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

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

Rates of Downstream Procedures and Complications Associated With Lung Cancer Screening in Routine Clinical Practice : A Retrospective Cohort Study.

BACKGROUND: Lung cancer screening (LCS) using low-dose computed tomography (LDCT) reduces lung cancer mortality but can lead to downstream procedures, complications, and other potential harms. Estimates of these events outside NLST (National Lung Screening Trial) have been variable and lacked evaluation by screening result, which allows more direct comparison with trials. OBJECTIVE: To identify rates of downstream procedures and complications associated with LCS. DESIGN: Retrospective cohort study. SETTING: 5 U.S. health care systems. PATIENTS: Individuals who completed a baseline LDCT scan for LCS between 2014 and 2018. MEASUREMENTS: Outcomes included downstream imaging, invasive diagnostic procedures, and procedural complications. For each, absolute rates were calculated overall and stratified by screening result and by lung cancer detection, and positive and negative predictive values were calculated. RESULTS: Among the 9266 screened patients, 1472 (15.9%) had a baseline LDCT scan showing abnormalities, of whom 140 (9.5%) were diagnosed with lung cancer within 12 months (positive predictive value, 9.5% [95% CI, 8.0% to 11.0%]; negative predictive value, 99.8% [CI, 99.7% to 99.9%]; sensitivity, 92.7% [CI, 88.6% to 96.9%]; specificity, 84.4% [CI, 83.7% to 85.2%]). Absolute rates of downstream imaging and invasive procedures in screened patients were 31.9% and 2.8%, respectively. In patients undergoing invasive procedures after abnormal findings, complication rates were substantially higher than those in NLST (30.6% vs. 17.7% for any complication; 20.6% vs. 9.4% for major complications). LIMITATION: Assessment of outcomes was retrospective and was based on procedural coding. CONCLUSION: The results indicate substantially higher rates of downstream procedures and complications associated with LCS in practice than observed in NLST. Diagnostic management likely needs to be assessed and improved to ensure that screening benefits outweigh potential harms. PRIMARY FUNDING SOURCE: National Cancer Institute and Gordon and Betty Moore Foundation.

An NLP Framework for the Extraction of Concept Measurements from Radiology and Pathology Notes.

Natural language processing (NLP) tools can automate the identification of cancer patients eligible for specific pathways. We developed and validated a cancer agnostic, rules-based NLP framework to extract the dimensions and measurements of several concepts from pathology and radiology reports. This framework was then efficiently and cost-effectively deployed to identify patients eligible for breast, lung, and prostate cancers clinical pathways.

Uptake of Lung Cancer Screening CT After a Provider Order for Screening in the PROSPR-Lung Consortium.

BACKGROUND: Uptake of lung cancer screening (LCS) has been slow with less than 20% of eligible people who currently or formerly smoked reported to have undergone a screening CT. OBJECTIVE: To determine individual-, health system-, and neighborhood-level factors associated with LCS uptake after a provider order for screening. DESIGN AND SUBJECTS: We conducted an observational cohort study of screening-eligible patients within the Population-based Research to Optimize the Screening Process (PROSPR)-Lung Consortium who received a radiology referral/order for a baseline low-dose screening CT (LDCT) from a healthcare provider between January 1, 2015, and June 30, 2019. MAIN MEASURES: The primary outcome is screening uptake, defined as LCS-LDCT completion within 90 days of the screening order date. KEY RESULTS: During the study period, 18,294 patients received their first order for LCS-LDCT. Orders more than doubled from the beginning to the end of the study period. Overall, 60% of patients completed screening after receiving their first LCS-LDCT order. Across health systems, uptake varied from 41 to 87%. In both univariate and multivariable analyses, older age, male sex, former smoking status, COPD, and receiving care in a centralized LCS program were positively associated with completing LCS-LDCT. Unknown insurance status, other or unknown race, and lower neighborhood socioeconomic status, as measured by the Yost Index, were negatively associated with screening uptake. CONCLUSIONS: Overall, 40% of patients referred for LCS did not complete a LDCT within 90 days, highlighting a substantial gap in the lung screening care pathway, particularly in decentralized screening programs.

