When to reinvite initially ineligible populations for targeted lung cancer screening?

INTRODUCTION: Targeted low-dose CT lung cancer screening reduces lung cancer mortality. England's Targeted Lung Health Check programme uses risk prediction tools to determine eligibility for biennial screening among people with a smoking history aged 55-74. Some participants initially ineligible for lung cancer screening will later become eligible with increasing age and ongoing tobacco exposure. It is, therefore, important to understand how many people could qualify for reinvitation, and after how long, to inform implementation of services. METHODS: We prospectively predicted future risk (using Prostate, Lung, Colorectal and Ovarian trial's risk model (PLCOm2012) and Liverpool Lung Project version 2 (LLPv2) risk models) and time-to-eligibility of 5345 participants to estimate how many would become eligible through the course of a Lung Health Check screening programme for 55-74 years. RESULTS: Approximately a quarter eventually become eligible, with those with the lowest baseline risks unlikely to ever become eligible. Time-to-eligibility is shorter for participants with higher baseline risk, increasing age and ongoing smoking status. At a PLCOm2012 threshold ≥1.51%, 68% of those who continue to smoke become eligible compared with 18% of those who have quit. DISCUSSION: Predicting which participants may become eligible, and when, during a screening programme can help inform reinvitation strategies and service planning. Those with risk scores closer to the eligibility threshold, particularly people who continue to smoke, will reach eligibility in subsequent rounds while those at the lowest risk may be discharged from the programme from the outset.

Loss of Medicaid Coverage During the Renewal Process.

Importance: Medicaid beneficiaries must periodically redemonstrate their eligibility in a process that is called renewal, redetermination, or recertification. The number and characteristics of people who lose Medicaid coverage due to renewal requirements are not known. Objective: To measure the proportion of people who lose Medicaid coverage at the renewal deadline, overall and by enrollee characteristics, and time until regaining Medicaid coverage among those losing coverage at the deadline. Design, Setting, and Participants: This cohort study tracked the duration of Medicaid enrollment among Wisconsin Medicaid enrollees with a 12-month renewal deadline. Data were collected for all nonelderly (aged <65 years) new enrollees from January 2016 through January 2018, except those enrolled due to disability or pregnancy. Individuals were followed through January 2020 to provide at least 24 months of data on each enrollment spell. Data were analyzed from August 2023 to February 2024. Main Outcomes and Measures: The primary outcome was coverage loss during the renewal process, defined as a loss in Medicaid coverage from month 12 to month 13 for people who were still enrolled at the start of month 12. Secondary outcomes included coverage loss prior to the renewal deadline and the duration of the gap in Medicaid coverage among those who lost coverage during the renewal process. Results: The study sample included 684 245 Medicaid enrollment spells across 586 044 people (51% female and 47% children 18 years or younger). Among enrollees, 20% lost Medicaid coverage at the renewal deadline. Of those who lost coverage, 37% regained Medicaid coverage within 6 months, and an additional 10% regained coverage within 12 months. Children younger than 12 years and people with more Medicaid-covered health care (top quartile of Medicaid-covered health care costs during the first 6 months of enrollment) were less likely than other groups to lose coverage during the renewal process (15% and 6% lost coverage at renewal, respectively) and more likely to regain Medicaid quickly. Personal characteristics such as gender and race and ethnicity remained associated with the risk of losing Medicaid at the renewal deadline after adjustment for baseline household income, enrollment group, and past use of Medicaid services. Conclusions and Relevance: In this cohort study, the risk of coverage loss during the Medicaid renewal process was associated with age, past use of care, and other personal characteristics. These findings shed light on how renewal requirements shape access to Medicaid.

Broadening Eligibility Criteria and Diversity among Patients for Cancer Clinical Trials.

