Low-dose Computed Tomography Lung Cancer Research Articles

Risk-based lung cancer screening performance in a universal healthcare setting.

Globally, lung cancer is the leading cause of cancer death. Previous trials demonstrated that low-dose computed tomography lung cancer screening of high-risk individuals can reduce lung cancer mortality by 20% or more. Lung cancer screening has been approved by major guidelines in the United States, and over 4,000 sites offer screening. Adoption of lung screening outside the United States has, until recently, been slow. Between June 2017 and May 2019, the Ontario Lung Cancer Screening Pilot successfully recruited 7,768 individuals at high risk identified by using the PLCOm2012noRace lung cancer risk prediction model. In total, 4,451 participants were successfully screened, retained and provided with high-quality follow-up, including appropriate treatment. In the Ontario Lung Cancer Screening Pilot, the lung cancer detection rate and the proportion of early-stage cancers were 2.4% and 79.2%, respectively; serious harms were infrequent; and sensitivity to detect lung cancers was 95.3% or more. With abnormal scans defined as ones leading to diagnostic investigation, specificity was 95.5% (positive predictive value, 35.1%), and adherence to annual recall and early surveillance scans and clinical investigations were high (>85%). The Ontario Lung Cancer Screening Pilot provides insights into how a risk-based organized lung screening program can be implemented in a large, diverse, populous geographic area within a universal healthcare system.

176MO Low-dose computed tomography lung cancer screening participants live longer than matched controls: A population-based study

176MO Low-dose computed tomography lung cancer screening participants live longer than matched controls: A population-based study

Quantifying the Value of Reduced Health Disparities: Low-Dose Computed Tomography Lung Cancer Screening of High-Risk Individuals Within the United States

ObjectiveThis study aimed to measure the value of increasing lung cancer screening rates for high-risk individuals and its impact on health disparities. MethodsThe model estimated changes in health economic outcomes if low-dose computed tomography screening increased from current to 100% compliance, following clinical guidelines. Current low-dose computed tomography screening rates were estimated by income, education, and race, using 2017-2019 Behavioral Risk Factor Surveillance System data. The model contained a decision tree module to segment the population by screening outcomes and a Markov chain module to estimate cancer progression over time. Model parameters included information on survival, quality of life, and costs related to cancer diagnosis, treatment, and adverse events. Distributional cost-effectiveness analysis estimated the net monetary value from reduced health disparities—measured using quality-adjusted life expectancy—across income, education, and race groups. Outcomes were assessed over 30 years. ResultsLung cancer screening eligibility using US Preventive Services Task Force guidelines was higher for individuals with income <$15 000 (47.2%) and without a high-school education (46.1%) than individuals with income >$50 000 (16.6%) and with a college degree (13.5%), respectively. Increasing lung cancer screening to 100% compliance was cost-effective ($64 654 per quality-adjusted life-year) and produced economic value by up to $560 per person ($182.1 billion for United States overall). Up to 32.2% of the value was due to reductions in health disparities. ConclusionsSignificant value in increasing lung cancer screening rates derived from reducing health disparities. Policy makers and clinicians may not be appropriately prioritizing cancer screening if value from reducing health disparities is unconsidered.

Combining Low-Dose Computer-Tomography-Based Radiomics and Serum Metabolomics for Diagnosis of Malignant Nodules in Participants of Lung Cancer Screening Studies.

Radiomics is an emerging approach to support the diagnosis of pulmonary nodules detected via low-dose computed tomography lung cancer screening. Serum metabolome is a promising source of auxiliary biomarkers that could help enhance the precision of lung cancer diagnosis in CT-based screening. Thus, we aimed to verify whether the combination of these two techniques, which provides local/morphological and systemic/molecular features of disease at the same time, increases the performance of lung cancer classification models. The collected cohort consists of 1086 patients with radiomic and 246 patients with serum metabolomic evaluations. Different machine learning techniques, i.e., random forest and logistic regression were applied for each omics. Next, model predictions were combined with various integration methods to create a final model. The best single omics models were characterized by an AUC of 83% in radiomics and 60% in serum metabolomics. The model integration only slightly increased the performance of the combined model (AUC equal to 85%), which was not statistically significant. We concluded that radiomics itself has a good ability to discriminate lung cancer from benign lesions. However, additional research is needed to test whether its combination with other molecular assessments would further improve the diagnosis of screening-detected lung nodules.

