Browsing by Author "Pollin, Toni I."

Now showing 1 - 7 of 7
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    Developing a Common Framework for Evaluating the Implementation of Genomic Medicine Interventions in Clinical Care: The IGNITE Network’s Common Measures Working Group
    (Nature Publishing group, 2018-06) Orlando, Lori A.; Sperber, Nina R.; Voils, Corrine; Nichols, Marshall; Myers, Rachel A.; Wu, R. Ryanne; Rakhra-Burris, Tejinder; Levy, Kenneth D.; Levy, Mia; Pollin, Toni I.; Guan, Yue; Horowitz, Carol R.; Ramos, Michelle; Kimmel, Stephen E.; McDonough, Caitrin W.; Madden, Ebony B.; Damschroder, Laura J.; Medicine, School of Medicine
    Purpose Implementation research provides a structure for evaluating the clinical integration of genomic medicine interventions. This paper describes the Implementing GeNomics In PracTicE (IGNITE) Network’s efforts to promote: 1) a broader understanding of genomic medicine implementation research; and 2) the sharing of knowledge generated in the network. Methods To facilitate this goal the IGNITE Network Common Measures Working Group (CMG) members adopted the Consolidated Framework for Implementation Research (CFIR) to guide their approach to: identifying constructs and measures relevant to evaluating genomic medicine as a whole, standardizing data collection across projects, and combining data in a centralized resource for cross network analyses. Results CMG identified ten high-priority CFIR constructs as important for genomic medicine. Of those, eight didn’t have standardized measurement instruments. Therefore, we developed four survey tools to address this gap. In addition, we identified seven high-priority constructs related to patients, families, and communities that did not map to CFIR constructs. Both sets of constructs were combined to create a draft genomic medicine implementation model. Conclusion We developed processes to identify constructs deemed valuable for genomic medicine implementation and codified them in a model. These resources are freely available to facilitate knowledge generation and sharing across the field.
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    Lifestyle and Metformin Ameliorate Insulin Sensitivity Independently of the Genetic Burden of Established Insulin Resistance Variants in Diabetes Prevention Program Participants
    (American Diabetes Association, 2016-02) Hivert, Marie-France; Christophi, Costas A.; Franks, Paul W.; Jablonski, Kathleen A.; Ehrmann, David A.; Kahn, Steven E.; Horton, Edward S.; Pollin, Toni I.; Mather, Kieren J.; Perreault, Leigh; Barrett-Connor, Elizabeth; Knowler, William C.; Florez, Jose C.; Department of Medicine, IU School of Medicine
    Large genome-wide association studies of glycemic traits have identified genetics variants that are associated with insulin resistance (IR) in the general population. It is unknown whether people with genetic enrichment for these IR variants respond differently to interventions that aim to improve insulin sensitivity. We built a genetic risk score (GRS) based on 17 established IR variants and effect sizes (weighted IR-GRS) in 2,713 participants of the Diabetes Prevention Program (DPP) with genetic consent. We tested associations between the weighted IR-GRS and insulin sensitivity index (ISI) at baseline in all participants, and with change in ISI over 1 year of follow-up in the DPP intervention (metformin and lifestyle) and control (placebo) arms. All models were adjusted for age, sex, ethnicity, and waist circumference at baseline (plus baseline ISI for 1-year ISI change models). A higher IR-GRS was associated with lower baseline ISI (β = -0.754 [SE = 0.229] log-ISI per unit, P = 0.001 in fully adjusted models). There was no differential effect of treatment for the association between the IR-GRS on the change in ISI; higher IR-GRS was associated with an attenuation in ISI improvement over 1 year (β = -0.520 [SE = 0.233], P = 0.03 in fully adjusted models; all treatment arms). Lifestyle intervention and metformin treatment improved the ISI, regardless of the genetic burden of IR variants.