BACKGROUND: Certain populations have been historically underrepresented in clinical trials. Broadening eligibility criteria is one approach to inclusive clinical research and achieving enrollment goals. How broadened trial eligibility criteria affect the diversity of eligible participants is unknown. METHODS: Using a nationwide electronic health record-derived deidentified database, we identified a retrospective cohort of patients diagnosed with 22 cancer types between April 1, 2013 and December 31, 2022 who received systemic therapy (N=235,234) for cancer. We evaluated strict versus broadened eligibility criteria using performance status and liver, kidney, and hematologic function around first line of therapy. We performed logistic regression to estimate odds ratios for exclusion by strict criteria and their association with measures of patient diversity, including sex, age, race or ethnicity, and area-level socioeconomic status (SES); estimated the impact of broadening criteria on the number and distribution of eligible patients; and performed Cox regression to estimate hazard ratios for real-world overall survival (rwOS) comparing patients meeting strict versus broadened criteria. RESULTS: When applying common strict cutoffs for eligibility criteria to patients with complete data and weighting each cancer type equally, 48% of patients were eligible for clinical trials. Female (odds ratio, 1.30; 95% confidence interval [CI], 1.25 to 1.35), older (age 75+ vs. 18 to 49 years old: odds ratio, 3.04; 95% CI, 2.85 to 3.24), Latinx (odds ratio, 1.46; 95% CI, 1.39 to 1.54), non-Latinx Black (odds ratio, 1.11; 95% CI, 1.06 to 1.16), and lower-SES patients were more likely to be excluded using strict eligibility criteria. Broadening criteria increased the number of eligible patients by 78%, with the strongest impact for older, female, non-Latinx Black, and lower-SES patients. Patients who met only broadened criteria had worse rwOS versus those with strict criteria (hazard ratio, 1.31; 95% CI, 1.27 to 1.34). CONCLUSIONS: Data-driven evaluation of clinical trial eligibility criteria may optimize the eligibility of certain historically underrepresented groups and promote access to more inclusive trials. (Sponsored by Flatiron Health.).

The association between disability and all-cause mortality in low-income and middle-income countries: a systematic review and meta-analysis.

BACKGROUND: There are 1·3 billion people with disabilities globally. On average, they have poorer health than their non-disabled peers, but the extent of increased risk of premature mortality is unknown. We aimed to systematically review the association between disability and mortality in low-income and middle-income countries (LMICs). METHODS: We searched MEDLINE, Global Health, PsycINFO, and EMBASE from Jan 1, 1990 to Nov 14, 2022. Longitudinal epidemiological studies in any language with a comparator group that measured the association between disability and all-cause mortality in people of any age were eligible for inclusion. Two reviewers independently assessed study eligibility, extracted data, and assessed risk of bias. We used a random-effects meta-analysis to calculate the pooled hazard ratio (HR) for all-cause mortality by disability status. We then conducted meta-analyses separately for different impairment and age groups. FINDINGS: We identified 6146 unique articles, of which 70 studies (81 cohorts) were included in the systematic review, from 22 countries. There was variability in the methods used to assess and report disability and mortality. The meta-analysis included 54 studies, representing 62 cohorts (comprising 270 571 people with disabilities). Pooled HRs for all-cause mortality were 2·02 (95% CI 1·77-2·30) for people with disabilities versus those without disabilities, with high heterogeneity between studies (τ2=0·23, I2=98%). This association varied by impairment type: from 1·36 (1·17-1·57) for visual impairment to 3·95 (1·60-9·74) for multiple impairments. The association was highest for children younger than 18 years (4·46, [3·01-6·59]) and lower in people aged 15-49 years (2·45 [1·21-4·97]) and people older than 60 years (1·97 [1·65-2·36]). INTERPRETATION: People with disabilities had a two-fold higher mortality rate than people without disabilities in LMICs. Interventions are needed to improve the health of people with disabilities and reduce their higher mortality rate. FUNDING: UK National Institute for Health and Care Research; and UK Foreign, Commonwealth and Development Office.

Driver's Licensure and Driving Outcomes Among Youths With Mood Disorders.

