Clinical Trial Data Collection Research Articles

Design of a randomised controlled hybrid trial of nintedanib in patients with progressive myositis-associated interstitial lung disease.

The Myositis Interstitial Lung Disease Nintedanib Trial (MINT) is a hybrid trial, which is enrolling patients both at local sites and remotely via a decentralised site. The trial will investigate the efficacy and safety of nintedanib in patients with progressive myositis-associated interstitial lung disease (MA-ILD). MINT is an exploratory, prospective randomised placebo-controlled trial. Eligible patients will have myositis and evidence of fibrosing ILD on high-resolution computed tomography (HRCT), be taking standard of care medications for myositis, and meet criteria for ILD progression within the prior 24months based on decline in FVC, worsened fibrosis on HRCT, and/or worsened dyspnoea. Patients will be randomised 1:1 to receive nintedanib 150mg twice daily or placebo for 12weeks then open-label nintedanib for 12weeks. Patients will be enrolled at local sites and a decentralised site. Most study visits will be completed remotely using telemedicine or digital health technologies. The primary endpoint is the change in Living with Pulmonary Fibrosis (L-PF) questionnaire dyspnoea domain score at week 12. Other endpoints include changes in other L-PF questionnaire domains, lung function, imaging, and physical activity, and assessment of adverse events. Data collected using remote versus clinic enrolment, and using home versus clinic spirometry, will be compared. MINT is an innovative, hybrid trial that will evaluate the effects of nintedanib on symptoms, quality of life, and ILD progression in patients with progressive MA-ILD and provide valuable information on the utility of decentralised recruitment and remote data collection in clinical trials. Clinicaltrials.gov NCT05799755 (date of registration: 05/04/2023).

Comparing the Accuracy of Traditional vs. FHIR®-Based Extraction of Electronic Health Record Data for Two Clinical Trials.

While pilots and production use of software based on the Health Level Seven (HL7®) Fast Healthcare Interoperability Resources (FHIR®) standard are increasing in clinical research, we lack consistent evaluative data on important outcomes, such as data accuracy. We compared the accuracy of EHR collected, FHIR® extracted data (called EHR-to-eCRF data collection) to traditional clinical trial data collection. The accuracy rate for EHR-collected data was significantly higher than for the same data collected through traditional methods. It is possible that EHR-collected (FHIR® extracted) data can substantially improve data quality in clinical studies while decreasing the burden on study sites.

Implementation and impact of an electronic patient reported outcomes system in a phase II multi-site adaptive platform clinical trial for early-stage breast cancer.

We describe the development and implementation of a system for monitoring patient-reported adverse events and quality of life using electronic Patient Reported Outcome (ePRO) instruments in the I-SPY2 Trial, a phase II clinical trial for locally advanced breast cancer. We describe the administration of technological, workflow, and behavior change interventions and their associated impact on questionnaire completion. Using the OpenClinica electronic data capture system, we developed rules-based logic to build automated ePRO surveys, customized to the I-SPY2 treatment schedule. We piloted ePROs at the University of California, San Francisco (UCSF) to optimize workflow in the context of trial treatment scenarios and staggered rollout of the ePRO system to 26 sites to ensure effective implementation of the technology. Increasing ePRO completion requires workflow solutions and research staff engagement. Over two years, we increased baseline survey completion from 25% to 80%. The majority of patients completed between 30% and 75% of the questionnaires they received, with no statistically significant variation in survey completion by age, race or ethnicity. Patients who completed the screening timepoint questionnaire were significantly more likely to complete more of the surveys they received at later timepoints (mean completion of 74.1% vs 35.5%, P < .0001). Baseline PROMIS social functioning and grade 2 or more PRO-CTCAE interference of Abdominal Pain, Decreased Appetite, Dizziness and Shortness of Breath was associated with lower survey completion rates. By implementing ePROs, we have the potential to increase efficiency and accuracy of patient-reported clinical trial data collection, while improving quality of care, patient safety, and health outcomes. Our method is accessible across demographics and facilitates an ease of data collection and sharing across nationwide sites. We identify predictors of decreased completion that can optimize resource allocation by better targeting efforts such as in-person outreach, staff engagement, a robust technical workflow, and increased monitoring to improve overall completion rates. https://clinicaltrials.gov/study/NCT01042379.

Data Flow Construction and Quality Evaluation of Electronic Source Data in Clinical Trials: Pilot Study Based on Hospital Electronic Medical Records in China.