Overcoming barriers to lung cancer screening using a systemwide approach with additional focus on the non-screened.

The lung cancer screening program at St Elizabeth Healthcare (Kentucky, USA) began in 2013. Over 33,000 low-dose computed tomography lung cancer screens have been performed. From 2015 through 2021, 2595 lung cancers were diagnosed systemwide. A Screening Program with Impactful Results from Early Detection, reviews that experience; 342 (13.2%) were diagnosed by screening and 2253 (86.8%) were non-screened. As a secondary objective, the non-screened cohort was queried to determine how many additional individuals could have been screened, identifying barriers and failures to meet eligibility. Our QlikSense database extracted the lung cancer patients from the Cancer Patient Data and Management System, and identified and categorized them separately as screened or non-screened populations. Stage distribution was compared in screened and non-screened groups. Those meeting age criteria, with any smoking history, were further queried for screening eligibility, accessing the electronic medical record smoking history and audit trail, and determining if enough information was available to substantiate screening eligibility. The same methodology was applied to CMS 2015 and USPSTF 2021 criteria. The screened and non-screened patients were accounted for in a stage migration chart demonstrating clear shift to early stage among screened lung cancer patients. Additionally, analysis of non-screened individuals is presented. Of the St Elizabeth Healthcare eligible patients attributed to primary care providers, 49.6% were screened in 2021. Despite this level of success, this study highlighted a sizeable pool of additional individuals that could have been screened. We are shifting focus to the non-screened pool of patients that meet eligibility, further enhancing the impact on our community.

Short-Term Outcomes of COVID-19 Pandemic on Non-Small Cell Lung Cancer Screening and Management.

Background To assess the impact of coronavirus disease 2019 (COVID-19) pandemic on non-small cell lung cancer (NSCLC) screening, staging, and management in a single health care system. Materials and Methods From November 2015 to December 2020, a total of 1,547 NSCLC cases was reported at our institution including 1,329 cases pre-COVID-19 and 218 cases during COVID-19. Pre-COVID-19 was defined as November 2015 to February 2020, while during COVID-19 was March 2020 to December 2020. Data were collected from tumor registry and medical record review. Patients with mesothelioma, lymphoma, small cell, or mixed small cell cancer were excluded from the study. Results Both pre-COVID-19 and during COVID-19 cohorts had similar comorbidities including age (70 vs. 71 years), current smokers (35 vs. 32%), and chronic obstructive lung disease (32 vs. 28%). The number of low-dose computed tomography lung cancer screening scans decreased by 25% during COVID-19 compared with pre-COVID-19 era. There were more cases of stage 1A NSCLC pre-COVID-19 (31 vs. 25%) and more stage 4 cancer during COVID-19 (42 vs. 33%); p = 0.01. The proportion of patients treated with radiotherapy was similar between pre-COVID-19 and during COVID-19 (49 vs. 50%), but fewer patients underwent surgery during COVID-19 (17 vs. 27%; p = 0.004). The median time to radiotherapy (67 days) and surgery (29 days) was similar between the groups. The unadjusted overall 6-month mortality after lung cancer diagnoses was higher during COVID-19 compared with pre-COVID-19 (28 vs. 22%; p = 0.04). Conclusion The COVID-19 pandemic resulted in delayed lung cancer screening scans, and more patients had diagnosis of advanced NSCLC; however, short-term mortality was unchanged.

