Screening for Lung Cancer: CHEST Guideline and Expert Panel Report

Harmonization of clinical practice guidelines for primary prevention and screening: actionable recommendations and resources for primary care

BACKGROUND

Clinical practice guidelines (CPGs) synthesize high-quality information to support evidence-based clinical practice. In primary care, numerous CPGs must be integrated to address the needs of patients with multiple risks and conditions. The BETTER program aims to improve prevention and screening for cancer and chronic disease in primary care by synthesizing CPGs into integrated, actionable recommendations. We describe the process used to harmonize high-quality cancer and chronic disease prevention and screening (CCDPS) CPGs to update the BETTER program.

METHODS

A review of CPG databases, repositories, and grey literature was conducted to identify international and Canadian (national and provincial) CPGs for CCDPS in adults 40-69 years of age across 19 topic areas: cancers, cardiovascular disease, chronic obstructive pulmonary disease, diabetes, hepatitis C, obesity, osteoporosis, depression, and associated risk factors (i.e., diet, physical activity, alcohol, cannabis, drug, tobacco, and vaping/e-cigarette use). CPGs published in English between 2016 and 2021, applicable to adults, and containing CCDPS recommendations were included. Guideline quality was assessed using the Appraisal of Guidelines for Research and Evaluation (AGREE) II tool and a three-step process involving patients, health policy, content experts, primary care providers, and researchers was used to identify and synthesize recommendations.

RESULTS

We identified 51 international and Canadian CPGs and 22 guidelines developed by provincial organizations that provided relevant CCDPS recommendations. Clinical recommendations were extracted and reviewed for inclusion using the following criteria: 1) pertinence to primary prevention and screening, 2) relevance to adults ages 40-69, and 3) applicability to diverse primary care settings. Recommendations were synthesized and integrated into the BETTER toolkit alongside resources to support shared decision-making and care paths for the BETTER program.

CONCLUSIONS

Comprehensive care requires the ability to address a person's overall health. An approach to identify high-quality clinical guidance to comprehensively address CCDPS is described. The process used to synthesize and harmonize implementable clinical recommendations may be useful to others wanting to integrate evidence across broad content areas to provide comprehensive care. The BETTER toolkit provides resources that clearly and succinctly present a breadth of clinical evidence that providers can use to assist with implementing CCDPS guidance in primary care.

Personalised follow-up and management schema for patients with screen-detected pulmonary nodules: A dynamic modelling study

BACKGROUND

Selecting the time target for follow-up testing in lung cancer screening is challenging. We aim to devise dynamic, personalized lung cancer screening schema for patients with pulmonary nodules detected through low-dose computed tomography.

METHODS

We developed and validated dynamic models using data of pulmonary nodule patients (aged 55-74 years) from the National Lung Screening Trial. We predicted patient-specific risk profiles at baseline (R0) and updated the risk evaluation results in repeated screening rounds (R1 and R2). We used risk cutoffs to optimize time-dependent sensitivity at an early decision point (3 months) and time-dependent specificity at a late decision point (1 year).

RESULTS

In validation, area under receiver operating characteristic curve for predicting 12-month lung cancer onset was 0.867 (95 % confidence interval: 0.827-0.894) and 0.807 (0.765-0.948) at R0 and R1-R2, respectively. The personalized schema, compared with National Comprehensive Cancer Network (NCCN) guideline and Lung-RADS, yielded lower rates of delayed diagnosis (1.7% vs. 1.7% vs. 6.9 %) and over-testing (4.9% vs. 5.6% vs. 5.6 %) at R0, and lower rates of delayed diagnosis (0.0% vs. 18.2% vs. 18.2 %) and over-testing (2.6% vs. 8.3% vs. 7.3 %) at R2. Earlier test recommendation among cancer patients was more frequent using the personalized schema (vs. NCCN: 29.8% vs. 20.9 %, p = 0.0065; vs. Lung-RADS: 33.2% vs. 22.8 %, p = 0.0025), especially for women, patients aged ≥65 years, and part-solid or non-solid nodules.

CONCLUSIONS

The personalized schema is easy-to-implement and more accurate compared with rule-based protocols. The results highlight value of personalized approaches in realizing efficient nodule management.

Lung cancer screening use among screening-eligible adults with disabilities

BACKGROUND

Lung cancer screening (LCS) use among adults with disabilities has not been well characterized. We estimated the prevalence of LCS use by disability types and counts and investigated the association between disability counts and LCS utilization among LCS-eligible adults.

METHODS

We used cross-sectional data from the 2019 Behavioral Risk Factor Surveillance System, Lung Cancer Screening Module. Based on the 2013 US Preventive Services Task Force criteria for LCS, the sample included 4407 LCS-eligible adults, aged 55-79 years, with current or former (quit smoking in the past 15 years) tobacco use history of at least 30 pack-years. Disability types included limitations in hearing, vision, cognition, mobility, self-care, and independent living. We also categorized respondents by number of disabilities (no disability, 1 disability, 2 disabilities, 3+ disabilities). We utilized descriptive statistics and multivariable logistic regression analyses to determine the association between disability counts and the receipt of LCS (yes/no) in the past 12 months.

RESULTS

In 2019, 16.4% of LCS-eligible adults were screened for lung cancer. Overall, 49.6% of participants had no disability, and 14.5% had >3 disabilities. Mobility was the most prevalent disability type (35.4%), followed by cognitive impairment (18.2%) and hearing (16.6%). LCS was more prevalent in adults with disability in self-care versus no disability in self-care (24.0% vs. 15.5%, p = 0.01), disability in independent living versus no disability in independent living (22.2% vs. 15.4%, p = 0.02), and cognitive impairment disability versus no cognitive impairment (22.1% vs. 15.3%, p = 0.03). The prevalence rates of LCS among groups of LCS-eligible adults with different disability counts were not significant (p = 0.17).

CONCLUSIONS

Despite the lack of clinical guidelines on LCS among individuals with disabilities, some individuals with disabilities are being screened for lung cancer. Future research should address this knowledge gap to determine clinical benefit versus harm of LCS among those with disabilities.

Effect of a Personalized Tobacco Treatment Intervention on Smoking Abstinence in Individuals Eligible for Lung Cancer Screening

INTRODUCTION

To determine whether personalized gain-framed messaging and biomarker feedback related to tobacco cessation or reduction decrease smoking behavior in patients undergoing or eligible for lung cancer screening.

METHODS

Between 2016 and 2020, 188 patients were enrolled in a two-phase, sequential, randomized controlled trial. Phase 1 evaluated whether standard of care (SC) (five in-person counseling sessions and 8 weeks of nicotine patch) plus gain-framed messaging (GFM) versus SC would increase 8-week biochemically verified smoking cessation rates. In 143 participants randomized in phase 2, we tested whether feedback on smoking-related biomarkers would reduce 6-month self-reported number of cigarettes smoked per day compared with a no feedback control. Chi-square test and mixed effects repeated measures analyses were used to evaluate group differences.

RESULTS

Participants were 62.5 ± 5.6 (mean ± SD) years of age, had a 50.3 ± 21 pack-year smoking history, and were smoking 16.9 ± 9.9 cigarettes per day. At 8 weeks, there was no difference in quit rates between those randomized to SC plus GFM (n = 15 of 93, 16.1%) and those randomized to SC (n = 16 of 95, 16.8%), with p equals to 0.90. At the 6-month post-randomization follow-up, number of cigarettes smoked per day was similar in the feedback (least-squares mean = 7.5, 95% confidence interval: 6.0-9.1) and no feedback arms (7.7, 95% confidence interval: 6.2-9.3), with p equals to 0.87.

CONCLUSIONS

Gain-framed messaging and health feedback did not significantly improve quit rates relative to comprehensive standard of care. Nevertheless, the overall program achieved clinically meaningful smoking quit rates in this older high pack-year cohort, highlighting the importance of intensive tobacco treatment for patients undergoing lung cancer screening. CLINICAL TRIAL REGISTERED WITH CLINICALTRIALS.GOV: NCT02658032.

Association of patient and health care organization factors with incidental nodule guidelines adherence: A multi-system observational study

BACKGROUND

Health care organizations are increasingly developing systems to ensure patients with pulmonary nodules receive guideline-adherent care. Our goal was to determine patient and organization factors that are associated with radiologist adherence as well as clinician and patient concordance to 2005 Fleischner Society guidelines for incidental pulmonary nodule follow-up.

MATERIALS

Trained researchers abstracted data from the electronic health record from two Veterans Affairs health care systems for patients with incidental pulmonary nodules as identified by interpreting radiologists from 2008 to 2016.

METHODS

We classified radiology reports and patient follow-up into two categories. Radiologist-Fleischner Adherence was the agreement between the radiologist's recommendation in the computed tomography report and the 2005 Fleischner Society guidelines. Clinician/Patient-Fleischner Concordance was agreement between patient follow-up and the guidelines. We calculated multivariable-adjusted predicted probabilities for factors associated with Radiologist-Fleischner Adherence and Clinician/Patient-Fleischner Concordance.

RESULTS

Among 3150 patients, 69% of radiologist recommendations were adherent to 2005 Fleischner guidelines, 4% were more aggressive, and 27% recommended less aggressive follow-up. Overall, only 48% of patients underwent follow-up concordant with 2005 Fleischner Society guidelines, 37% had less aggressive follow-up, and 15% had more aggressive follow-up. Radiologist-Fleischner Adherence was associated with Clinician/Patient-Fleischner Concordance with evidence for effect modification by health care system.

CONCLUSION

Clinicians and patients seem to follow radiologists' recommendations but often do not obtain concordant follow-up, likely due to downstream differential processes in each health care system. Health care organizations need to develop comprehensive and rigorous tools to ensure high levels of appropriate follow-up for patients with pulmonary nodules.