The traditional clinical trial data collection process requires a clinical research coordinator who is authorized by the investigators to read from the hospital's electronic medical record. Using electronic source data opens a new path to extract patients' data from electronic health records (EHRs) and transfer them directly to an electronic data capture (EDC) system; this method is often referred to as eSource. eSource technology in a clinical trial data flow can improve data quality without compromising timeliness. At the same time, improved data collection efficiency reduces clinical trial costs. This study aims to explore how to extract clinical trial-related data from hospital EHR systems, transform the data into a format required by the EDC system, and transfer it into sponsors' environments, and to evaluate the transferred data sets to validate the availability, completeness, and accuracy of building an eSource dataflow. A prospective clinical trial study registered on the Drug Clinical Trial Registration and Information Disclosure Platform was selected, and the following data modules were extracted from the structured data of 4 case report forms: demographics, vital signs, local laboratory data, and concomitant medications. The extracted data was mapped and transformed, deidentified, and transferred to the sponsor's environment. Data validation was performed based on availability, completeness, and accuracy. In a secure and controlled data environment, clinical trial data was successfully transferred from a hospital EHR to the sponsor's environment with 100% transcriptional accuracy, but the availability and completeness of the data could be improved. Data availability was low due to some required fields in the EDC system not being available directly in the EHR. Some data is also still in an unstructured or paper-based format. The top-level design of the eSource technology and the construction of hospital electronic data standards should help lay a foundation for a full electronic data flow from EHRs to EDC systems in the future.

American College of Rheumatology and Food and Drug Administration Summit: Summary of the Meeting, May 17-18, 2022.

The American College of Rheumatology and the US Food and Drug Administration co-sponsored a public meeting in May 2022 about challenges in the clinical development of drugs for rheumatoid arthritis (RA) and psoriatic arthritis (PsA), focusing on innovative clinical trial designs, outcome measures, and data collection methods. Recommendations include early dose-ranging studies and use of active comparators. Challenges and opportunities in assessing long-term safety by leveraging real-world data from electronic health records (EHRs) and claims data are discussed, along with insights from European registries and the evolving role of real-world evidence and artificial intelligence in regulatory evaluations. Endpoints for assessing disease activity and outcome measures used in RA and PsA trials are explored, emphasizing challenges in defining remission, assessing clinical response, and evaluating structural progression. The need for outcome measures that better reflect treatment targets and the potential of advanced imaging in future trials are highlighted. Challenges with placebo-controlled trials in RA are discussed and use of non-inferiority clinical trial design, in which new drugs are evaluated with active comparators, is proposed. Pragmatic trials in RA and PsA, employing decentralized approaches, are highlighted for their real-world relevance and administrative efficiencies. Strategies for identifying at-risk populations for RA and the challenges of using EHRs and insurance claims data in drug development are discussed. Registry data and digital health technologies show promise in bridging the gap between clinical trials and real-world effectiveness.

Abstract PO3-10-10: Are we adequately integrating patient reported outcomes in breast cancer clinical trials?

Abstract Background: Integrating patient reported outcomes (PROs) in cancer care enhances clinical outcomes and creates a paradigm shift in providing patient-centered care. Several studies performed in the past 15 years have demonstrated that systematic monitoring of patients using PROs through surveys improve patient-clinician communication, clinician awareness of symptoms, symptom management, patient satisfaction, quality of life, and overall survival. There has been uncertainty over the type of PRO system to implement in cancer care, how to evaluate PRO in clinical trials, and how to compare this to the clinician common terminology criteria for adverse events (CTCAE). The PRO concept was first introduced in 1975 with the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life (QoL) survey. In May 2018, the National Cancer Institute established the PRO-CTCAE to be utilized for cancer patients to report and grade their treatment related adverse events, like that of clinician reported CTCAE. The goal of our study was to evaluate frequency of PRO incorporation in phase III breast cancer clinical trials. Methods: New England Journal of Medicine, Journal of Clinical Oncology, and Lancet were systematically searched to identify phase III breast cancer clinical trials published between January 2018 and June 2023. A total of 113 phase III studies were identified, 87 of which had reported protocols. Studies that did not demonstrate protocols on these search engines were not included in the review. Of these 87 clinical trials, 36 studies documented evaluation of PRO. These studies were segregated by year of publication. For each year, the number of total phase III breast cancer clinical trials that were published were compared to those that were published and evaluated PRO. A percentage was generated and allowed for a longitudinal trend to be analyzed over a 5-year period to assess if there was improved frequency of PRO integration into breast cancer clinical trials. Summary statistics were calculated using SAS 9.4. Results: 36 of 113 trials demonstrated PRO use and 26 utilized EORTC-QoL, 1 used PRO-CTCAE, and 9 used another measure of PRO assessment within their study protocol (such as FACT-B and PHQ-9. Additionally, in 2018, 33% of published breast cancer studies included PRO data. Since then, there have been fluctuations in breast cancer studies collecting PRO; 2019: 33%, 2020: 47%, 2021: 43%, 2022: 73%, and since the start of 2023: 9%. Conclusions: Our data suggests a trend towards improvement in frequency of PRO data collection in breast cancer clinical trials over the past 5 years, exemplified by the marked increase in 2022. There remains a need to incorporate PROs in clinical trials and routine care to improve patient experience and provide patient-centered care. Citation Format: Yadav Rina, Zhengyan Huang, Jessica Moss, Garima Gupta. Are we adequately integrating patient reported outcomes in breast cancer clinical trials? [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-10-10.

Mechanical properties of human hepatic tissues to develop liver-mimicking phantoms for medical applications.

