CT-guided needle biopsy is not associated with increased ipsilateral pleural metastasis.

INTRODUCTION: Histological confirmation of a lung tumor is the prerequisite for treatment planning. It has been suspected that CT-guided needle biopsy (CTGNB) exposes the patient to a higher risk of pleural recurrence. However, the distance between tumor and pleura has largely been neglected as a possible confounder when comparing CTGNB to bronchoscopy. METHODS: All patients with lung cancer histologically confirmed by bronchoscopy or CTGNB between 2010 and 2020 were enrolled and studied. Patients' medical histories, radiologic and pathologic findings and surgical records were reviewed. Pleural recurrence was diagnosed by pleural biopsy, fluid cytology, or by CT chest imaging showing progressive pleural nodules. RESULTS: In this retrospective unicenter analysis, 844 patients underwent curative resection for early-stage lung cancer between 2010 and 2020. Median follow-up was 47.5 months (3-137). 27 patients (3.2 %) with ipsilateral pleural recurrence (IPR) were identified. The distance of the tumor to the pleura was significantly smaller in patients who underwent CTGNB. A tendency of increased risk of IPR was observed in tumors located in the lower lobe (HR: 2.18 [±0.43], p = 0.068), but only microscopic pleural invasion was a significant independent predictive factor for increased risk of IPR (HR: 5.33 [± 0.51], p = 0.001) by multivariate cox analysis. Biopsy by CTGNB did not affect IPR (HR: 1.298 [± 0.39], p = 0.504). CONCLUSION: CTGNB is safe and not associated with an increased incidence of IPR in our cohort of patients. This observation remains to be validated in a larger multicenter patient cohort.

Cost-Effectiveness of Low-Dose Computed Tomography Screenings for Lung Cancer in High-Risk Populations: A Markov Model.

Background: Domestic and foreign studies on lung cancer have been oriented to the medical efficacy of low-dose computed tomography (LDCT), but there is a lack of studies on the costs, value and cost-effectiveness of the treatment. There is a scarcity of conclusive evidence regarding the cost-effectiveness of LDCT within the specific context of Taiwan. This study is designed to address this gap by conducting a comprehensive analysis of the cost-effectiveness of LDCT and chest X-ray (CXR) as screening methods for lung cancer. Methods: Markov decision model simulation was used to estimate the cost-effectiveness of biennial screening with LDCT and CXR based on a health provider perspective. Inputs are based on probabilities, health status utility (quality-adjusted life years (QALYs)), costs of lung cancer screening, diagnosis, and treatment from the literatures, and expert opinion. A total of 1,000 simulations and five cycles of Markov bootstrapping simulations were performed to compare the incremental cost-utility ratio (ICUR) of these two screening strategies. Probability and one-way sensitivity analyses were also performed. Results: The ICUR of early lung cancer screening compared LDCT to CXR is $-24,757.65/QALYs, and 100% of the probability agree to adopt it under a willingness-to-pay (WTP) threshold of the Taiwan gross domestic product (GDP) per capita ($35,513). The one-way sensitivity analysis also showed that ICUR depends heavily on recall rate. Based on the prevalence rate of 39.7 lung cancer cases per 100,000 people in 2020, it could be estimated that LDCT screening for high-risk populations could save $17,154,115. Conclusion: LDCT can detect more early lung cancers, reduce mortality and is cost-saving than CXR in a long-term simulation of Taiwan's healthcare system. This study provides valuable insights for healthcare decision-makers and suggests analyzing cost-effectiveness for additional variables in future research.

A new communication approach to encourage lung cancer screening action in rural eligible populations.

Objective: The purpose of this study was to develop an effective communication approach to encourage lung cancer screening action within rural screening-eligible populations. Methods: An iterative research approach using targeted engagement with the priority population was used. Findings were triangulated through multiple methods, including two surveys and concept testing interviews. The Health Belief Model and the Extended Parallel Process Model served as study frameworks. Results: Initial findings suggest that threat levels are high in the priority population and an emphasis on barrier mitigation messaging may drive action. Health campaign posters integrating these findings were developed and tested with the priority population. The new health campaign posters were tested against examples of previously used health campaign posters. Findings suggest that the new health campaign posters were more effective in spurring lung cancer screening motivation and intention to act in the priority population compared to current health campaign poster examples. Conclusion: Messaging focused on gain-framing, inoculation messaging, and barrier mitigation may be more effective in encouraging lung cancer screening action in rural eligible populations. Innovation: This project outlines a systematic process to developing effective, targeted communication approaches using behavior change and persuasive communication frameworks along with engagement from priority populations.