Pack-Year Smoking History: An Inadequate and Biased Measure to Determine Lung Cancer Screening Eligibility

PURPOSE

Pack-year smoking history is an imperfect and biased measure of cumulative tobacco exposure. The use of pack-year smoking history to determine lung cancer screening eligibility in the current US Preventive Services Task Force (USPSTF) guideline may unintentionally exclude many high-risk individuals, especially those from racial and ethnic minority groups. It is unclear whether using a smoking duration cutoff instead of a smoking pack-year cutoff would improve the selection of individuals for screening.

METHODS

We analyzed 49,703 individuals with a smoking history from the Southern Community Cohort Study (SCCS) and 22,126 individuals with a smoking history from the Black Women's Health Study (BWHS) to assess eligibility for screening under the USPSTF guideline versus a proposed guideline that replaces the ≥20-pack-year criterion with a ≥20-year smoking duration criterion.

RESULTS

Under the USPSTF guideline, only 57.6% of Black patients with lung cancer in the SCCS would have qualified for screening, whereas a significantly higher percentage of White patients with lung cancer (74.0%) would have qualified (P < .001). Under the proposed guideline, the percentage of Black and White patients with lung cancer who would have qualified for screening increased to 85.3% and 82.0%, respectively, eradicating the disparity in screening eligibility between the groups. In the BWHS, using a 20-year smoking duration cutoff instead of a 20-pack-year cutoff increased the percentage of Black women with lung cancer who would have qualified for screening from 42.5% to 63.8%.

CONCLUSION

Use of a 20-year smoking duration cutoff instead of a 20-pack-year cutoff greatly increases the proportion of patients with lung cancer who would qualify for screening and eliminates the racial disparity in screening eligibility between Black versus White individuals; smoking duration has the added benefit of being easier to calculate and being a more precise assessment of smoking exposure compared with pack-year smoking history.

Lung cancer screening in Brazil: recommendations from the Brazilian Society of Thoracic Surgery, Brazilian Thoracic Association, and Brazilian College of Radiology and Diagnostic Imaging

Although lung cancer (LC) is one of the most common and lethal tumors, only 15% of patients are diagnosed at an early stage. Smoking is still responsible for more than 85% of cases. Lung cancer screening (LCS) with low-dose CT (LDCT) reduces LC-related mortality by 20%, and that reduction reaches 38% when LCS by LDCT is combined with smoking cessation. In the last decade, a number of countries have adopted population-based LCS as a public health recommendation. Albeit still incipient, discussion on this topic in Brazil is becoming increasingly broad and necessary. With the aim of increasing knowledge and stimulating debate on LCS, the Brazilian Society of Thoracic Surgery, the Brazilian Thoracic Association, and the Brazilian College of Radiology and Diagnostic Imaging convened a panel of experts to prepare recommendations for LCS in Brazil. The recommendations presented here were based on a narrative review of the literature, with an emphasis on large population-based studies, systematic reviews, and the recommendations of international guidelines, and were developed after extensive discussion by the panel of experts. The following topics were reviewed: reasons for screening; general considerations about smoking; epidemiology of LC; eligibility criteria; incidental findings; granulomatous lesions; probabilistic models; minimum requirements for LDCT; volumetric acquisition; risks of screening; minimum structure and role of the multidisciplinary team; practice according to the Lung CT Screening Reporting and Data System; costs versus benefits of screening; and future perspectives for LCS.

Promoting Lung Cancer Screen Decision-Making and Early Detection Behaviors: A Systematic Review and Meta-analysis

BACKGROUND

Promoting lung cancer screening (LCS) is complex. Previous studies have overlooked that LCS behaviors are stage based and thus did not identify the characteristics of LCS interventions at different screening stages.

OBJECTIVE

The aims of this study were to explore the characteristics and efficacy of interventions in promoting LCS decision making and behaviors and to evaluate these interventions.

METHODS

We conducted a study search from the inception of each bibliographic database to April 8, 2023. The precaution adoption process model was used to synthesize and classify the evidence. The RE-AIM framework was used to evaluate the effectiveness of LCS programs. Heterogeneity tests and meta-analysis were performed using RevMan 5.4 software.

RESULTS

We included 31 studies that covered 4 LCS topics: knowledge of lung cancer, knowledge of LCS, value clarification exercises, and LCS supportive resources. Patient decision aids outperformed educational materials in improving knowledge and decision outcomes with a significant reduction in decision conflict (standardized mean difference, 0.81; 95% confidence interval, -1.15 to -0.47; P < .001). Completion rates of LCS ranged from 3.6% to 98.8%. Interventions that included screening resources outperformed interventions that used patient decision aids alone in improving LCS completion. The proportions of reported RE-AIM indicators were highest for reach (69.59%), followed by adoption (43.87%), effectiveness (36.13%), implementation (33.33%), and maintenance (9.68%).

CONCLUSION

Evidence from 31 studies identified intervention characteristics and effectiveness of LCS interventions based on different stages of decision making.

IMPLICATIONS FOR PRACTICE

It is crucial to develop targeted and systematic interventions based on the characteristics of each stage of LCS to maximize intervention effectiveness and reduce the burden of lung cancer.

Bone mineral density in lower thoracic vertebra for osteoporosis diagnosis in older adults during CT lung cancer screening

BACKGROUND

Quantitative computed tomography (QCT)-based lumbar bone mineral density (LBMD) has been used to diagnose osteoporosis. This study explored the value of lower thoracic BMD (TBMD) in diagnosing osteoporosis in older adults during CT lung cancer screening.

METHODS

This study included 751 subjects who underwent QCT scans with both LBMD and TBMD. 141 of them was selected for a validation. Osteoporosis was diagnosed based on LBMD using the ACR criteria (gold standard). TBMD thresholds were obtained using receiver operating characteristic curve. TBMD was also translated into LBMD (TTBMD) and osteoporosis was defined based on TTBMD using ACR criteria. The performance of TBMD and TTBMD in identifying osteoporosis was determined by Kappa test. The associations between TBMD- and TTBMD-based osteoporosis and fracture were tested in 227 subjects with followed up status of spine fracture.

RESULTS

The performance of TBMD in identifying osteoporosis was low (kappa = 0.66) if using the ACR criteria. Two thresholds of TBMD for identifying osteopenia (128 mg/cm3) and osteoporosis (91 mg/cm3) were obtained with areas under the curve of 0.97 and 0.99, respectively. The performance of the identification of osteoporosis/osteopenia using the two thresholds or TTBMD both had good agreement with the gold standard (kappa = 0.78, 0.86). Similar results were observed in validation population. Osteoporosis identified using the thresholds (adjusted hazard ratio (HR) = 18.72, 95% confidence interval (CI): 5.13-68.36) or TTBMD (adjusted HR = 10.28, 95% CI: 4.22-25.08) were also associated with fractures.

CONCLUSION

Calculating the threshold of TBMD or normalizing TBMD to LBMD are both useful in identifying osteoporosis in older adults during CT lung cancer screening.

A Highly Sensitive and Specific Non-Invasive Test through Genome-Wide 5-Hydroxymethylation Mapping for Early Detection of Lung Cancer

Low-dose computed tomography screening can increase the detection for non-small-cell lung cancer (NSCLC). To improve the diagnostic accuracy of early-stage NSCLC detection, ultrasensitive methods are used to detect cell-free DNA (cfDNA) 5-hydroxymethylcytosine (5hmC) in plasma. Genome-wide 5hmC is profiled in 1990 cfDNA samples collected from patients with non-small cell lung cancer (NSCLC, n = 727), healthy controls (HEA, n = 1,092), as well as patients with small cell lung cancer (SCLC, n = 41), followed by sample randomization, differential analysis, feature selection, and modeling using a machine learning approach. Differentially modified features reflecting tissue origin. A weighted diagnostic model comprised of 105 features is developed to compute a detection score for each individual, which showed an area under the curve (AUC) range of 86.4%-93.1% in the internal and external validation sets for distinguishing lung cancer from HEA controls, significantly outperforming serum biomarkers (p < 0.001). The 5hmC-based model detected high-risk pulmonary nodules (AUC: 82%)and lung cancer of different subtypes with high accuracy as well. A highly sensitive and specific blood-based test is developed for detecting lung cancer. The 5hmC biomarkers in cfDNA offer a promising blood-based test for lung cancer.

Impact of the COVID-19 Pandemic on Lung Cancer Screening Processes in a Northeast Tertiary Health Care Network

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic disrupted health care systems, including implementation of lung cancer screening programs. The impact and recovery from this disruption on screening processes is not well appreciated. Herein, the radiology database of a Northeast tertiary health care network was reviewed before and during the pandemic (2013-2022). In the 3 months before the pandemic, an average of 77.3 lung cancer screening with computed tomography scans (LCS-CT) were performed per month. The average dropped to 23.3 between April and June of 2020, whereas COVID-19 hospitalizations peaked at 1604. By July, average hospitalizations dropped to 50, and LCS-CTs rose to >110 per month for the remaining year. LCS-CTs did not decline during COVID-19 surges in December of 2021 and 2022. The LCS-CT performance grew by 4.5% in 2020, 69.6% in 2021, and 27.0% in 2022, exceeding projected growth by 722 examinations. This resiliency indicates a potentially smaller impact of COVID-19 on lung cancer diagnoses than initially feared.

Deep Learning-Based Kernel Adaptation Enhances Quantification of Emphysema on Low-Dose Chest CT for Predicting Long-Term Mortality

OBJECTIVES

The aim of this study was to ascertain the predictive value of quantifying emphysema using low-dose computed tomography (LDCT) post deep learning-based kernel adaptation on long-term mortality.

