To meet current and expected future demand for genome sequencing in the neonatal intensive care unit (NICU), adjustments to traditional service delivery models are necessary. Effective programs for the training of non-genetics providers (NGPs) may address the known barriers to providing genetic services including limited genetics knowledge and lack of confidence. The SouthSeq project aims to use genome sequencing to make genomic diagnoses in the neonatal period and evaluate a scalable approach to delivering genome sequencing results to populations with limited access to genetics professionals. Thirty-three SouthSeq NGPs participated in a live, interactive training intervention and completed surveys before and after participation. Here, we describe the protocol for the provider training intervention utilized in the SouthSeq study and the associated impact on NGP knowledge and confidence in reviewing, interpreting, and using genome sequencing results. Participation in the live training intervention led to an increased level of confidence in critical skills needed for real-world implementation of genome sequencing. Providers reported a significant increase in confidence level in their ability to review, understand, and use genome sequencing result reports to guide patient care. Reported barriers to implementation of genome sequencing in a NICU setting included test cost, lack of insurance coverage, and turn around time. As implementation of genome sequencing in this setting progresses, effective education of NGPs is critical to provide access to high-quality and timely genomic medicine care.

Abstract INTRODUCTION Under-representation in health-related research is one of a multitude of factors that contribute to cancer disparities experienced by African American and Latinx communities. Barriers to research participation stem from historical social injustices, are multi-faceted and include factors specific to the research process, research team members and community experiences and expectations about research participation. Informed consent is a longitudinal process and represents an opportunity to address these barriers and potentially improve access to research by individuals from underrepresented groups. The purpose of the Strengthening Translational Research in Diverse Enrollment (STRIDE) study was to develop and test an integrated, literacy- and culturally-sensitive, multi-component intervention that addresses barriers to research participation during the informed consent process. METHODS A multi-pronged community engaged approach was used to inform the development the three components of the STRIDE intervention. At each of the three study sites, Community Investigators, local community members of diverse racial/ethnic backgrounds, contribute to intervention development, pilot testing and dissemination activities. Community engagement studios provided a semi-structured opportunity to solicit feedback from community experts in a facilitated group regarding the relevance, usability and understandability of the STRIDE intervention components. Additionally, component-specific approaches to obtaining community input were utilized. RESULTS The three components were developed and refined with community input. The STRIDE intervention includes: (1) an electronic consent (eConsent) framework within the REDCap software platform that incorporates tools designed to facilitate material comprehension and relevance, (2) a storytelling intervention in which prior research participants from diverse backgrounds share their experiences, and (3) a simulation-based training program for research assistants that emphasizes cultural competency and communication skills for assisting in the informed consent process. CONCLUSIONS The STRIDE project had produced an integrated set of interventions that are available to support researchers across the CTSA hubs and beyond in efforts to enhance diversity in clinical research. Early dissemination of STRIDE intervention components include utilization in national COVID-19 trials and research networks. Citation Format: Stephenie C. Lemon, Jeroan J. Allison, Maria I. Danila, Karin Valentine Goins, German Chiriboga, Melissa Fischer, Melissa Puliafico, Amy S. Mudano, Elizabeth J. Rahn, Jeanne Merchant, Colleen E. Lawrrence, Leah Dunkel, Tiffany Israel, Bruce Barton, Fred Jenoure, Tiffany Alexander, Danny Cruz, Marva Douglas, Jacqueline Sims, Al Richmond, Erik Roberson, Carol Chambless, Paul A. Harris, Kenneth G. Saag. Improving access to research among individuals from under-represented racial and ethnic minority communities: The Strengthening Research In Diverse Enrollment (STRIDE) Study [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr IA-52.