Integrating Smoking Cessation Into Low-Dose Computed Tomography Lung Cancer Screening: Results of the Ontario, Canada Pilot

IntroductionLow-dose computed tomography screening in high-risk individuals reduces lung cancer mortality. To inform the implementation of a provincial lung cancer screening program, Ontario Health undertook a Pilot study, which integrated smoking cessation (SC). MethodsThe impact of integrating SC into the Pilot was assessed by the following: rate of acceptance of a SC referral; proportion of individuals who were currently smoking cigarettes and attended a SC session; the quit rate at 1 year; change in the number of quit attempts; change in Heaviness of Smoking Index; and relapse rate in those who previously smoked. ResultsA total of 7768 individuals were recruited predominantly through primary care physician referral. Of these, 4463 were currently smoking and were risk assessed and referred to SC services, irrespective of screening eligibility: 3114 (69.8%) accepted referral to an in-hospital SC program, 431 (9.7%) to telephone quit lines, and 50 (1.1%) to other programs. In addition, 4.4% reported no intention to quit and 8.5% were not interested in participating in a SC program. Of the 3063 screen-eligible individuals who were smoking at baseline low-dose computed tomography scan, 2736 (89.3%) attended in-hospital SC counseling. The quit rate at 1 year was 15.5% (95% confidence interval: 13.4%–17.7%; range: 10.5%–20.0%). Improvements were also observed in Heaviness of Smoking Index (p < 0.0001), number of cigarettes smoked per day (p < 0.0001), time to first cigarette (p < 0.0001), and number of quit attempts (p < 0.001). Of those who reported having quit within the previous 6 months, 6.3% had resumed smoking at 1 year. Furthermore, 92.7% of the respondents reported satisfaction with the hospital-based SC program. ConclusionsOn the basis of these observations, the Ontario Lung Screening Program continues to recruit through primary care providers, to assess risk for eligibility using trained navigators, and to use an opt-out approach to referral for cessation services. In addition, initial in-hospital SC support and intensive follow-on cessation interventions will be provided to the extent possible.

Accuracy of baseline low-dose computed tomography lung cancer screening: a systematic review and meta-analysis.

Screening using low-dose computed tomography (LDCT) is a more effective approach and has the potential to detect lung cancer more accurately. We aimed to conduct a meta-analysis to estimate the accuracy of population-based screening studies primarily assessing baseline LDCT screening for lung cancer. MEDLINE, Excerpta Medica Database, and Web of Science were searched for articles published up to April 10, 2022. According to the inclusion and exclusion criteria, the data of true positives, false-positives, false negatives, and true negatives in the screening test were extracted. Quality Assessment of Diagnostic Accuracy Studies-2 was used to evaluate the quality of the literature. A bivariate random effects model was used to estimate pooled sensitivity and specificity. The area under the curve (AUC) was calculated by using hierarchical summary receiver-operating characteristics analysis. Heterogeneity between studies was measured using the Higgins I2 statistic, and publication bias was evaluated using a Deeks' funnel plot and linear regression test. A total of 49 studies with 157,762 individuals were identified for the final qualitative synthesis; most of them were from Europe and America (38 studies), ten were from Asia, and one was from Oceania. The recruitment period was 1992 to 2018, and most of the subjects were 40 to 75 years old. The analysis showed that the AUC of lung cancer screening by LDCT was 0.98 (95% CI: 0.96-0.99), and the overall sensitivity and specificity were 0.97 (95% CI: 0.94-0.98) and 0.87 (95% CI: 0.82-0.91), respectively. The funnel plot and test results showed that there was no significant publication bias among the included studies. Baseline LDCT has high sensitivity and specificity as a screening technique for lung cancer. However, long-term follow-up of the whole study population (including those with a negative baseline screening result) should be performed to enhance the accuracy of LDCT screening.

Assessment of the EarlyCDT-Lung test as an early biomarker of lung cancer in ever-smokers: A retrospective nested case-control study in two prospective cohorts.