Patient Preferences for Lung Cancer Interception Therapy.

Importance: Interception therapy requires individuals to undergo treatment to prevent a future medical event, but little is known about preferences of individuals at high risk for lung cancer and whether they would be interested in this type of treatment. Objective: To explore preferences of individuals at high risk for lung cancer for potential interception therapies to reduce this risk. Design, Setting, and Participants: This survey study used a discrete-choice experiment and included hypothetical lung cancer interception treatments with 4 attributes: reduction in lung cancer risk over 3 years, injection site reaction severity, nonfatal serious infection, and death from serious infection. Respondents were assigned to a baseline lung cancer risk of 6%, 10%, or 16% over 3 years. The discrete-choice experiment was administered online (July 13 to September 6, 2022) to US respondents eligible for lung cancer screening according to US Preventive Services Task Force guidelines. Participants included adults aged 50 to 80 years with at least a 20 pack-year smoking history. Statistical analysis was performed from September to December 2022. Main Outcomes and Measures: Attribute-level preference weights were estimated, and conditional relative attribute importance, maximum acceptable risks, and minimum acceptable benefits were calculated. Characteristics of respondents who always selected no treatment were also explored. Results: Of the 803 survey respondents, 495 (61.6%) were female, 138 (17.2%) were African American or Black, 55 (6.8%) were Alaska Native, American Indian, or Native American, 44 (5.5%) were Asian or Native Hawaiian or Other Pacific Islander, 104 (13.0%) were Hispanic, Latin American, or Latinx, and 462 (57.5%) were White, Middle Eastern or North African, or a race or ethnicity not listed; and mean (SD) age was 63.0 (7.5) years. Most respondents were willing to accept interception therapy and viewed reduction in lung cancer risk as the most important attribute. Respondents would accept a greater than or equal to a 12.0 percentage point increase in risk of nonfatal serious infection if lung cancer risk was reduced by at least 20.0 percentage points; and a greater than or equal to 1.2 percentage point increase in risk of fatal serious infection if lung cancer risk was reduced by at least 30.0 percentage points. Respondents would require at least a 15.4 (95% CI, 10.6-20.2) percentage point decrease in lung cancer risk to accept a 12.0 percentage point increase in risk of nonfatal serious infection; and at least a 23.1 (95% CI, 16.4-29.8) percentage point decrease in lung cancer risk to accept a 1.2 percentage point increase in risk of death from serious infection. Respondents who were unwilling to accept interception therapy in any question (129 [16.1%]) were more likely to be older and to currently smoke with no prior cessation attempt, and less likely to have been vaccinated against COVID-19 or examined for skin cancer. Conclusions and Relevance: In this survey study of individuals at high risk of lung cancer, most respondents were willing to consider interception therapy. These results suggest the importance of benefit-risk assessments for future lung cancer interception treatments.

Development of an Electronic Health Record-Based Algorithm for Predicting Lung Cancer Screening Eligibility in the Population-Based Research to Optimize the Screening Process Lung Research Consortium.

PURPOSE: Lung cancer screening (LCS) guidelines in the United States recommend LCS for those age 50-80 years with at least 20 pack-years smoking history who currently smoke or quit within the last 15 years. We tested the performance of simple smoking-related criteria derived from electronic health record (EHR) data and developed and tested the performance of a multivariable model in predicting LCS eligibility. METHODS: Analyses were completed within the Population-based Research to Optimize the Screening Process Lung Consortium (PROSPR-Lung). In our primary validity analyses, the reference standard LCS eligibility was based on self-reported smoking data collected via survey. Within one PROSPR-Lung health system, we used a training data set and penalized multivariable logistic regression using the Least Absolute Shrinkage and Selection Operator to select EHR-based variables into the prediction model including demographics, smoking history, diagnoses, and prescription medications. A separate test data set assessed model performance. We also conducted external validation analysis in a separate health system and reported AUC, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy metrics associated with the Youden Index. RESULTS: There were 14,214 individuals with survey data to assess LCS eligibility in primary analyses. The overall performance for assigning LCS eligibility status as measured by the AUC values at the two health systems was 0.940 and 0.938. At the Youden Index cutoff value, performance metrics were as follows: accuracy, 0.855 and 0.895; sensitivity, 0.886 and 0.920; specificity, 0.896 and 0.850; PPV, 0.357 and 0.444; and NPV, 0.988 and 0.992. CONCLUSION: Our results suggest that health systems can use an EHR-derived multivariable prediction model to aid in the identification of those who may be eligible for LCS.

