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David Yankelevitz
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ES08 - Critical Concerns in Screening (ID 11)
- Event: WCLC 2019
- Type: Educational Session
- Track: Screening and Early Detection
- Presentations: 1
- Now Available
- Moderators:Ugo Pastorino, John Kirkpatrick Field
- Coordinates: 9/08/2019, 13:30 - 15:00, Copenhagen (1980)
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ES08.04 - Management Algorithms (Now Available) (ID 3194)
13:30 - 15:00 | Author(s): David Yankelevitz
- Abstract
- Presentation
Abstract
Introduction
Clinical management decisions arising from the first, baseline round of screening for lung cancer are most challenging, as nodules that are seen for the first time may have accumulated over a lifetime and almost all of them are of no clinical concern [1]. In contrast, new or changing findings on subsequent annual repeat low-dose CT scans (LDCTs) have much greater clinical significance.
Efficiency is particularly important in the baseline round in order to minimize unnecessary harms caused by work-up within the 12 months after the baseline LDCT. Potential workup includes surgery, biopsies, and diagnostic tests requiring intravenous injection (e.g., PET scans, contrast CT). Biopsies and surgery have greater risks than LDCT, and thus the management protocols should aim to minimize these higher risk procedures as much as possible [2]. It is also important not to discourage participants undergoing the baseline round from future participation in annual rounds as these provide the real benefit of annual LDCT screening.
Methods
We compared the efficiency of three published baseline LDCT screening protocols [2], the International Early Lung Cancer Action Program (I-ELCAP) [3], American College of Radiology (ACR)-LungRADS [4], and the European Consortium protocols [5] for participants 50 years of age or older with at least 20 pack-years of smoking.
The three protocols provide recommendations for immediate workup, 3-month and 6-month LDCT as shown in Table 1 [1]. The three protocols use the diameter of the entire solid and nonsolid non-calcified nodule (NCN), but differ for part-solid NCNs. For part-solid NCNs, I-ELCAP uses the diameter of the solid component [6], while ACR-LungRADS uses both the entire diameter of the part-solid NCN as well as the diameter of its solid component. The European Consortium protocol determines the volume of a solid NCN using their software [5], but also specifies the equivalent diameter values for the entire part-solid and nonsolid NCNs as volumetric measurements for these are problematic as was recognized [5]. Measurement error and rounding of measurements are also an important consideration [7,8].
Efficiency was defined as an efficiency ratio (ER): the number of participants recommended for a particular workup divided by the resulting number of participants diagnosed with lung cancer [2]. An ER of 1 would mean that each recommended workup resulted in a diagnosis of lung cancer. An optimum ER has not been established for lung cancer, but it has been suggested that for lung surgery, a rate of 10% for non-malignant resections is desirable (9), this would be an ER of 1.1. In breast cancer biopsies which have a much lower risk than lung biopsies, it is recommended that 40% of biopsies should be negative to ensure sufficient workup to diagnose breast cancers early enough this would represent an ER of 1.4
Results
Table 1 provides the frequency of following the recommendations, the number of cancers diagnosed and the ER for each protocol. In summary, I-ELCAP recommendations had the lowest ER values for overall, immediate and delayed workup, and for potential biopsies.
Discussion
All three protocols used LDCT to guide evaluation of NCNs, particularly for the smaller NCNs. LDCT is a very low risk test as it requires no injection of contrast, the radiation dose is deemed “small” and “hypothetical” by the American Association of Physicists in Medicine [10], and the charge for a LDCT is 10-20 times lower than for a PET scan. This underscores the recognition that LDCT is a very useful tool for identifying growth at a malignant rate prior to further invasive testing.
The main point is that the definition of a “positive result” needs to be continually reevaluated and updated in light of emerging technology and evidence from ongoing screening programs with the goal of reducing unnecessary invasive procedures for non-malignant pulmonary NCNs, which will markedly reduce the concerns about potential harms and increase the benefit by early diagnosis and treatment of small, early curable lung cancers.
References
1. Henschke CI, Salvatore M, Cham M, Powell CA, DiFabrizio L, Flores R, et al. Baseline and annual repeat rounds of screening: implications for optimal regimens of screening. Eur Radiol. 2018; 28:1085-1094.
