that the technology/device can be created and developing the prototype(s); (d) operationalization, testing the intervention in a real‐world setting; and (e) summative evaluation, collecting and analyzing viability metrics, including process data, to evaluate whether the technology and the intervention have the desired effect.Clinical RelevanceInterventions using technology are increasingly popular in precision health. Use of a standard multistep process for the development and testing of technology is essential.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151985/1/jnu12518.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151985/2/jnu12518_am.pd

Biomarkers as Common Data Elements for Symptom and Selfâ Management Science

PurposeBiomarkers as common data elements (CDEs) are important for the characterization of biobehavioral symptoms given that once a biologic moderator or mediator is identified, biologically based strategies can be investigated for treatment efforts. Just as a symptom inventory reflects a symptom experience, a biomarker is an indicator of the symptom, though not the symptom per se. The purposes of this position paper are to (a) identify a â minimum setâ of biomarkers for consideration as CDEs in symptom and selfâ management science, specifically biochemical biomarkers; (b) evaluate the benefits and limitations of such a limited array of biomarkers with implications for symptom science; (c) propose a strategy for the collection of the endorsed minimum set of biologic samples to be employed as CDEs for symptom science; and (d) conceptualize this minimum set of biomarkers consistent with National Institute of Nursing Research (NINR) symptoms of fatigue, depression, cognition, pain, and sleep disturbance.Design and MethodsFrom May 2016 through January 2017, a working group consisting of a subset of the Directors of the NINR Centers of Excellence funded by P20 or P30 mechanisms and NINR staff met bimonthly via telephone to develop this position paper suggesting the addition of biomarkers as CDEs. The full group of Directors reviewed drafts, provided critiques and suggestions, recommended the minimum set of biomarkers, and approved the completed document. Best practices for selecting, identifying, and using biological CDEs as well as challenges to the use of biological CDEs for symptom and selfâ management science are described. Current platforms for sample outcome sharing are presented. Finally, biological CDEs for symptom and selfâ management science are proposed along with implications for future research and use of CDEs in these areas.FindingsThe recommended minimum set of biomarker CDEs include proâ and antiâ inflammatory cytokines, a hypothalamicâ pituitaryâ adrenal axis marker, cortisol, the neuropeptide brainâ derived neurotrophic factor, and DNA polymorphisms.ConclusionsIt is anticipated that this minimum set of biomarker CDEs will be refined as knowledge regarding biologic mechanisms underlying symptom and selfâ management science further develop. The incorporation of biological CDEs may provide insights into mechanisms of symptoms, effectiveness of proposed interventions, and applicability of chosen theoretical frameworks. Similarly, as for the previously suggested NINR CDEs for behavioral symptoms and selfâ management of chronic conditions, biological CDEs offer the potential for collaborative efforts that will strengthen symptom and selfâ management science.Clinical RelevanceThe use of biomarker CDEs in biobehavioral symptoms research will facilitate the reproducibility and generalizability of research findings and benefit symptom and selfâ management science.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143764/1/jnu12378.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143764/2/jnu12378_am.pd

Ultrafast and high-throughput mass spectrometric assay for therapeutic drug monitoring of antiretroviral drugs in pediatric HIV-1 infection applying dried blood spots

Kaletra® (Abott Laboratories) is a co-formulated medication used in the treatment of HIV-1-infected children, and it contains the two antiretroviral protease inhibitor drugs lopinavir and ritonavir. We validated two new ultrafast and high-throughput mass spectrometric assays to be used for therapeutic drug monitoring of lopinavir and ritonavir concentrations in whole blood and in plasma from HIV-1-infected children. Whole blood was blotted onto dried blood spot (DBS) collecting cards, and plasma was collected simultaneously. DBS collecting cards were extracted by an acetonitrile/water mixture while plasma samples were deproteinized with acetone. Drug concentrations were determined by matrix-assisted laser desorption/ionization-triple quadrupole tandem mass spectrometry (MALDI-QqQ-MS/MS). The application of DBS made it possible to measure lopinavir and ritonavir in whole blood in therapeutically relevant concentrations. The MALDI-QqQ-MS/MS plasma assay was successfully cross-validated with a commonly used high-performance liquid chromatography (HPLC)–ultraviolet (UV) assay for the therapeutic drug monitoring (TDM) of HIV-1-infected patients, and it showed comparable performance characteristics. Observed DBS concentrations showed as well, a good correlation between plasma concentrations obtained by MALDI-QqQ-MS/MS and those obtained by the HPLC-UV assay. Application of DBS for TDM proved to be a good alternative to the normally used plasma screening. Moreover, collection of DBS requires small amounts of whole blood which can be easily performed especially in (very) young children where collection of large whole blood amounts is often not possible. DBS is perfectly suited for TDM of HIV-1-infected children; but nevertheless, DBS can also easily be applied for TDM of patients in areas with limited or no laboratory facilities

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Genomic characterization of malignant progression in neoplastic pancreatic cysts