Importance: Mood disorders are prevalent among adolescents and young adults, and their onset often coincides with driving eligibility. The understanding of how mood disorders are associated with youth driving outcomes is limited. Objective: To examine the association between the presence of a mood disorder and rates of licensing, crashes, violations, and suspensions among adolescents and young adults. Design, Setting, and Participants: This cohort study was conducted among New Jersey residents who were born 1987 to 2000, age eligible to acquire a driver's license from 2004 to 2017, and patients of the Children's Hospital of Philadelphia network within 2 years of licensure eligibility at age 17 years. The presence of a current (ie, ≤2 years of driving eligibility) mood disorder was identified using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) or International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes. Rates of licensure and driving outcomes among youths who were licensed were compared among 1879 youths with and 84 294 youths without a current mood disorder from 2004 to 2017. Data were analyzed from June 2022 to July 2023. Main Outcomes and Measures: Acquisition of a driver's license and first involvement as a driver in a police-reported crash and rates of other adverse driving outcomes were assessed. Survival analysis was used to estimate adjusted hazard ratios (aHRs) for licensing and driving outcomes. Adjusted rate ratios (aRRs) were estimated for driving outcomes 12 and 48 months after licensure. Results: Among 86 173 youths (median [IQR] age at the end of the study, 22.8 [19.7-26.5] years; 42 894 female [49.8%]), there were 1879 youths with and 84 294 youths without a mood disorder. A greater proportion of youths with mood disorders were female (1226 female [65.2%]) compared with those without mood disorders (41 668 female [49.4%]). At 48 months after licensure eligibility, 75.5% (95% CI, 73.3%-77.7%) and 83.8% (95% CI, 83.5%-84.1%) of youths with and without mood disorders, respectively, had acquired a license. Youths with mood disorders were 30% less likely to acquire a license than those without a mood disorder (aHR, 0.70 [95% CI, 0.66-0.74]). Licensed youths with mood disorders had higher overall crash rates than those without mood disorders over the first 48 months of driving (137.8 vs 104.8 crashes per 10 000 driver-months; aRR, 1.19 [95% CI, 1.08-1.31]); licensed youths with mood disorders also had higher rates of moving violations (aRR, 1.25 [95% CI, 1.13-1.38]) and license suspensions (aRR, 1.95 [95% CI, 1.53-2.49]). Conclusions and Relevance: This study found that youths with mood disorders were less likely to be licensed and had higher rates of adverse driving outcomes than youths without mood disorders. These findings suggest that opportunities may exist to enhance driving mobility in this population and elucidate the mechanisms by which mood disorders are associated with crash risk.

Automated Clinical Trial Cohort Definition and Evaluation with CQL and CDS-Hooks.

BACKGROUND: Patient recruitment for clinical trials faces major challenges with current methods being costly and often requiring time-consuming acquisition of medical histories and manual matching of potential subjects. OBJECTIVES: Designing and implementing an Electronic Health Record (EHR) and domain-independent automation architecture using Clinical Decision Support (CDS) standards that allows researchers to effortlessly enter standardized trial criteria to retrieve eligibility statistics and integration into a clinician workflow to automatically trigger evaluation without added clinician workload. METHODS: Cohort criteria are translated into the Clinical Quality Language (CQL) and integrated into Measures and CDS-Hooks for patient- and population-level evaluation. RESULTS: Successful application of simplified real-world trial criteria to Fast Healthcare Interoperability Resources (FHIR®) test data shows the feasibility of obtaining individual patient eligibility and trial details as well as population eligibility statistics and a list of qualifying patients. CONCLUSION: Employing CDS standards for automating cohort definition and evaluation shows promise in streamlining patient selection, aligning with increasing legislative demands for standardized healthcare data.

Quantitative evaluation of the impact of relaxing eligibility criteria on the risk-benefit profile of drugs for lung cancer based on real-world data.

INTRODUCTION: Restrictive eligibility criteria in cancer drug trials result in low enrollment rates and limited population diversity. Relaxed eligibility criteria (REC) based on solid evidence is becoming necessary for stakeholders worldwide. However, the absence of high-quality, favorable evidence remains a major challenge. This study presents a protocol to quantitatively evaluate the impact of relaxing eligibility criteria in common non-small cell lung cancer (NSCLC) protocols in China, on the risk-benefit profile. This involves a detailed explanation of the rationale, framework, and design of REC. METHODS: To evaluate our REC in NSCLC drug trials, we will first construct a structured, cross-dimensional real-world NSCLC database using deep learning methods. We will then establish randomized virtual cohorts and perform benefit-risk assessment using Monte Carlo simulation and propensity matching. Shapley value will be utilized to quantitatively measure the effect of the change of each eligibility criterion on patient volume, clinical efficacy and safety. DISCUSSION: This study is one of the few that focuses on the problem of overly stringent eligibility criteria cancer drug clinical trials, providing quantitative evaluation of the effect of relaxing each NSCLC eligibility criterion. This study will not only provide scientific evidence for the rational design of population inclusion in lung cancer clinical trials, but also establish a data governance system, as well as a REC evaluation framework that can be generalized to other cancer studies.

European and US Guideline-Based Statin Eligibility, Genetically Predicted Coronary Artery Disease, and the Risk of Major Coronary Events.