2. Henschke CI, Yip R, Ma T, Aguayo SM, Zulueta J, Yankelevitz DF, for the I-ELCAP Investigators. CT screening for lung cancer: comparison of three baseline screening protocols. Eur Radiol 2018; 29:3321-3322.
3. International Early Lung Cancer Action Program protocol. (2016) www.IELCAP.org/sites/default/files/I-ELCAP-protocol.pdf Accessed June 27, 2019
4. American College of Radiology (ACR). Lung CT screening reporting & data system (Lung-RADS Version 1.0). https://www.acr.org/Quality-Safety/Resources/LungRADS
5. Oudkerk M, Devaraj A, Vliegenthart R, Henzler T, Prosch H, Heussel CP, et al. European position statement on lung cancer screening. Lancet Oncology 2017; 18: e754-e766.
6. Henschke CI, Yip R, Wolf A, Flores R, Liang M, Salvatore M, et al. CT screening for lung cancer: part-solid nodules in baseline and annual repeat rounds. AJR Am J Roentgenol 2016; 11:1-9.
7. Radiologic Society of North America Quantitative Imaging Biomarkers Alliance (QIBA) Calculator. (2017) http://accumetra.com/solutions/qiba-lung-nodule-calculator. Accessed May 1, 2018.
8. Li K, Yip R, Avila R, Henschke CI, Yankelevitz DF. Size and growth assessment of pulmonary nodules: consequence of the rounding. J Thorac Oncol 2016; 12: 657-62.
9. Flores R, Bauer T, Aye R, et al. Balancing curability and unnecessary surgery in the context of computed tomography screening for lung cancer. J Thorac Cardiovasc Surg. 2014; 147:1619-26.
10. American Association of Physicists in Medicine. AAPM Position Statement on Radiation Risks from Medical Imaging Procedures. https://www.aapm.org/org/policies/details.asp?id=406&type=PP Accessed June 27, 2019
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MS10 - Lung Cancer Screening, Opportunistic Evaluation of Findings (ID 73)
- Event: WCLC 2019
- Type: Mini Symposium
- Track: Screening and Early Detection
- Presentations: 1
- Now Available
- Moderators:Dorith Shaham, Eduard Monsó
- Coordinates: 9/09/2019, 15:45 - 17:15, Copenhagen (1980)
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MS10.03 - Aortic Valve Calcifications (Now Available) (ID 3494)
15:45 - 17:15 | Author(s): David Yankelevitz
- Abstract
- Presentation
Abstract
INTRODUTION: Smoking is a major risk factor for both cardiovascular disease and lung cancer. Low-dose computed tomography (LDCT) screening for lung cancer provides an opportunity to identify both diseases in asymptomatic smokers (1). The extent of aortic valve calcification (AVC) is the predominant driver of degenerative aortic valve stenosis (AS) (2), which is an underdiagnosed and undertreated disease. Cardiovascular morbidity and mortality is higher for people with moderate/severe AVC as compared to those with none or mild AVC as demonstrated on echocardiography (3). Our study aimed to assess sensitivity and reliability of visual AVC scoring on LDCT for predicting AS in older smokers. In addition, we aimed to determine the frequency of any AVC and its significant predictors in a program of LDCT screening for lung cancer, separately on baseline and annual repeat screenings.
MOTHODS: We reviewed 1225 consecutive participants in annual LDCT screening for lung cancer at the Mount Sinai Hospital before July 2018, who had at least two LDCTs without aortic valve replacement (AVR) before enrolled. The baseline LDCT was the first scan obtained at the time of enrollment and the most recent LDCT was the last LDCT obtained before July 2018, unless the participant had either AVR or had died before July 2018; for these cases, the last LDCT scan before surgery or death was used. Sensitivity and specificity of moderate/severe visual AVC score on LDCT to identify AS on echocardiogram was calculated for 126 participants who had both tests within 12 months. Using regression analyses, risk factors for AVC at baseline, for progression, and for new AVC on annual rounds of screening were identified. Reliability of AVC assessment on LDCT was assessed by comparing AVC visual scores with 1) standard-dose, electrocardiography (ECG)-gated CT for 31 participants who had both tests within 12 months, 2) with Agatston scores of 1225 participants on the most recent follow-up LDCT, and 3) by determining the intra-reader agreement on baseline LDCTs and separately for the most recent LDCTs of all participants.