The EarlyCDT-Lung test is a blood-based autoantibody assay intended to identify high-risk individuals for low-dose computed tomography lung cancer screening. However, there is a paucity of evidence on the performance of the EarlyCDT-Lung test in ever-smokers. We conducted a nested case-control study within two prospective cohorts to evaluate the risk-discriminatory performance of the EarlyCDT-Lung test using prediagnostic blood samples from 154 future lung cancer cases and 154 matched controls. Cases were selected from those who had ever smoked and had a prediagnostic blood sample <3 years prior to diagnosis. Conditional logistic regression was used to estimate the association between EarlyCDT-Lung test results and lung cancer risk. Sensitivity and specificity of the EarlyCDT-Lung test were calculated in all subjects and subgroups based on age, smoking history, lung cancer stage, sample collection time before diagnosis and year of sample collection. The overall lung cancer odds ratios were 0.89 (95% CI: 0.34-2.30) for a moderate risk EarlyCDT-Lung test result and 1.09 (95% CI: 0.48-2.47) for a high-risk test result compared to no significant test result. The overall sensitivity was 8.4% (95% CI: 4.6-14) and overall specificity was 92% (95% CI: 87-96) when considering a high-risk result as positive. Stratified analysis indicated higher sensitivity (17%, 95% CI: 7.2-32.1) in subjects with blood drawn up to 1year prior to diagnosis. In conclusion, our study does not support a role of the EarlyCDT-Lung test in identifying the high-risk subjects in ever-smokers for lung cancer screening in the EPIC and NSHDS cohorts.

Barriers and facilitators for low-dose computed tomography lung cancer screening in rural populations in the United States: a scoping review protocol.

The objective of this scoping review is to identify barriers and facilitators for low-dose computed tomography lung cancer screening uptake and adherence among rural populations in the United States. Lung cancer is the leading cause of cancer-related death in the United States, and cancer patients from rural areas have poorer outcomes than those from metropolitan areas. Evidence exists that lung cancer screening by low-dose computed tomography significantly increases survival time but is also significantly underutilized. Studies completed in the United States with adults who fit United States Preventive Services Task Force guidelines for lung cancer screening and who live in rural areas will be included. Studies published in English since 2013 that report on barriers and facilitators for low-dose computed tomography lung cancer screening uptake and adherence will be included in this review. Quantitative, qualitative, or mixed-methods studies will be included, along with opinion pieces published by government agencies or professional cancer-related organizations. The search strategy will locate published primary studies, reviews, and opinion papers, including those by government and nonprofit agencies focused on cancer. The databases to be searched include MEDLINE, CINAHL Complete, Embase, Web of Science, and Cochrane Library. Gray literature databases and sources of unpublished studies will also be searched. Independent reviewers will be used throughout the search and selection process.

Emotions and lung cancer screening: Prioritising a humanistic approach to care.

Low-dose computed tomography lung cancer screening has mortality benefits. Yet, uptake has been low. To inform strategies to better deliver and promote screening, in 2018, we interviewed 27 long-term smokers immediately following lung cancer screening in Australia, prior to receiving scan results. Existing lung screening studies employ the Health Belief Model. Reflecting growing acknowledgement of the centrality of emotions to screening uptake, we draw on psychological and sociological theories on emotions to thematically and abductively analyse the emotional dimensions of lung cancer screening, with implications for screening promotion and delivery. As smokers, interviewees described feeling stigmatised, with female participants internalising and male participants resisting stigma. Guilt and fear related to lung cancer were described as screening motivators. The screening itself elicited mild positive emotions. Notably, interviewees expressed gratitude for the care implicitly shown through lung screening to smokers. More than individual risk assessment, findings suggest lung screening campaigns should prioritise emotions. Peer workers have been found to increase cancer screening uptake in marginalised communities, however the risk to confidentiality-especially for female smokers-limits its feasibility in lung cancer screening. Instead, we suggest involving peer consultants in developing targeted screening strategies that foreground emotions. Furthermore, findings suggest prioritising humanistic care in lung screening delivery. Such an approach may be especially important for smokers from low socioeconomic backgrounds, who perceive lung cancer screening and smoking as sources of stigma and face a higher risk of dying from lung cancer and lower engagement with screening.