MATERIALS AND METHODS

This retrospective study investigated LDCTs obtained from asymptomatic individuals aged 60 years or older during health checkups between February 2009 and December 2016. These LDCTs were reconstructed using a 1- or 1.25-mm slice thickness alongside high-frequency kernels. A deep learning algorithm, capable of generating CT images that resemble standard-dose and low-frequency kernel images, was applied to these LDCTs. To quantify emphysema, the lung volume percentage with an attenuation value less than or equal to -950 Hounsfield units (LAA-950) was gauged before and after kernel adaptation. Low-dose chest CTs with LAA-950 exceeding 6% were deemed emphysema-positive according to the Fleischner Society statement. Survival data were sourced from the National Registry Database at the close of 2021. The risk of nonaccidental death, excluding causes such as injury or poisoning, was explored according to the emphysema quantification results using multivariate Cox proportional hazards models.

RESULTS

The study comprised 5178 participants (mean age ± SD, 66 ± 3 years; 3110 males). The median LAA-950 (18.2% vs 2.6%) and the proportion of LDCTs with LAA-950 exceeding 6% (96.3% vs 39.3%) saw a significant decline after kernel adaptation. There was no association between emphysema quantification before kernel adaptation and the risk of nonaccidental death. Nevertheless, after kernel adaptation, higher LAA-950 (hazards ratio for 1% increase, 1.01; P = 0.045) and LAA-950 exceeding 6% (hazards ratio, 1.36; P = 0.008) emerged as independent predictors of nonaccidental death, upon adjusting for age, sex, and smoking status.

CONCLUSIONS

The application of deep learning for kernel adaptation proves instrumental in quantifying pulmonary emphysema on LDCTs, establishing itself as a potential predictive tool for long-term nonaccidental mortality in asymptomatic individuals.

Machine-Learning-Based Classification Model to Address Diagnostic Challenges in Transbronchial Lung Biopsy

BACKGROUND

When obtaining specimens from pulmonary nodules in TBLB, distinguishing between benign samples and mis-sampling from a tumor presents a challenge. Our objective is to develop a machine-learning-based classifier for TBLB specimens.

METHODS

Three pathologists assessed six pathological findings, including interface bronchitis/bronchiolitis (IB/B), plasma cell infiltration (PLC), eosinophil infiltration (Eo), lymphoid aggregation (Ly), fibroelastosis (FE), and organizing pneumonia (OP), as potential histologic markers to distinguish between benign and malignant conditions. A total of 251 TBLB cases with defined benign and malignant outcomes based on clinical follow-up were collected and a gradient-boosted decision-tree-based machine learning model (XGBoost) was trained and tested on randomly split training and test sets.

RESULTS

Five pathological changes showed independent, mild-to-moderate associations (AUC ranging from 0.58 to 0.75) with benign conditions, with IB/B being the strongest predictor. On the other hand, FE emerged to be the sole indicator of malignant conditions with a mild association (AUC = 0.66). Our model was trained on 200 cases and tested on 51 cases, achieving an AUC of 0.78 for the binary classification of benign vs. malignant on the test set.

CONCLUSION

The machine-learning model developed has the potential to distinguish between benign and malignant conditions in TBLB samples excluding the presence or absence of tumor cells, thereby improving diagnostic accuracy and reducing the burden of repeated sampling procedures for patients.

Sex differences and racial/ethnic disparities in the presentation and treatment of medullary thyroid cancer

BACKGROUND

This study assessed for disparities in the presentation and management of medullary thyroid cancer (MTC).

METHODS

Patients with MTC (2010-2020) were identified from the National Cancer Database. Differences in disease presentation and likelihood of guideline-concordant surgical management (total thyroidectomy and resection of ≥1 lymph node) were assessed by sex and race/ethnicity.

RESULTS

Of 6154 patients, 68.2% underwent guideline-concordant surgery. Tumors >4 ​cm were more likely in men (vs. women: OR 2.47, p ​< ​0.001) and Hispanic patients (vs. White patients: OR 1.52, p ​= ​0.001). Non-White patients were more likely to have distant metastases (Black: OR 1.63, p ​= ​0.002; Hispanic: OR 1.44, p ​= ​0.038) and experienced longer time to surgery (Black: HR 0.66, p ​< ​0.001; Hispanic: HR 0.71, p ​< ​0.001). Black patients were less likely to undergo guideline-concordant surgery (OR 0.70, p ​= ​0.022).

CONCLUSIONS

Male and non-White patients with MTC more frequently present with advanced disease, and Black patients are less likely to undergo guideline-concordant surgery.

What Goes into Patient Selection for Lung Cancer Screening? Factors Associated with Clinician Judgments of Suitability for Screening

Rationale: Achieving the net benefit of lung cancer screening (LCS) depends on optimizing patient selection. Objective: To identify factors associated with clinician assessments that a patient was unlikely to benefit from LCS ("LCS-inappropriate") because of comorbidities or limited life expectancy. Methods: Retrospective analysis of patients assessed for LCS at 30 Veterans Health Administration facilities from January 1, 2015 to February 1, 2021. We conducted hierarchical mixed-effects logistic regression analyses to determine factors associated with clinicians' designations of LCS inappropriateness (primary outcome), accounting for 3-year predicted probability (i.e., competing risk) of non-lung cancer death. Measurements and Main Results: Among 38,487 LCS-eligible patients, 1,671 (4.3%) were deemed LCS-inappropriate by clinicians, whereas 4,383 (11.4%) had an estimated 3-year competing risk of non-lung cancer death greater than 20%. Patients with higher competing risks of non-lung cancer death were more likely to be deemed LCS-inappropriate (odds ratio [OR], 2.66; 95% confidence interval [CI], 2.32-3.05). Older patients (ages 75-80; OR, 1.45; 95% CI, 1.18-1.78) and those with interstitial lung disease (OR, 1.98; 95% CI, 1.51-2.59) were more likely to be deemed LCS-inappropriate than would be explained by competing risk of non-lung cancer death, whereas patients currently smoking (OR, 0.65; 95% CI, 0.58-0.73) were less likely to be deemed LCS-inappropriate, suggesting that clinicians over- or underweighted these factors. The probability of being deemed LCS-inappropriate varied from 0.4% to 74%, depending on the clinician making the assessment (median OR, 3.07; 95% CI, 2.89-3.25). Conclusion: Concerningly, the likelihood that a patient is deemed LCS-inappropriate is more strongly associated with the clinician making the assessment than with patient characteristics. Patient selection may be optimized by providing decision support to help clinicians assess net LCS benefit.

A cost-effectiveness analysis of lung cancer screening with low-dose computed tomography and a polygenic risk score

INTRODUCTION

Several studies have proved that Polygenic Risk Score (PRS) is a potential candidate for realizing precision screening. The effectiveness of low-dose computed tomography (LDCT) screening for lung cancer has been proved to reduce lung cancer specific and overall mortality, but the cost-effectiveness of diverse screening strategies remained unclear.

METHODS

The comparative cost-effectiveness analysis used a Markov state-transition model to assess the potential effect and costs of the screening strategies incorporating PRS or not. A hypothetical cohort of 300,000 heavy smokers entered the study at age 50-74 years and were followed up until death or age 79 years. The model was run with a cycle length of 1 year. All the transition probabilities were validated and the performance value of PRS was extracted from published literature. A societal perspective was adopted and cost parameters were derived from databases of local medical insurance bureau. Sensitivity analyses and scenario analyses were conducted.

RESULTS

The strategy incorporating PRS was estimated to obtain an ICER of CNY 156,691.93 to CNY 221,741.84 per QALY gained compared with non-screening with the initial start age range across 50-74 years. The strategy that screened using LDCT alone from 70-74 years annually could obtain an ICER of CNY 80,880.85 per QALY gained, which was the most cost-effective strategy. The introduction of PRS as an extra eligible criteria was associated with making strategies cost-saving but also lose the capability of gaining more LYs compared with LDCT screening alone.

CONCLUSION

The PRS-based conjunctive screening strategy for lung cancer screening in China was not cost-effective using the willingness-to-pay threshold of 1 time Gross Domestic Product (GDP) per capita, and the optimal screening strategy for lung cancer still remains to be LDCT screening for now. Further optimization of the screening modality can be useful to consider adoption of PRS and prospective evaluation remains a research priority.

Predicting the Invasiveness of Pulmonary Adenocarcinomas in Pure Ground-Glass Nodules Using the Nodule Diameter: A Systematic Review, Meta-Analysis, and Validation in an Independent Cohort

The nodule diameter was commonly used to predict the invasiveness of pulmonary adenocarcinomas in pure ground-glass nodules (pGGNs). However, the diagnostic performance and optimal cut-off values were inconsistent. We conducted a meta-analysis to evaluate the diagnostic performance of the nodule diameter for predicting the invasiveness of pulmonary adenocarcinomas in pGGNs and validated the cut-off value of the diameter in an independent cohort. Relevant studies were searched through PubMed, MEDLINE, Embase, and the Cochrane Library, from inception until December 2022. The inclusion criteria comprised studies that evaluated the diagnostic accuracy of the nodule diameter to differentiate invasive adenocarcinomas (IAs) from non-invasive adenocarcinomas (non-IAs) in pGGNs. A bivariate mixed-effects regression model was used to obtain the diagnostic performance. Meta-regression analysis was performed to explore the heterogeneity. An independent sample of 220 pGGNs (82 IAs and 128 non-IAs) was enrolled as the validation cohort to evaluate the performance of the cut-off values. This meta-analysis finally included 16 studies and 2564 pGGNs (761 IAs and 1803 non-IAs). The pooled area under the curve, the sensitivity, and the specificity were 0.85 (95% confidence interval (CI), 0.82-0.88), 0.82 (95% CI, 0.78-0.86), and 0.73 (95% CI, 0.67-0.78). The diagnostic performance was affected by the measure of the diameter, the reconstruction matrix, and patient selection bias. Using the prespecified cut-off value of 10.4 mm for the mean diameter and 13.2 mm for the maximal diameter, the mean diameter showed higher sensitivity than the maximal diameter in the validation cohort (0.85 vs. 0.72, p < 0.01), while there was no significant difference in specificity (0.83 vs. 0.86, p = 0.13). The nodule diameter had adequate diagnostic performance in differentiating IAs from non-IAs in pGGNs and could be replicated in a validation cohort. The mean diameter with a cut-off value of 10.4 mm was recommended.