Intraductal papillary mucinous neoplasms (IPMNs) and mucinous cystic neoplasms (MCNs) are non-invasive neoplasms that are often observed in association with invasive pancreatic cancers, but their origins and evolutionary relationships are poorly understood. In this study, we analyze 148 samples from IPMNs, MCNs, and small associated invasive carcinomas from 18 patients using whole exome or targeted sequencing. Using evolutionary analyses, we establish that both IPMNs and MCNs are direct precursors to pancreatic cancer. Mutations in SMAD4 and TGFBR2 are frequently restricted to invasive carcinoma, while RNF43 alterations are largely in non-invasive lesions. Genomic analyses suggest an average window of over three years between the development of high-grade dysplasia and pancreatic cancer. Taken together, these data establish non-invasive IPMNs and MCNs as origins of invasive pancreatic cancer, identifying potential drivers of invasion, highlighting the complex clonal dynamics prior to malignant transformation, and providing opportunities for early detection and intervention

Network Models of TEM β-Lactamase Mutations Coevolving under Antibiotic Selection Show Modular Structure and Anticipate Evolutionary Trajectories

Understanding how novel functions evolve (genetic adaptation) is a critical goal of evolutionary biology. Among asexual organisms, genetic adaptation involves multiple mutations that frequently interact in a non-linear fashion (epistasis). Non-linear interactions pose a formidable challenge for the computational prediction of mutation effects. Here we use the recent evolution of β-lactamase under antibiotic selection as a model for genetic adaptation. We build a network of coevolving residues (possible functional interactions), in which nodes are mutant residue positions and links represent two positions found mutated together in the same sequence. Most often these pairs occur in the setting of more complex mutants. Focusing on extended-spectrum resistant sequences, we use network-theoretical tools to identify triple mutant trajectories of likely special significance for adaptation. We extrapolate evolutionary paths (n = 3) that increase resistance and that are longer than the units used to build the network (n = 2). These paths consist of a limited number of residue positions and are enriched for known triple mutant combinations that increase cefotaxime resistance. We find that the pairs of residues used to build the network frequently decrease resistance compared to their corresponding singlets. This is a surprising result, given that their coevolution suggests a selective advantage. Thus, β-lactamase adaptation is highly epistatic. Our method can identify triplets that increase resistance despite the underlying rugged fitness landscape and has the unique ability to make predictions by placing each mutant residue position in its functional context. Our approach requires only sequence information, sufficient genetic diversity, and discrete selective pressures. Thus, it can be used to analyze recent evolutionary events, where coevolution analysis methods that use phylogeny or statistical coupling are not possible. Improving our ability to assess evolutionary trajectories will help predict the evolution of clinically relevant genes and aid in protein design

Structure and Inhibition of Microbiome β-Glucuronidases Essential to the Alleviation of Cancer Drug Toxicity

SummaryThe selective inhibition of bacterial β-glucuronidases was recently shown to alleviate drug-induced gastrointestinal toxicity in mice, including the damage caused by the widely used anticancer drug irinotecan. Here, we report crystal structures of representative β-glucuronidases from the Firmicutes Streptococcus agalactiae and Clostridium perfringens and the Proteobacterium Escherichia coli, and the characterization of a β-glucuronidase from the Bacteroidetes Bacteroides fragilis. While largely similar in structure, these enzymes exhibit marked differences in catalytic properties and propensities for inhibition, indicating that the microbiome maintains functional diversity in orthologous enzymes. Small changes in the structure of designed inhibitors can induce significant conformational changes in the β-glucuronidase active site. Finally, we establish that β-glucuronidase inhibition does not alter the serum pharmacokinetics of irinotecan or its metabolites in mice. Together, the data presented advance our in vitro and in vivo understanding of the microbial β-glucuronidases, a promising new set of targets for controlling drug-induced gastrointestinal toxicity

Characteristics of HIV-1 Discordant Couples Enrolled in a Trial of HSV-2 Suppression to Reduce HIV-1 Transmission: The Partners Study

Background: The Partners HSV-2/HIV-1 Transmission Study (Partners Study) is a phase III, placebo-controlled trial of daily acyclovir for genital herpes (HSV-2) suppression among HIV-1/HSV-2 co-infected persons to reduce HIV-1 transmission to their HIV-1 susceptible partners, which requires recruitment of HIV-1 serodiscordant heterosexual couples. We describe the baseline characteristics of this cohort. Methods: HIV-1 serodiscordant heterosexual couples, in which the HIV-1 infected partner was HSV-2 seropositive, had a CD4 count ≥250 cells/mcL and was not on antiretroviral therapy, were enrolled at 14 sites in East and Southern Africa. Demographic, behavioral, clinical and laboratory characteristics were assessed. Results: Of the 3408 HIV-1 serodiscordant couples enrolled, 67% of the HIV-1 infected partners were women. Couples had cohabitated for a median of 5 years (range 2–9) with 28% reporting unprotected sex in the month prior to enrollment. Among HIV-1 susceptible participants, 86% of women and 59% of men were HSV-2 seropositive. Other laboratory-diagnosed sexually transmitted infections were uncommon (500 relative to <350, respectively, p<0.001). Conclusions: The Partners Study successfully enrolled a cohort of 3408 heterosexual HIV-1 serodiscordant couples in Africa at high risk for HIV-1 transmission. Follow-up of this cohort will evaluate the efficacy of acyclovir for HSV-2 suppression in preventing HIV-1 transmission and provide insights into biological and behavioral factors determining heterosexual HIV-1 transmission. Trial Registration ClinicalTrials.gov NCT0019451