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    Multisite Investigation of Outcomes With Implementation of CYP2C19 Genotype-Guided Antiplatelet Therapy After Percutaneous Coronary Intervention
    (Elsevier, 2018-01-22) Cavallari, Larisa H.; Lee, Craig R.; Beitelshees, Amber L.; Cooper-DeHoff, Rhonda M.; Duarte, Julio D.; Voora, Deepak; Kimmel, Stephen E.; McDonough, Caitrin W.; Gong, Yan; Dave, Chintan V.; Pratt, Victoria M.; Alestock, Tameka D.; Anderson, R. David; Alsip, Jorge; Ardati, Amer K.; Brott, Brigitta C.; Brown, Lawrence; Chumnumwat, Supatat; Clare-Salzler, Michael J.; Coons, James C.; Denny, Joshua C.; Dillon, Chrisly; Elsey, Amanda R.; Hamadeh, Issam; Harada, Shuko; Hillegass, William B.; Hines, Lindsay; Horenstein, Richard B.; Howell, Lucius A.; Jeng, Linda J.B.; Kelemen, Mark D.; Lee, Y.M.; Magvanjav, Oyunbileg; Montasser, May; Nelson, David R.; Nutescu, Edith A.; Nwaba, Devon C.; Pakyz, Ruth E.; Palmer, Kathleen; Peterson, Josh F.; Pollin, Toni I.; Quinn, Alison H.; Robinson, Shawn W.; Schub, Jamie; Skaar, Todd C.; Smith, Donald M.; Sriramoju, Vindhya B.; Starostik, Petr; Stys, Tomasz P.; Stevenson, James M.; Varunok, Nicholas; Vesely, Mark R.; Wake, Dyson T.; Weck, Karen E.; Weitzel, Kristin W.; Wilke, Russell A.; Willig, James; Zhao, Richard Y.; Kreutz, Rolf P.; Stouffer, George A.; Empey, Philip E.; Limdi, Nita A.; Shuldiner, Alan R.; Winterstein, Almut G.; Johnson, Julie A.; Medical and Molecular Genetics, School of Medicine
    OBJECTIVES: This multicenter pragmatic investigation assessed outcomes following clinical implementation of CYP2C19 genotype-guided antiplatelet therapy after percutaneous coronary intervention (PCI). BACKGROUND: CYP2C19 loss-of-function alleles impair clopidogrel effectiveness after PCI. METHODS: After clinical genotyping, each institution recommended alternative antiplatelet therapy (prasugrel, ticagrelor) in PCI patients with a loss-of-function allele. Major adverse cardiovascular events (defined as myocardial infarction, stroke, or death) within 12 months of PCI were compared between patients with a loss-of-function allele prescribed clopidogrel versus alternative therapy. Risk was also compared between patients without a loss-of-function allele and loss-of-function allele carriers prescribed alternative therapy. Cox regression was performed, adjusting for group differences with inverse probability of treatment weights. RESULTS: Among 1,815 patients, 572 (31.5%) had a loss-of-function allele. The risk for major adverse cardiovascular events was significantly higher in patients with a loss-of-function allele prescribed clopidogrel versus alternative therapy (23.4 vs. 8.7 per 100 patient-years; adjusted hazard ratio: 2.26; 95% confidence interval: 1.18 to 4.32; p = 0.013). Similar results were observed among 1,210 patients with acute coronary syndromes at the time of PCI (adjusted hazard ratio: 2.87; 95% confidence interval: 1.35 to 6.09; p = 0.013). There was no difference in major adverse cardiovascular events between patients without a loss-of-function allele and loss-of-function allele carriers prescribed alternative therapy (adjusted hazard ratio: 1.14; 95% confidence interval: 0.69 to 1.88; p = 0.60). CONCLUSIONS: These data from real-world observations demonstrate a higher risk for cardiovascular events in patients with a CYP2C19 loss-of-function allele if clopidogrel versus alternative therapy is prescribed. A future randomized study of genotype-guided antiplatelet therapy may be of value.
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    Physician-Reported Benefits and Barriers to Clinical Implementation of Genomic Medicine: A Multi-Site IGNITE-Network Survey
    (MDPI, 2018-07-24) Obeng, Aniwaa Owusu; Fei, Kezhen; Levy, Kenneth D.; Elsey, Amanda R.; Pollin, Toni I.; Ramirez, Andrea H.; Weitzel, Kristin W.; Horowitz, Carol R.; Medicine, School of Medicine
    Genetic medicine is one of the key components of personalized medicine, but adoption in clinical practice is still limited. To understand potential barriers and provider attitudes, we surveyed 285 physicians from five Implementing GeNomics In pracTicE (IGNITE) sites about their perceptions as to the clinical utility of genetic data as well as their preparedness to integrate it into practice. These responses were also analyzed in comparison to the type of study occurring at the physicians' institution (pharmacogenetics versus disease genetics). The majority believed that genetic testing is clinically useful; however, only a third believed that they had obtained adequate training to care for genetically "high-risk" patients. Physicians involved in pharmacogenetics initiatives were more favorable towards genetic testing applications; they found it to be clinically useful and felt more prepared and confident in their abilities to adopt it into their practice in comparison to those participating in disease genetics initiatives. These results suggest that investigators should explore which attributes of clinical pharmacogenetics (such as the use of simplified genetics-guided recommendations) can be implemented to improve attitudes and preparedness to implement disease genetics in care. Most physicians felt unprepared to use genetic information in their practice; accordingly, major steps should be taken to develop effective clinical tools and training strategies for physicians.