RESULTS: Among these 126 participants who had LDCT and echocardiography within 12 months, 7 (5.6%) were diagnosed with moderate/severe AS, 3 (2.4%) were diagnosed with mild AS, 37 (29.4%) with aortic sclerosis, and 79 (62.7%) with no sclerosis or AS (Table 1). Of the 3 diagnosed as severe AS on echocardiography, all 3 had severe (grade 3) AVC on LDCT and of the 4 diagnosed as moderate AS on echocardiography, all 4 had moderate (grade 2) AVC on LDCT. Visual AVC scores on LDCT had substantial agreement with the severity of AS on echocardiography (weighted kappa=0.68, 95% CI: 0.56, 0.80). In addition, correlation was significant between the AVC visual scores on LDCT and both the echocardiographically determined mean pressure gradient (p = 0.02) and aortic valve area (p = 0.02) in these 10 participants with AS. Sensitivity and specificity of moderate/severe visual AVC scores for moderate/severe AS on echocardiogram was 100% and 94%, respectively.
There is substantial inter- (total weighted kappa of 0.73) and excellent intra-observer agreement (Baseline LDCT: weighted Kappa=0.91, 95% CI: 0.88-0.95; The most recent LDCT: weighted Kappa=0.90, 95% CI: 0.88-0.92).
Of the 1225 participants, no AVC was identified on the baseline LDCT in 1081 (88.2%), while 116 had mild AVC (grade 1), 26 moderate AVC (grade 2), and 2 severe AVC (grade 3). On the most recent LDCT, median follow-up time from baseline LDCT was 10.9 years (IQR: 4.2 to 15.1 yrs.), 865 (70.6%) had no AVC, 262 (21.4%) mild AVC, 80 (6.5%) moderate AVC, and 18 (1.5%) severe AVC. Multivariable logistic regression analysis showed significant predictors for baseline AVC were male sex (OR=3.39), age (OR=1.11) and CAC score (OR=1.28), for AVC progression after baseline, was pack-years of smoking (HR=1.01), and for new AVC on annual LDCT, were male sex (HR=1.65), age (HR=1.06), and BMI (HR=1.06).
CONCLUSIONS: Our results suggest that moderate to severe AVC scores could be reliably obtained on LDCT, should also be reported on screening LDCTs and further workup by echocardiography should be recommended as finding moderate or severe AVC on LDCT was associated with a high probability of AS in asymptomatic smokers.
References:
1. Lu MT, Onuma OK, Massaro JM, D'Agostino RB, Sr., O'Donnell CJ, Hoffmann U. Lung Cancer Screening Eligibility in the Community: Cardiovascular Risk Factors, Coronary Artery Calcification, and Cardiovascular Events. Circulation. 2016;134(12):897-9.
2. Nguyen V, Cimadevilla C, Estellat C, et al. Haemodynamic and anatomic progression of aortic stenosis. Heart. 2015;101(12):943-7.
3. Otto CM, Lind BK, Kitzman DW, Gersh BJ, Siscovick DS. Association of aortic-valve sclerosis with cardiovascular mortality and morbidity in the elderly. The New England journal of medicine. 1999;341(3):142-7.
TABLE 1. Agreement of AVC Score on LDCT by Extent of Aortic Stenosis on Echocardiogram Among Those Who Had Both Tests Within 12 Months.
Aortic stenosis categories based on Echocardiography*
No Aortic Stenosis
Aortic Stenosis
Total
None
Aortic sclerosis
Mild
Moderate
Severe
Visual AVC scores ꝉ
None (0)
72
14
0
0
0
86
Mild (1)
7
18
1
0
0
26
Moderate (2)
0
5
2
4
0
11
Severe (3)
0
0
0
0
3
3
Total
79
37
3
4
3
126
Weighted Kappa=0.68 (95% CI: 0.56, 0.80).
