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Purpose: Racial and ethnic minorities remain underrepresented in clinical trials . Underrepresentation of racial groups leads to the selection of therapeutic interventions that may not be representative of the population expected to use the medicine. This study evaluates the effectiveness of a set of implementation strategies to increase underrepresented patients in gynecologic cancer clinical trials. Methods: An interrupted time series analysis evaluating implementation strategies (pre-screening and fast-track referral) was conducted from January 2021 to May 2022. Descriptive analysis of gynecologic oncology patient screening and accrual was compared before and after intervention implementation. Results: During the study period (pre- and post-intervention), 26 patients were screened, and 9 patients enrolled in therapeutic gynecologic cancer clinical trials. Prior to the intervention, 7 patients were screened and 2 patients enrolled onto a clinical trial. Following the intervention, 19 patients were screened and 7 patients enrolled in a cancer clinical trial. Black patients comprised 13 of 19 (68.4%) of patients post-intervention compared to 1 of 7 (14.3 %) of patients screened pre-intervention (p < 0.05). All 7 patients enrolled post intervention were racial and ethnic minorities (non-Hispanic Black [4 of 7] and Hispanic White [3 of 7]) compared to no minority patients enrolled pre-intervention (p < 0.05). Screening increased 2.5-fold for all patients, and 5- fold for minority patients. Clinical trial enrollment increased 3.5-fold following intervention. Conclusions: A combination of pre-screening and fast-track referral intervention in a racial and ethnically diverse urban academic hospital was associated with a significant increase in minority screening and enrollment. Structured strategies to overcome barriers to underrepresented racial and ethnic patient accrual in academic hospitals are urgently warranted.

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Objectives: Rural patients have poor cancer outcomes and clinical trial (CT) enrollment compared to urban patients due to attitudinal, awareness, and healthcare access differential. Knowledge of cancer survival disparities and CT enrollment is important for designing interventions and innovative approaches to address the stated barriers. The study explores the potential disparities in cancer survival rates and clinical trial enrollments in rural and urban breast and lung cancer patients. Our hypotheses are that for both cancer types, urban cancer patients will have longer 5-year survival rates and higher enrollment rates in clinical trials than those in rural counties. Methods: We compared breast and lung cancer patients' survival rates and enrollment ratios in clinical trials between rural (RUCC 4-9) and urban counties in Georgia at a Comprehensive Cancer Center (CCC). To assess these differences, we carried out a series of independent samples t-tests and Chi-Square tests. Results: The outcomes indicate comparable 5-year survival rates across rural and urban counties for breast and lung cancer patients, failing to substantiate our hypothesis. While clinical trial enrollment rates demonstrated a significant difference between breast and lung cancer patients at CCC, no significant variation was observed based on rural or urban classification. Conclusion: These findings underscore the need for further research into the representation of rural patients with diverse cancer types at CCC and other cancer centers. Further, the findings have considerable implications for the initiation of positive social change to improve CT participation and reduce cancer survival disparities.

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Background: Vaccine clinical trials should strive to recruit a racially, socioeconomically, and ethnically diverse range of participants to ensure appropriate representation that matches population characteristics. Yet, full inclusion in research is often limited. Methods: A single-center retrospective study was conducted of adults enrolled at Brigham and Women's Hospital (Boston, MA) between July 2020 and December 2021. Demographic characteristics, including age, race, ethnicity, ZIP code, and sex assigned at birth, were analyzed from both HIV and COVID-19 vaccine trials during the study period, acknowledging the limitations to representation under these parameters. We compared the educational attainment of vaccine trial participants to residents of the Massachusetts metropolitan area, geocoded participants' addresses to their census block group, and linked them to reported median household income levels from publicly available data for 2020. Frequency and quartile analyses were carried out, and spatial analyses were performed using ArcGIS Online web-based mapping software (Esri). Results: A total of 1030 participants from four COVID-19 vaccine trials (n = 916 participants) and six HIV vaccine trials (n = 114 participants) were included in the analysis. The median age was 49 years (IQR 33-63) and 28 years (IQR 24-34) for the COVID-19 and HIV vaccine trials, respectively. Participants identifying as White were the majority group represented for both the COVID-19 (n = 598, 65.3%) and HIV vaccine trials (n = 83, 72.8%). Fewer than 25% of participants identified as Hispanic or Latin. Based on ZIP code of residence, the median household income for COVID-19 vaccine clinical trial participants (n = 846) was 102,088 USD (IQR = 81,442-126,094). For HIV vaccine clinical trial participants (n = 109), the median household income was 101,266 USD (IQR 75,052-108,832). Conclusion: We described the characteristics of participants enrolled for HIV and COVID-19 vaccine trials at a single center and found similitude in geographical distribution, median incomes, and proportion of underrepresented individuals between the two types of vaccine candidate trials. Further outreach efforts are needed to ensure the inclusion of individuals from lower educational and socioeconomic brackets. In addition, continued and sustained efforts are necessary to ensure inclusion of individuals from diverse racial and ethnic backgrounds.