Using liver phantoms for mimicking human tissue in clinical training, disease diagnosis, and treatment planning is a common practice. The fabrication material of the liver phantom should exhibit mechanical properties similar to those of the real liver organ in the human body. This tissue-equivalent material is essential for qualitative and quantitative investigation of the liver mechanisms in producing nutrients, excretion of waste metabolites, and tissue deformity at mechanical stimulus. This paper reviews the mechanical properties of human hepatic tissues to develop liver-mimicking phantoms. These properties include viscosity, elasticity, acoustic impedance, sound speed, and attenuation. The advantages and disadvantages of the most common fabrication materials for developing liver tissue-mimicking phantoms are also highlighted. Such phantoms will give a better insight into the real tissue damage during the disease progression and preservation for transplantation. The liver tissue-mimicking phantom will raise the quality assurance of patient diagnostic and treatment precision and offer a definitive clinical trial data collection.

Correlation Between Remote Symptom Reporting by Caregivers and Adverse Clinical Outcomes: Mixed Methods Study.

Timely collection of patient-reported outcomes (PROs) decreases emergency department visits and hospitalizations and increases survival. However, little is known about the outcome predictivity of unpaid informal caregivers' reporting using similar clinical outcome assessments. The aim of this study is to assess whether caregivers and adults with cancer adhered to a planned schedule for electronically collecting patient-reported outcomes (PROs) and if PROs were associated with future clinical events. We developed 2 iPhone apps to collect PROs, one for patients with cancer and another for caregivers. We enrolled 52 patient-caregiver dyads from Kaiser Permanente Northern California in a nonrandomized study. Participants used the apps independently for 4 weeks. Specific clinical events were obtained from the patients' electronic health records up to 6 months following the study. We used logistic and quasi-Poisson regression analyses to test associations between PROs and clinical events. Participants completed 97% (251/260) of the planned Patient-Reported Outcomes Common Terminology Criteria for Adverse Events (PRO-CTCAE) surveys and 98% (254/260) of the Patient-Reported Outcomes Measurement Information System (PROMIS) surveys. PRO-CTCAE surveys completed by caregivers were associated with patients' hospitalizations or emergency department visits, grade 3-4 treatment-related adverse events, dose reductions (P<.05), and hospice referrals (P=.03). PROMIS surveys completed by caregivers were associated with hospice referrals (P=.02). PRO-CTCAE surveys completed by patients were not associated with any clinical events, but their baseline PROMIS surveys were associated with mortality (P=.03), while their antecedent or final PROMIS surveys were associated with all clinical events examined except for total days of treatment breaks. In this study, caregivers and patients completed PROs using smartphone apps as requested. The association of caregiver PRO-CTCAE surveys with patient clinical events suggests that this is a feasible approach to reducing patient burden in clinical trial data collection and may help provide early information about increasing symptom severity.

Chinese Clinical Trial Registry 13-year data collection and analysis: geographic distribution, financial support, research phase, duration, and disease categories.

To evaluate the current status of trial registration on the Chinese Clinical Trial Registry (ChiCTR). In this descriptive study, a multi-dimensional grouping analysis was conducted to estimate trends in the annual trial registration, geographical distribution, sources of funding, targeted diseases, and trial subtypes. We have analyzed all clinical trial records (over 30,000) registered on the Chinese Clinical Trial Registry (ChiCTR) from 2007 to 2020 executed in China. The main outcome was the baseline characteristics of registered trials. These trials were categorized and analyzed based on geographical distribution, year of implementation, disease type, resource and funding type, trial duration, trial phase, and the type of experimental approach. From 2008 to 2017, a consistent upward trend in clinical trial registrations was observed, showing an average annual growth rate of 29.2%. The most significant year-on-year (yoy%) growth in registrations occurred in 2014 (62%) and 2018 (68.5%). Public funding represented the predominant source of funding in the Chinese healthcare system. The top five ChiCTR registration sites for all disease types were highly populated urban regions of China, including Shanghai (5,658 trials, 18%), Beijing (5,127 trials, 16%), Guangdong (3,612 trials, 11%), Sichuan (2,448 trials, 8%), and Jiangsu (2,196 trials, 7%). Trials targeting neoplastic diseases accounted for the largest portion of registrations, followed by cardio/cerebrovascular disease (CCVD) and orthopedic diseases-related trials. The largest proportions of registration trial duration were 1-2 years, less than 1 year, and 2-3 years (at 27.36, 26.71, and 22.46%). In the case of the research phase, the top three types of all the registered trials are exploratory research, post-marketing drugs, and clinical trials of new therapeutic technology. Oncological and cardiovascular diseases receive the highest share of national public funding for medical clinical trial-based research in China. Publicly funded trials represent a major segment of the ChiCTR registry, indicating the dominating role of public governance in this health research sector. Furthermore, the growing number of analyzed records reflect the escalation of clinical research activities in China. The tendency to distribute funding resources toward exceedingly populated areas with the highest incidence of oncological and cardiovascular diseases reveals an aim to reduce the dominating disease burden in the urban conglomerates in China.