BACKGROUND: A study was designed to investigate whether the coronary artery disease polygenic risk score (CAD-PRS) may guide lipid-lowering treatment initiation as well as deferral in primary prevention beyond established clinical risk scores. METHODS AND RESULTS: Participants were 311 799 individuals from the UK Biobank free of atherosclerotic cardiovascular disease, diabetes, chronic kidney disease, and lipid-lowering treatment at baseline. Participants were categorized as statin indicated, statin indication unclear, or statin not indicated as defined by the European and US guidelines on statin use. For a median of 11.9 (11.2-12.6) years, 8196 major coronary events developed. CAD-PRS added to European-Systematic Coronary Risk Evaluation 2 (European-SCORE2) and US-Pooled Cohort Equation (US-PCE) identified 18% and 12% of statin-indication-unclear individuals whose risk of major coronary events were the same as or higher than the average risk of statin-indicated individuals and 16% and 12% of statin-indicated individuals whose major coronary event risks were the same as or lower than the average risk of statin-indication-unclear individuals. For major coronary and atherosclerotic cardiovascular disease events, CAD-PRS improved C-statistics greater among statin-indicated or statin-indication-unclear than statin-not-indicated individuals. For atherosclerotic cardiovascular disease events, CAD-PRS added to the European evaluation and US equation resulted in a net reclassification improvement of 13.6% (95% CI, 11.8-15.5) and 14.7% (95% CI, 13.1-16.3) among statin-indicated, 10.8% (95% CI, 9.6-12.0) and 15.3% (95% CI, 13.2-17.5) among statin-indication-unclear, and 0.9% (95% CI, 0.6-1.3) and 3.6% (95% CI, 3.0-4.2) among statin-not-indicated individuals. CONCLUSIONS: CAD-PRS may guide statin initiation as well as deferral among statin-indication-unclear or statin-indicated individuals as defined by the European and US guidelines. CAD-PRS had little clinical utility among statin-not-indicated individuals.

COVID-19 Medicaid Continuous Enrollment Provision Yielded Gains In Postpartum Continuity Of Coverage.

The Medicaid continuous enrollment provision mandated by the Families First Coronavirus Response Act of 2020 effectively prohibited the termination of enrollees from Medicaid during the COVID-19 public health emergency, including people enrolled in Medicaid during pregnancy. Using data from the Transformed Medicaid Statistical Information System, we found that the rate of continuous Medicaid enrollment during the twelve months postpartum increased from 59.3 percent for births during March-December 2018 to 90.7 percent for births during March-December 2020, when the public health emergency was in effect. This corresponds to approximately 430,000 fewer people losing Medicaid coverage after pregnancy and an average of more than 2.5 months of additional postpartum enrollment. These findings indicate that states that have extended or that plan to extend pregnancy-related Medicaid eligibility in the postpartum year are likely to experience significant gains in continuity of coverage.

Association between racial iniquities and oral health status: a systematic review. / Associação entre iniquidades raciais e condição de saúde bucal: revisão sistemática.

The present study aimed to investigate the association between racial iniquities and oral health status. This is a systematic review with a protocol registered on the Prospero Platform (CRD42021228417), with searches carried out in electronic databases and in gray literature. Our study identified 3,028 publications. After applying the eligibility criteria and risk of bias analysis, 18 studies were selected. The results indicate that individuals of black/brown race/skin color have unfavorable oral health conditions, mainly represented by self-rated oral health, tooth loss, caries, and periodontitis. The results showed racial iniquities in oral health in different countries, for all analyzed indicators, with a greater vulnerability of the black population.

O objetivo deste estudo é investigar a associação entre iniquidades raciais e condição de saúde bucal. Trata-se de revisão sistemática com protocolo cadastrado na plataforma prospero (CRD42021228417), com buscas realizadas em bases de dados eletrônicas e na literatura cinzenta. Identificou-se 3.028 publicações e após aplicação dos critérios de elegibilidade e análise do risco de vieses, 18 estudos foram selecionados. Os resultados indicam que indivíduos de raça/cor da pele preta/parda apresentam condições de saúde bucal desfavorável, representada principalmente pela autoavaliação de saúde bucal, perda dentária, cárie e periodontite. Os resultados evidenciaram iniquidades raciais em saúde bucal em diferentes países, para todos os indicadores analisados, com maior vulnerabilidade da população negra.

Predictors of COVID-19 vaccine uptake: an online three-wave survey study of US adults.