Background Previous studies have noted significant variation in serum urate (sUA) levels, and it is unknown how this influences the accuracy of hyperuricemia classification based on single data points. Despite this known variability, hyperuricemic patients are often used as a control group in gout studies. Our objective was to determine the accuracy of hyperuricemia classifications based on single data points versus multiple data points given the degree of variability observed with serial measurements of sUA. Methods Data was analyzed from a cross-over clinical trial of urate-lowering therapy in young adults without a gout diagnosis. In the control phase, sUA levels used for this analysis were collected at 2–4 week intervals. Mean coefficient of variation for sUA was determined, as were rates of conversion between normouricemia (sUA ≤6.8 mg/dL) and hyperuricemia (sUA > 6.8 mg/dL). Results Mean study participant ( n = 85) age was 27.8 ± 7.0 years, with 39% female participants and 41% African-American participants. Mean sUA coefficient of variation was 8.5% ± 4.9% (1 to 23%). There was no significant difference in variation between men and women, or between participants initially normouricemic and those who were initially hyperuricemic. Among those initially normouricemic ( n = 72), 21% converted to hyperuricemia during at least one subsequent measurement. The subgroup with initial sUA < 6.0 ( n = 54) was much less likely to have future values in the range of hyperuricemia compared to the group with screening sUA values between 6.0–6.8 ( n = 18) (7% vs 39%, p = 0.0037). Of the participants initially hyperuricemic ( n = 13), 46% were later normouricemic during at least one measurement. Conclusion Single sUA measurements were unreliable in hyperuricemia classification due to spontaneous variation. Knowing this, if a single measurement must be used in classification, it is worth noting that those with an sUA of < 6.0 mg/dL were less likely to demonstrate future hyperuricemic measurements and this could be considered a safer threshold to rule out intermittent hyperuricemia based on a single measurement point. Trial registration Data from parent study ClinicalTrials.gov Identifier: NCT02038179 .

Introduction: Barriers to research participation by racial and ethnic minority group members are multi-factorial, stem from historical social injustices and occur at participant, research team, and research process levels. The informed consent procedure is a key component of the research process and represents an opportunity to address these barriers. This manuscript describes the development of the Strengthening Translational Research in Diverse Enrollment (STRIDE) intervention, which aims to improve research participation by individuals from underrepresented groups. Methods: We used a community-engaged approach to develop an integrated, culturally, and literacy-sensitive, multi-component intervention that addresses barriers to research participation during the informed consent process. This approach involved having Community Investigators participate in intervention development activities and using community engagement studios and other methods to get feedback from community members on intervention components. Results: The STRIDE intervention has three components: a simulation-based training program directed toward clinical study research assistants that emphasizes cultural competency and communication skills for assisting in the informed consent process, an electronic consent (eConsent) framework designed to improve health-related research material comprehension and relevance, and a “storytelling” intervention in which prior research participants from diverse backgrounds share their experiences delivered via video vignettes during the consent process. Conclusions: The community engaged development approach resulted in a multi-component intervention that addresses known barriers to research participation and can be integrated into the consent process of research studies. Results of an ongoing study will determine its effectiveness at increasing diversity among research participants.

ObjectiveTo determine whether serum urate reduction with allopurinol lowers blood pressure (BP) in young adults and the mechanisms mediating this hypothesized effect.MethodsWe conducted a single‐center, randomized, double‐blind, crossover clinical trial. Adults ages 18–40 years with baseline systolic BP ≥120 and <160 mm Hg or diastolic BP ≥80 and <100 mm Hg, and serum urate ≥5.0 mg/dl for men or ≥4.0 mg/dl for women were enrolled. Main exclusion criteria included chronic kidney disease, gout, or past use of urate‐lowering therapies. Participants received oral allopurinol (300 mg daily) or placebo for 1 month followed by a 2–4 week washout and then were crossed over. Study outcome measures were change in systolic BP from baseline, endothelial function estimated as flow‐mediated dilation (FMD), and high‐sensitivity C‐reactive protein (hsCRP) levels. Adverse events were assessed.ResultsNinety‐nine participants were randomized, and 82 completed all visits. The mean ± SD age was 28.0 ± 7.0 years, 62.6% were men, and 40.4% were African American. In the primary intent‐to‐treat analysis, systolic BP did not change during the allopurinol treatment phase (mean ± SEM −1.39 ± 1.16 mm Hg) or placebo treatment phase (−1.06 ± 1.08 mm Hg). FMD increased during allopurinol treatment periods compared to placebo treatment periods (mean ± SEM 2.5 ± 0.55% versus −0.1 ± 0.42%; P < 0.001). There were no changes in hsCRP level and no serious adverse events.ConclusionOur findings indicate that urate‐lowering therapy with allopurinol does not lower systolic BP or hsCRP level in young adults when compared with placebo, despite improvements in FMD. These findings do not support urate lowering as a treatment for hypertension in young adults.