Enhancing Small Tabular Clinical Trial Dataset through Hybrid Data Augmentation: Combining SMOTE and WCGAN-GP

This study addressed the challenge of training generative adversarial networks (GANs) on small tabular clinical trial datasets for data augmentation, which are known to pose difficulties in training due to limited sample sizes. To overcome this obstacle, a hybrid approach is proposed, combining the synthetic minority oversampling technique (SMOTE) to initially augment the original data to a more substantial size for improving the subsequent GAN training with a Wasserstein conditional generative adversarial network with gradient penalty (WCGAN-GP), proven for its state-of-art performance and enhanced stability. The ultimate objective of this research was to demonstrate that the quality of synthetic tabular data generated by the final WCGAN-GP model maintains the structural integrity and statistical representation of the original small dataset using this hybrid approach. This focus is particularly relevant for clinical trials, where limited data availability due to privacy concerns and restricted accessibility to subject enrollment pose common challenges. Despite the limitation of data, the findings demonstrate that the hybrid approach successfully generates synthetic data that closely preserved the characteristics of the original small dataset. By harnessing the power of this hybrid approach to generate faithful synthetic data, the potential for enhancing data-driven research in drug clinical trials become evident. This includes enabling a robust analysis on small datasets, supplementing the lack of clinical trial data, facilitating its utility in machine learning tasks, even extending to using the model for anomaly detection to ensure better quality control during clinical trial data collection, all while prioritizing data privacy and implementing strict data protection measures.

Diversity data in oncology electronic data capture and database design: A global overview, gap analysis and recommendations for industry from the imCORE network, a worldwide research network designed to connect members in an open environment of shared information, expertise, and decisions.

101 Background: The importance of enrolling diverse and inclusive patient populations in clinical trials has never been more critical however the implementation of measures to ensure inclusive clinical trials remains inconsistent and challenging industry wide. One key mechanism for tracking diversity in clinical trials is the database design of patient demographic classifications. Methods: In this paper we utilize the global reach of the imCORE network to explore the current trends in clinical trial database design for demographic data. We collect and review data on the design of electronic database systems from a diversity of sources including Roche Genentech clinical trial database frameworks and databases at our imCORE sites. We then provide a global electronic database demographic data classification overview and gap analysis. Results: Findings related to electronic database design, demographic data collection process, barriers to capturing diversity and demographic data are presented. Conclusions: Based on our findings we make recommendations from the site and sponsor perspective for an improved future state of electronic demographic diversity data collection in clinical trials with the goal of ultimately leading to meaningful change toward fully inclusive and equitable clinical trials.

Technology-enabled clinical trials: Intentional capture of source data (IDC) in the electronic-health record (EHR) and direct transfer to trial database (electronic data capture [EDC]) in a phase II multicenter trial.

1568 Background: Traditional data collection for clinical trials can be cumbersome and inefficient. FDA guidance now promotes capturing clinical trial source data in electronic form and transmitting it to the EDC, recognizing that this should reduce double data entry and improve data quality and timeliness. Electronic data originators can include the EHR, which can be used during routine clinical care and for gathering data during a clinical investigation. We evaluated a pilot of structured EHR data transfer to EDC in a clinical trial setting. Methods: IDC capability in the EHR was developed and applied to a subset of patients for an open label prospective Phase II study. EHR variables, that include free text, standard dictionaries (eg CTCAEv5, CDISC, First Databank), and derived responses, were mapped to the electronic case report form (eCRF). Bulk transmission of IDC clinical data (adverse events, AEs; concomitant medications, CMs; past medical history, PMH) from the EHR to EDC was executed at a designated time point during study conduct. We assessed the quantity (records) and quality (queries) of data captured and transferred, and timeliness of entry. Data to be used for the production analysis of the trial was collected via eCRF in an EDC system in parallel per usual standards. Results: Data for 102 patients across 8 sites of care by 99 different users was captured in the EHR via IDC from 3/1/2021 to 9/9/2022 and transferred from EHR to EDC in bulk on 9/9/22. 3,958 data records were transferred (852 AEs; 1,581 CMs; 1,525 PMHs). Of the AEs, 99% had an associated grade. Of the CMs and PMHs, none were copy-forwarded (all were entered de novo). Regarding queries in the EDC for transcription error validation among matching records, EHR data produced 205 opened edit check queries from 12 edit checks across all domains (149 AEs, 0 CMs, and 56 PMHs). Regarding timeliness, 95% of matched records were entered in IDC prior to entry in the production EDC. Conclusions: For an open label Phase II study, clinical trial source data was captured electronically through IDC using the EHR as the data originator, and directly bulk-transmitted to EDC. This may enable the elimination of transcription of source data entry into eCRF and result in more timely access to the data in the EDC. Additional investigation into how IDC with EHR-to-EDC compares in quality to traditional EDC is warranted. Planned follow up research includes interviewing site users to evaluate their experiences with IDC data entry.

Association between state Medicaid policies and accrual of Black and Hispanic patients to cancer clinical trials.