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Introduction: Patients with localized pancreatic adenocarcinoma (PDAC) benefit from multi-modality therapy. Whether care patterns and oncologic outcomes vary if a patient was seen through a pancreatic multi-disciplinary clinic (PMDC) versus only individual specialty clinics is unclear. Methods: Using institutional Pancreatic Cancer Registry, we identified patients with localized PDAC from 2019- 2022 who eventually underwent resection. It was our standard practice for borderline resectable (BRPC) patients to undergo ≤4 months of neoadjuvant chemotherapy, ± radiation, followed by exploration, while locally advanced (LAPC) patients were treated with 4-6 months of chemotherapy, followed by radiation and potential exploration. Descriptive and multivariable analyses (MVA) were performed to examine the association between clinic type (PMDC vs individual specialty clinics i.e. surgical oncology, medical oncology, or radiation oncology) and study outcomes. Results: A total of 416 patients met inclusion criteria. Of these, 267 (64.2%) had PMDC visits. PMDC group received radiation therapy more commonly (53.9% versus 27.5%, p=0.001), as compared to individual specialty clinic group. Completion of neoadjuvant treatment (NAT) was far more frequent in patients seen through PMDC compared to patients seen through individual specialty clinics (69.3% vs 48.9%). On MVA, PMDC group was significantly associated with receipt of NAT per institutional standards (adjusted OR 2.23, 95% CI 1.46-7.07, p=0.006). Moreover, the average treatment effect of PMDC on progression-free survival (PFS) was 4.45 (95CI: 0.87-8.03) months. No significant association between overall survival (OS) and clinic type was observed. Discussion: Provision of care through PMDC was associated with significantly higher odds of completing NAT per institutional standards as compared to individual specialty clinics, which possibly translated into improved PFS. The development of multidisciplinary clinics for management of pancreatic cancer should be incentivized, and any barriers to such development should be addressed.

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Background Clinical trial matching, essential for advancing medical research, involves detailed screening of potential participants to ensure alignment with specific trial requirements. Research staff face challenges due to the high volume of eligible patients and the complexity of varying eligibility criteria. The traditional manual process, both time-consuming and error-prone, often leads to missed opportunities. Recently, large language models (LLMs), specifically generative pre-trained transformers (GPTs), have become impressive and impactful tools. Utilizing such tools from artificial intelligence (AI) and natural language processing (NLP) may enhance the accuracy and efficiency of this process through automated patient screening against established criteria. Methods Utilizing data from the National NLP Clinical Challenges (n2c2) 2018 Challenge, we utilized 202 longitudinal patient records. These records were annotated by medical professionals and evaluated against 13 selection criteria encompassing various health assessments. Our approach involved embedding medical documents into a vector database to determine relevant document sections and then using an LLM (OpenAI's GPT-3.5 Turbo and GPT-4) in tandem with structured and chain-of-thought prompting techniques for systematic document assessment against the criteria. Misclassified criteria were also examined to identify classification challenges. Results This study achieved an accuracy of 0.81, sensitivity of 0.80, specificity of 0.82, and a micro F1 score of 0.79 using GPT-3.5 Turbo, and an accuracy of 0.87, sensitivity of 0.85, specificity of 0.89, and micro F1 score of 0.86 using GPT-4. Notably, some criteria in the ground truth appeared mislabeled, an issue we couldn't explore further due to insufficient label generation guidelines on the website. Conclusion Our findings underscore the potential of AI and NLP technologies, including LLMs, in the clinical trial matching process. The study demonstrated strong capabilities in identifying eligible patients and minimizing false inclusions. Such automated systems promise to alleviate the workload of research staff and improve clinical trial enrollment, thus accelerating the process and enhancing the overall feasibility of clinical research. Further work is needed to determine the potential of this approach when implemented on real clinical data.