FIGURE 1. Visual and Agatston AVC Scoring.
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P1.11 - Screening and Early Detection (ID 177)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Screening and Early Detection
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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P1.11-22 - Lung Cancer Growth: Impact of Different Assumptions (ID 2522)
09:45 - 18:00 | Presenting Author(s): David Yankelevitz
- Abstract
Background
The purpose of this study is to determine which of two models, exponential or linear best approximates growth of lung cancer so as to predict when follow up CT exams should be obtained when a nodule is found.
Method
We reviewed our database of documented lung biopsies and identified those cases where the diagnosis of lung cancer in a solid nodule was confirmed and there were a total of three scans. Volume doubling times (VDTs) were calculated based on the first two scans using either the exponential method or the radial method and the third time point was used to determine which model best fit the actual result. We also allowed for measurement error to be considered based on the QIBA small nodule profile.
Result
We identified 100 cases that met the inclusion criteria. All were adenocarcinomas. On the first scan, the median nodule size was 8.2mm [Interquartile range(IQR):6.0-11.8)]. The median time between scans was 133.5 days (IQR:77.5-202 days) for the first and second scans, 75 days (IQR: 31.5-186.0 days) between second and third scans and 242.0 days (IQR: 131.5-424.0 days) between first and third scans. Median VDT from the first two scans was 139.0 days (IQR: 73.8-365.1 days). Using the calculated VDT from the first two scans, we found that 94 of the 100 cases had the third scan within 3 VDTs as estimated from the two scans. For these 94 cases, when accounting for the QIBA error measurements, both the linear or exponential models are plausible. For the 6 cases where the time interval between the second and third scan was longer, the exponential model provided a better fit for two, the linear model was better for two, and for the remaining two cases, it was not clear which model provided the better fit.
Conclusion
When considering the short time intervals typically used in obtaining follow-up CT scans for small pulmonary nodules, we found that it had minimal impact in predicting the ultimate size of the nodule as measurement error could account for results using either method. It was only after at least 3 doubling times that the potential impact of choice of method becomes apparent as with the exponential method the doubling time remains constant while with the radial method the doubling time increases with increasing size and therefore overall growth substantially decreases with longer time interval.There remains uncertainty in terms of how nodules grow, whether it is only along the advancing edge or by all cells doubling. This has little impact clinically in terms of short term follow up. However, when considering situations where there may be long delays between CT scans such as moving the interval for screening from 1 year to 2 years, it has a very large impact.
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P1.13 - Staging (ID 181)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Staging
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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P1.13-01 - The Importance of Staging of Lung Cancers, 30 mm or Less, Separately for Subsolid and Solid Nodules (ID 1413)
09:45 - 18:00 | Author(s): David Yankelevitz
- Abstract
Background
To determine pathologic results on non-small-cell lung cancers (NSCLCs), 30 mm or less in maximum diameter, separately by tumor consistency (solid, subsolid) on CT scans as we had shown that long-term survival was significantly different by tumor consistency and by type of parenchymal invasion.
Method
We reviewed all patients enrolled in the Initiative for Early Lung Cancer Research on Treatment (IELCART), a prospective cohort study of patients with first primary T1a-T1c NSCLC between 2016 and 2018 who had surgical resection. Short-axis diameter of N1-N3 lymph node on CT and SUVmax uptake on FDG-PET, if performed, were documented with values ≥ 2.5 defined as PET positive. Pathology reports were reviewed for N1-N3 lymph nodes (LNs) metastases and parenchymal invasion.
Result
Among 347 patients, 280 (80.7%) and 67 (19.3%) had solid and subsolid NSCLCs, respectively; all subsolid NSCLCs were adenocarcinoma. There was FDG-PET uptake in 253 (93.3%) with solid NSCLCs and in 55 (91.7%) with subsolid NSCLCs.None of the 67 subsolid NSCLCs had N1 or N2 LN metastases (Table 1). Among the 280 solid NSCLCs, none of the 42 NSCLCs≤ 10 mm had N1 or N2 metastases, while 5 of the 238 solid NSCLCs greater than 10 mm had N2 and 14 had N1 LN metastases. None of the N2 LNs were positive on FDG-PET and only 4(28.6%) of the 14 N1 LNs were positive on FDG-PET.