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.

Together We Go Farther: Improving Access to Cancer Screening Through a Multidisciplinary, One-Stop-Shop Approach.

RATIONALE AND OBJECTIVES: Despite significant scientific advances in cancer treatment in recent decades, Black Americans still face marked inequities in cancer screening, diagnosis, and treatment. Redressing these persistent inequities will require innovative strategies for community engagement. Radiologists, as experts in cancer screening and diagnosis for multiple malignancies, including breast, lung, and colon, are ideally suited to lead and implement community-based strategies to address local cancer disparities. MATERIALS AND METHODS: Through an established academic-community partnership in West Philadelphia built over the course of multiple prior community healthcare events, the authors piloted a novel radiology-led multidisciplinary approach to improve access to cancer screening for the predominantly Black, medically-underserved residents. Using a "one-stop-shop" framework to provide a comprehensive suite of screening and ancillary services in the heart of the community, the authors sought to remove as many impediments to screening as possible. RESULTS: Approximately 350 participants attended the health fair, and a total of 232 screening tests or assessments were completed. Data from this event suggest that this inclusive approach, as well as the use of a health fair "passport" to incentivize engagement, can successfully improve access to screening and follow-up in an underserved community. CONCLUSION: This "one-stop-shop" community approach can be replicated by radiology-led teams in other settings as a high-value, scalable opportunity to reduce disparities in access to cancer screening.

Estimating Pack-Year Eligibility for Lung Cancer Screening Using 2 Yes or No Questions.

This cross-sectional study describes the development and testing the accuracy of using 2 yes or no questions to estimate pack-year eligibility for lung cancer screening.

Lung Cancer Screening Decision Aid Designed for a Primary Care Setting: A Randomized Clinical Trial.

Importance: Guidelines recommend shared decision-making prior to initiating lung cancer screening (LCS). However, evidence is lacking on how to best implement shared decision-making in clinical practice. Objective: To evaluate the impact of an LCS Decision Tool (LCSDecTool) on the quality of decision-making and LCS uptake. Design, Setting, and Participants: This randomized clinical trial enrolled participants at Veteran Affairs Medical Centers in Philadelphia, Pennsylvania; Milwaukee, Wisconsin; and West Haven, Connecticut, from March 18, 2019, to September 29, 2021, with follow-up through July 18, 2022. Individuals aged 55 to 80 years with a smoking history of at least 30 pack-years who were current smokers or had quit within the past 15 years were eligible to participate. Individuals with LCS within 15 months were excluded. Of 1047 individuals who were sent a recruitment letter or had referred themselves, 140 were enrolled. Intervention: A web-based patient- and clinician-facing LCS decision support tool vs an attention control intervention. Main Outcome and Measures: The primary outcome was decisional conflict at 1 month. Secondary outcomes included decisional conflict immediately after intervention and 3 months after intervention, knowledge, decisional regret, and anxiety immediately after intervention and 1 and 3 months after intervention and LCS by 6 months. Results: Of 140 enrolled participants (median age, 64.0 [IQR, 61.0-69.0] years), 129 (92.1%) were men and 11 (7.9%) were women. Of 137 participants with data available, 75 (53.6%) were African American or Black and 62 (44.3%) were White; 4 participants (2.9%) also reported Hispanic or Latino ethnicity. Mean decisional conflict score at 1 month did not differ between the LCSDecTool and control groups (25.7 [95% CI, 21.4-30.1] vs 29.9 [95% CI, 25.6-34.2], respectively; P = .18). Mean LCS knowledge score was greater in the LCSDecTool group immediately after intervention (7.0 [95% CI, 6.3-7.7] vs 4.9 [95% CI, 4.3-5.5]; P < .001) and remained higher at 1 month (6.3 [95% CI, 5.7-6.8] vs 5.2 [95% CI, 4.5-5.8]; P = .03) and 3 months (6.2 [95% CI, 5.6-6.8] vs 5.1 [95% CI, 4.4-5.8]; P = .01). Uptake of LCS was greater in the LCSDecTool group at 6 months (26 of 69 [37.7%] vs 15 of 71 [21.1%]; P = .04). Conclusions and Relevance: In this randomized clinical trial of an LCSDecTool compared with attention control, no effect on decisional conflict occurred at 1 month. The LCSDecTool used in the primary care setting did not yield a significant difference in decisional conflict. The intervention led to greater knowledge and LCS uptake. These findings can inform future implementation strategies and research in LCS shared decision-making. Trial Registration: ClinicalTrials.gov Identifier: NCT02899754.