1510 Background: The U.S. Medicaid health insurance program may play a key role in mitigating racial and ethnic disparities in cancer clinical trial enrollment, given Medicaid’s disproportionate representation of these populations and its coverage of the routine costs of trial participation in some states. We sought to evaluate the effect of Medicaid expansion under the Affordable Care Act (ACA) on changes in the accrual of racial and ethnic minority patients in cancer clinical trials, across all states and specifically those mandating Medicaid coverage of routine trial costs. Methods: The study used anonymous enrollment data from Medidata Rave, a large commercial clinical trial data collection platform. We conducted a retrospective difference-in-differences (DID) analysis to examine accrual demographics in states that expanded Medicaid eligibility under the ACA compared with non-expansion states, before and after expansion; and assessed effect modification based on state-mandated Medicaid coverage of routine trial costs. Participants included adults enrolled in interventional cancer clinical trials from 2012-2019, located in U.S. hospital referral regions with &gt;5% Black or Hispanic population. The primary outcome was participant race/ethnicity, defined dichotomously as Black or Hispanic (vs non-Black, non-Hispanic). We used ordinary least squares regression to model participant race/ethnicity as a function of (1) an indicator for trial enrollment in an expansion state after policy implementation, (2) state fixed effects, and (3) year fixed effects, with standard errors clustered at the state level. To assess effect modification, we stratified the main model across states with and without coverage mandates of routine trial costs. Results: The study included 75,700 participants across 1,409 clinical trials and 351 sites. In expansion states, the proportion of participants who identified as Black and/or Hispanic increased from 13.4% before expansion to 13.8% after expansion (0.4 percentage-point [PP] change, 95% CI -0.8 to 1.7). In non-expansion states, this proportion decreased from 17.0% to 15.2% (-1.7 PP change, 95% CI -3.7 to 0.2). These trends yielded a non-significant DID estimate of 2.0 PP (95% CI -1.0 to 5.0). In stratified analyses, Medicaid expansion was associated with a 4.5 PP (95% CI 0.4 to 8.6) increase in the enrollment of Black and/or Hispanic participants in states with coverage mandates, but not in states without coverage mandates (1.1 PP, 95% CI -2.6 to 4.8). Conclusions: Medicaid expansion was associated with a significant increase in the proportion of Black and Hispanic oncology trial participants in states that mandated Medicaid coverage of the routine costs of trial participation, but not overall across all states. These findings suggest that Medicaid policies have the potential to advance equitable enrollment in cancer clinical trials.

Concordance between clinical outcomes in the Systolic Blood Pressure Intervention Trial and in the electronic health record

BackgroundRandomized trials are the gold standard for generating clinical practice evidence, but follow-up and outcome ascertainment are resource-intensive. Electronic health record (EHR) data from routine care can be a cost-effective means of follow-up, but concordance with trial-ascertained outcomes is less well-studied. MethodsWe linked EHR and trial data for participants of the Systolic Blood Pressure Intervention Trial (SPRINT), a randomized trial comparing intensive and standard blood pressure targets. Among participants with available EHR data concurrent to trial-ascertained outcomes, we calculated sensitivity, specificity, positive predictive value, and negative predictive value for EHR-recorded cardiovascular disease (CVD) events, using the gold standard of SPRINT-adjudicated outcomes (myocardial infarction (MI)/acute coronary syndrome (ACS), heart failure, stroke, and composite CVD events). We additionally compared the incidence of non-CVD adverse events (hyponatremia, hypernatremia, hypokalemia, hyperkalemia, bradycardia, and hypotension) in trial versus EHR data. Results2468 SPRINT participants were included (mean age 68 (SD 9) years; 26% female). EHR data demonstrated ≥80% sensitivity and specificity, and ≥ 99% negative predictive value for MI/ACS, heart failure, stroke, and composite CVD events. Positive predictive value ranged from 26% (95% CI; 16%, 38%) for heart failure to 52% (95% CI; 37%, 67%) for MI/ACS. EHR data uniformly identified more non-CVD adverse events and higher incidence rates compared with trial ascertainment. ConclusionsThese results support a role for EHR data collection in clinical trials, particularly for capturing laboratory-based adverse events. EHR data may be an efficient source for CVD outcome ascertainment, though there is clear benefit from adjudication to avoid false positives.

P02 Novel pharmacy roles strengthen the multidisciplinary hospital infection team