Facing an un-met need in lung cancer screening: The never smokers.

Lung cancer (LC) is the leading cause of cancer-related deaths worldwide and the second most common cancer in both men and women. In addition to smoking, other risk factors, such as environmental tobacco smoke, air pollution, biomass combustion, radon gas, occupational exposure, lung disease, family history of cancer, geographic variability, and genetic factors, play an essential role in developing LC. Current screening guidelines and eligibility criteria have limited efficacy in identifying LC cases (50 %), as most screening programs primarily target subjects with a smoking history as the leading risk factor. Implementing LC screening programs in people who have never smoked (PNS) can significantly impact cancer-specific survival and early disease detection. However, the available evidence regarding the feasibility and effectiveness of such programs is limited. Therefore, further research on LC screening in PNS is warranted to determine the necessary techniques for accurately identifying individuals who should be included in screening programs.

Incidental Findings in Lung Cancer Screening.

While low-dose computed tomography (LDCT) for lung cancer screening (LCS) has been recognized for its effectiveness in reducing lung cancer mortality, it often simultaneously leads to the detection of incidental findings (IFs) unrelated to the primary screening indication. These IFs present diagnostic and management challenges, potentially causing unnecessary anxiety and further invasive diagnostic procedures for patients. This review article provides an overview of IFs encountered in LDCT, emphasizing their clinical significance and recommended management strategies. We categorize IFs based on their anatomical locations (intrathoracic-intrapulmonary, intrathoracic-extrapulmonary, and extrathoracic) and discuss the most common findings. We highlight the importance of utilizing guidelines and standardized reporting systems by the American College of Radiology (ACR) to guide appropriate follow-ups. For each category, we present specific IF examples, their radiologic features, and the suggested management approach. This review aims to provide radiologists and clinicians with a comprehensive understanding of IFs in LCS for accurate assessment and management, ultimately enhancing patient care. Finally, we outline a few key aspects for future research and development in managing IFs.

A tailored decision aid improves understanding of lung cancer screening in people with HIV.

BACKGROUND: People with HIV are at increased risk for lung cancer and multimorbidity, complicating the balance of risks and benefits of lung cancer screening. We previously adapted Decision Precision (screenlc.com) to guide shared decision-making for lung cancer screening in people with HIV. RESEARCH QUESTION: Does an HIV-adapted and personally tailored decision aid improve shared decision-making regarding lung cancer screening in people with HIV as measured by knowledge, decisional conflict, and acceptability? STUDY DESIGN AND METHODS: This was a single-arm pilot trial of the decision aid in 40 participants with HIV eligible for lung cancer screening. The decision aid included personalized screening recommendations and HIV-specific, five-year risk estimates of lung cancer and all-cause mortality. Participants reviewed the decision aid at shared decision-making visits and completed pre- and post-visit surveys with measures of knowledge about lung cancer screening, acceptability, and decisional conflict. RESULTS: The 40 enrolled participants were a median 62 years old and 60% were currently smoking with median five-year risks of lung cancer and all-cause mortality of 2.0% (IQR 1.4-3.3%) and 4.1% (IQR 3.3-7.9%). Personalized recommendations included "Encourage Screening" for 53% of participants and "Preference Sensitive" recommendations for the remainder. Participants showed improvement in two validated knowledge measures with relative improvement of 60% (p<0.001) on the LCS-12 and 27% (p<0.001) on the LKS-7, with significant improvement on questions regarding false-positive and false-negative findings, incidental findings, lung cancer-specific mortality benefit, and the possible harms of screening. Participants reported low scores on the decisional conflict scale (median score 0, IQR 0-5) and high acceptability. Ninety percent ultimately underwent screening within one month of the visit. INTERPRETATION: This HIV-adapted and personally tailored decision aid improved participants' knowledge of risks, benefits, and characteristics of screening with low decisional conflict and high acceptability. This decision aid can enable high-quality shared decision-making in this high-risk population.