OBJECTIVE:To determine the relationship between gout flare rate and self-categorization into remission, low disease activity (LDA), and patient acceptable symptom state (PASS). METHODS:Patients with gout self-categorized as remission, LDA, and PASS, and reported number of flares over the preceding 6 and 12 months. Multinomial logistic regression was used to determine the association between being in each disease state (LDA and PASS were combined) and flare count, and self-reported current flare. A distribution-based approach and extended Youden index identified possible flare count thresholds for each state. RESULTS:Investigators from 17 countries recruited 512 participants. Remission was associated with a median recalled flare count of zero over both 6 and 12 months. Each recalled flare reduced the likelihood of self-perceived remission compared with being in higher disease activity than LDA/PASS, by 52% for 6 months and 23% for 12 months, and the likelihood of self-perceived LDA/PASS by 15% and 5% for 6 and 12 months, respectively. A threshold of 0 flares in preceding 6 and 12 months was associated with correct classification of self-perceived remission in 58% and 56% of cases, respectively. CONCLUSION:Flares are significantly associated with perceptions of disease activity in gout, and no flares over the prior 6 or 12 months is necessary for most people to self-categorize as being in remission. However, recalled flare counts alone do not correctly classify all patients into self-categorized disease activity states, suggesting that other factors may also contribute to self-perceived gout disease activity.

Introduction Uric acid is the final byproduct of purine metabolism. The loss of the enzyme that hydrolyzes uric acid to allantoin was lost, leading to a decrease in uric acid excretion and its further accumulation. The buildup of uric acid leads to damage in different organ systems, including the cardiovascular system. With the increasing burden of cardiovascular disease worldwide, a growing body of evidence has addressed the relationship between urate, cardiovascular outcomes, and gout medication cardiovascular safety. Areas covered: We discuss the most common gout therapies used for the reduction of serum urate and management of gout flares in different observational and clinical trials and their effects on different aspects of cardiovascular disease. We selected the most representative clinical studies that evaluated cardiovascular outcomes with each gout therapy as well as recommendation given by the most representative guidelines from Rheumatology societies for the management of gout.Expert opinion The treatment of gout reduces joint damage and it can also lessen CV morbidity. Allopurinol shows CV safety profile when compared to other ULTs. Evidence supporting CV safety with the use of colchicine and IL-1 agents is promising and research needs to be conducted to further assess this outcome.

ObjectiveThis ancillary study examined the impact of depressive symptoms on the effectiveness of a urate‐lowering therapy in the context of a clinical trial.MethodsParticipants included 67 adults (ages 18–40) with elevated blood pressure who were enrolled in a double‐blind, randomized, crossover clinical trial evaluating the effectiveness of allopurinol (300 mg/d) versus placebo to decrease blood pressure. Depressive symptoms were measured at the beginning of each 4‐week phase with the Center for Epidemiological Studies Depression scale (CESD‐10). Serum urate (sUA) was assessed at the beginning and end of each treatment phase. Compliance to treatment was measured by having detectable oxypurinol levels. Linear regressions tested associations between depressive symptoms and change in sUA in each phase, adjusting for sex and race. Logistic regression predicted compliance from depressive symptoms.ResultsParticipants had a mean age of 27 years and were 64% male and 39% African American. sUA levels decreased during the allopurinol treatment period but did not change during the placebo period. Higher depressive symptoms at pretreatment were associated with an attenuated urate‐lowering response during the allopurinol phase (β = 0.24, p < 0.05), but had no effect on sUA changes during the placebo phase. Depressive symptoms were not associated with treatment compliance assessed by oxypurinol levels.ConclusionDepressive symptoms were associated with reduced efficacy of allopurinol treatment for hyperuricemia in a clinical trial targeting hypertension. Studies evaluating the efficacy of urate‐lowering therapies may benefit from screening for depressive symptoms.