Angiolymphatic invasion was most frequently, followed by pleural and major vascular invasion (Table 1). For solid NSCLCs, invasion increased with increasing tumor diameter.
Conclusion
No N1-N3 LN metastases were identified in solid NSCLCs ≤ 10 mm; none in subsolid NSCLCs ≤ 30 mm. None with N2 LN metastases were positive on FDG-PET. This suggests that for NSCLCs, 30 mm or less, clinical staging be based on solely tumor size. For pathologic staging, we recommend differentiating staging classification by tumor consistency in line with the latest recommendations for pathologic assessment.
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P2.11 - Screening and Early Detection (ID 178)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Screening and Early Detection
- Presentations: 3
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.11-08 - CT Screening of Never Smokers (ID 1411)
10:15 - 18:15 | Author(s): David Yankelevitz
- Abstract
Background
We wanted to update our previous reports of the impact of SHTS on lung cancer and cardiovascular disease in never smokers and the usefulness of low-dose CT (LDCT) screening using the I-ELCAP protocol.
Method
Never smokers, defined as having smoked less than 100 cigarettes in their lifetime, were enrolled in our LDCT screening program. All signed IRB-HIPAA compliant consents. Patient demographics, medical history, and validated SHTS-exposure questionnaire were obtained at baseline. The SHTS-exposure score was computed for all participants together with LDCT Ordinal score for coronary artery calcifications (CAC), emphysema, lung cancer diagnosis and treatment were documented. At two of the institutions, we also performed pulmonary function tests, and measured the main pulmonary artery(MPA) and ascending aorta(AA) measurements, determined the automated aortic calcium score and extent of atherosclerotic plaque present in the coronary arteries using CT angiograms. Frequency of abnormal pulmonary function (FEV1/FVC ratio<0.7) and MPA/AA ratio≥1.0 were evaluated. We examined the relationship between SHTS exposure and these disease conditions.
Result
Among 14,018 never smokers, 6733 (48.1%) were women, 7276 (51.9%) men. Among them, 5236 (37.4%) had at least one noncalcified nodules (NCNs). Of the 14,018, 855 (6.1%) had at least one NCN 6.0 mm but less than 15.0 mm for which follow-up LDCT is recommended and 113 (0.8%) had NCN 15.0 mm or larger (Table 1).
Lung cancer was diagnosed in 55 (0.4%); 53(96.4%) resulting from findings on baseline LDCT and 2(3.6%) from the subsequent annual repeat LDCTs. Of the 55, 47 (85.5%) were clinical stage I; 49 had surgical resection, 4 treated with radiation therapy, and 2 with chemotherapy. Diagnosis was adenocarcinoma in 44, squamous-cell in 7, small-cell in 1 and other in 3. Post-surgically, 45 (81.8%) of the 47 were pathologic Stage IA (T1a-1cN0M0).
Of the 14,018 never smokers, the CAC score was 0 for 10,956 (78.2%), 1-3 for 1941 (13.9%), and 4-12 for 1211(8.0%). Emphysema was present in 310 (2.2%) participants.
The prevalence of lung cancer (p=0.04) was significantly associated with SHTS exposure, as was CAC (p<0.0001) and emphysema (p=0.03). In the subset of participants where additional measurements are available, abnormal pulmonary function tests (p=0.04), automated aortic calcium score (p=0.009), MPA/AA ratio≥1.0 (p=0.009) and presence and extent of coronary artery plaque (p<0.0001).
Conclusion
These results suggest that LDCT screening is of benefit for never smokers exposed to SHTS for identification of early lung cancer, cardiovascular disease and emphysema.
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P2.11-23 - Performance of Lung Cancer Risk Prediction Models in I-ELCAP Smokers (ID 1389)
10:15 - 18:15 | Author(s): David Yankelevitz
- Abstract
Background
To determine the performance of lung cancer risk prediction models in predicting lung cancer in smokers enrolled in the International Early Lung Cancer Program (I-ELCAP).