Evaluation of an in-use chest CT protocol in lung cancer screening - A single institutional study.

Background: Lung cancer is the most common cause of cancer-related death worldwide and therefore there has been a growing demand for low-dose computed tomography (LDCT) protocols. Purpose: To investigate and evaluate the dose and image quality of patients undergoing lung cancer screening (LCS) using LDCT in Norway. Materials and Methods: Retrospective dosimetry data, volumetric CT dose index (CTDIvol) and dose-length product (DLP), from 70 average-size and 70 large-size patients who underwent LDCT scan for LCS were included in the survey. Effective dose and size-specific dose were calculated for each examination and were compared with the American Association of Physicists in Medicine (AAPM) requirement. For a quantitative image quality analysis, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were determined for different regions in the chest with two iterative reconstruction techniques, iDose and Iterative Model Reconstruction. Differences in dose and image quality between average-size and large-size patients were evaluated by Independent sample t test, and Wilcoxon signed rank test within the same patient group. Results: The independent sample t test revealed significant differences (p < .05) in dose values between average-size and large-size patients. Mean CTDIvol and DLP for average-size patients were 2.8 mGy and 115 mGy.cm, respectively, with appropriate increment for the large-size patients. Image quality (image noise, SNR, and CNR) did not significantly differ between patient groups when images were reconstructed with a model based iterative reconstruction algorithm. Conclusion: The screening protocol assessed in this study resulted in CTDIvol values that were compliant with AAPM recommendation. No significant differences in objective image quality were found between patient groups.

The pros and cons of lung cancer screening.

Several trials have shown that low-dose computed tomography-based lung cancer screening (LCS) allows a substantial reduction in lung cancer-related mortality, carrying the potential for other clinical benefits. There are, however, some uncertainties to be clarified and several aspects to be implemented to optimize advantages and minimize the potential harms of LCS. This review summarizes current evidence on LCS, discussing some of the well-established and potential benefits, including lung cancer (LC)-related mortality reduction and opportunity for smoking cessation interventions, as well as the disadvantages of LCS, such as overdiagnosis and overtreatment. CLINICAL RELEVANCE STATEMENT: Different perspectives are provided on LCS based on the updated literature. KEY POINTS: Lung cancer is a leading cancer-related cause of death and screening should reduce associated mortality. This review summarizes current evidence related to LCS. Several aspects need to be implemented to optimize benefits and minimize potential drawbacks of LCS.

Smartphone application versus written material for smoking reduction and cessation in individuals undergoing low-dose computed tomography (LDCT) screening for lung cancer: a phase II open-label randomised controlled trial.

Background: Counseling, nicotine replacement, and other cessation medications have been proven effective in smoking cessation. The wide-scale adoption of smartphones and other mobile devices has opened new possibilities for scalable and personalized smoking cessation approaches. The study investigated whether a smartphone application would be more effective than written material for smoking cessation and reduction in smoking in individuals undergoing low-dose computed tomography (LDCT) screening for lung cancer (NCT05630950). Methods: This randomized controlled trial enrolled 201 current smokers with marked smoking history (smoked ≥15 cigarettes/day for ≥25 years or smoked ≥10 cigarettes/day for ≥30 years). Participants were stratified by age and pack-years and randomized in 1:1 fashion to the developed smartphone application (experimental arm) or written material (standard of care). All the subjects underwent LDCT screening. Self-reported smoking cessation at three and six months were the primary endpoints of the study. The smoking-related secondary endpoints of the study were the percentage of individuals who had reduced the number of smoked cigarettes/d from the baseline. Findings: Between Nov 18, 2022, and Apr 14, 2023, 201 patients were screened at Oulu University Hospital, Finland, of whom all were randomly assigned to smartphone application (n = 101) or written cessation material (n = 100); 200 were included in the full analysis set. Study arms were well-balanced for all the studied demographic factors. Subjects randomized to the smartphone application arm had significantly higher rates for self-reported smoking cessation at three (19.8 versus 7.1%; OR 3.175 CI 95% 1.276-7.899) and six months (18.8 versus 7.1%; OR 2.847 CI 95% 1.137-7.128). In the experimental arm, individuals with a frequent use of the application had a higher chance for smoking cessation at three (p < 0.001) and six months (p = 0.003). Interpretation: The study showed that the developed smartphone application increases the likelihood for smoking cessation in individuals undergoing lung cancer LDCT screening. Funding: AstraZeneca, Roche, and Cancer Foundation Finland.