Background: Osteoporosis medication use is suboptimal. Simple interventions personalized to a patients' stage of readiness are needed to encourage osteoporosis medication use. Objectives: To estimate interrelationships of sociodemographic factors, perceived fracture risk, health literacy, receipt of medication information, medication trust and readiness to use osteoporosis medication; and apply observed relationships to inform design specifications for a clinical decision support application that can be used for personalized patient counseling. Methods: Data from a national sample of older women (n = 1759) with self-reported history of fractures and no current use of osteoporosis medication treatment were used to estimate an acceptable path model that describes associations among key sociodemographic characteristics, health literacy, perceived fracture risk, receipt of osteoporosis medication information within the past year, trust in osteoporosis medications, and readiness to use osteoporosis medication. Path model results were used to inform an application for personalized patient counseling that can be easily integrated into clinical decision support systems. Results: Increased age (beta = 0.13), trust for medications (beta = 0.12), higher perceived fracture risk (beta = 0.21), and having received medication information within the past year (beta = 0.21) were all positively associated with readiness to use osteoporosis medication (p < 0.0001). Whereas, health literacy (beta = 0.09) was inversely associated with readiness to use osteoporosis medication (p < 0.0001). Using these results, a brief 6-item question set was constructed for simple integration into clinical decision support applications. Patient responses were used to inform a provider dashboard that integrates a patient's stage of readiness for osteoporosis medication use, predictors of readiness, and personalized counseling points appropriate to their stage of readiness. Conclusion: Content of counseling strategies must be aligned with a patient's stage of readiness to use treatment. Path modeling can be effectively used to identify factors for inclusion in an evidenced-based clinical decision support application designed to assist providers with personalized patient counseling and osteoporosis medication use decisions.

INTRODUCTION:The updated common rule, for human subjects research, requires that consents "begin with a 'concise and focused' presentation of the key information that will most likely help someone make a decision about whether to participate in a study" (Menikoff, Kaneshiro, Pritchard. The New England Journal of Medicine. 2017; 376(7): 613-615.). We utilized a community-engaged technology development approach to inform feature options within the REDCap software platform centered around collection and storage of electronic consent (eConsent) to address issues of transparency, clinical trial efficiency, and regulatory compliance for informed consent (Harris, et al. Journal of Biomedical Informatics 2009; 42(2): 377-381.). eConsent may also improve recruitment and retention in clinical research studies by addressing: (1) barriers for accessing rural populations by facilitating remote consent and (2) cultural and literacy barriers by including optional explanatory material (e.g., defining terms by hovering over them with the cursor) or the choice of displaying different videos/images based on participant's race, ethnicity, or educational level (Phillippi, et al. Journal of Obstetric, Gynecologic, & Neonatal Nursing. 2018; 47(4): 529-534.). METHODS:We developed and pilot tested our eConsent framework to provide a personalized consent experience whereby users are guided through a consent document that utilizes avatars, contextual glossary information supplements, and videos, to facilitate communication of information. RESULTS:The eConsent framework includes a portfolio of eight features, reviewed by community stakeholders, and tested at two academic medical centers. CONCLUSIONS:Early adoption and utilization of this eConsent framework have demonstrated acceptability. Next steps will emphasize testing efficacy of features to improve participant engagement with the consent process.