Development and application of an electronic synoptic report for reporting and management of low-dose computed tomography lung cancer screening examination

BackgroundInterpretation of Low Dose CT scans and protocol driven management of findings is a key aspect of lung cancer screening program performance. Reliable and reproducible methods are needed to communicate radiologists’ interpretation to the screening program or clinicians driving management decision.MethodsWe performed an audit of a subset of dictated reports from the PANCAN study to assess for omissions. We developed an electronic synoptic reporting tool for radiologists embedded in a clinical documentation system software. The tool was then used for reporting as part of the Alberta Lung Cancer Screening Study and McGill University Health Centre Pilot Lung Cancer Screening Program.ResultsFifty reports were audited for completeness. At least one omission was noted in 30 (70%) of reports, with a major omission (missing lobe, size, type of nodule in report or actionable incidental finding in recommendation section of report) in 24 (48%). Details of the reporting template and functionality such as automated nodule cancer risk assessment, Lung-RADS category assignment, auto-generated narrative type report as well as personalize participant results letter is provided. A description of the system’s performance in its application in 2815 CT reports is then summarized.ConclusionsWe found that narrative type radiologist reports for lung cancer screening CT examinations frequently lacked specific discrete data elements required for management. We demonstrate the successful implementation of a radiology synoptic reporting system for use in lung cancer screening, and the use of this information to drive program management and communications.

Swiss pilot low-dose computed tomography lung cancer screening study

Abstract Objective Low-dose computed tomography (LDCT) lung cancer screening is endorsed by US guidelines and has recently been shown effective in a large European randomized controlled trial. Nevertheless, actual realization of a lung cancer screening program is challenging and depends on country-specific factors. This pilot study aimed to evaluate implementation, execution, and performance of LDCT lung cancer screening in Switzerland. Methods Since October 2018, asymptomatic participants aged 55–74 years with more than 30 pack-years smoking history were enrolled at a tertiary hospital in Switzerland. Participants with history of lung cancer, major (palliative) health problems or those that had a thorax CT scan 18 months prior to enrollment were excluded. First, we evaluated lung cancer risk according to NLST guidelines. Second, we estimated lung cancer risk using the PLCOm2012 model risk calculator with threshold of 5%. Lung nodules were assessed according to Lung-RADS (Version 1.1. 2019). Participants were recruited through flyers, a newspaper article and pulmonary specialists. Screening consisted of one LDCT-scan, follow-up was recommended for suspicious nodules only. LDCT assessment was performed by two radiologists, one of them a board certified chest radiologist. Enrollment and follow-up are currently ongoing. Results To date, 75 participants (25 (33%) females) with a median age of 62 years (interquartile range [IQR] 56–67 years) were included. Median number of pack years smoked was 49 (IQR 41–58 pack years). Median PLCOm2012 6-year lung cancer probability was 2.7% (IQR 2.6–2.9%), 19 (26%) participants had stopped smoking before enrollment. 6 participants required follow up imaging of suspect nodules, resulting in a recall rate of 8%. At baseline, lung cancer was found in 2 (2.7%, one squamous cell (stage IIIA) and one adenocarcinoma (stage IV)) participants. Conclusion In this Swiss LDCT lung cancer screening pilot study using modified inclusion criteria, 2.7% were diagnosed with lung cancer to date.

Race & sex disparities related to low-dose computed tomography lung cancer screening eligibility criteria: A lung cancer cases review