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    Qualitative study of system-level factors related to genomic implementation
    (Springer Nature, 2019-07) Zebrowski, Alexis M.; Ellis, Darcy E.; Barg, Frances K.; Sperber, Nina R.; Bernhardt, Barbara A.; Denny, Joshua C.; Dexter, Paul R.; Ginsburg, Geoffrey S.; Horowitz, Carol R.; Johnson, Julie A.; Levy, Mia A.; Orlando, Lori A.; Pollin, Toni I.; Skaar, Todd C.; Kimmel, Stephen E.; Medicine, School of Medicine
    PURPOSE: Research on genomic medicine integration has focused on applications at the individual level, with less attention paid to implementation within clinical settings. Therefore, we conducted a qualitative study using the Consolidated Framework for Implementation Research (CFIR) to identify system-level factors that played a role in implementation of genomic medicine within Implementing GeNomics In PracTicE (IGNITE) Network projects. METHODS: Up to four study personnel, including principal investigators and study coordinators from each of six IGNITE projects, were interviewed using a semistructured interview guide that asked interviewees to describe study site(s), progress at each site, and factors facilitating or impeding project implementation. Interviews were coded following CFIR inner-setting constructs. RESULTS: Key barriers included (1) limitations in integrating genomic data and clinical decision support tools into electronic health records, (2) physician reluctance toward genomic research participation and clinical implementation due to a limited evidence base, (3) inadequate reimbursement for genomic medicine, (4) communication among and between investigators and clinicians, and (5) lack of clinical and leadership engagement. CONCLUSION: Implementation of genomic medicine is hindered by several system-level barriers to both research and practice. Addressing these barriers may serve as important facilitators for studying and implementing genomics in practice.
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    Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine
    (Springer Nature, 2023) Tobias, Deirdre K.; Merino, Jordi; Ahmad, Abrar; Aiken, Catherine; Benham, Jamie L.; Bodhini, Dhanasekaran; Clark, Amy L.; Colclough, Kevin; Corcoy, Rosa; Cromer, Sara J.; Duan, Daisy; Felton, Jamie L.; Francis, Ellen C.; Gillard, Pieter; Gingras, Véronique; Gaillard, Romy; Haider, Eram; Hughes, Alice; Ikle, Jennifer M.; Jacobsen, Laura M.; Kahkoska, Anna R.; Kettunen, Jarno L. T.; Kreienkamp, Raymond J.; Lim, Lee-Ling; Männistö, Jonna M. E.; Massey, Robert; Mclennan, Niamh-Maire; Miller, Rachel G.; Morieri, Mario Luca; Most, Jasper; Naylor, Rochelle N.; Ozkan, Bige; Patel, Kashyap Amratlal; Pilla, Scott J.; Prystupa, Katsiaryna; Raghavan, Sridharan; Rooney, Mary R.; Schön, Martin; Semnani-Azad, Zhila; Sevilla-Gonzalez, Magdalena; Svalastoga, Pernille; Takele, Wubet Worku; Tam, Claudia Ha-Ting; Thuesen, Anne Cathrine B.; Tosur, Mustafa; Wallace, Amelia S.; Wang, Caroline C.; Wong, Jessie J.; Yamamoto, Jennifer M.; Young, Katherine; Amouyal, Chloé; Andersen, Mette K.; Bonham, Maxine P.; Chen, Mingling; Cheng, Feifei; Chikowore, Tinashe; Chivers, Sian C.; Clemmensen, Christoffer; Dabelea, Dana; Dawed, Adem Y.; Deutsch, Aaron J.; Dickens, Laura T.; DiMeglio, Linda A.; Dudenhöffer-Pfeifer, Monika; Evans-Molina, Carmella; Fernández-Balsells, María Mercè; Fitipaldi, Hugo; Fitzpatrick, Stephanie L.; Gitelman, Stephen E.; Goodarzi, Mark O.; Grieger, Jessica A.; Guasch-Ferré, Marta; Habibi, Nahal; Hansen, Torben; Huang, Chuiguo; Harris-Kawano, Arianna; Ismail, Heba M.; Hoag, Benjamin; Johnson, Randi K.; Jones, Angus G.; Koivula, Robert W.; Leong, Aaron; Leung, Gloria K. W.; Libman, Ingrid M.; Liu, Kai; Long, S. Alice; Lowe, William L., Jr.; Morton, Robert W.; Motala, Ayesha A.; Onengut-Gumuscu, Suna; Pankow, James S.; Pathirana, Maleesa; Pazmino, Sofia; Perez, Dianna; Petrie, John R.; Powe, Camille