Screening for lung cancer: 2023 guideline update from the American Cancer Society

Lung cancer is the leading cause of mortality and person-years of life lost from cancer among US men and women. Early detection has been shown to be associated with reduced lung cancer mortality. Our objective was to update the American Cancer Society (ACS) 2013 lung cancer screening (LCS) guideline for adults at high risk for lung cancer. The guideline is intended to provide guidance for screening to health care providers and their patients who are at high risk for lung cancer due to a history of smoking. The ACS Guideline Development Group (GDG) utilized a systematic review of the LCS literature commissioned for the US Preventive Services Task Force 2021 LCS recommendation update; a second systematic review of lung cancer risk associated with years since quitting smoking (YSQ); literature published since 2021; two Cancer Intervention and Surveillance Modeling Network-validated lung cancer models to assess the benefits and harms of screening; an epidemiologic and modeling analysis examining the effect of YSQ and aging on lung cancer risk; and an updated analysis of benefit-to-radiation-risk ratios from LCS and follow-up examinations. The GDG also examined disease burden data from the National Cancer Institute's Surveillance, Epidemiology, and End Results program. Formulation of recommendations was based on the quality of the evidence and judgment (incorporating values and preferences) about the balance of benefits and harms. The GDG judged that the overall evidence was moderate and sufficient to support a strong recommendation for screening individuals who meet the eligibility criteria. LCS in men and women aged 50-80 years is associated with a reduction in lung cancer deaths across a range of study designs, and inferential evidence supports LCS for men and women older than 80 years who are in good health. The ACS recommends annual LCS with low-dose computed tomography for asymptomatic individuals aged 50-80 years who currently smoke or formerly smoked and have a ≥20 pack-year smoking history (strong recommendation, moderate quality of evidence). Before the decision is made to initiate LCS, individuals should engage in a shared decision-making discussion with a qualified health professional. For individuals who formerly smoked, the number of YSQ is not an eligibility criterion to begin or to stop screening. Individuals who currently smoke should receive counseling to quit and be connected to cessation resources. Individuals with comorbid conditions that substantially limit life expectancy should not be screened. These recommendations should be considered by health care providers and adults at high risk for lung cancer in discussions about LCS. If fully implemented, these recommendations have a high likelihood of significantly reducing death and suffering from lung cancer in the United States.

Absolute lung cancer risk increases among individuals with >15 quit-years: Analyses to inform the update of the American Cancer Society lung cancer screening guidelines

BACKGROUND

This report quantifies counteracting effects of quit-years and concomitant aging on lung cancer risk, especially on exceeding 15 quit-years, when the US Preventive Services Task Force (USPSTF) recommends curtailing lung-cancer screening.

METHODS

Cox models were fitted to estimate absolute lung cancer risk among Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO) and National Lung Screening Trial (NLST) participants who ever smoked. Absolute lung cancer risk and gainable years of life from screening for individuals aged 50 to 80 in the US-representative National Health Interview Survey (NHIS) 2015-2018 who ever smoked were projected. Relaxing USPSTF recommendations to 20/25/30 quit-years versus augmenting USPSTF criteria with individuals whose estimated gain in life expectancy from screening exceeded 16.2 days according to the Life Years From Screening-CT (LYFS-CT) prediction model was compared.

RESULTS

Absolute lung cancer risk increased by 8.7%/year (95% CI, 7.7%-9.7%; p < .001) as individuals aged beyond 15 quit-years in the PLCO, with similar results in NHIS and NLST. For example, mean 5-year lung cancer risk for those aged 65 years with 15 quit-years = 1.47% (95% CI, 1.35%-1.59%) versus 1.76% (95% CI, 1.62%-1.90%) for those aged 70 years with 20 quit-years in the PLCO. Removing the quit-year criterion would make 4.9 million more people eligible and increase the proportion of preventable lung cancer deaths prevented (sensitivity) from 63.7% to 74.2%. Alternatively, augmentation using LYFS-CT would make 1.7 million more people eligible while increasing the lung cancer death sensitivity to 74.0%.

CONCLUSIONS

Because of aging, absolute lung cancer risk increases beyond 15 quit-years, which does not support exemption from screening or curtailing screening once it has been initiated. Compared with relaxing the USPSTF quit-year criterion, augmentation using LYFS-CT could prevent most of the deaths at substantially superior efficiency, while also preventing deaths among individuals who currently smoke with low intensity or long duration.

Lung cancer diagnosis and mortality beyond 15 years since quit in individuals with a 20+ pack-year history: A systematic review

Current US lung cancer screening recommendations limit eligibility to adults with a pack-year (PY) history of ≥20 years and the first 15 years since quit (YSQ). The authors conducted a systematic review to better understand lung cancer incidence, risk and mortality among otherwise eligible individuals in this population beyond 15 YSQ. The PubMed and Scopus databases were searched through February 14, 2023, and relevant articles were searched by hand. Included studies examined the relationship between adults with both a ≥20-PY history and ≥15 YSQ and lung cancer diagnosis, mortality, and screening ineligibility. One investigator abstracted data and a second confirmed. Two investigators independently assessed study quality and certainty of evidence (COE) and resolved discordance through consensus. From 2636 titles, 22 studies in 26 articles were included. Three studies provided low COE of elevated lung cancer incidence beyond 15 YSQ, as compared with people who never smoked, and six studies provided moderate COE that the risk of a lung cancer diagnosis after 15 YSQ declines gradually, but with no clinically significant difference just before and after 15 YSQ. Studies examining lung cancer-related disparities suggest that outcomes after 15 YSQ were similar between African American/Black and White participants; increasing YSQ would expand eligibility for African American/Black individuals, but for a significantly larger proportion of White individuals. The authors observed that the risk of lung cancer not only persists beyond 15 YSQ but that, compared with individuals who never smoked, the risk may remain significantly elevated for 2 or 3 decades. Future research of nationally representative samples with consistent reporting across studies is needed, as are better data from which to examine the effects on health disparities across different populations.

Clinician Perceptions on Using Decision Tools to Support Prediction-Based Shared Decision Making for Lung Cancer Screening

Background

Considering a patient's full risk factor profile can promote personalized shared decision making (SDM). One way to accomplish this is through encounter tools that incorporate prediction models, but little is known about clinicians' perceptions of the feasibility of using these tools in practice. We examined how clinicians react to using one such encounter tool for personalizing SDM about lung cancer screening (LCS).

Design

We conducted a qualitative study based on field notes from academic detailing visits during a multisite quality improvement program. The detailer engaged one-on-one with 96 primary care clinicians across multiple Veterans Affairs sites (7 medical centers and 6 outlying clinics) to get feedback on 1) the rationale for prediction-based LCS and 2) how to use the DecisionPrecision (DP) encounter tool with eligible patients to personalize LCS discussions.

Results

Thematic content analysis from detailing visit data identified 6 categories of clinician willingness to use the DP tool to personalize SDM for LCS (adoption potential), varying from "Enthusiastic Potential Adopter" (n = 18) to "Definite Non-Adopter" (n = 16). Many clinicians (n = 52) articulated how they found the concept of prediction-based SDM highly appealing. However, to varying degrees, nearly all clinicians identified challenges to incorporating such an approach in routine practice.

Limitations

The results are based on the clinician's initial reactions rather than longitudinal experience.

Conclusions

While many primary care clinicians saw real value in using prediction to personalize LCS decisions, more support is needed to overcome barriers to using encounter tools in practice. Based on these findings, we propose several strategies that may facilitate the adoption of prediction-based SDM in contexts such as LCS.

Highlights

Encounter tools that incorporate prediction models promote personalized shared decision making (SDM), but little is known about clinicians' perceptions of the feasibility of using these tools in practice.We examined how clinicians react to using one such encounter tool for personalizing SDM about lung cancer screening (LCS).While many clinicians found the concept of prediction-based SDM highly appealing, nearly all clinicians identified challenges to incorporating such an approach in routine practice.We propose several strategies to overcome adoption barriers and facilitate the use of prediction-based SDM in contexts such as LCS.

Opportunistic Screening With Low-Dose Computed Tomography and Lung Cancer Mortality in China

Importance

Despite the recommendations of lung cancer screening guidelines and the evidence supporting the effectiveness of population-based lung screening, a common barrier to effective lung cancer screening is that the participation rates of low-dose computed tomography (LDCT) screening among individuals with the highest risk are not large. There are limited data from clinical practice regarding whether opportunistic LDCT screening is associated with reduced lung-cancer mortality.

Objective

To evaluate whether opportunistic LDCT screening is associated with improved prognosis among adults with lung cancer in mainland China.

Design, Setting, and Participants

This cohort study included patients diagnosed with lung cancer at Weihai Municipal Hospital Healthcare Group, Weihai City, China, from 2016 to 2021. Data were analyzed from January 2022 to February 2023.