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BACKGROUND: For results to be generalizable to all patients with cancer, clinical trials need to include a diverse patient demographic that is representative of the general population. We sought to characterize the effect of receiving care at a minority-serving hospital (MSH) and/or safety-net hospital on clinical trial enrollment among patients with gastrointestinal (GI) malignancies. METHODS: Adult patients with GI cancer who underwent oncologic surgery and were enrolled in institutional-/National Cancer Institute-funded clinical trials between 2012 and 2019 were identified in the National Cancer Database. Multivariable regression was used to assess the relationship between MSH and safety-net status relative to clinical trial enrollment. RESULTS: Among 1,112,594 patients, 994,598 (89.4%) were treated at a non-MSH, whereas 117,996 (10.6%) were treated at an MSH. Only 1857 patients (0.2%) were enrolled in a clinical trial; most patients received care at a non-MSH (1794 [96.6%]). On multivariable analysis, the odds of enrollment in a clinical trial were markedly lower among patients treated at an MSH vs non-MSH (odds ratio [OR], 0.32; 95% CI, 0.22-0.46). In addition, even after controlling for receipt of care at MSH, Black patients remained at lower odds of enrollment in a clinical trial than White patients (OR, 0.57; 95% CI, 0.45-0.73; both P < .05). CONCLUSION: Overall, clinical trial participation among patients with GI cancer was extremely low. Patients treated at an MSH and high safety-net burden hospitals and Black individuals were much less likely to be enrolled in a clinical trial. Efforts should be made to improve trial enrollment and address disparities in trial representation.

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Introduction: Clinical trials investigating the safety and efficacy of experimental drugs and devices are the cornerstone of medicinal advancement. Enrolling sufficient participants in these trials is vital to ensure adequate statistical power and generalizability. Clinical trial participation is particularly low among certain populations, including medically underserved communities (i.e., rural areas) and Black, Indigenous, and People of Color (BIPOC). Methods: A retrospective study design was used to understand patient outcomes and access/barriers to clinical trial participation in the rural northwest United States. A quantitatively focused retrospective chart review was conducted for adult participants enrolled in at least one clinical trial in a single northwest health system between 1999 and 2022. Descriptive and inferential statistical analyses were performed to assess trial outcomes at a significance level 0.05. Results: The retrospective chart review yielded 833 clinical trial records with 753 individual enrolled participants. The all-cause relative frequency of death at last known follow-up amongst clinical trial participants was 8.90% (n = 67). Based on logistic regression, the death was significantly associated with the participants' age at initial trial screening (ß = 0.09, p-value <0.001), those that resided in non-metro areas (ß = -0.86, p-value = 0.045), and those that lived in Northeastern Montana (ß = 1.27, p-value = 0.025). Additionally, death at last known follow-up was significantly associated with enrollment in 2021-2022 (ß = -1.52, p-value <0.001), enrolled in more than one study (ß = 0.84, p-value = 0.023), in internationally sponsored trials (ß = -2.08, p-value <0.001), in Phase I (ß = 5.34, p-value <0.001), in Phase II trials (ß = 1.37, p-value = 0.013), diabetes as a primary trial target (ß = -2.04, p-value = 0.003). Conclusion: As decentralized trial design and remote or virtual elements of traditional trials become normative, representation of rural and frontier populations is imperative to support the generalizability of trial data encouraged by the FDA.

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Despite dedicated efforts to improve equitable access to cancer care in the United States, disparities in cancer outcomes persist, and geographically underserved patients remain at an increased risk of cancer with lower rates of survival. The critical evaluation of cancer prevention inequities and clinical trial access presents the opportunity to outline novel strategies to incrementally improve bookended access to gynecologic cancer care for geographically underserved patients. Cancer prevention strategies that can be addressed in the rural patient population mirror priorities in the Healthy People 2030 objectives and include increased identification of high risk individuals who may benefit from increased cancer screening and risk reduction, increasing the proportion of people who discuss interventions to prevent cancer, such as HPV vaccination, with their provider, and increasing the proportion of adults who complete evidence based cancer screening. Barriers to accrual to clinical trials for rural patients overlap significantly with the same barriers to obtaining health care in general. These barriers include: lack of facilities and specialized providers; lack of robust health infrastructure; inability to travel; and financial barriers. In this review, we will discuss current knowledge and opportunities to improve cancer prevention initiatives and clinical trial enrollment in geographically underserved populations with a focus on rurality.