IntroductionThe United States Preventive Services Task Force (USPSTF) recommendations do not account for race and sex differences in lung cancer risk. We compared the sensitivity for finding lung cancer cases eligible for lung cancer screening (LCS) by USPSTF 2013 recommendations versus the PLCOm2012 model at an equivalent threshold. MethodsUsing Georgetown University Hospital tumor registry, we identified lung cancer cases (≥55 years old) between 2014 and 2018. Medical chart review collected age, sex, race, education, smoking, and clinical characteristics. We compared the percentage meeting eligibility criteria overall, and by race and sex. ResultsThe cases (N = 447) were 36.6% Black and 52.6% female. The PLCOm2012 and USPSTF 2013 criteria identified 71.4% and 45.6% of cases, respectively (p < 0.0001). This difference was consistent across race and sex sub-groups (p < 0.0001). The PLCOm2012 was more sensitive than the USPSTF in Blacks (69.9% vs. 46.6%, p < 0.0001) and in women (69.8% vs. 41.3%, p < 0.0001). The USPSTF had poor sensitivity for both race groups (Black 46.6%, White 45.9%, p = 0.886) and had lower sensitivity in women vs. men (41.3% vs. 51.4%, p = 0.032). The PLCOm2012 had higher sensitivities in women and men, and difference between sexes was not significant (69.8% vs. 72.6%, p = 0.506). ConclusionsCompared to the USPSTF 2013 recommendations, the PLCOm2012 model selected a larger proportion of lung cancer cases in all race-sex strata and removed the sex disparity observed for the USPSTF. The PLCOm2012 risk model could be used to identify those who will benefit from LCS.

Implementation of a Web-Based Tool for Shared Decision-making in Lung Cancer Screening: Mixed Methods Quality Improvement Evaluation.

BackgroundLung cancer risk and life expectancy vary substantially across patients eligible for low-dose computed tomography lung cancer screening (LCS), which has important consequences for optimizing LCS decisions for different patients. To account for this heterogeneity during decision-making, web-based decision support tools are needed to enable quick calculations and streamline the process of obtaining individualized information that more accurately informs patient-clinician LCS discussions. We created DecisionPrecision, a clinician-facing web-based decision support tool, to help tailor the LCS discussion to a patient’s individualized lung cancer risk and estimated net benefit.ObjectiveThe objective of our study is to test two strategies for implementing DecisionPrecision in primary care at eight Veterans Affairs medical centers: a quality improvement (QI) training approach and academic detailing (AD).MethodsPhase 1 comprised a multisite, cluster randomized trial comparing the effectiveness of standard implementation (adding a link to DecisionPrecision in the electronic health record vs standard implementation plus the Learn, Engage, Act, and Process [LEAP] QI training program). The primary outcome measure was the use of DecisionPrecision at each site before versus after LEAP QI training. The second phase of the study examined the potential effectiveness of AD as an implementation strategy for DecisionPrecision at all 8 medical centers. Outcomes were assessed by comparing absolute tool use before and after AD visits and conducting semistructured interviews with a subset of primary care physicians (PCPs) following the AD visits.ResultsPhase 1 findings showed that sites that participated in the LEAP QI training program used DecisionPrecision significantly more often than the standard implementation sites (tool used 190.3, SD 174.8 times on average over 6 months at LEAP sites vs 3.5 SD 3.7 at standard sites; P<.001). However, this finding was confounded by the lack of screening coordinators at standard implementation sites. In phase 2, there was no difference in the 6-month tool use between before and after AD (95% CI −5.06 to 6.40; P=.82). Follow-up interviews with PCPs indicated that the AD strategy increased provider awareness and appreciation for the benefits of the tool. However, other priorities and limited time prevented PCPs from using them during routine clinical visits.ConclusionsThe phase 1 findings did not provide conclusive evidence of the benefit of a QI training approach for implementing a decision support tool for LCS among PCPs. In addition, phase 2 findings showed that our light-touch, single-visit AD strategy did not increase tool use. To enable tool use by PCPs, prediction-based tools must be fully automated and integrated into electronic health records, thereby helping providers personalize LCS discussions among their many competing demands. PCPs also need more time to engage in shared decision-making discussions with their patients.Trial RegistrationClinicalTrials.gov NCT02765412; https://clinicaltrials.gov/ct2/show/NCT02765412

Cancer Screening Practices Among Healthcare Workers During the COVID-19 Pandemic.