Exposures

Data collected included demographic indicators, tumor characteristics, comorbidities, blood indexes, and treatment information. Patients were classified into screened and nonscreened groups on the basis of whether or not their lung cancer diagnosis occurred through opportunistic screening.

Main Outcomes and Measures

Follow-up outcome indicators included lung cancer-specific mortality and all-cause mortality. Propensity score matching (PSM) was adopted to account for potential imbalanced factors between groups. The associations between LDCT screening and outcomes were analyzed using Cox regression models based on the matched data. Propensity score regression adjustment and inverse probability treatment weighting were used for sensitivity analysis.

Results

A total of 5234 patients (mean [SD] baseline age, 61.8 [9.8] years; 2518 [48.1%] female) with complete opportunistic screening information were included in the analytical sample, with 2251 patients (42.91%) receiving their lung cancer diagnosis through opportunistic screening. After 1:1 PSM, 2788 patients (1394 in each group) were finally included. The baseline characteristics of the matched patients were balanced between groups. Opportunistic screening with LDCT was associated with a 49% lower risk of lung cancer death (HR, 0.51; 95% CI, 0.42-0.62) and 46% lower risk of all-cause death (HR, 0.54; 95% CI, 0.45-0.64).

Conclusions and Relevance

In this cohort study of patients with lung cancer, opportunistic lung cancer screening with LDCT was associated with lower lung cancer mortality and all-cause mortality. These findings suggest that opportunistic screening is an important supplement to population screening to improve prognosis of adults with lung cancer.

Noninvasive diagnosis of pulmonary nodules using a circulating tsRNA-based nomogram

Evaluating the accuracy of pulmonary nodule diagnosis avoids repeated low-dose computed tomography (LDCT)/CT scans or invasive examination, yet remains a main clinical challenge. Screening for new diagnostic tools is urgent. Herein, we established a nomogram based on the diagnostic signature of five circulating tsRNAs and CT information to predict malignant pulmonary nodules. In total, 249 blood samples of patients with pulmonary nodules were selected from three different lung cancer centers. Five tsRNAs were identified in the discovery and training cohorts and the diagnostic signature was established by the randomForest algorithm (tRF-Ser-TGA-003, tRF-Val-CAC-005, tRF-Ala-AGC-060, tRF-Val-CAC-024, and tiRNA-Gln-TTG-001). A nomogram was developed by combining tsRNA signature and CT information. The high level of accuracy was identified in an internal validation cohort (n = 83, area under the receiver operating characteristic curve [AUC] = 0.930, sensitivity 100.0%, specificity 73.8%) and external validation cohort (n = 66, AUC = 0.943, sensitivity 100.0%, specificity 86.8%). Furthermore, the diagnostic ability of our model discriminating invasive malignant ones from noninvasive lesions was assessed. A robust performance was achieved in the diagnosis of invasive malignant lesions in both training and validation cohorts (discovery cohort: AUC = 0.850, sensitivity 86.0%, specificity 81.4%; internal validation cohort: AUC = 0.784, sensitivity 78.8%, specificity 78.1%; and external validation cohort: AUC = 0.837, sensitivity 85.7%, specificity 84.0%). This novel circulating tsRNA-based diagnostic model has potential significance in predicting malignant pulmonary nodules. Application of the model could improve the accuracy of pulmonary nodule diagnosis and optimize surgical plans.

[Early detection of lung cancer - current status and implementation scenarios]

The prognosis of conventionally diagnosed lung cancer patients is still rather poor. Two large, randomized trials using screening by low dose CT could demonstrate that early detection in persons with smoking as risk factor can improve this prognosis. Early detection of lung cancer can be achieved by structured screening programs using low dose CT for persons at increased risk, but in addition also by consequent management of incidental pulmonary nodules, which are seen on imaging for other reasons. Integral part of these programs should be prevention measures, especially a consequent, repeated, low-threshold offer of a service for smoking cessation. Programs for lung cancer screening for persons at increased risk are only beneficial for the screenees and cost-effective, if the various parts of the program are optimally integrated and coordinated and all necessary disciplines (especially respiratory medicine, radiology, pathology, thoracic surgery, radiotherapy) are included in a multidisciplinary manner. For Germany the certified lung cancer centres in structured cooperation with physicians in private practice (respiratory physicians, radiologists, general practitioners) would be a good option. It is essential that there is a good perception for the need of early detection of lung cancer in politics and the public and that the persons at risk are reached, contacted and motivated by various methods.

Electronic Health Record Prompt to Improve Lung Cancer Screening in Primary Care

INTRODUCTION

Lung cancer is the leading cause of cancer death in the U.S. Combusted tobacco use, the primary risk factor, accounts for 90% of all lung cancers. Early detection of lung cancer improves survival, yet lung cancer screening rates are much lower than those of other cancer screening tests. Electronic health record (EHR) systems are an underutilized tool that could improve screening rates.

METHODS

This study was conducted in the Rutgers Robert Wood Johnson Medical Group, a university-affiliated network in New Brunswick, NJ. Two novel EHR workflow prompts were implemented on July 1, 2018. These prompts included fields to determine tobacco use and lung cancer screening eligibility and facilitated low-dose computed tomography ordering for eligible patients. The prompts were designed to improve tobacco use data entry, allowing for better lung cancer screening eligibility identification. Data were analyzed in 2022 retrospectively for the period July 1, 2017 to June 30, 2019. The analyses represented 48,704 total patient visits.

RESULTS

The adjusted odds of patient record completeness to determine eligibility for low-dose computed tomography (AOR=1.19, 95% CI=1.15, 1.23), eligibility for low-dose computed tomography (AOR=1.59, 95% CI=1.38, 1.82), and whether low-dose computed tomography was ordered (AOR=1.04, 95% CI=1.01, 1.07) all significantly increased after the electronic medical record prompts were implemented.

CONCLUSIONS

These findings show the utility and benefit of EHR prompts in primary care settings to increase identification for lung cancer screening eligibility as well as increased low-dose computed tomography ordering.

Implementation of Lung Cancer Screening in Primary Care and Pulmonary Clinics: Pragmatic Clinical Trial of Electronic Health Record-Integrated Everyday Shared Decision-Making Tool and Clinician-Facing Prompts

BACKGROUND

Although low-dose CT (LDCT) scan imaging lung cancer screening (LCS) can reduce lung cancer mortality, it remains underused. Shared decision-making (SDM) is recommended to assess the balance of benefits and harms for each patient.

RESEARCH QUESTION

Do clinician-facing electronic health record (EHR) prompts and an EHR-integrated everyday SDM tool designed to support routine incorporation of SDM into primary care improve LDCT scan imaging ordering and completion?

STUDY DESIGN AND METHODS

A preintervention and postintervention analysis was conducted in 30 primary care and four pulmonary clinics for visits with patients who met United States Preventive Services Task Force criteria for LCS. Propensity scores were used to adjust for covariates. Subgroup analyses were conducted based on the expected benefit from screening (high benefit vs intermediate benefit), pulmonologist involvement (ie, whether the patient was seen in a pulmonary clinic in addition to a primary care clinic), sex, and race and ethnicity.

RESULTS

In the 12-month preintervention phase among 1,090 eligible patients, 77 patients (7.1%) had LDCT scan imaging orders and 48 patients (4.4%) completed screenings. In the 9-month intervention phase among 1,026 eligible patients, 280 patients (27.3%) had LDCT scan imaging orders and 182 patients (17.7%) completed screenings. Adjusted ORs were 4.9 (95% CI, 3.4-6.9; P < .001) and 4.7 (95% CI, 3.1-7.1; P < .001) for LDCT imaging ordering and completion, respectively. Subgroup analyses showed increases in ordering and completion for all patient subgroups. In the intervention phase, the SDM tool was used by 23 of 102 ordering providers (22.5%) and for 69 of 274 patients (25.2%) for whom LDCT scan imaging was ordered and who needed SDM at the time of ordering.

INTERPRETATION

Clinician-facing EHR prompts and an EHR-integrated everyday SDM tool are promising approaches to improving LCS in the primary care setting. However, room for improvement remains. As such, further research is warranted.

TRIAL REGISTRY

ClinicalTrials.gov; No.: NCT04498052; URL: www.

CLINICALTRIALS

gov.

Considerations for using predictive models that include race as an input variable: The case study of lung cancer screening

Indiscriminate use of predictive models incorporating race can reinforce biases present in source data and lead to an exacerbation of health disparities. In some countries, such as the United States, there is therefore a push to remove race from prediction models; however, there are still many prediction models that use race as an input. Biomedical informaticists who are given the responsibility of using these predictive models in healthcare environments are likely to be faced with questions like how to deal with race covariates in these models. Thus, there is a need for a pragmatic framework to help model users think through how to include race in their chosen model so as to avoid inadvertently exacerbating disparities. In this paper, we use the case study of lung cancer screening to propose a simple framework to guide how model users can approach the use (or non-use) of race inputs in the predictive models they are tasked with leveraging in electronic health records and clinical workflows.

Accuracy of Preliminary Pathology for Robotic Bronchoscopic Biopsy

BACKGROUND

Diagnosis and treatment of peripheral pulmonary lesions (PPLs) currently require at least 2 procedures. An all-in-1 approach would require diagnosing malignancy with preliminary cytology results. This study investigated the concordance between preliminary cytology and final pathology results in biopsies of PPLs obtained by shape-sensing robotic-assisted bronchoscopy (ssRAB).

METHODS

This study was a retrospective, consecutive, single-arm, single-center study of 110 ssRABs for PPLs. Concordance was defined as agreement between preliminary cytology and final pathology results. Accuracy, sensitivity, specificity, positive and negative predictive values, and safety outcomes were examined.