Characteristics of lung cancer screening eligible population in the US and prediction of the eligibility with simplified criteria.

Background: In 2021, updates to the lung cancer screening (LCS) guidelines extended the eligibility to include younger individuals and those with lower lifetime smoking intensity. A significant challenge in the LCS implementation is identifying eligible individuals because lifetime smoking intensity, a key criterion of current guidelines, is typically unavailable in electronic health records and difficult to assess accurately. This study aimed to (I) examine the characteristics of the eligible population in the US based on current guidelines and (II) evaluate the performance of five simplified criteria as alternative tools for predicting LCS eligibility. Methods: National Health and Nutrition Examination Survey (NHANES) 2013-2018 data were used. Five simplified criteria were: (I) ever smoker, defined as an individual with any positive smoking history; (II) current or former smoker, an individual with any positive smoking history or who quit smoking within 15 years; (III) current smoker, an individual currently smoking; (IV) current smoker, an individual currently smoking >0.5 packs per day (ppd); (V) current smoker, a person currently smoking >1 ppd. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated. The complex survey design was considered. Results: About 16.70 million individuals (representing 16.01% of population aged 50-80 years) were eligible for LCS in the US. The percentage of LCS eligibility was higher among people who were younger, male, non-Hispanic White, less educated, single, not insured, with poorer health status and lower socioeconomic status. Except for the criterion of current smoker with >1 ppd having low sensitivity (0.08), other criteria had sensitivity ranging between 0.45 and 1.00. The accuracy of the five criteria used ranged between 0.70 and 0.91. Conclusions: Individuals with less favorable social and clinical characteristics have higher chances of being eligible for LCS, potentially amplifying disparities in LCS utilization. Simplified criteria can be used as prescreening tools to identify target populations, which could facilitate LCS implementation at the population level.

Lung Cancer and Air Quality in a Large Urban County in the United States.

Lung cancer is the leading cancer-related killer in the United States. The incidence varies geographically and may be affected by environmental pollutants. Our goal was to determine associations within time series for specific air pollutants and lung cancer cases over a 33-year period in Wayne County, Michigan, controlling for population change. Lung cancer data for Wayne County were queried from the Michigan Cancer Registry from 1985 to 2018. Air pollutant data were obtained from the United States Environmental Protection Agency from 1980 to 2018. Autoregressive distributed lag (ARDL) models were estimated to investigate time lags in years between specific air pollution levels and lung cancer development. A total of 58,866 cases of lung cancer were identified. The mean age was 67.8 years. Females accounted for 53 percent of all cases in 2018 compared to 44 percent in 1985. Three major clusters of lung cancer incidence were detected with the most intense clusters in downtown Detroit and the heavily industrialized downriver area. Sulfur dioxide (SO2) had the strongest statistically significant relationship with lung cancer, showing both short- and long-term effects (lag range, 1-15 years). Particulate matter (PM2.5) (lag range, 1-3 years) and nitrogen dioxide (NO2) (lag range, 2-4 years) had more immediate effects on lung cancer development compared to carbon monoxide (CO) (lag range, 5-6 years), hazardous air pollutants (HAPs) (lag range, 9 years) and lead (Pb) (lag range, 10-12 years), which had more long-term effects on lung cancer development. Areas with poor air quality may benefit from targeted interventions for lung cancer screening and reductions in environmental pollution.

Navigating the Pitfalls of Lung Cancer Screening: A Case Study on the Risks and Costs of Negative Screenings.