BACKGROUND: To effectively promote vaccine uptake, it is important to understand which people are most and least inclined to be vaccinated and why. In this study, we examined predictors of COVID-19 vaccine uptake and reasons for non-vaccination. METHODS: We conducted an online English-language survey study in December-2020, January-2021, and March-2021. A total of 930 US respondents completed all surveys. Multiple logistic regression models were run to test whether the early vaccine eligibility, demographic factors, and psychological factors predict getting at least one dose of a COVID-19 vaccination in January-2021 and in March-2021. RESULTS: The proportion of respondents who received ≥ 1-dose of a COVID-19 vaccine increased from 18% (January) to 67% (March). Older age predicted vaccine uptake in January (OR = 2.02[95%CI = 1.14-3.78], p < .001) and March (10.92[6.76-18.05], p < .001). In January, additional predictors were higher numeracy (1.48[1.20-1.86], p < .001), COVID-19 risk perceptions (1.35[1.03-1.78], p = .029), and believing it is important adults get the COVID-19 vaccine (1.66[1.05-2.66], p = .033). In March, additional predictors of uptake were believing it is important adults get the COVID-19 vaccine (1.63[1.15-2.34], p = .006), prior COVID-19 vaccine intentions (1.37[1.10-1.72], p = .006), and belief in science (0.84[0.72-0.99], p = .041). Concerns about side effects and the development process were the most common reasons for non-vaccination. Unvaccinated respondents with no interest in getting a COVID-19 vaccine were younger (0.27[0.09-0.77], p = .016), held negative views about COVID-19 vaccines for adults (0.15[0.08-0.26], p < .001), had lower trust in healthcare (0.59[0.36-0.95], p = .032), and preferred to watch and wait in clinically ambiguous medical situations (0.66[0.48-0.89], p = .007). CONCLUSIONS: Evidence that attitudes and intentions towards COVID-19 vaccines were important predictors of uptake provides validation for studies using these measures and reinforces the need to develop strategies for addressing safety and development concerns which remain at the forefront of vaccine hesitancy.

Health literacy in the context of child health promotion: a scoping review of conceptualizations and descriptions.

BACKGROUND: Increasing health literacy (HL) in children could be an opportunity for a more health literate future generation. The aim of this scoping review is to provide an overview of how HL is conceptualized and described in the context of health promotion in 9-12-year-old children. METHODS: A systematic and comprehensive search for 'health literacy' and 'children' and 'measure' was performed in accordance with PRISMA ScR in PubMed, Embase.com and via Ebsco in CINAHL, APA PsycInfo and ERIC. Two reviewers independently screened titles and abstracts and evaluated full-text publications regarding eligibility. Data was extracted systematically, and the extracted descriptions of HL were analyzed qualitatively using deductive analysis based on previously published HL definitions. RESULTS: The search provided 5,401 original titles, of which 26 eligible publications were included. We found a wide variation of descriptions of learning outcomes as well as competencies for HL. Most HL descriptions could be linked to commonly used definitions of HL in the literature, and some combined several HL dimensions. The descriptions varied between HL dimensions and were not always relevant to health promotion. The educational setting plays a prominent role in HL regarding health promotion. CONCLUSION: The description of HL is truly diverse and complex encompassing a wide range of topics. We recommend adopting a comprehensive and integrated approach to describe HL dimensions, particularly in the context of health promotion for children. By considering the diverse dimensions of HL and its integration within educational programs, children can learn HL skills and competencies from an early age.

Reproductive Planning: Short-Acting Reversible Contraceptives.

Short-acting reversible contraceptives (SARCs) are prescribed routinely by primary care clinicians. SARCs are among the most commonly prescribed contraceptive methods and include combined hormonal oral contraceptive pills, the combined hormonal transdermal patch, the combined hormonal vaginal ring, progestin-only pills, and the 3-month depot medroxyprogesterone acetate injection. To ensure safe prescribing and reduce barriers to receiving SARC methods, family physicians should be familiar with two evidence-based national contraceptive guidelines, the U.S. Medical Eligibility Criteria for Contraceptive Use (U.S. MEC) and the U.S. Selected Practice Recommendations for Contraceptive Use (U.S. SPR). SARCs have benefits in addition to pregnancy prevention; as such, these methods may be chosen for reasons other than contraception.

Sociotechnical feasibility of natural language processing-driven tools in clinical trial eligibility prescreening for Alzheimer's disease and related dementias.