RESULTS

The concordance was 89% for needle biopsies, 85% for forceps biopsies, and 92% overall, with substantial agreement. There was no significant association of concordance with patients' demographics or lesion characteristics. Preliminary cytology resulted in a malignant diagnosis in 70%, a nonmalignant diagnosis in 4%, and a nondiagnostic result in 26%, with accuracy of 86% and sensitivity of 84%. The total complication rate was 3.6%, with a pneumothorax rate of 1.8%.

CONCLUSIONS

This study compared the concordance of preliminary pathology results with final pathology results for ssRAB biopsies in PPLs. The results showed that preliminary samples have a high concordance with final pathology results and may enable management of PPLs with a single anesthetic procedure including biopsy, staging, and treatment.

Impact of lung cancer screening with low-dose chest computed tomography on an older population: a retrospective cohort study

Background

The older population is at high risk of lung cancer (LC). However, the importance of lung cancer screening (LCS) in this population is rarely investigated. Herein, we evaluated the effect of LCS with low-dose computed tomography (LDCT) in the older population.

Methods

This retrospective cohort study was conducted in a single center and included patients aged 70-80 years who had undergone LCS with LDCT. They were categorized into the early 70s (70-74 years) and late 70s (75-80 years) groups based on their age. Using propensity score matching, the control group included patients with non-screening-detected LC from an LC cohort. LC detection, characteristics, and treatment were compared between the early and late 70s groups and between screening-detected LC and non-screening-detected LC.

Results

The study included 1,281 participants who underwent LDCT for LCS, of whom 1,020 were in their early 70s and 261 in their late 70s. Among the screening groups, 87.7% of the patients were ever-smokers. The overall LC detection rate was 2.8%. Interestingly, the LC detection rate in the late 70s group was similar to that in the early 70s group (3.4% vs. 2.7%, P=0.485). Furthermore, the incidence of LC was 6.1 cases and 8.3 cases per 1,000 person-years in the early 70s and late 70s groups, respectively (P=0.428). When comparing LC characteristics, patients with screening-detected LC showed a higher proportion of stage I LC (52.8% vs. 30.6%, P=0.010) and a lower proportion of stage IV LC (19.4% vs. 42.2%, P=0.010) than those with non-screening-detected LC. Moreover, 80.6% of patients with screening-detected LC received appropriate tumor reduction treatment based on the cancer stage.

Conclusions

In the older population, LCS using LDCT showed remarkable detection of LC, with a higher proportion of cases detected at an early stage.

Individual- and neighborhood-level characteristics of lung cancer screening participants undergoing telemedicine shared decision making

BACKGROUND

Although lung cancer screening (LCS) for high-risk individuals reduces lung cancer mortality in clinical trial settings, many questions remain about how to implement high-quality LCS in real-world programs. With the increasing use of telemedicine in healthcare, studies examining this approach in the context of LCS are urgently needed. We aimed to identify sociodemographic and other factors associated with screening completion among individuals undergoing telemedicine Shared Decision Making (SDM) for LCS.

METHODS

This retrospective study examined patients who completed Shared Decision Making (SDM) via telemedicine between May 4, 2020 - March 18, 2021 in a centralized LCS program. Individuals were categorized into Complete Screening vs. Incomplete Screening subgroups based on the status of subsequent LDCT completion. A multi-level, multivariate model was constructed to identify factors associated with incomplete screening.

RESULTS

Among individuals undergoing telemedicine SDM during the study period, 20.6% did not complete a LDCT scan. Bivariate analysis demonstrated that Black/African-American race, Medicaid insurance status, and new patient type were associated with greater odds of incomplete screening. On multi-level, multivariate analysis, individuals who were new patients undergoing baseline LDCT or resided in a census tract with a high level of socioeconomic deprivation had significantly higher odds of incomplete screening. Individuals with a greater level of education experienced lower odds of incomplete screening.

CONCLUSIONS

Among high-risk individuals undergoing telemedicine SDM for LCS, predictors of incomplete screening included low education, high neighborhood-level deprivation, and new patient type. Future research should focus on testing implementation strategies to improve LDCT completion rates while leveraging telemedicine for high-quality LCS.

Methods for Using Race and Ethnicity in Prediction Models for Lung Cancer Screening Eligibility

Importance

Using race and ethnicity in clinical prediction models can reduce or inadvertently increase racial and ethnic disparities in medical decisions.

Objective

To compare eligibility for lung cancer screening in a contemporary representative US population by refitting the life-years gained from screening-computed tomography (LYFS-CT) model to exclude race and ethnicity vs a counterfactual eligibility approach that recalculates life expectancy for racial and ethnic minority individuals using the same covariates but substitutes White race and uses the higher predicted life expectancy, ensuring that historically underserved groups are not penalized.

Design, Setting, and Participants

The 2 submodels composing LYFS-CT NoRace were refit and externally validated without race and ethnicity: the lung cancer death submodel in participants of a large clinical trial (recruited 1993-2001; followed up until December 31, 2009) who ever smoked (n = 39 180) and the all-cause mortality submodel in the National Health Interview Survey (NHIS) 1997-2001 participants aged 40 to 80 years who ever smoked (n = 74 842, followed up until December 31, 2006). Screening eligibility was examined in NHIS 2015-2018 participants aged 50 to 80 years who ever smoked. Data were analyzed from June 2021 to September 2022.

Exposure

Including and removing race and ethnicity (African American, Asian American, Hispanic American, White) in each LYFS-CT submodel.

Main Outcomes and Measures

By race and ethnicity: calibration of the LYFS-CT NoRace model and the counterfactual approach (ratio of expected to observed [E/O] outcomes), US individuals eligible for screening, predicted days of life gained from screening by LYFS-CT.

Results

The NHIS 2015-2018 included 25 601 individuals aged 50 to 80 years who ever smoked (2769 African American, 649 Asian American, 1855 Hispanic American, and 20 328 White individuals). Removing race and ethnicity from the submodels underestimated lung cancer death risk (expected/observed [E/O], 0.72; 95% CI, 0.52-1.00) and all-cause mortality (E/O, 0.90; 95% CI, 0.86-0.94) in African American individuals. It also overestimated mortality in Hispanic American (E/O, 1.08, 95% CI, 1.00-1.16) and Asian American individuals (E/O, 1.14, 95% CI, 1.01-1.30). Consequently, the LYFS-CT NoRace model increased Hispanic American and Asian American eligibility by 108% and 73%, respectively, while reducing African American eligibility by 39%. Using LYFS-CT with the counterfactual all-cause mortality model better maintained calibration across groups and increased African American eligibility by 13% without reducing eligibility for Hispanic American and Asian American individuals.

Conclusions and Relevance

In this study, removing race and ethnicity miscalibrated LYFS-CT submodels and substantially reduced African American eligibility for lung cancer screening. Under counterfactual eligibility, no one became ineligible, and African American eligibility increased, demonstrating the potential for maintaining model accuracy while reducing disparities.

The Philadelphia Lung Cancer Learning Community: a multi-health-system, citywide approach to lung cancer screening

BACKGROUND

Lung cancer screening uptake for individuals at high risk is generally low across the United States, and reporting of lung cancer screening practices and outcomes is often limited to single hospitals or institutions. We describe a citywide, multicenter analysis of individuals receiving lung cancer screening integrated with geospatial analyses of neighborhood-level lung cancer risk factors.

METHODS

The Philadelphia Lung Cancer Learning Community consists of lung cancer screening clinicians and researchers at the 3 largest health systems in the city. This multidisciplinary, multi-institutional team identified a Philadelphia Lung Cancer Learning Community study cohort that included 11 222 Philadelphia residents who underwent low-dose computed tomography for lung cancer screening from 2014 to 2021 at a Philadelphia Lung Cancer Learning Community health-care system. Individual-level demographic and clinical data were obtained, and lung cancer screening participants were geocoded to their Philadelphia census tract of residence. Neighborhood characteristics were integrated with lung cancer screening counts to generate bivariate choropleth maps.

RESULTS

The combined sample included 37.8% Black adults, 52.4% women, and 56.3% adults who currently smoke. Of 376 residential census tracts in Philadelphia, 358 (95.2%) included 5 or more individuals undergoing lung cancer screening, and the highest counts were geographically clustered around each health system's screening sites. A relatively low percentage of screened adults resided in census tracts with high tobacco retailer density or high smoking prevalence.

CONCLUSIONS

The sociodemographic characteristics of lung cancer screening participants in Philadelphia varied by health system and neighborhood. These results suggest that a multicenter approach to lung cancer screening can identify vulnerable areas for future tailored approaches to improving lung cancer screening uptake. Future directions should use these findings to develop and test collaborative strategies to increase lung cancer screening at the community and regional levels.

Endobronchial ultrasound: a pictorial essay

BACKGROUND AND AIM

endobronchial ultrasound has gained widespread popularity in the last decade, becoming the primary technique for minimally invasive evaluation of the mediastinum and staging of lung cancer. Several tertiary and quaternary care institutes use this method, performed by trained and accredited specialists. Its main indications are (I) diagnosis and staging of lung cancer, (II) mediastinal lymphadenopathy diagnosis (III) sampling peripheral pulmonary lesions.

CONCLUSIONS

this manuscript aims to describe the operational potential of both convex endobronchial ultrasound probe and radial endobronchial ultrasound probe technology, focusing on lung cancer. This narrative review is complemented with by the description of peculiar clinical cases in which endobronchial ultrasound played a pivotal role in reaching the diagnosis.