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BACKGROUND: Identifying patient- and disease-specific characteristics associated with clinical trial enrollment of adolescents and young adults (AYAs) with cancer may target efforts to improve accrual. METHODS: Alliance for Clinical Trials in Oncology (Alliance) trials opened from January 1, 2000, and closed before January 1, 2018, for common AYA cancers were identified. Proportions of AYAs (aged 18-39 years old) versus non-AYAs (aged ≥40 years old) enrolled by cancer type were summarized by descriptive statistics. Among studies with ≥20 AYAs enrolled, demographic and disease characteristics of AYAs versus non-AYAs were compared with χ2 and Kruskal-Wallis tests. A qualitative review was also conducted of therapeutic trials included in analysis in PubMed through December 31, 2021, that reported AYA-specific survival. RESULTS: Among 188 trials enrolling 40,396 patients, AYAs represented 11% (4468 of 40,396) of accrual. AYA accrual varied by cancer type (leukemia, 23.6%; breast, 9.9%; lymphoma, 14.8%; colorectal, 6.2%; central nervous system, 8.1%; melanoma, 11.8%; sarcoma, 12%). Across ages, the proportion of Black and Hispanic patients enrolled was 1%-10%. Compared to non-AYAs, AYAs in breast and colorectal cancer trials were less likely to be White and more likely to be Hispanic. Disease characteristics differed by age for selected trials. Two trials reported AYA-specific survival, with no significant differences observed by age. CONCLUSIONS: AYA accrual to Alliance trials was comparable to or exceeded population-based, age-specific prevalence estimates for most cancer types. Greater proportional representation of Hispanic and non-White patients among AYAs reflects US demographic trends. The small number of minority patients enrolled across ages underscores the persistent challenge of ensuring equitable access to trials, including for AYAs.

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OBJECTIVE: Despite declining lung cancer mortality in the United States, survival differences remain among racial and ethnic minorities in addition to those with limited health care access. Improvements in lung cancer treatment can be obtained through clinical trials, yet there are disparities in clinical trial enrollment of other cancer types. This study aims to evaluate disparities in lung cancer clinical trial enrollment to inform future enrollment initiatives. METHODS: We analyzed patients with non-small cell lung cancer from the National Cancer Database (2004-2018), categorizing them as enrolled or not enrolled in clinical trials based on "rx_summ_other" data element. Clinical, demographic, and institutional factors associated with trial enrollment were assessed using bivariate and multivariate analysis, adjusting for institutional-level clustering. RESULTS: A total of 1924 (0.12%) patients with lung cancer were enrolled in clinical trials. Enrolled patients were predominantly non-Hispanic White (82%), with greater socioeconomic status, treated at academic programs (67%), and had private insurance (42%) or Medicare (44%). They also traveled further for treatment compared with unenrolled patients (56 vs 27 miles, P < .001). After adjusting for demographic and clinical factors, lung cancer trial enrollment was significantly less likely among Black (odds ratio, 0.55; 95% confidence interval, 0.5-0.7, P < .001) and Hispanic (0.66; 95% confidence interval, 0.5-0.9, P = .01) patients. Patients with Medicaid or uninsured, in the lowest socioeconomic status group, and those treated at community-based cancer programs were the least likely to enroll. CONCLUSIONS: Enrollment in lung cancer trials disproportionally excludes minority patients, those in the lowest socioeconomic status, community cancer programs, and the underinsured. These disparities in demographic and access for trial participation show a need for improved enrollment strategies.

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The informed consent form (ICF) is intended to assure that subject participation in research studies is informed and voluntary. Yet, there is ample evidence that many subjects do not adequately understand the concepts and language in a clinical trial ICF, which may undermine their willingness to participate in a clinical trial. In a randomized setting, we compared a standard read-only ICF to an audio-assisted ICF with or without teach-back. We found that audio-assisted ICFs significantly improved willingness to participate in a mock clinical trial among our sample of primarily African-American participants.

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BACKGROUND: Significant racial disparities in prostate cancer incidence and mortality have been reported between African American Men (AAM), who are at increased risk for prostate cancer, and European American Men (EAM). In most of the studies carried out on prostate cancer, this population is underrepresented. With the advancement of genome-wide association studies, several genetic predictor models of prostate cancer risk have been elaborated, as well as numerous studies that identify both germline and somatic mutations with clinical utility. RECENT FINDINGS: Despite significant advances, the AAM population continues to be underrepresented in genomic studies, which can limit generalizability and potentially widen disparities. Here we outline racial disparities in currently available genomic applications that are used to estimate the risk of individuals developing prostate cancer and to identify personalized oncology treatment strategies. While the incidence and mortality of prostate cancer are different between AAM and EAM, samples from AAM remain to be unrepresented in different studies. CONCLUSION: This disparity impacts the available genomic data on prostate cancer. As a result, the disparity can limit the predictive utility of the genomic applications and may lead to the widening of the existing disparities. More studies with substantially higher recruitment and engagement of African American patients are necessary to overcome this disparity.