BACKGROUND: Alzheimer's disease and related dementias (ADRD) affect over 55 million globally. Current clinical trials suffer from low recruitment rates, a challenge potentially addressable via natural language processing (NLP) technologies for researchers to effectively identify eligible clinical trial participants. OBJECTIVE: This study investigates the sociotechnical feasibility of NLP-driven tools for ADRD research prescreening and analyzes the tools' cognitive complexity's effect on usability to identify cognitive support strategies. METHODS: A randomized experiment was conducted with 60 clinical research staff using three prescreening tools (Criteria2Query, Informatics for Integrating Biology and the Bedside [i2b2], and Leaf). Cognitive task analysis was employed to analyze the usability of each tool using the Health Information Technology Usability Evaluation Scale. Data analysis involved calculating descriptive statistics, interrater agreement via intraclass correlation coefficient, cognitive complexity, and Generalized Estimating Equations models. RESULTS: Leaf scored highest for usability followed by Criteria2Query and i2b2. Cognitive complexity was found to be affected by age, computer literacy, and number of criteria, but was not significantly associated with usability. DISCUSSION: Adopting NLP for ADRD prescreening demands careful task delegation, comprehensive training, precise translation of eligibility criteria, and increased research accessibility. The study highlights the relevance of these factors in enhancing NLP-driven tools' usability and efficacy in clinical research prescreening. CONCLUSION: User-modifiable NLP-driven prescreening tools were favorably received, with system type, evaluation sequence, and user's computer literacy influencing usability more than cognitive complexity. The study emphasizes NLP's potential in improving recruitment for clinical trials, endorsing a mixed-methods approach for future system evaluation and enhancements.

Revisiting the lung cancer screening eligibility criteria to promote equity for Black individuals.

BACKGROUND: Early detection using low-dose computed tomography reduces lung-cancer-specific mortality by 20% among high-risk individuals. Blacks are less likely than Whites to meet lung cancer screening (LCS) criteria under both the former and the updated United States Preventive Services Task Force (USPSTF) guidelines. The purpose of this study was to assess racial disparities in LCS eligibility and to propose tailored eligibility criteria for Blacks to enable equitable screening rate between Whites and Blacks. METHODS: Data for this study were obtained from the Behavioral Risk Factor Surveillance System (2017-2021). 101,552 subjects were included in the final analysis. By employing a systematic approach, we sought cut-off points at which Blacks were equally likely as Whites to be eligible for LCS. We evaluated the minimum age and smoking pack-years for Blacks while we retained the 2021 USPSTF criteria for Whites. The final decision was based on the minimum Wald's Chi-square statistics. RESULTS: The model we employed identified cut-off points at which Blacks were equally likely as Whites to be eligible for LCS. Retaining the 2021 USPSTF criteria for Whites, the model discovered a new pair of points for Blacks by reducing the minimum age to 43 years and decreasing the cumulative number of cigarettes smoked to 15 pack-years. Based on these cut-off points, we created tailored criteria for Blacks. Under the tailored criteria, Blacks (OR: 1.00; 95 %CI: 0.88-1.14) had the same odds of eligibility for LCS as Whites. The odds of eligibility for LCS by sex under the tailored criteria did not differ significantly for Black men (OR: 1.02; 95 %CI: 0.85-1.24) and Black women (OR: 0.95; 95 %CI: 0.81-1.12) compared to their respective White counterparts. CONCLUSIONS: These tailored criteria for Blacks eliminate the disparities between Blacks and Whites in LCS eligibility. Future studies should test the sensitivity and specificity of these tailored criteria.

[Development of an artificial intelligence system to improve cancer clinical trial eligibility screening]. / Développement d'une solution d'intelligence artificielle pour améliorer le screening en recherche clinique.

INTRODUCTION: The recruitment step of all clinical trials is time consuming, harsh and generate extra costs. Artificial intelligence tools could improve recruitment in order to shorten inclusion phase. The objective was to assess the performance of an artificial intelligence driven tool (text mining, machine learning, classification…) for the screening and detection of patients, potentially eligible for recruitment in one of the clinical trials open at the "Institut de Cancérologie de Lorraine". METHODS: Computerized clinical data during the first medical consultation among patients managed in an anticancer center over the 2019-2023 period were used to study the performances of an artificial intelligence tool (SAS® Viya). Recall, precision and F1-score were used to determine the artificial intelligence algorithm effectiveness. Time saved on screening was determined by the difference between the time taken using the artificial intelligence-assisted method and that taken using the standard method in clinical trial participant screening. RESULTS: Out of 9876 patients included in the study, the artificial intelligence algorithm obtained the following scores: precision of 96 %, recall of 94 % and a 0.95 F1-score to detect patients with breast cancer (n=2039) and potentially eligible for inclusion in a clinical trial. The screening of 258 potentially eligible patient's files took 20s per file vs. 5min and 6s with standard method. DISCUSSION: This study suggests that artificial intelligence could yield sizable improvements over standard practices in several aspects of the patient screening process, as well as in approaches to feasibility, site selection, and trial selection.