Faculty Bibliography

Lung cancer screening (LCS) has evolved over the past decade with research advances and clinical experience helping to define target populations for screening, improve lung nodule detection and management, and identify structural components of programs that improve the quality of screening delivery. The 2015 American College of Chest Physicians and American Thoracic Society Policy Statement, Components Necessary for High-Quality Lung Cancer Screening, identified nine essential components for high-quality LCS. Ten years later, optimizing the balance between the benefits and harms of LCS and ensuring equitable screening among all population groups remain fundamental objectives. In this 2025 update we aim to summarize new knowledge and highlight critical components that are needed for providing high-quality LCS. A multidisciplinary group of LCS experts was assembled to review evidence from the past ten years. The original components were reviewed and updated to develop eight refined components that should be considered essential structural elements of screening programs. Each component recommended by the authors is supported by an evidence update. Applying this framework will allow screening programs across the country to ensure implementation of high-quality, net-benefit LCS.

BACKGROUND:Optimal surveillance strategies for patients with small pulmonary nodules are uncertain. The Watch the Spot Trial, a large, cluster-randomized, pragmatic clinical trial, compared less- versus more-intensive strategies for surveillance of patients with incidental or screening-detected nodules ≤15 mm. METHODS:We describe between-site variation in methods to identify and enroll patients with small nodules; we used standard measures to describe baseline characteristics of participants and nodules. RESULTS:Participants included a diverse sample of 34,686 individuals who were passively enrolled at one of 14 participating healthcare systems using methods tailored to fit each site. Most patient characteristics were similar between the more- and less-intensive study arms, but participants in the more-intensive arm were more likely to identify as Hispanic/Latino (19.9% vs. 16.5%) or Black (17.8% vs. 10.5%). People who never smoked comprised 35.9% of the sample, and 22.7% of participants had ≥3 comorbidities. Screening-detected nodules were more common in the less-intensive arm (26.2% vs. 14.3%), but arms were balanced for nodule size, lobe, laterality and attenuation. Over 40% of identified nodules measured ≤4 mm in size, while only 14.1% of nodules measured >8 mm. Nodule attenuation and edge characteristics were not described in 36.7% and 74.5% of radiology reports, respectively. Few nodules were noted to be nonsolid (9.5%) or part-solid (3.2%). CONCLUSIONS:In a real-world sample of patients with pulmonary nodules measuring ≤15 mm, many nodules were of questionable importance (≤4 mm), and information about nodule attenuation and edge was often not specified by radiologists, representing important opportunities for quality improvement. CLINICAL TRIALS REGISTRATION/BACKGROUND:NCT02623712.

OBJECTIVE:To evaluate the feasibility and limitations of measuring health-related social risks (HRSRs) affecting individuals in a lung cancer screening (LCS) cohort from multiple data sources. METHODS:A single-institution study analyzed data from 227 participants in a pragmatic LCS trial in west and southwest Philadelphia. HRSRs were assessed using three approaches: (1) electronic health records (EHRs) capturing individual-level social risks (eg, financial strain, housing stability); (2) neighborhood-level analysis using a modified Yost index to determine socio-economic status; and (3) semistructured interviews with 15 participants to identify barriers and facilitators to LCS adherence. RESULTS:EHR data revealed financial strain and housing instability as the most documented HRSRs, although missing data ranged from 64% to 69%. Neighborhood-level analysis showed participants had lower socio-economic status compared with their broader communities, with Yost index scores of 1.28 (west Philadelphia) and 1.20 (southwest Philadelphia). Interviews highlighted limited knowledge of LCS (87% unaware before clinician referral), reliance on public or supplemental transportation, and overall trust in health care providers. Transportation was not a significant reported barrier to LCS adherence. DISCUSSION/CONCLUSIONS:This study demonstrates the promise and limitations of EHR data, neighborhood-level data, and patient interviews to assess HRSRs. Although EHRs provided limited and inconsistent data, interviews captured granular individual experiences, and neighborhood-level analysis contextualized socio-economic influences. Comprehensive and consistent data collection across multiple sources is critical in understanding HRSRs experienced by individuals.