Methylated Circulating Tumor DNA in Blood as a Tool for Diagnosing Lung Cancer: A Systematic Review and Meta-Analysis

Lung cancer is the leading cause of cancer-related deaths, and early detection is crucial for improving patient outcomes. Current screening methods using computed tomography have limitations, prompting interest in non-invasive diagnostic tools such as methylated circulating tumor DNA (ctDNA). The PRISMA guidelines for systematic reviews were followed. The electronic databases MEDLINE, Embase, Web of Science, and Cochrane Library were systematically searched for articles. The search string contained three main topics: Lung cancer, blood, and methylated ctDNA. The extraction of data and quality assessment were carried out independently by the reviewers. In total, 33 studies were eligible for inclusion in this systematic review and meta-analysis. The most frequently studied genes were SHOX2, RASSF1A, and APC. The sensitivity and specificity of methylated ctDNA varied across studies, with a summary sensitivity estimate of 46.9% and a summary specificity estimate of 92.9%. The area under the hierarchical summary receiver operating characteristics curve was 0.81. The included studies were generally of acceptable quality, although they lacked information in certain areas. The risk of publication bias was not significant. Based on the findings, methylated ctDNA in blood shows potential as a rule-in tool for lung cancer diagnosis but requires further research, possibly in combination with other biomarkers.

Assessing a biomarker's ability to reduce invasive procedures in patients with benign lung nodules: Results from the ORACLE study

A blood-based integrated classifier (IC) has been clinically validated to improve accuracy in assessing probability of cancer risk (pCA) for pulmonary nodules (PN). This study evaluated the clinical utility of this biomarker for its ability to reduce invasive procedures in patients with pre-test pCA ≤ 50%. This was a propensity score matching (PSM) cohort study comparing patients in the ORACLE prospective, multicenter, observational registry to control patients treated with usual care. This study enrolled patients meeting the intended use criteria for IC testing: pCA ≤ 50%, age ≥40 years, nodule diameter 8-30 mm, and no history of lung cancer and/or active cancer (except for non-melanomatous skin cancer) within 5 years. The primary aim of this study was to evaluate invasive procedure use on benign PNs of registry patients as compared to control patients. A total of 280 IC tested, and 278 control patients met eligibility and analysis criteria and 197 were in each group after PSM (IC and control groups). Patients in the IC group were 74% less likely to undergo an invasive procedure as compared to the control group (absolute difference 14%, p <0.001) indicating that for every 7 patients tested, one unnecessary invasive procedure was avoided. Invasive procedure reduction corresponded to a reduction in risk classification, with 71 patients (36%) in the IC group classified as low risk (pCA < 5%). The proportion of IC group patients with malignant PNs sent to surveillance were not statistically different than the control group, 7.5% vs 3.5% for the IC vs. control groups, respectively (absolute difference 3.91%, p 0.075). The IC for patients with a newly discovered PN has demonstrated valuable clinical utility in a real-world setting. Use of this biomarker can change physicians' practice and reduce invasive procedures in patients with benign pulmonary nodules. Trial registration: Clinical trial registration: ClinicalTrials.gov NCT03766958.

Integrative analysis of DNA methylomes reveals novel cell-free biomarkers in lung adenocarcinoma

Lung cancer is a leading cause of cancer-related deaths worldwide, with a low 5-year survival rate due in part to a lack of clinically useful biomarkers. Recent studies have identified DNA methylation changes as potential cancer biomarkers. The present study identified cancer-specific CpG methylation changes by comparing genome-wide methylation data of cfDNA from lung adenocarcinomas (LUAD) patients and healthy donors in the discovery cohort. A total of 725 cell-free CpGs associated with LUAD risk were identified. Then XGBoost algorithm was performed to identify seven CpGs associated with LUAD risk. In the training phase, the 7-CpGs methylation panel was established to classify two different prognostic subgroups and showed a significant association with overall survival (OS) in LUAD patients. We found that the methylation of cg02261780 was negatively correlated with the expression of its representing gene GNA11. The methylation and expression of GNA11 were significantly associated with LAUD prognosis. Based on bisulfite PCR, the methylation levels of five CpGs (cg02261780, cg09595050, cg20193802, cg15309457, and cg05726109) were further validated in tumor tissues and matched non-malignant tissues from 20 LUAD patients. Finally, validation of the seven CpGs with RRBS data of cfDNA methylation was conducted and further proved the reliability of the 7-CpGs methylation panel. In conclusion, our study identified seven novel methylation markers from cfDNA methylation data which may contribute to better prognosis for LUAD patients.

Differentiating Lung Nodules Due to Coccidioides from Those Due to Lung Cancer Based on Radiographic Appearance

BACKGROUND

Coccidioidomycosis (cocci) is an endemic fungal disease that can cause asymptomatic or post-symptomatic lung nodules which are visible on chest CT scanning. Lung nodules are common and can represent early lung cancer. Differentiating lung nodules due to cocci from those due to lung cancer can be difficult and lead to invasive and expensive evaluations.

MATERIALS AND METHODS

We identified 302 patients with biopsy-proven cocci or bronchogenic carcinoma seen in our multidisciplinary nodule clinic. Two experienced radiologists who were blinded to the diagnosis read the chest CT scans and identified radiographic characteristics to determine their utility in differentiating lung cancer nodules from those due to cocci.

RESULTS

Using univariate analysis, we identified several radiographic findings that differed between lung cancer and cocci infection. We then entered these variables along with age and gender into a multivariate model and found that age, nodule diameter, nodule cavitation, presence of satellite nodules and radiographic presence of chronic lung disease differed significantly between the two diagnoses. Three findings, cavitary nodules, satellite nodules and chronic lung disease, have sufficient discrimination to potentially be useful in clinical decision-making.

CONCLUSIONS

Careful evaluation of the three obtained radiographic findings can significantly improve our ability to differentiate benign coccidioidomycosis infection from lung cancer in an endemic region for the fungal disease. Using these data may significantly reduce the cost and risk associated with distinguishing the cause of lung nodules in these patients by preventing unnecessary invasive studies.

Lung Cancer Screening Among U.S. Military Veterans by Health Status and Race and Ethnicity, 2017-2020: A Cross-Sectional Population-Based Study

Introduction

Veterans are at high risk for lung cancer and are an important group for lung cancer screening. Previous research suggests that lung cancer screening may not be reaching healthier and/or non-White individuals, who stand to benefit most from lung cancer screening. We sought to test whether lung cancer screening is associated with poor health and/or race and ethnicity among veterans.

Methods

This cross-sectional, population-based study included veterans eligible for lung cancer screening (aged 55-79 years, ≥30 pack-year smoking history, current smokers or quit within 15 years, no previous lung cancer) in the 2017-2020 Behavioral Risk Factor Surveillance System surveys. Exposures were (1) poor health, defined as fair/poor health status and difficulty walking or climbing stairs, aligning with eligibility criteria for a pivotal lung cancer screening trial, and (2) race/ethnicity. The outcome was a receipt of lung cancer screening. All variables were self-reported.

Results

Of 3,376 lung cancer screening-eligible veterans representing an underlying population of 866,000 individuals, 20.3% (95% CI=17.3, 23.6) had poor health, and 13.7% (95% CI=10.6, 17.5) identified as non-White. Poor health was strongly associated with lung cancer screening (adjusted RR=1.64, 95% CI=1.06, 2.27); one third of veterans screened for lung cancer would not qualify for a pivotal lung cancer screening trial in terms of health. Marked racial disparities were observed among veterans: after adjustment, non-White veterans were 67% less likely to report lung cancer screening than White veterans (adjusted RR=0.33, 95% CI=0.11, 0.66).

Conclusions

Lung cancer screening is correlated with poorer health and White race/ethnicity among veterans, which may undermine its population-level effectiveness. These results highlight the need to promote lung cancer screening, especially for healthier and/or non-White veterans, an important group of Americans for lung cancer screening.

A Closer Look-Who Are We Screening for Lung Cancer?

Objective

To evaluate the characteristics of individuals receiving lung cancer screening (LCS) and identify those with potentially limited benefit owing to coexisting chronic illnesses and/or comorbidities.

Patients and Methods

In this retrospective study in the United States, patients were selected from a large clinical database who received LCS from January 1, 2019, through December 31, 2019, with at least 1 year of continuous enrollment. We assessed for potentially limited benefit in LCS defined strictly as not meeting the traditional risk factor inclusion criteria (age <55 years or >80 years, previous computed tomography scan within 11 months before an LCS examination, or a history of nonskin cancer) or liberally as having the potential exclusion criteria related to comorbid life-limiting conditions, such as cardiac and/or respiratory disease.

Results

A total of 51,551 patients were analyzed. Overall, 8391 (16.3%) individuals experienced a potentially limited benefit from LCS. Among those who did not meet the strict traditional inclusion criteria, 317 (3.8%) were because of age, 2350 (28%) reported a history of nonskin malignancy, and 2211 (26.3%) underwent a previous computed tomography thorax within 11 months before an LCS examination. Of those with potentially limited benefit owing to comorbidity, 3680 (43.9%) were because of severe respiratory comorbidity (937 [25.5%] with any hospitalization for coronary obstructive pulmonary disease, interstitial lung disease, or respiratory failure; 131 [3.6%] with hospitalization for respiratory failure requiring mechanical ventilation; or 3197 [86.9%] with chronic obstructive disease/interstitial lung disease requiring outpatient oxygen) and 721 (8.59%) with cardiac comorbidity.

Conclusion

Up to 1 of 6 low-dose computed tomography examinations may have limited benefit from LCS.