Background Understanding factors associated with the readiness for adopting osteoporosis treatment change may inform the design of behavioural interventions to improve osteoporosis treatment uptake in women at high risk for fracture. Objectives To examine the factors associated with the readiness for adopting osteoporosis treament change among US women with prior fractures. Methods US women in the Global Longitudinal Study of Osteoporosis (GLOW) with prior self-reported fractures who were not currently using osteoporosis therapy were eligible to participate in the Activating Patients at Risk for OsteoPOroSis (APROPOS) Study. Participants’ readiness for behaviour change was assessed using a modified form of the Weinstein Precaution Adoption Process Model (PAPM). We defined pre-contemplative participants as those who self-classified in the unaware and unengaged stages of PAPM. Contemplative participants were defined by the undecided, decided not to act, and decided to act stages of PAPM. Bivariate tests and stepwise multivariable logistic regression evaluated the following factors associated with these two levels of readiness for behaviour change: sociodemographic characteristics, health literacy, self-reported history of depression and dementia, previous treatment for osteoporosis, whether participants had been told they had osteoporosis/osteopenia, and whether they had concerns about osteoporosis. Results A total of 2684 women were enrolled in APROPOS. Participants were 95% Caucasian, with a mean (SD) age 74.9 (8.0) years and 77% had some college education. Overall, 25% (n=544) self-classified in the contemplative stage of behaviour change. Compared to women who self-classified as pre-contemplative, contemplative women were more likely to be concerned about osteoporosis (adjusted OR [aOR]=3.2, 95% CI 2.3–4.4) and to report prior osteoporosis treatment (aOR 4.3, 95% CI 3.1–6.0). Participants who were told they had osteoporosis had a 12.4 fold odds to be in the contemplative group (95% CI 8.5–18.1), while those who were told they had osteopenia had 4.1 fold odds to be in the contemplative group (95% CI 2.9–5.9). Conclusions Among women with high risk of future fracture, having been told by a health care provider that they had osteoporosis/osteopenia was independently associated with considering taking medications for osteoporosis. Our results suggest that in considering osteoporosis intervention design efficiency and effectiveness, women’s recognition of a diagnosis of osteoporosis/osteopenia are critical components to be considered when attempting to influence stage of behaviour transitions. Disclosure of Interest M. I. Danila: None declared, E. Rahn: None declared, A. Mudano: None declared, R. Outman: None declared, P. Li: None declared, D. Redden: None declared, F. Anderson Grant/research support from: Portola, Consultant for: Millennium Pharmaceuticals, S. Greenspan Grant/research support from: Amgen, Lilly, Consultant for: Merck, A. LaCroix Consultant for: Amgen, Pfizer, Sermonix, J. Nieves: None declared, S. Silverman Grant/research support from: Amgen, Lilly, Consultant for: Amgen, Speakers bureau: Amgen, Lilly, E. Siris Consultant for: Amgen, Radius, N. Watts Shareholder of: OsteoDynamics, Grant/research support from: Shire, Consultant for: AbbVie, Amgen, Janssen, Merck, Radius, Sanofi, Paid instructor for: Amgen, Shire, S. Ladores: None declared, K. Meneses: None declared, J. Curtis Grant/research support from: Amgen, Consultant for: Amgen, K. Saag Grant/research support from: Amgen, Lilly, Merck, Consultant for: Amgen, Lilly, Merck

Objective. To investigate the factors associated with discordance between patient and physician on the presence of a gout flare.Methods. Patients' self-reports of current gout flares were assessed with the question, 'Are you having a gout flare today?' which was then compared with a concurrent, blinded, physician's assessment. Based on agreement or disagreement with physicians on the presence of a gout flare, flares were divided into concordant and discordant groups, respectively. Within the discordant group, two subgroups-patient-reported flare but the physician disagreed and physician-reported flare but the patient disagreed-were identified. The factors associated with discordance were analysed with multivariable logistic regression analysis.Results. Of 268 gout flares, 81 (30.2%) flares were discordant, with either patient or physician disagreeing on the presence of a flare. Of the discordant flares, in 57 (70.4%) the patient reported a flare but the physician disagreed. In multivariable logistic regression analysis adjusted for demographics, disagreement among patients and physicians on the presence of a gout flare was associated with lower pain scores at rest [odds ratio (OR) for each point increase on 0-10 point pain scale 0.81 (95% Wald CI 0.73, 0.90), P < 0.0001] and less presence of joint swelling [OR 0.24 (95% CI 0.10, 0.61), P = 0.003] or joint warmth [OR 0.39 (95% CI 0.20, 0.75), P = 0.005].Conclusion. Although patients and physicians generally agree about the presence of gout flare, discordance may occur in the setting of low pain scores and in the absence of swollen or warm joints.

We investigated the factors associated with readiness for initiating osteoporosis treatment in women at high risk of fracture. We found that women in the contemplative stage were more likely to report previously being told having osteoporosis or osteopenia, acknowledge concern about osteoporosis, and disclose prior osteoporosis treatment. Understanding factors associated with reaching the contemplative stage of readiness to initiate osteoporosis treatment may inform the design of behavioral interventions to improve osteoporosis treatment uptake in women at high risk for fracture. We measured readiness to initiate osteoporosis treatment using a modified form of the Weinstein Precaution Adoption Process Model (PAPM) among 2684 women at high risk of fracture from the Activating Patients at Risk for OsteoPOroSis (APROPOS) clinical trial. Pre-contemplative participants were those who self-classified in the unaware and unengaged stages of PAPM (stages 1 and 2). Contemplative participants were those in the undecided, decided not to act, or decided to act stages of PAPM (stages 3, 4, and 5). Using multivariable logistic regression, we evaluated participant characteristics associated with levels of readiness to initiate osteoporosis treatment. Overall, 24% (N = 412) self-classified in the contemplative stage of readiness to initiate osteoporosis treatment. After adjusting for age, race, education, health literacy, and major osteoporotic fracture in the past 12 months, contemplative women were more likely to report previously being told they had osteoporosis or osteopenia (adjusted odds ratio [aOR] (95% CI) 11.8 (7.8–17.9) and 3.8 (2.5–5.6), respectively), acknowledge concern about osteoporosis (aOR 3.5 (2.5–4.9)), and disclose prior osteoporosis treatment (aOR 4.5 (3.3–6.3)) than women who self-classified as pre-contemplative. For women at high risk for future fractures, ensuring women’s recognition of their diagnosis of osteoporosis/osteopenia and addressing their concerns about osteoporosis are critical components to consider when attempting to influence stage of behavior transitions in osteoporosis treatment.