Abstract Background Pharmacists have an essential role to play in the NHS Long Term Plan. Hospital pharmacy departments need to develop novel roles to strengthen teams and improve patient care. In September 2017, Mid Yorkshire Hospitals NHS Trust appointed a consultant antimicrobial pharmacist along with an administrative apprentice to strengthen pharmacy and infection leadership and support the delivery of the antimicrobial resistance national targets. From January 2018 to June 2020, the infection team worked with locums but no substantive consultant microbiologists. Objectives To describe the benefits of developing novel pharmacy roles to strengthen an infection multidisciplinary team Methods A shortage of consultant microbiologists provided opportunities to develop and enhance other infection roles. These included one year of funding from Pathology for a Band 6 Specialist Pharmacy Technician. The role was subsequently funded by the Adult Community Services team to support the home intravenous antibiotic service. Senior support was provided by the Pathology Group Manager, Head of Infection Prevention and Control and Director of Pharmacy. The apprenticeship levy supported a Level 4 Data analyst qualification to develop the pharmacy administrator role. Two other infection roles were developed: Advanced Clinical Practitioner and Trainee Clinical Scientist, both of which could not be sustained for lack of adequate consultant microbiologist resources for clinical supervision within the team. Results The Specialist Pharmacy Technician coordinates the home intravenous antibiotic service. Clinical responsibility remains with the discharging consultant medical officer. The antimicrobial pharmacy team led the introduction of antibiotic elastomeric pumps for home use, saving 2500 inpatient bed days. Patient and staff feedback on the novel pharmacy roles has been positive. Band 5 Pharmacy Data Analyst – Antimicrobials responsibilities include clinical trial participation, data collection and analysis including ward level working, reporting and coordination of the audit programme. The role has enabled contribution to national research studies, including Antibiotic Review Kit (ARK-Hospital) and Procalcitonin: Evaluation of Antibiotic Use in COVID-19 Hospitalised Patients (PEACH). Through a new strategy, consultant microbiologist workforce has progressively grown back to three full time equivalents and a 4th post advertised, enabling an increase in participation in ward rounds, multidisciplinary team meetings, antimicrobial stewardship, infection prevention &amp; control, Director of Infection Prevention and Control role and leading NIHR research trials. The consultant pharmacist remains in post as a senior leader, and also has a Trust role as Director of Innovation. This change provided funding for an increase from Band 3 to Band 5 data analyst, promotion of a senior Band 7 pharmacist to a Band 8a advanced clinical pharmacist, and conversion of a part time Band 7 pharmacist to a full-time role. Discussion An innovative approach to development of pharmacy, data, nurse and scientist roles has strengthened the infection service in a regional hospital and community services Trust. Pharmacy-led team meetings are now routine in the Trust allowing for more efficient use of consultant microbiologist time. Conclusions Potential future roles are further administrative support, pharmacy assistant, clinical nurse specialist – antimicrobials, and antimicrobial pharmacy team leader.

151. Molecular diversity and resistance mechanisms of Klebsiella pneumoniae bloodstream infections in Peru

Abstract Background Klebsiella pneumoniae, a leading pathogen for mortality associated with antimicrobial resistance (AMR), was responsible for &amp;gt; 250,000 deaths in 2019. Genomic surveillance can guide the development of vaccines and new antibiotics against this pathogen. While AMR disproportionally affects low-and middle-income countries, limited genomic data are available from these countries. To close this gap, this study provides genomic characterization of K. pneumoniae blood isolates recovered in Peru. Methods Consecutive non-duplicate K. pneumoniae blood culture isolates were collected during an AMR surveillance study (VIRAPERU) from Jul 2017 to Oct 2019, from 15 tertiary hospitals from 13 regions of Peru. DNA extraction (GeneJET, Thermo Fisher Scientific), DNA library (Nextera XT, Illumina) and genome sequencing (MiSeq 500bp-V2, Illumina) were conducted. De novo assembling (SPAdes v3.13.1), quality assessment and annotation (Nullarbor v2.0), and identification of species, ST group, K/O loci, AMR (Kleborate v2.0.1) were conducted. Phylogenetic trees were built with Microreact v.192. Results From 119 K. pneumoniae isolates, 114 were recovered and confirmed to belong to the Klebsiella taxon. Six species were identified, the most prevalent being K. pneumoniae (106), followed by K. quasipneumoniae (3). Among carbapenem-resistant isolates (n=13), 10 (77%) carried the blaNDM-1 gene, while other three carried blaKPC-2 (1), blaIMP-16 (1) or no carbapenemase (1). Phenotypic co-resistance to colistin was present in 2 isolates, both negative for mcr-1 gene. The most common mechanisms of resistance to 3rd generation cephalosporins, quinolones and to aminoglycosides were CTX-M-15 (74.4%), qnrB (63.6%), aac(6')-Ib-cr (87.5%), respectively. Many other AMR genetic determinants were identified (Fig. 1). Sixty ST groups were identified, but only 6 ST groups carried a carbapenemase gene (Fig. 2). A wide diversity of K and O locus was also identified (54 distinct K-loci and 14 distinct O-loci). Figure 1.Genetic determinants of antimicrobial resistance and virulence found in Klebsiella pneumoniae blood isolates of PeruFigure 2.Distribution of ST groups according to specific antimicrobial resistance profiles Conclusion Bloodstream infections in Peru are caused by a wide diversity of K. pneumoniae strains, carrying multiple AMR genes. Carbapenem resistance is principally a result of blaNDM-1 carriage, found across 6 specific ST groups. Disclosures Omai Garner, PhD, Beckman Coulter, Inc.: Clinical trial data collection funded by Beckman Coulter, Inc. Victor Nizet, MD, Cellics Therapeutics: Advisor/Consultant|Clarametyx Biosciences: Advisor/Consultant|Vaxcyte, Inc.: Advisor/Consultant|Vaxcyte, Inc.: Grant/Research Support.