UNLABELLED:The indicator cell assay platform (iCAP) is a tool for blood-based diagnostics that addresses the low signal-to-noise ratio of blood biomarkers by using cells as biosensors. The assay exposes small volumes of patient serum to standardized cells in culture and classifies disease by machine learning analysis of the gene expression readout from the cells. We developed the lung cancer iCAP (LC-iCAP) as a rule-out test for nodule management in computed tomography (CT)-based lung-cancer screening. We performed analytical optimization, rigorous reproducibility testing, and assessed performance in a study with prospective-specimen-collection, retrospective-blinded-evaluation (PRoBE) design. LC-iCAP achieved an AUC of 0.64 (95% CI, 0.51-0.76) on the ROC curve in validation. Post-validation integration of the assay readout with CT-based features showed improved clinical utility compared to the Mayo Clinic model, with 90% sensitivity, 64% specificity, and 95% negative predictive value at 25% prevalence. The lung-cancer specific readout was enriched for hypoxia-responsive genes and was reproducible across different indicator cell lineages. This is the first validation study of an iCAP and the first application for early cancer detection. The LC-iCAP uses immortalized cells, is scalable and cost-effective and has a multivariate readout. This study supports its potential as a next-generation multivalent platform for precision medicine applications in multi-cancer screening and drug development. KEY POINTS/UNASSIGNED:We developed the LC-iCAP, novel approach for liquid biopsies that uses cultured cells as biosensors. The cells detect cancer signals in serum and transduce them into standardized gene expression profiles, which are analyzed by machine learning for disease classification. The assay is inexpensive and scalable and has a multivariate readout with potential utility for precision medicine and multi-cancer early detection.A LC-iCAP-based lung cancer risk classifier demonstrated improved specificity compared to existing tests, suggesting meaningful clinical utility for managing indeterminate pulmonary nodules.We identified a lung-cancer specific transcriptional response to hypoxia in the assay readout, implicating HIF1A and HIF2A activity in the response consistent with known lung cancer biology and highlighting the platform's mechanistic relevance.Standardized controls and validation studies demonstrated assay reproducibility, lineage stability, and detection of technical errors-supporting the platform's readiness for clinical deployment.

BACKGROUND:With the recent shift in lung cancer staging towards early-stage disease coinciding with the introduction of lung cancer screening (LCS), little is known if LCS has affected the rate of recurrence and survival in community settings. Our objective was to evaluate variation in the detection and outcomes of recurrent lung cancer stratified by receipt of LCS. METHODS:Patients aged 55-80 years old diagnosed with stage I-IIIA non-small cell lung cancer (NSCLC) between 1/1/2014 and 12/31/2020 who completed definitive therapy and were considered disease-free were identified. Rates of recurrence were calculated in discrete 12-month intervals and by cumulative incidence. Survival was evaluated by multivariable adjusted Restricted Mean Survival Time (aRMST). Factors associated with recurrence were evaluated by Poisson models. RESULTS:Among 916 patients meeting study criteria, 708 (77 %) were non-screen-detected and 208 (23 %) were considered screen-detected. The proportion of recurrence between non-screen-detected (22 %) and screen-detected (17 %) was similar (P = 0.11). Recurrence rates during the first and second years after definitive therapy were 10.1 and 4.1 per 100 person-years for the non-screen-detected and 6.0 and 4.5 per 100 person-years for screen-detected, respectively. Two-year cumulative incidence of recurrence was 16.5 % (95 % CI, 13.9 %-19.4 %) for non-screen-detected patients and 13.8 % (95 % CI, 9.3 %-19.0 %) in the screen-detected group. Recurrence-free survival and survival after recurrence were similar between the two groups. Screening status was not associated with the likelihood of recurrence (RR=0.94, 95 % CI, 0.59-1.50). CONCLUSION/CONCLUSIONS:These findings provide evidence of recurrence being a part of the intrinsic nature of disease progression despite mode of detection. Our findings emphasize the need for all patients to receive surveillance and survivorship care after treatment for early-stage NSCLC regardless of mode of detection. Further study with longer follow-up is warranted.