INTRODUCTION:Implementation of genome-scale sequencing in clinical care has significant challenges: the technology is highly dimensional with many kinds of potential results, results interpretation and delivery require expertise and coordination across multiple medical specialties, clinical utility may be uncertain, and there may be broader familial or societal implications beyond the individual participant. Transdisciplinary consortia and collaborative team science are well poised to address these challenges. However, understanding the complex web of organizational, institutional, physical, environmental, technologic, and other political and societal factors that influence the effectiveness of consortia is understudied. We describe our experience working in the Clinical Sequencing Evidence-Generating Research (CSER) consortium, a multi-institutional translational genomics consortium.METHODS:A key aspect of the CSER consortium was the juxtaposition of site-specific measures with the need to identify consensus measures related to clinical utility and to create a core set of harmonized measures. During this harmonization process, we sought to minimize participant burden, accommodate project-specific choices, and use validated measures that allow data sharing.RESULTS:Identifying platforms to ensure swift communication between teams and management of materials and data were essential to our harmonization efforts. Funding agencies can help consortia by clarifying key study design elements across projects during the proposal preparation phase and by providing a framework for data sharing data across participating projects.CONCLUSIONS:In summary, time and resources must be devoted to developing and implementing collaborative practices as preparatory work at the beginning of project timelines to improve the effectiveness of research consortia.

Glucocorticoid-induced osteoporosis (GIOP) is the most common form of secondary osteoporosis. To date, six large randomized controlled clinical trials on the efficacy of pharmaceutical treatment in GIOP have been conducted. All of these studies have focused predominately on bone mineral density outcomes, and none of them have been statistically powered to address fracture endpoints. The purpose of this review is to highlight differences in the design and results within these large randomized GIOP clinical trials, and how these differences might affect clinical decisions. Differences between studies in trial design, populations studied, and variable efficacy impact the comparability and generalizability of these findings, and ultimately should affect practitioners’ behavior. We review the clinical trials that provide the best quality evidence on comparative efficacy and safety of GIOP treatments. We also propose suggestions on the design of future GIOP clinical trials with attention to improved generalizability, and, ideally, study designs that might achieve fracture outcomes.

Background: Self-reported fracture history data is frequently used in epidemiological studies of osteoporosis. Self-reported fracture data may differ from fracture history coded in electronic health records (EHR) due to imperfect patient recall, incomplete communication with clinicians, or lack of a universal EHR. Because both self-reported fracture history and EHR data can define phenotypes for clinical research studies, it is important to understand how these 2 data sources compare. Objectives: To compare self-reported fracture history using survey data with fracture codes from an available EHR dataset. Methods: Self-reported fracture data was derived from the Activating Patients at Risk for OsteoPOroSis (APROPOS) trial, which recruited participants from the Global Longitudinal study of Osteoporosis in Women (GLOW) cohort. Prior fracture data was collected using a survey deployed June - August 2015. Women were asked if they ever had a fracture and for each fracture type the date of the most recent one. Data on fractures recorded in the EHR September 2011 - June 2015 was obtained from Kaiser Permanente Washington Health Research Institute. We excluded skull, toes and fingers fractures. We defined concordance between the EHR and self-reported data if the location of a fracture was reported to be the same and if the reported dates were within 1 year of each other. Kappa (κ) statistic described the concordance between the 2 sources of fracture history. Descriptive statistics evaluated potential factors associated with discordance between the self-reported and EHR-coded fracture history. Results: A total of 133 fractures from 360 women (91% white, mean[SD)] age 74.5(7.5) years, 82% had some college education) were included. There were 35 fractures reported on the survey but not in the EHR and 39 fractures coded in the EHR but not in the survey. Agreement between self-reported and EHR fractures was κ 0.48. Of the discordant fractures, we were more likely to find claims for fractures in EHR referent to self-report among whites (OR=5.5, 95%CI 1.1-27.9), for major osteoporotic fractures (OR=2.8, 95%CI 1.1-7.1), and for fragility fractures that typically require hospitalization (vertebral, hip, femur, pelvis) (OR=3.8, 95%CI 1.3-10.7). Discordance between EHR codes and self-reported fractures did not vary by age, formal education, or health literacy. Conclusion: There was only modest correlation between self-reported fracture history and EHR fracture codes. This discrepancy may have implications for clinical and epidemiological studies of fractures suggesting that combining both types of data may be optimal. Disclosure of Interests:: Maria Danila Grant/research support from: Pfizer, Inc., Consultant for: Sanofi Genzyme & Regeneron, Amy Mudano: None declared, Elizabeth Rahn: None declared, Andrea LaCroix: None declared, Jeffrey Curtis: None declared, Kenneth Saag Grant/research support from: Amgen, Ironwood/AstraZeneca, Horizon, SOBI, Takeda, Consultant for: Abbvie, Amgen, Ironwood/AstraZeneca, Bayer, Gilead, Horizon, Kowa, Radius, Roche/Genentech, SOBI, Takeda, Teijin