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BACKGROUND: Assessment for risks associated with acute stable COVID-19 is important to optimize clinical trial enrollment and target patients for scarce therapeutics. To assess whether healthcare system engagement location is an independent predictor of outcomes we performed a secondary analysis of the ACTIV-4B Outpatient Thrombosis Prevention trial. METHODS: A secondary analysis of the ACTIV-4B trial that was conducted at 52 US sites between September 2020 and August 2021. Participants were enrolled through acute unscheduled episodic care (AUEC) enrollment location (emergency department, or urgent care clinic visit) compared to minimal contact (MC) enrollment (electronic contact from test center lists of positive patients).We report the primary composite outcome of cardiopulmonary hospitalizations, symptomatic venous thromboembolism, myocardial infarction, stroke, transient ischemic attack, systemic arterial thromboembolism, or death among stable outpatients stratified by enrollment setting, AUEC versus MC. A propensity score for AUEC enrollment was created, and Cox proportional hazards regression with inverse probability weighting (IPW) was used to compare the primary outcome by enrollment location. RESULTS: Among the 657 ACTIV-4B patients randomized, 533 (81.1%) with known enrollment setting data were included in this analysis, 227 from AUEC settings and 306 from MC settings. In a multivariate logistic regression model, time from COVID test, age, Black race, Hispanic ethnicity, and body mass index were associated with AUEC enrollment. Irrespective of trial treatment allocation, patients enrolled at an AUEC setting were 10-times more likely to suffer from the adjudicated primary outcome, 7.9% vs. 0.7%; p < 0.001, compared with patients enrolled at a MC setting. Upon Cox regression analysis adjustment patients enrolled at an AUEC setting remained at significant risk of the primary composite outcome, HR 3.40 (95% CI 1.46, 7.94). CONCLUSIONS: Patients with clinically stable COVID-19 presenting to an AUEC enrollment setting represent a population at increased risk of arterial and venous thrombosis complications, hospitalization for cardiopulmonary events, or death, when adjusted for other risk factors, compared with patients enrolled at a MC setting. Future outpatient therapeutic trials and clinical therapeutic delivery programs of clinically stable COVID-19 patients may focus on inclusion of higher-risk patient populations from AUEC engagement locations. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04498273.

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For thyroid cancer clinical trials, the inclusion of participants from diverse patient populations is uniquely important given existing racial/ethnic disparities in thyroid cancer care. Since 2011, a paradigm shift has occurred in the treatment of advanced thyroid cancer with the approval of multiple systemic therapies by the US Food and Drug Administration based on their use in the clinical trials setting. Although these clinical trials recruited patients from up to 164 sites in 25 countries, the inclusion of racial/ethnic minority patients remained low. In this mini-review, we provide an overview of barriers to accessing cancer clinical trials, framed in the context of why patients with thyroid cancer may be uniquely vulnerable. Multilevel interventions and increased funding for thyroid cancer research are necessary to increase access to and recruitment of under-represented patient populations into thyroid cancer clinical trials.

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INTRODUCTION: Alzheimer's disease (AD) blood tests are likely to become increasingly important in clinical practice, but they need to be evaluated in diverse groups before use in the general population. METHODS: This study enrolled a community-based sample of older adults in the St. Louis, Missouri, USA area. Participants completed a blood draw, Eight-Item Informant Interview to Differentiate Aging and Dementia (AD8® ), Montreal Cognitive Assessment (MoCA), and survey about their perceptions of the blood test. A subset of participants completed additional blood collection, amyloid positron emission tomography (PET), magnetic resonance imaging (MRI), and Clinical Dementia Rating (CDR® ). RESULTS: Of the 859 participants enrolled in this ongoing study, 20.6% self-identified as Black or African American. The AD8 and MoCA correlated moderately with the CDR. The blood test was well accepted by the cohort, but it was perceived more positively by White and highly educated individuals. DISCUSSION: Studying an AD blood test in a diverse population is feasible and may accelerate accurate diagnosis and implementation of effective treatments. HIGHLIGHTS: A diverse group of older adults was recruited to evaluate a blood amyloid test. The enrollment rate was high and the blood test was well accepted by participants. Cognitive impairment screens have moderate performance in a diverse population. Alzheimer's disease blood tests are likely to be feasible for use in real-world settings.