A protocol for a cluster randomized trial of care delivery models to improve the quality of smoking cessation and shared decision making for lung cancer screening

BACKGROUND

Patients eligible for lung cancer screening (LCS) are those at high risk of lung cancer due to their smoking histories and age. While screening for LCS is effective in lowering lung cancer mortality, primary care providers are challenged to meet beneficiary eligibility for LCS from the Centers for Medicare & Medicaid Services, including a patient counseling and shared decision-making (SDM) visit with the use of patient decision aid(s) prior to screening.

METHODS

We will use an effectiveness-implementation type I hybrid design to: 1) identify effective, scalable smoking cessation counseling and SDM interventions that are consistent with recommendations, can be delivered on the same platform, and are implemented in real-world clinical settings; 2) examine barriers and facilitators of implementing the two approaches to delivering smoking cessation and SDM for LCS; and 3) determine the economic implications of implementation by assessing the healthcare resources required to increase smoking cessation for the two approaches by delivering smoking cessation within the context of LCS. Providers from different healthcare organizations will be randomized to usual care (providers delivering smoking cessation and SDM on site) vs. centralized care (smoking cessation and SDM delivered remotely by trained counselors). The primary trial outcomes will include smoking abstinence at 12-weeks and knowledge about LCS measured at 1-week after baseline.

CONCLUSION

This study will provide important new evidence about the effectiveness and feasibility of a novel care delivery model for addressing the leading cause of lung cancer deaths and supporting high-quality decisions about LCS.

CLINICALTRIALS

GOV PROTOCOL REGISTRATION

NCT04200534 TRIAL REGISTRATION: ClinicalTrials.govNCT04200534.

Using User-Centered Design to Facilitate Adherence to Annual Lung Cancer Screening: Protocol for a Mixed Methods Study for Intervention Development

BACKGROUND

Lung cancer is the leading cause of cancer-related death in the United States, with the majority of lung cancer occurrence diagnosed after the disease has already metastasized. Lung cancer screening (LCS) with low-dose computed tomography can diagnose early-stage disease, especially when eligible individuals participate in screening on a yearly basis. Unfortunately, annual adherence has emerged as a challenge for academic and community screening programs, endangering the individual and population health benefits of LCS. Reminder messages have effectively increased adherence rates in breast, colorectal, and cervical cancer screenings but have not been tested with LCS participants who experience unique barriers to screening associated with the stigma of smoking and social determinants of health.

OBJECTIVE

This research aims to use a theory-informed, multiphase, and mixed methods approach with LCS experts and participants to develop a set of clear and engaging reminder messages to support LCS annual adherence.

METHODS

In aim 1, survey data informed by the Cognitive-Social Health Information Processing model will be collected to assess how LCS participants process health information aimed at health protective behavior to develop content for reminder messages and pinpoint options for message targeting and tailoring. Aim 2 focuses on identifying themes for message imagery through a modified photovoice activity that asks participants to identify 3 images that represent LCS and then participate in an interview about the selection, likes, and dislikes of each photo. A pool of candidate messages for multiple delivery platforms will be developed in aim 3, using results from aim 1 for message content and aim 2 for imagery selection. The refinement of message content and imagery combinations will be completed through iterative feedback from LCS experts and participants.

RESULTS

Data collection began in July 2022 and will be completed by May 2023. The final reminder message candidates are expected to be completed by June 2023.

CONCLUSIONS

This project proposes a novel approach to facilitate adherence to annual LCS through the development of reminder messages that embrace content and imagery representative of the target population directly in the design process. Developing effective strategies to increase LCS adherence is instrumental in achieving optimal LCS outcomes at individual and population health levels.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/46657.

A multicenter evaluation of a deep learning software (LungQuant) for lung parenchyma characterization in COVID-19 pneumonia

BACKGROUND

The role of computed tomography (CT) in the diagnosis and characterization of coronavirus disease 2019 (COVID-19) pneumonia has been widely recognized. We evaluated the performance of a software for quantitative analysis of chest CT, the LungQuant system, by comparing its results with independent visual evaluations by a group of 14 clinical experts. The aim of this work is to evaluate the ability of the automated tool to extract quantitative information from lung CT, relevant for the design of a diagnosis support model.

METHODS

LungQuant segments both the lungs and lesions associated with COVID-19 pneumonia (ground-glass opacities and consolidations) and computes derived quantities corresponding to qualitative characteristics used to clinically assess COVID-19 lesions. The comparison was carried out on 120 publicly available CT scans of patients affected by COVID-19 pneumonia. Scans were scored for four qualitative metrics: percentage of lung involvement, type of lesion, and two disease distribution scores. We evaluated the agreement between the LungQuant output and the visual assessments through receiver operating characteristics area under the curve (AUC) analysis and by fitting a nonlinear regression model.

RESULTS

Despite the rather large heterogeneity in the qualitative labels assigned by the clinical experts for each metric, we found good agreement on the metrics compared to the LungQuant output. The AUC values obtained for the four qualitative metrics were 0.98, 0.85, 0.90, and 0.81.

CONCLUSIONS

Visual clinical evaluation could be complemented and supported by computer-aided quantification, whose values match the average evaluation of several independent clinical experts.

KEY POINTS

We conducted a multicenter evaluation of the deep learning-based LungQuant automated software. We translated qualitative assessments into quantifiable metrics to characterize coronavirus disease 2019 (COVID-19) pneumonia lesions. Comparing the software output to the clinical evaluations, results were satisfactory despite heterogeneity of the clinical evaluations. An automatic quantification tool may contribute to improve the clinical workflow of COVID-19 pneumonia.

Secondary prevention and treatment innovation of early stage non-small cell lung cancer: Impact on diagnostic-therapeutic pathway from a multidisciplinary perspective

Lung cancer (LC) is the leading cause of cancer-related death worldwide, mostly because the lack of a screening program so far. Although smoking cessation has a central role in LC primary prevention, several trials on LC screening through low-dose computed tomography (LDCT) in a high risk population showed a significant reduction of LC related mortality. Most trials showed heterogeneity in terms of selection criteria, comparator arm, detection nodule method, timing and intervals of screening and duration of the follow-up. LC screening programs currently active in Europe as well as around the world will lead to a higher number of early-stage Non Small Cell Lung Cancer (NSCLC) at the diagnosis. Innovative drugs have been recently transposed from the metastatic to the perioperative setting, leading to improvements in terms of resection rates and pathological responses after induction chemoimmunotherapy, and disease free survival with targeted agents and immune checkpoint inhibitors. The present review summarizes available evidence about LC screening, highlighting potential pitfalls and benefits and underlining the impact on the diagnostic therapeutic pathway of NSCLC from a multidisciplinary perspective. Future perspectives in terms of circulating biomarkers under evaluation for patients' risk stratification as well as a focus on recent clinical trials results and ongoing studies in the perioperative setting will be also presented.

Lung cancer screening

Randomised controlled trials, including the National Lung Screening Trial (NLST) and the NELSON trial, have shown reduced mortality with lung cancer screening with low-dose CT compared with chest radiography or no screening. Although research has provided clarity on key issues of lung cancer screening, uncertainty remains about aspects that might be critical to optimise clinical effectiveness and cost-effectiveness. This Review brings together current evidence on lung cancer screening, including an overview of clinical trials, considerations regarding the identification of individuals who benefit from lung cancer screening, management of screen-detected findings, smoking cessation interventions, cost-effectiveness, the role of artificial intelligence and biomarkers, and current challenges, solutions, and opportunities surrounding the implementation of lung cancer screening programmes from an international perspective. Further research into risk models for patient selection, personalised screening intervals, novel biomarkers, integrated cardiovascular disease and chronic obstructive pulmonary disease assessments, smoking cessation interventions, and artificial intelligence for lung nodule detection and risk stratification are key opportunities to increase the efficiency of lung cancer screening and ensure equity of access.

Timely Curative Treatment and Overall Mortality Among Veterans With Stage I NSCLC

Introduction

Early stage lung cancer (LC) outcomes depend on the receipt of timely therapy. We aimed to determine the proportions of Veterans with stage I NSCLC in the age group eligible for LC screening (LCS) receiving timely curative treatment (≤12 wk after diagnosis), the factors associated with timely treatment and modality, and the factors associated with overall mortality.

Methods

Retrospective cohort study in Veterans aged 55 to 80 years when diagnosed with stage I NSCLC during 2011 to 2015. We used multivariate logistic regression models to determine factors associated with receiving timely therapy and receiving surgery versus stereotactic body radiation therapy (SBRT). We used multivariate Cox proportional hazards regression analysis to determine factors associated with overall mortality.

Results

We identified 4796 Veterans with stage I NSCLC; the cohort was predominantly older, White males, current or former smokers, and living in urban areas. Overall, 84% underwent surgery and 16% underwent SBRT. The median time to treatment was 63 days (61 d for surgery; 71 d for SBRT), with 30% treated more than 12 weeks. Unmarried Veterans with higher social deprivation index were less likely to receive timely therapy. Black race, female sex, and never smoking were associated with lower overall mortality. Older Veterans receiving treatment >12 wk, with higher comorbidity index, and squamous cell carcinoma had higher overall mortality.

Conclusions

A total of 30% of the Veterans with stage I NSCLC in the age group eligible for LCS received curative treatment more than 12 weeks after diagnosis, which was associated with higher overall mortality. Delays in LC treatment could decrease the mortality benefits of LCS among the Veterans.

Disparities in thoracic surgical oncology

Disparities in access and outcomes of thoracic surgical oncology are long standing. This article examines the patient, population, and systems-level factors that contribute to these disparities and inequities. The need for research and policy to identify and solve these problems is apparent. As leaders in the field of thoracic oncology, surgeons will be instrumental in narrowing these gaps and moving the discipline forward.