E.; Quinteros, Alejandra; Jain, Rashmi; Ray, Debashree; Ried-Larsen, Mathias; Saeed, Zeb; Santhakumar, Vanessa; Kanbour, Sarah; Sarkar, Sudipa; Monaco, Gabriela S. F.; Scholtens, Denise M.; Selvin, Elizabeth; Sheu, Wayne Huey-Herng; Speake, Cate; Stanislawski, Maggie A.; Steenackers, Nele; Steck, Andrea K.; Stefan, Norbert; Støy, Julie; Taylor, Rachael; Tye, Sok Cin; Ukke, Gebresilasea Gendisha; Urazbayeva, Marzhan; Van der Schueren, Bart; Vatier, Camille; Wentworth, John M.; Hannah, Wesley; White, Sara L.; Yu, Gechang; Zhang, Yingchai; Zhou, Shao J.; Beltrand, Jacques; Polak, Michel; Aukrust, Ingvild; de Franco, Elisa; Flanagan, Sarah E.; Maloney, Kristin A.; McGovern, Andrew; Molnes, Janne; Nakabuye, Mariam; Njølstad, Pål Rasmus; Pomares-Millan, Hugo; Provenzano, Michele; Saint-Martin, Cécile; Zhang, Cuilin; Zhu, Yeyi; Auh, Sungyoung; de Souza, Russell; Fawcett, Andrea J.; Gruber, Chandra; Mekonnen, Eskedar Getie; Mixter, Emily; Sherifali, Diana; Eckel, Robert H.; Nolan, John J.; Philipson, Louis H.; Brown, Rebecca J.; Billings, Liana K.; Boyle, Kristen; Costacou, Tina; Dennis, John M.; Florez, Jose C.; Gloyn, Anna L.; Gomez, Maria F.; Gottlieb, Peter A.; Greeley, Siri Atma W.; Griffin, Kurt; Hattersley, Andrew T.; Hirsch, Irl B.; Hivert, Marie-France; Hood, Korey K.; Josefson, Jami L.; Kwak, Soo Heon; Laffel, Lori M.; Lim, Siew S.; Loos, Ruth J. F.; Ma, Ronald C. W.; Mathieu, Chantal; Mathioudakis, Nestoras; Meigs, James B.; Misra, Shivani; Mohan, Viswanathan; Murphy, Rinki; Oram, Richard; Owen, Katharine R.; Ozanne, Susan E.; Pearson, Ewan R.; Perng, Wei; Pollin, Toni I.; Pop-Busui, Rodica; Pratley, Richard E.; Redman, Leanne M.; Redondo, Maria J.; Reynolds, Rebecca M.; Semple, Robert K.; Sherr, Jennifer L.; Sims, Emily K.; Sweeting, Arianne; Tuomi, Tiinamaija; Udler, Miriam S.; Vesco, Kimberly K.; Vilsbøll, Tina; Wagner, Robert; Rich, Stephen S.; Franks, Paul W.; Pediatrics, School of Medicine
    Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.
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    Strategies to Integrate Genomic Medicine into Clinical Care: Evidence from the IGNITE Network
    (MDPI, 2021-07-08) Sperber, Nina R.; Dong, Olivia M.; Roberts, Megan C.; Dexter, Paul; Elsey, Amanda R.; Ginsburg, Geoffrey S.; Horowitz, Carol R.; Johnson, Julie A.; Levy, Kenneth D.; Ong, Henry; Peterson, Josh F.; Pollin, Toni I.; Rakhra-Burris, Tejinder; Ramos, Michelle A.; Skaar, Todd C.; Orlando, Lori A.; Medicine, School of Medicine
    The complexity of genomic medicine can be streamlined by implementing some form of clinical decision support (CDS) to guide clinicians in how to use and interpret personalized data; however, it is not yet clear which strategies are best suited for this purpose. In this study, we used implementation science to identify common strategies for applying provider-based CDS interventions across six genomic medicine clinical research projects funded by an NIH consortium. Each project’s strategies were elicited via a structured survey derived from a typology of implementation strategies, the Expert Recommendations for Implementing Change (ERIC), and follow-up interviews guided by both implementation strategy reporting criteria and a planning framework, RE-AIM, to obtain more detail about implementation strategies and desired outcomes. We found that, on average, the three pharmacogenomics implementation projects used more strategies than the disease-focused projects. Overall, projects had four implementation strategies in common; however, operationalization of each differed in accordance with each study’s implementation outcomes. These four common strategies may be important for precision medicine program implementation, and pharmacogenomics may require more integration into clinical care. Understanding how and why these strategies were successfully employed could be useful for others implementing genomic or precision medicine programs in different contexts.