230. Multicenter Assessment of the Accuracy of MIC Results for Colistin with MicroScan Dried Gram Negative MIC Panels using CLSI Breakpoints

Abstract Background A multicenter study was performed to evaluate the accuracy of MIC results for colistin on a MicroScan Dried Gram Negative MIC (MSDGN) Panel when compared to results obtained with frozen broth microdilution panels prepared according to CLSI/EUCAST methodology. Note: Colistin is not available in all countries. Methods MSDGN panels were evaluated at three clinical sites (including Beckman Coulter) by comparing MIC values obtained using the MSDGN panels to MICs obtained utilizing a CLSI/EUCAST broth microdilution reference panel. The study included 407 clinical isolates tested using the turbidity and Prompt® methods of inoculation. MSDGN panels were incubated in the WalkAway System (35 ± 1°C) and read on the WalkAway System, the autoSCAN-4 instrument, and read visually at 16-20 hours. Frozen reference panels were prepared and inoculated according to CLSI/EUCAST Joint Working Group Recommendations for MIC determination of Colistin (Polymyxin E) and incubated for 16-20 hours and read visually. CLSI M100 ED32 breakpoints (µg/mL) used for interpretation of MIC results were: Enterobacterales ≤ 2 I, ≥ 4 R; P. aeruginosa ≤ 2 I, ≥ 4 R. Results Essential, categorical agreement, and categorical errors were calculated using MIC results from WalkAway reads for MSDGN panels in Table 1. All other read methods yielded similar results. Categorical agreement was not calculated for Acinetobacter spp. as MIC only is reported. Table 1- Results Conclusion This multicenter study showed that colistin MIC results for Gram Negative bacteria obtained with the MSDGN panel correlate well with MICs obtained using frozen reference panels with CLSI interpretive criteria. © 2022 Beckman Coulter. All rights reserved. All other trademarks are the property of their respective owners. Beckman Coulter, the stylized logo, and the Beckman Coulter product and service marks mentioned herein are trademarks or registered trademarks of Beckman Coulter, Inc. in the U.S. and other countries. Disclosures Stefan Riedel, M.D., PhD., D(ABMM), FCAP, Beckman Coulter, Inc.: Clinical trial data collection funded by Beckman Coulter, Inc. Maria Traczewski, BS, Beckman Coulter, Inc.: Clinical trial data collection funded by Beckman Coulter, Inc. Denise Beasley, BS, Beckman Coulter, Inc.: Clinical trial data collection funded by Beckman Coulter, Inc. Regina Brookman, BS, Beckman Coulter, Inc.: Employee of Beckman Coulter Jose Diaz, BS, Beckman Coulter, Inc.: Employee of Beckman Coulter Zabrina Lockett, PhD, Beckman Coulter, Inc.: Employee of Beckman Coulter Jennifer Chau, PhD, Beckman Coulter, Inc.: Employee of Beckman Coulter.

342. Multicenter Evaluation of Fosfomycin MIC Results for Enterobacterales Using EUCAST V11 Breakpoints (i.v. and oral for uncomplicated UTI only, E. coli) on MicroScan Dried Gram Negative MIC Panels

Abstract Background EUCAST V11 fosfomycin breakpoints for Enterobacterales (i.v. and oral for uncomplicated UTI only, E. coli) were evaluated against data from a multicenter clinical study on a MicroScan Dried Gram Negative MIC (MSDGN) Panel. MIC results were compared to results obtained with agar dilution reference prepared according to CLSI methodology. Methods A total of 344 Gram negative clinical isolates including 191 Enterobacterales were tested using the turbidity and Prompt® methods of inoculation during the efficacy phase at three clinical sites. An evaluation was conducted by comparing MIC values obtained using the MSDGN panels to MICs utilizing the CLSI agar dilution reference. MSDGN panels were incubated at 35 ± 1°C and read on the WalkAway System, the autoSCAN-4 instrument, and read visually at 16-20 hours. Agar dilution plates were prepared according to CLSI methodology, incubated for 16-20 hours and read visually. EUCAST v11.0 fosfomycin breakpoints (mg/L) used for interpretation of MIC results were: i.v. for Enterobacterales ≤ 32 S, &amp;gt; 32 R and oral for uncomplicated UTI only, E. coli ≤ 8 S, &amp;gt; 8 R. Results Essential agreement, categorical agreement and categorical errors were calculated compared to MIC results from agar dilution plates. Results for all efficacy isolates with turbidity inoculation and manual read are found in Table 1. Table 1- Results Conclusion This multicenter study showed that fosfomycin MIC results for i.v. for Enterobacterales and E. coli (oral, for uncomplicated UTI only) obtained with the MSDGN panel correlate well with MICs obtained using CLSI agar dilution reference using EUCAST interpretive criteria. © 2022 Beckman Coulter. All rights reserved. All other trademarks are the property of their respective owners. Beckman Coulter, the stylized logo, and the Beckman Coulter product and service marks mentioned herein are trademarks or registered trademarks of Beckman Coulter, Inc. in the United States and other countries. Disclosures Omai Garner, PhD, Beckman Coulter, Inc.: Clinical trial data collection funded by Beckman Coulter, Inc. Amanda Harrington, PhD, Beckman Coulter, Inc.: Clinical trial data collection funded by Beckman Coulter, Inc.|bioMeriuex/BioFire: Grant/Research Support Sharon DesJarlais, BS, Beckman Coulter, Inc.: Clinical trial data collection funded by Beckman Coulter, Inc. Maria Traczewski, BS, Beckman Coulter, Inc.: Clinical trial data collection funded by Beckman Coulter, Inc. Denise Beasley, BS, Beckman Coulter, Inc.: Clinical trial data collection funded by Beckman Coulter, Inc. Jose Diaz, BS, Beckman Coulter, Inc.: Employee of Beckman Coulter Regina Brookman, BS, Beckman Coulter, Inc.: Employee of Beckman Coulter Zabrina Lockett, PhD, Beckman Coulter, Inc.: Employee of Beckman Coulter Jennifer Chau, PhD, Beckman Coulter, Inc.: Employee of Beckman Coulter.