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In the summer of 2020, multiple efforts were undertaken to establish safe and effective vaccines to combat the spread of the coronavirus disease (COVID-19). In the United States (U.S.), Operation Warp Speed (OWS) was the program designated to coordinate such efforts. OWS was a partnership between the Department of Health and Human Services (HHS), the Department of Defense (DOD), and the private sector, that aimed to help accelerate control of the COVID-19 pandemic by advancing development, manufacturing, and distribution of vaccines, therapeutics, and diagnostics. The U.S. Department of Veterans Affairs' (VA) was identified as a potential collaborator in several large-scale OWS Phase III clinical trial efforts designed to evaluate the safety and efficacy of various vaccines that were in development. Given the global importance of these trials, it was recognized that there would be a need for a coordinated, centralized effort within VA to ensure that its medical centers (sites) would be ready and able to efficiently initiate, recruit, and enroll into these trials. The manuscript outlines the partnership and start-up activities led by two key divisions of the VA's Office of Research and Development's clinical research enterprise. These efforts focused on site and enterprise-level requirements for multiple trials, with one trial serving as the most prominently featured of these studies within the VA. As a result, several best practices arose that included designating clinical trial facilitators to study sites to support study initiation activities and successful study enrollment at these locations in an efficient and timely fashion.

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BACKGROUND: To advance new therapies into clinical care, clinical trials must recruit enough participants. Yet, many trials fail to do so, leading to delays, early trial termination, and wasted resources. Under-enrolling trials make it impossible to draw conclusions about the efficacy of new therapies. An oft-cited reason for insufficient enrollment is lack of study team and provider awareness about patient eligibility. Automating clinical trial eligibility surveillance and study team and provider notification could offer a solution. METHODS: To address this need for an automated solution, we conducted an observational pilot study of our TAES (TriAl Eligibility Surveillance) system. We tested the hypothesis that an automated system based on natural language processing and machine learning algorithms could detect patients eligible for specific clinical trials by linking the information extracted from trial descriptions to the corresponding clinical information in the electronic health record (EHR). To evaluate the TAES information extraction and matching prototype (i.e., TAES prototype), we selected five open cardiovascular and cancer trials at the Medical University of South Carolina and created a new reference standard of 21,974 clinical text notes from a random selection of 400 patients (including at least 100 enrolled in the selected trials), with a small subset of 20 notes annotated in detail. We also developed a simple web interface for a new database that stores all trial eligibility criteria, corresponding clinical information, and trial-patient match characteristics using the Observational Medical Outcomes Partnership (OMOP) common data model. Finally, we investigated options for integrating an automated clinical trial eligibility system into the EHR and for notifying health care providers promptly of potential patient eligibility without interrupting their clinical workflow. RESULTS: Although the rapidly implemented TAES prototype achieved only moderate accuracy (recall up to 0.778; precision up to 1.000), it enabled us to assess options for integrating an automated system successfully into the clinical workflow at a healthcare system. CONCLUSIONS: Once optimized, the TAES system could exponentially enhance identification of patients potentially eligible for clinical trials, while simultaneously decreasing the burden on research teams of manual EHR review. Through timely notifications, it could also raise physician awareness of patient eligibility for clinical trials.

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Background The Florida Association of Pediatric Tumor Programs (FAPTP) has used the Statewide Patient Information Reporting System (SPIRS) since 1981 to track all new cases of pediatric cancer. We reviewed the last 40 years of data to see how pediatric cancer care has evolved. Methods We retrospectively analyzed SPIRS data from 1981 through 2020 in five-year increments, looking at numbers of new diagnoses, care delivery sites, and trial enrollment in Children's Oncology Group (COG) studies. Results From 1981-2020 Florida's population increased almost 88% while the pediatric population only grew 61%. New pediatric cancer diagnoses increased 326% to over 1,000 new cases/year. The percentage of patients treated at FAPTP centers grew from 30% to 57% with an annual percentage change (APC) of 10.3% (95% Confidence Interval [CI] of 0.6 to 20.9%). The rate of COG clinical trial enrollment decreased from 32% in 1981-1985 to 20% in 2016-2020, for an APC of 8.91% (95% CI of -13.3 to -4.3%). Conclusions The striking increase in pediatric cancer cases in Florida over the last 40 years was out of proportion to the population growth. More patients received care at FAPTP centers, but a lower percentage were enrolled on COG trials.