The COVID-19 pandemic has the potential to impact long-standing efforts to increase adherence to cancer screening guidelines. Healthcare workers (HCWs) experienced significant hardship, but generally have greater access to preventive services, making them a particularly relevant population in which to understand cancer screening behaviors during the pandemic. We report data from 794 HCWs enrolled in the NCI-funded Serological Sciences Network for Coronavirus Associations and Longitudinal Evaluation Study from December 2020 to April 2021. Participants reported lifestyle and screening behaviors during relevant look-back periods which included the pandemic timeframe. Among women between the ages of 40 and 74, 25.7% were overdue for mammographic breast cancer screening. Among participants 50–75 years old, 38.9% were overdue for colorectal cancer screening. The proportion over-due varied according to race/ethnicity. Lifetime low-dose computed tomography lung cancer screening among HCWs age 50–80 years who were smokers was 10.9%. Strategies to address screening disruptions are needed to minimize the impact of later stage of diagnosis.

Abstract PO-268: Investigating patient barriers to low-dose computed tomography lung cancer screenings among the African American population

Abstract Background Lung cancer remains the leading cause of cancer death in the United States. Lung cancer screening (LCS) with Low-Dose Computerized Tomography (LDCT) has been found to reduce lung cancer mortality up to 26% and all-cause mortality by 7%. Yet, uptake of LCS is less than 4% among those eligible. African Americans (AAs) have the highest cancer mortality rate and are also more likely to die of lung cancer compared to whites. Furthermore, little research has been done to understand this groups in terms of their knowledge, awareness, and perceptions related to LCS, and the potential barriers or facilitators to LCS. Guided by the Health Believe Models, this study aims to examine the demographic, behavioral, and psychosocial profiles related to LCS in AAs, and identify the predictors to the uptake of LCS with LDCT. Methods We have recruited 200 AA patients eligible for LDCT for a case-control cohort (100 AAs who have completed a LDCT screening and 100 who did not) through the electric medical record of a safety-net hospital. We are currently conducting online and telephone surveys to collect information on participants' personal and family history, health literacy, beliefs, psychosocial factors, patient-provider relationship, knowledge of lung cancer, perception of screening and potential care cost, transportation barriers, and racial discrimination. Results We will conduct descriptive analysis of the sociodemographic characteristics and the modifiable lifestyle behaviors of the participants separately for those who completed LDCT and those who did not. We will then conduct bivariate analysis (chi-square and t-test) to compare various psychosocial and health-related factors by LDCT completion status. Finally, we will conduct binary logistic regression to examine the association between the predictors and LDCT completion. Conclusion The findings of this study will provide critical empirical evidence on the psychosocial facilitators and barriers to LDCT uptake among AAs, a vulnerable and medically underserved population. The facilitators and barriers identified in this study will be used to design both clinic-based and community-based behavioral intervention studies to promote LDCT uptake among eligible AAs. Citation Format: Alexander Nguyen, Lin Zhu, Ra'Ann Merceir, Grace X Ma, Cherie P Erkmen. Investigating patient barriers to low-dose computed tomography lung cancer screenings among the African American population [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-268.

Comparison of National Comprehensive Cancer Network and European Position Statement protocols for nodule management in low-dose computed tomography lung cancer screening in a general Chinese population.