Lung cancer is the leading cause of cancer-related deaths in the United States. Low-dose computed tomography is the preferred screening method for high-risk individuals. However, with a false-negative rate reaching 15%, this method can underestimate disease prevalence and delay necessary treatment. This case examines a 61-year-old female smoker with chronic obstructive pulmonary disease who initially received a negative result from screening. Her imaging findings were categorized as Lung Imaging Reporting and Data System (Lung-RADS) 2 but advanced to small cell lung carcinoma. This progression emphasizes the imperative of thoroughly evaluating screening results and patient history. False-negative results from screenings have profound implications, leading to delayed diagnoses, adversely affecting patient outcomes, and increasing healthcare costs. The necessity for vigilant follow-up enhanced diagnostic precision and transparent communication about limitations is paramount. An economic analysis emphasizes the significant financial impact of diagnosing lung cancer at advanced stages, highlighting the need for timely and accurate diagnostics. Comprehensive strategies, such as physician education, patient awareness, and stringent quality control, are crucial to improving the efficacy of lung cancer screening. Addressing the issue of false negatives is vital for enhancing early detection rates, decreasing healthcare expenses, and advancing patient care in lung cancer management. Continuous evaluation and adjustment of screening protocols are essential to reduce risks and optimize outcomes.

Impact of lung cancer screening on stage migration and mortality among the national Veterans Health Administration population with lung cancer.

BACKGROUND: Despite randomized trials demonstrating a mortality benefit to low-dose computed tomography screening to detect lung cancer, uptake of lung cancer screening (LCS) has been slow, and the benefits of screening remain unclear in clinical practice. METHODS: This study aimed to assess the impact of screening among patients in the Veterans Health Administration (VA) health care system diagnosed with lung cancer between 2011 and 2018. Lung cancer stage at diagnosis, lung cancer-specific survival, and overall survival between patients with cancer who did and did not receive screening before diagnosis were evaluated. We used Cox regression modeling and inverse propensity weighting analyses with lead time bias adjustment to correlate LCS exposure with patient outcomes. RESULTS: Of 57,919 individuals diagnosed with lung cancer in the VA system between 2011 and 2018, 2167 (3.9%) underwent screening before diagnosis. Patients with screening had higher rates of stage I diagnoses (52% vs. 27%; p ≤ .0001) compared to those who had no screening. Screened patients had improved 5-year overall survival rates (50.2% vs. 27.9%) and 5-year lung cancer-specific survival (59.0% vs. 29.7%) compared to unscreened patients. Among screening-eligible patients who underwent National Comprehensive Cancer Network guideline-concordant treatment, screening resulted in substantial reductions in all-cause mortality (adjusted hazard ratio [aHR], 0.79; 95% confidence interval [CI], 0.67-0.92; p = .003) and lung-specific mortality (aHR, 0.61; 95% CI, 0.50-0.74; p < .001). CONCLUSIONS: While LCS uptake remains limited, screening was associated with earlier stage diagnoses and improved survival. This large national study corroborates the value of LCS in clinical practice; efforts to widely adopt this vital intervention are needed.

Impact of OLD/Emphysema in LC Mortality Risk in Screening Programs: An Analysis of NLST and P-IELCAP.

INTRODUCTION: The impact of obstructive lung disease (OLD) and emphysema on lung cancer (LC) mortality in patients undergoing LC screening is controversial. METHODS: Patients with spirometry and LC diagnosed within the first three rounds of screening were selected from the National Lung Screening Trial (NLST) and from the Pamplona International Early Lung Cancer Detection Program (P-IELCAP). Medical and demographic data, tumor characteristics, comorbidities and presence of emphysema were collected. The effect of OLD and emphysema on the risk of overall survival was assessed using unadjusted and adjusted Cox models, competing risk regression analysis, and propensity score matching. RESULTS: Data from 353 patients with LC, including 291 with OLD and/or emphysema and 62 with neither, were analyzed. The median age was 67.3 years-old and 56.1% met OLD criteria, predominantly mild (1: 28.3%, 2: 65.2%). Emphysema was present in 69.4% of the patients. Patients with OLD and/or emphysema had worse survival on univariate analysis (HR: 1.40; 95% CI: 0.86-2.31; p=0.179). However, after adjusting for LC stage, age, and sex, the HR was 1.02 (95% CI: 0.61-1.70; p=0.952). Specific LC survival between both groups showed an adjusted HR of 0.90 (95% CI: 0.47-1.72; p=0.76). Propensity score matching found no statistically significant difference in overall survival (HR: 1.03; 95% CI: 0.59-1.9; p=0.929). CONCLUSION: The survival of LC patients diagnosed in the context of screening is not negatively impacted by the coexistence of mild OLD and/or emphysema.