Background Gout is frequently misdiagnosed and/or miscoded, making approaches to identifying eligible patients for observational and interventional studies more challenging. Ethnic and racial minorities are under-represented in many gout studies. Methods to better identify minorities and confirm gout diagnosis are essential to ensure studies have both validity and generalizability. Objectives To define efficient methods for identifying African Americans (AA) interested in participating in a gout registry and who satisfy the American College of Rheumatology (ACR) and European League Against Rheumatism (EULAR) gout classification criteria. Methods We identified all AA patients seen at University of Alabama at Birmingham 01/09/2017 and 31/08/2018 with an ICD 9/10 code for gout. Patients not “opted out” by their primary care provider (PCP) were invited to participate. Those interested underwent detailed medical record review followed by phone contact to determine eligibility. Those with a high likelihood of meeting diagnostic criteria for gout were invited for an in person visit to confirm diagnosis (Abstract AB0861 Figure 1). We compared descriptive characteristic of participants enrolled in the registry and the larger potential gout populations Results From 3,032 AA patients with an ICD 9/10 gout diagnosis we generated a random sample of 400 patients. 5 patients were excluded by their PCPs, thus 395 patients were preliminarily eligible and invited via e-mail (N=176) and/or letter (N=375). 1 patient (< 1%) communicated lack of interest, 19 (4.8%) were unreachable, 322 (81.5%) did not respond to the invitation, and 53 (13.4%) expressed preliminary interest and underwent medical record review. We successfully scheduled 30 subjects for a registry visit, 24 completed the visit, and 23 (6% of initial sample) satisfied 2015 ACR/EULAR gout classification criteria (see Table 1). We found no significant difference in age, sex, and the number of medical encounters in the last year between enrolled patients and the remaining population. Conclusion We present a strategy for identifying and recruiting AA patients with ACR/EULAR classified gout into a population-based registry. Among a randomly selected cohort of AAs with an initial ICD 9/10 diagnosis code of presumed gout, slightly under 15% expressed interest and 6% satisfied the 2015 ACR/EULAR criteria and successfully enrolled in the registry. Our experience emphasizes a potential approach as well as some challenges in creating a generalizable gout registry. Disclosure of Interests Giovanni Adami: None declared, Josh Melnick: None declared, Jeff Foster: None declared, Elizabeth Rahn: None declared, Amy Mudano: None declared, Jeffrey Curtis: None declared, Tony Merriman Grant/research support from: Ardeabiosciences, Ironwood Pharmaceuticals, Consultant for: Ardeabiosciences, Ironwood Pharmaceuticals, Lou Bridges: None declared, Kenneth Saag Grant/research support from: Amgen, Ironwood/AstraZeneca, Horizon, SOBI, Takeda, Consultant for: Abbvie, Amgen, Ironwood/AstraZeneca, Bayer, Gilead, Horizon, Kowa, Radius, Roche/Genentech, SOBI, Takeda, Teijin