Method
62,071 asymptomatic ever-smokers enrolled into the international multi-institutions I-ELCAP for low-dose CT screening between 1993-2018. Demographics, smoking history, comorbidities, exposures and family history of lung cancer were collected at time of baseline CT scan. All participants received a baseline screening scan and subsequently annual repeat CT scans, and they were prospectively followed for the diagnosis of lung cancer. Diagnosis and treatment of lung cancer were verified and documented in the ELCAP Management System. To compare the predicted risk of lung cancer, we applied four lung cancer risk models: the Bach Model, the Liverpool Lung Project Incidence (LLPi) Risk model, the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Model 2012 (PLCOM2012), and the Pittsburgh Predictor Model to the I-ELCAP cohort. Model calibration and discrimination were assessed using expected-to-observed (E/O) ratio and the area under the curve (AUC) statistics. E/O ratio >1 indicates that the model predicts more lung cancer cases than observed.
Result
PLCOM2012 model was the most predictive of lung cancer for ever-smokers in I-ELCAP with the AUC 0.61 being the highest, followed by Bach model (AUC 0.58), LLPi model (AUC 0.57) and Pittsburgh Predictor (AUC 0.52). E/O ratios suggested that the PLCOM2012 model, Bach model, LLPi model and Pittsburgh Predictor model tends to overestimate the number of lung cancers. The LLPi model overestimated as many as 4 times more lung cancer cases.
Conclusion
Using data from I-ELCAP, the four existing lung cancer risk prediction models have AUCs ranged between 0.52-0.61, PLCOM2012 model was the top performer out of the four models.
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P2.11-33 - Organizational Readiness for Implementation of Lung Cancer Screening in a Veterans Affairs Healthcare System (ID 709)
10:15 - 18:15 | Author(s): David Yankelevitz
- Abstract
Background
Implementation of high quality lung cancer screening is complex and requires close coordination between radiology and primary care teams. Organizational readiness for change (ORC) is an important factor in successful implementation of complex healthcare programs such as lung cancer screening. Using the Consolidated Framework for Implementation Research (CFIR), we tested the hypothesis that ORC would differ between radiology and primary care prior to deployment of a centralized lung cancer screening program.
Method
We conducted a cross-sectional observational study. We invited all radiology and primary care providers (hospital and community-based) and affiliated staff at a single large VA Healthcare System in the US by email to participate in a web-based survey. We measured demographic information and adapted 9 validated items on ORC (domains of change commitment and change efficacy) and 10 items on change valence (value of a planned organizational change) using a 7-point Likert-type scale. Respondents’ ORC and change valence scores were calculated by averaging individual item responses for each scale. The primary outcome, ORC, was evaluated as a continuous variable with higher scores representing more readiness. We compared mean ORC scores between radiology and primary care using independent 2-sample t-tests.
Result
The overall response rate was 54% (76/128 [59.4%] radiology, 206/398 [51.8%] primary care). After 12 respondents were excluded for incomplete data (5 from radiology and 7 from primary care), the analytical sample was 270 respondents. Respondents were on average 47 years old [SD 11.24], 72% female, and 17% self-identified as having a leadership role. Individuals affiliated with radiology reported higher ORC than those affiliated with primary care (5.50 [SD 1.42] versus 5.07 [SD 1.22], p=0.03). Individuals self-identifying as having leadership roles in implementation of lung cancer screening reported higher ORC than those without leadership roles (5.56 [SD 1.38] vs 5.11 [SD 1.28], p=0.05). Those with leadership roles reported higher change valence than those without (5.91 [SD 1.20] vs. 5.36 [SD 1.88], p=0.006). We found no difference in reported change valence between radiology and primary care.
Conclusion
Radiology providers and staff have higher perceived ORC to implement a centralized lung cancer screening program compared to primary care. Providers and staff with implementation leadership roles reported higher ORC than those without leadership roles. Understanding these differences in readiness will inform future work as we focus on strategies to engage primary care providers and staff during implementation of lung cancer screening. We will deploy these strategies at Veterans Health Administration facilities across the US with the support of the VA-Partnership to increase Access to Lung cancer Screening (VA-PALS) and the VA Office of Rural Health.