Assessing the efficiency of eligibility criteria for low-dose computed tomography lung screening in China according to current guidelines.

BACKGROUND: Evidence from observational studies indicates that lung cancer screening (LCS) guidelines with high rates of lung cancer (LC) underdiagnosis, and although current screening guidelines have been updated and eligibility criteria for screening have been expanded, there are no studies comparing the efficiency of LCS guidelines in Chinese population. METHODS: Between 2005 and 2022, 31,394 asymptomatic individuals were screened using low-dose computed tomography (LDCT) at our institution. Demographic data and relevant LC risk factors were collected. The efficiency of the LCS for each guideline criteria was expressed as the efficiency ratio (ER). The inclusion rates, eligibility rates, LC detection rates, and ER based on the different eligibility criteria of the four guidelines were comparatively analyzed. The four guidelines were as follows: China guideline for the screening and early detection of lung cancer (CGSL), the National Comprehensive Cancer Network (NCCN), the United States Preventive Services Task Force (USPSTF), and International Early Lung Cancer Action Program (I-ELCAP). RESULTS: Of 31,394 participants, 298 (155 women, 143 men) were diagnosed with LC. For CGSL, NCCN, USPSTF, and I-ELCAP guidelines, the eligibility rates for guidelines were 13.92%, 6.97%, 6.81%, and 53.46%; ERe for eligibility criteria were 1.46%, 1.64%, 1.51%, and 1.13%, respectively; and for the inclusion rates, they were 19.0%, 9.5%, 9.3%, and 73.0%, respectively. LCs which met the screening criteria of CGSL, NCCN, USPSTF, and I-ELCAP guidelines were 29.2%, 16.4%, 14.8%, and 86.6%, respectively. The age and smoking criteria for CGSL were stricter, hence resulting in lower rates of LC meeting the screening criteria. The CGSL, NCCN, and USPSTF guidelines showed the highest underdiagnosis in the 45-49 age group (17.4%), while the I-ELCAP guideline displayed the highest missed diagnosis rate (3.0%) in the 35-39 age group. Males and females significantly differed in eligibility based on the criteria of the four guidelines (P < 0.001). CONCLUSIONS: The I-ELCAP guideline has the highest eligibility rate for both males and females. But its actual efficiency ratio for those deemed eligible by the guideline was the lowest. Whereas the NCCN guideline has the highest ERe value for those deemed eligible by the guideline.

Radiomics and Clinical Data for the Diagnosis of Incidental Pulmonary Nodules and Lung Cancer Screening: Radiolung Integrative Predictive Model.

INTRODUCTION: Early diagnosis of lung cancer (LC) is crucial to improve survival rates. Radiomics models hold promise for enhancing LC diagnosis. This study assesses the impact of integrating a clinical and a radiomic model based on deep learning to predict the malignancy of pulmonary nodules (PN). METHODOLOGY: Prospective cross-sectional study of 97 PNs from 93 patients. Clinical data included epidemiological risk factors and pulmonary function tests. The region of interest of each chest CT containing the PN was analysed. The radiomic model employed a pre-trained convolutional network to extract visual features. From these features, 500 with a positive standard deviation were chosen as inputs for an optimised neural network. The clinical model was estimated by a logistic regression model using clinical data. The malignancy probability from the clinical model was used as the best estimate of the pre-test probability of disease to update the malignancy probability of the radiomic model using a nomogram for Bayes' theorem. RESULTS: The radiomic model had a positive predictive value (PPV) of 86%, an accuracy of 79% and an AUC of 0.67. The clinical model identified DLCO, obstruction index and smoking status as the most consistent clinical predictors associated with outcome. Integrating the clinical features into the deep-learning radiomic model achieves a PPV of 94%, an accuracy of 76% and an AUC of 0.80. CONCLUSIONS: Incorporating clinical data into a deep-learning radiomic model improved PN malignancy assessment, boosting predictive performance. This study supports the potential of combined image-based and clinical features to improve LC diagnosis.