BackgroundLow-dose computed tomography (LDCT) lung cancer screening often refers individuals to unnecessary examinations. This study aims to compare the European Position Statement (EUPS) and National Comprehensive Cancer Network (NCCN) protocols in management of participants at baseline screening round.MethodsLDCT lung cancer screening was prospectively performed in a Chinese asymptomatic population aged 40–74 years. A total of 1,000 consecutive baseline LDCT scans were read twice independently. All screen-detected lung nodules by the first reader were included. The first reader manually measured the diameter of lung nodules (NCCN protocol), and the second reader semi-automatically measured the volume and diameter (EUPS volume and diameter protocols). The protocols were used to classify the participants into three management groups: next screening round, short-term repeat LDCT scan and referral to a pulmonologist. Groups were compared using Wilcoxon test for paired samples. Number of lung cancers by protocols was provided.ResultsOf the 1,000 participants (61.4±6.7 years old), 168 lung nodules in 124 participants were visually detected and manually measured in the first reading, and re-measured semi-automatically. Applying the NCCN protocol, EUPS volume and diameter protocol, the proportion of referrals among all participants was 0.6%, 1.9%, and 1.4%, respectively. The proportion of short-term repeat scans was 4.5%, 9.7% and 4.5%, respectively. Among the 10 lung cancer patients, one would have been diagnosed earlier if the EUPS volume protocol would have been followed.ConclusionsIn a first round screening in a Chinese general population, the lower threshold for referral in the EUPS protocol as compared to the NCCN protocol, leads to more referrals to a pulmonologist, with the potential of earlier cancer diagnosis. The EUPS volume protocol recommends fewer participants to short-term repeat LDCT scan than the EUPS diameter protocol. Follow-up studies should show the impact of both protocols on (interval) cancer diagnosis.

P61.10 Swiss Pilot Low-Dose Computed Tomography Lung Cancer Screening Study

Low-dose computed tomography (LDCT) lung cancer screening is endorsed by United States guidelines and has recently been shown effective in a large European randomized controlled trial. Nevertheless, the actual realization of a lung cancer screening program is challenging and depends on country-specific factors. This pilot study aimed to evaluate implementation, execution and performance of LDCT lung cancer screening in Switzerland. Starting from October 2018, asymptomatic participants aged 55-74 years with more than 30 pack-years smoking history were enrolled at a tertiary hospital in Switzerland. Participants with history of lung cancer, major (palliative) health problems or those that had a thorax CT scan 18 months prior to enrollment were excluded. First line we evaluated lung cancer risk according NLST guidelines. Secondly, we estimated lung cancer risk using the PLCOm2012 model risk calculater with a threshold of 5%. Lung nodules were assessed according Lung-RADS 1.1 {ACoR. Lung-Screening Reporting and Data System (LungRADS) Version 1.1. 2019}. Participants were predominantly recruited through flyers, a newspaper article and pulmonary specialists. Screening consisted of one LDCT-scan and follow-up was recommended for suspicious nodules only. LDCT assessment was performed by two radiologists, one of them a board certified chest radiologist. Enrollment and follow-up are currently ongoing. To date, 75 participants with a median age of 62 years (interquartile range [IQR] 56-67 years) were included. The median number of pack years smoked was 49 (IQR 41-58 pack years) and 25 (33%) were female. The median PLCOm2012 6-year lung cancer probability was 2.7% (IQR 2.6-2.9%) and 19 (26%) participants had stopped smoking before enrollment. Of the 75 participants, 61 (81%) were found to have calcified or non-calcified lung nodules. 6 participants required follow up imaging of suspect nodules which resulted in a recall rate of 8%. At baseline, lung cancer was found in 2 (2.7%) participants. The lung cancers were one squamous cell carcinoma (stage IIIA) and one adenocarcinoma (stage IV). In this Swiss LDCT lung cancer screening pilot study using modified inclusion criteria, lung nodules were found in a significant number of participants of whom 2.7 % were diagnosed with lung cancer to date. To date, the recall rate for follow-up imaging is 8%.

OA19.01 Prospective Study of Lung Cancer Screening Criteria: USPSTF2013 vs PLCOm2012 – International Lung Screening Trial (ILST) Results

Low-dose computed tomography lung cancer screening has been demonstrated to substantially reduce lung cancer mortality. Lung cancer screening is most effective when applied to high-risk individuals. One approach to determining eligibility is based on categorical age/pack-years/quit-years, which has been exemplified by the United States Preventive Services Task Force (USPSTF2013) eligibility criteria: age 55-80 years, ≥30 pack-years smoked, and in former smokers quit ≤15 years. Many comparative studies have found that determining screening eligibility using a validated risk prediction model, such as the PLCOm2012, is more effective.