IMPORTANCE/UNASSIGNED:Adherence to annual lung cancer screening (LCS) is a proposed quality metric for LCS programs, but data linking annual adherence to lung cancer outcomes are lacking. OBJECTIVE/UNASSIGNED:To investigate annual LCS adherence rates across 2 subsequent LCS rounds among adults undergoing baseline LCS and examine the association of adherence with lung cancer diagnosis rates. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This retrospective cohort study included adults aged 55 to 75 years who formerly or currently smoked and underwent baseline LCS between January 1, 2015, and December 31, 2018, across 5 US health care systems in the Population-Based Research to Optimize the Screening Process-Lung Consortium. Participants with missing Lung Computed Tomography Screening Reporting & Data System scores or a lung cancer diagnosis prior to LCS initiation were excluded. Data were analyzed from October 2023 to October 2024. EXPOSURES/UNASSIGNED:For negative baseline screening results, T1 and T2 screening adherence was defined as chest computed tomography (CT) between 10 and 18 months and 22 and 30 months after baseline, respectively. For positive baseline screening results, T1 and T2 adherence was defined as chest CT between 11 and 21 months and 28 and 36 months after baseline, respectively. MAIN OUTCOMES AND MEASURES/UNASSIGNED:The main outcomes were annual T1 and T2 LCS adherence rates and associations between T1 and T2 screening adherence; annual incident lung cancer diagnoses in rounds T0 (0-12 months after baseline), T1 (>12 to 24 months after baseline), and T2 (>24 to 36 months after baseline); and cancer stage distribution. RESULTS/UNASSIGNED:A total of 10 170 individuals received baseline LCS (median age, 65 years [IQR, 60-69 years]; 5415 [53.2%] male). During round T1, 6141 of 10 033 eligible patients (61.2% [95% CI, 60.2%-62.2%]) were adherent, and during round T2, 5028 of 9966 eligible patients (50.5% [95% CI, 49.5%-51.4%]) were adherent. T1 adherence was significantly associated with T2 adherence (adjusted relative risk, 2.40; 95% CI, 2.06-2.79). Across 36 months of follow-up, 279 patients (2.7%; 95% CI, 2.4%-3.1%) were diagnosed with lung cancer. Incident lung cancer diagnosis rates were 1.3% (95% CI, 1.1%-1.6%), 0.7% (95% CI, 0.5%-0.8%), and 0.8% (95% CI, 0.6%-0.9%) during rounds T0, T1, and T2, respectively. Lung cancer diagnosis rates were higher among individuals who were LCS adherent vs nonadherent during both rounds T1 (59 of 6141 [1.0%; 95% CI, 0.7%-1.2%] vs 8 of 3892 [0.2%; 95% CI, 0.1%-0.4%]; P < .001) and T2 (63 of 5028 [1.3%; 95% CI, 1.0%-1.6%] vs 12 of 4938 [0.2%; 95% CI, 0.1%-0.4%]; P < .001). A greater proportion of early-stage lung cancers were diagnosed among individuals adherent to screening at T2 compared with those who were not (46 of 63 [73.0%] vs 3 of 12 [25.0%]; P = .006). CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this multicenter cohort study of adults undergoing LCS, screening adherence was associated with increased overall and early-stage lung cancer detection rates; however, adherence decreased annually after baseline screening, suggesting that it is an important LCS quality metric.

BACKGROUND/UNASSIGNED:Uptake of new systemic therapy treatments among patients with advanced non-small cell lung cancer (NSCLC) occurred rapidly after FDA approval. Few studies have characterized the association of these therapies on survival in community settings. We assessed survival by type of systemic therapy received among patients diagnosed with advanced NSCLC who were treated in community-based settings. METHODS/UNASSIGNED:In this retrospective cohort, patients diagnosed with de novo stage IV NSCLC between March 2012 and December 2020 were followed through December 31, 2021. Survival was ascertained with restricted mean survival time from treatment receipt through 12 and 60 months and compared by RMST differences adjusting for demographic and tumor characteristics. Trends in one-year survival probabilities were assessed using joinpoint regression. RESULTS/UNASSIGNED:Of 945 patients receiving systemic therapy, 46% received cytotoxic chemotherapy (Chemo-Only), 15% bevacizumab +/- Chemo, 22% immunotherapy +/- Chemo, and 16% targeted therapies. Median days from diagnosis to treatment ranged from 32 to 42. Compared to those receiving Chemo-Only, patients receiving immunotherapy +/- Chemo survived 1.4 months longer [95% confidence interval (CI): 0.5 to 2.3 months; P=0.002] and 3.2 months longer (95% CI: -1.4 to 7.9 months; P=0.18) through 12 and 60 months follow-up, respectively. Relative to those receiving Chemo-Only, patients receiving targeted therapies survived 1.6 months longer (95% CI: 0.7 to 2.5 months; P<0.001) and 5.5 months longer (95% CI: 0.7 to 10.4 months; P=0.02) through 12 and 60 months follow-up. One-year survival significantly increased from 30% to 59% between 2012 and 2020 (P=0.007). CONCLUSIONS/UNASSIGNED:We found patients receiving targeted therapies and immunotherapy +/- Chemo survived longer than those on Chemo-Only. One-year survival probabilities significantly increased between 2012 and 2020. Additional research is needed to better understand the potential benefits and harms, including patient adverse events and financial toxicity.

UNLABELLED: HIGHLIGHTS/UNASSIGNED:Most lung cancer screening (LCS) interventions evaluated to date have been educational in nature and focused primarily on shared decision making or the initial uptake of screening, with some interventions demonstrating statistically significant improvements in patient knowledge and initial LCS order/uptake.A critical gap in knowledge remains regarding how to effectively support LCS eligibility assessment as well as adherence to annual screening and appropriate diagnostic testing.Findings underscore the need for the field to expand beyond education-focused interventions and incorporate multilevel targets when designing interventions to support high-quality LCS in practice.