403. Strain Epidemiology of Clostridioides difficile across Three Geographically Distinct Medical Centers in Chicago

Abstract Background Clostridioides difficile infections (CDI) are caused by a large and diverse group of strains with differences in prevalence and associated morbidity. Over the past 20 years the C. difficile (CD) molecular epidemiology has changed as the prevalence of the epidemic strain recognized as restriction endonuclease analysis (REA) group BI or PCR-Ribotype group (RT) 027 has decreased. The objective of this study was to determine the current epidemiology of CD in the city of Chicago. Methods Baseline characteristics and symptoms were compared for 81 patients who tested positive for CD by PCR (tcdB) between 9/1/2021 and 10/7/2021 at 3 hospitals in the city of Chicago. Patients were classified as having healthcare-associated CDI (HA-CDI) if symptoms began &amp;gt;72 hours after hospital admission, community-associated CDI (CA-CDI) if symptoms began ≤72 hours prior to admission, and community-onset healthcare-associated CDI (COHA-CDI) if they had been hospitalized ≤4 weeks prior to CDI diagnosis. Available stools were cultured and recovered CD isolates underwent REA typing. Determination of CD colonization was made by review of symptoms including chronicity of symptoms, stool frequency, and response to treatment. Results Among all patients, 33% (27/81) were CA-CDI, 28% (23/81) COHA-CDI, 11% (9/81) HA-CDI, and 27% (22/81) were classified as colonized. Primary CDI accounted for 66% (39/59) of the infections. Among patients with a primary CDI, 46% (18/39) of patients were classified as CA-CDI whereas COHA-CDI and HA-CDI accounted for 54% (21/39) of infections. REA group Y was the most common group strain accounting for 29% (22/75) of isolates. (Figure 1) REA group Y accounted for 26% (7/27) of CA-CDI compared to 0 REA group BI [p=0.06], and REA group Y accounted for 35% (7/20) of all colonized patients. (Figure 2) Figure 1Figure 2 Conclusion There has been a marked change in the CD epidemiology within the city of Chicago since 2009 when REA group BI accounted for 61% of CDI (Black et al ICHE 2011; 32:897-902). REA group Y (typically identified as RT 014/020) is now the most common group strain in Chicago supplanting REA group BI (RT027). REA group Y appears to be associated primarily with CA-CDI and CD colonization. A detailed genomic analysis of REA group Y is required to determine potential reservoirs of REA group Y. Disclosures Mary K. Hayden, MD, Sanofi: Member, clinical adjudication panel Nicholas M. Moore, PhD, D(ABMM), Abbott Molecular: Grant/Research Support|Cepheid: Grant/Research Support Amanda Harrington, PhD, Beckman Coulter, Inc.: Clinical trial data collection funded by Beckman Coulter, Inc.|bioMeriuex/BioFire: Grant/Research Support Dale N. Gerding, MD, Destiny Pharma plc.: Advisor/Consultant Stuart Johnson, M.D., Ferring Pharmaceuticals: Membership on Ferring Publication Steering Committee|Ferring Pharmaceuticals: Employee|Summit Plc: Advisor/Consultant.

Making Clinical Data Acquisition Standards Harmonization (CDASH) Electronic Case Report Forms Available on the REDCap Shared Data Instrument Library.

A guiding principle behind the development and deployment of the REDCap data management platform has always included attention to workflow design that allows easy implementation of best practices for clinical and translational researchers. CDISC standards such as CDASH have helped the clinical research community improve the efficiency, actionability, and quality of their clinical trials data, but have had limited uptake among the academic institutions. To create a scalable methodology to convert CDISC CDASH eCRF instrument metadata into REDCap data dictionaries for the purpose of simplifying adoption and use of CDASH instruments by research teams across the REDCap Consortium. We have used our replicable methods to translate metadata from 34 CDASH Foundational eCRFs and 20 CDASH Crohn's Disease eCRFs into REDCap eCRF metadata and have made these instruments available in the REDCap Shared Data Instrument Library for widespread sharing and uptake across the REDCap Consortium. Users can import the standardized eCRFs directly into their REDCap projects for immediate use in clinical trial data collection. Disseminating CDISC standards through the REDCap community will increase the accessibility of these standards for academic medical centers. Having academic clinical researchers using CDISC standards may lead to more research datasets that interoperate with pharmaceutical sponsored trials, and more discoveries from secondary use of clinical research data.