Tobacco quitline staffs' knowledge and attitudes about connecting quitline callers to lung cancer screening educational materials.

OBJECTIVE: To evaluate the impact of training quitline staff in lung cancer screening (LCS) on knowledge and attitudes towards connecting quitline callers to LCS educational materials. METHODS: We conducted a pre-post evaluation within a larger implementation project in the U.S. to support LCS among quitline callers. From July 2020 to June 2021, staff from four quitline service providers completed surveys before and after training on LCS knowledge. After training, staff completed the acceptability of intervention measure, intervention appropriateness measure, and feasibility of the intervention measure. RESULTS: A total of 245 staff completed the initial demographic survey (analytic sample), 130 completed the pre-training survey, and 225 completed the post-training survey. Staff were on average 47.4 years old and 76.7% were female. LCS knowledge improved after the training (n = 120, mean difference = +26.5%, 95% CI 21.6, 31.4, p < 0.001). Overall, staff felt that connecting quitline callers to LCS education materials was acceptable (M = 4.0, SD = 0.8), appropriate (M = 4.1, SD = 0.7), and feasible (M = 4.0, SD = 0.7). CONCLUSIONS: Receiving training about LCS eligibility and the benefits and harms of screening improved LCS knowledge among quitline staff. Quitline staff found that connecting callers with LCS educational materials is acceptable, appropriate, and feasible, and aligned with their primary mission.

Development of an Electronic Health Record Self-Referral Tool for Lung Cancer Screening: One-Group Posttest Study.

BACKGROUND: Approximately 14 million individuals in the United States are eligible for lung cancer screening (LCS), but only 5.8% completed screening in 2021. Given the low uptake despite the potential great health benefit of LCS, interventions aimed at increasing uptake are warranted. The use of a patient-facing electronic health record (EHR) patient portal direct messaging tool offers a new opportunity to both engage eligible patients in preventative screening and provide a unique referral pathway for tobacco treatment. OBJECTIVE: This study sought to develop and pilot an EHR patient-facing self-referral tool for an established LCS program in an academic medical center. METHODS: Guided by constructs of the Health Belief Model associated with LCS uptake (eg, knowledge and self-efficacy), formative development of an EHR-delivered engagement message, infographic, and self-referring survey was conducted. The survey submits eligible self-reported patient information to a scheduler for the LCS program. The materials were pretested using an interviewer-administered mixed methods survey captured through venue-day-time sampling in 5 network-affiliated pulmonology clinics. Materials were then integrated into the secure patient messaging feature in the EHR system. Next, a one-group posttest quality improvement pilot test was conducted. RESULTS: A total of 17 individuals presenting for lung screening shared-decision visits completed the pretest survey. More than half were newly referred for LCS (n=10, 60%), and the remaining were returning patients. When asked if they would use a self-referring tool through their EHR messaging portal, 94% (n=16) reported yes. In it, 15 participants provided oral feedback that led to refinement in the tool and infographic prior to pilot-testing. When the initial application of the tool was sent to a convenience sample of 150 random patients, 13% (n=20) opened the self-referring survey. Of the 20 who completed the pilot survey, 45% (n=9) were eligible for LCS based on self-reported smoking data. A total of 3 self-referring individuals scheduled an LCS. CONCLUSIONS: Pretest and initial application data suggest this tool is a positive stimulus to trigger the decision-making process to engage in a self-referral process to LCS among eligible patients. This self-referral tool may increase the number of patients engaging in LCS and could also be used to aid in self-referral to other preventative health screenings. This tool has implications for clinical practice. Tobacco treatment clinical services or health care systems should consider using EHR messaging for LCS self-referral. This approach may be cost-effective to improve LCS engagement and uptake. Additional referral pathways could be built into this EHR tool to not only refer patients who currently smoke to LCS but also simultaneously trigger a referral to clinical tobacco treatment.