Application of team science best practices to the project management of a large, multi-site lung cancer screening research consortium.

Research is increasingly conducted through multi-institutional consortia, and best practices for establishing multi-site research collaborations must be employed to ensure efficient, effective, and productive translational research teams. In this manuscript, we describe how the Population-based Research to Optimize the Screening Process Lung Research Center (PROSPR-Lung) utilized evidence-based Science of Team Science (SciTS) best practices to establish the consortium's infrastructure and processes to promote translational research in lung cancer screening. We provide specific, actionable examples of how we: (1) developed and reinforced a shared mission, vision, and goals; (2) maintained a transparent and representative leadership structure; (3) employed strong research support systems; (4) provided efficient and effective data management; (5) promoted interdisciplinary conversations; and (6) built a culture of trust. We offer guidance for managing a multi-site research center and data repository that may be applied to a variety of settings. Finally, we detail specific project management tools and processes used to drive collaboration, efficiency, and scientific productivity.

Association of multi-criteria derived air toxics hazard score with lung cancer incidence in a major metropolitan area.

Background: Lung cancer remains a major health problem world-wide. Environmental exposure to lung cancer carcinogens can affect lung cancer incidence. We investigated the association between lung cancer incidence and an air toxics hazard score of environmental carcinogen exposures derived previously under the exposome concept. Methods: Lung cancer cases diagnosed in Philadelphia and the surrounding counties between 2008 and 2017 were identified from the Pennsylvania Cancer Registry. Age-adjusted incidence rates at the ZIP code level were calculated based on the residential address at diagnosis. The air toxics hazard score, an aggregate measure for lung cancer carcinogen exposures, was derived using the criteria of toxicity, persistence, and occurrence. Areas with high incidence or hazard score were identified. Spatial autoregressive models were fitted to evaluate the association, with and without adjusting for confounders. Stratified analysis by smoking prevalence was performed to examine potential interactions. Results: We observed significantly higher age-adjusted incidence rates in ZIP codes that had higher air toxics hazard score values after controlling for demographic variables, smoking prevalence, and proximity to major highways. Analyzes stratified by smoking prevalence suggested that exposure to environmental lung carcinogens had a larger effect on cancer incidence in locations with higher smoking prevalence. Conclusion: The positive association between the multi-criteria derived air toxics hazard score and lung cancer incidence provides the initial evidence to validate the hazard score as an aggregate measure of carcinogenic exposures in the environment. The hazard score can be used to supplement the existing risk factors in identifying high risk individuals. Communities with higher incidence/hazard score may benefit from greater awareness of lung cancer risk factors and targeted screening programs.

The Effect of Definitions and Cancer Prevalence on Diagnostic Yield Estimates of Bronchoscopy: A Simulation-based Analysis.

Rationale: Studies of bronchoscopy have reported diagnostic yield (DY) using different calculation methods, which has hindered comparisons across studies. Objectives: To quantify the effect of the variability of four methods on DY estimates of bronchoscopy. Methods: We performed a simulation-based analysis of patients undergoing bronchoscopy using variations around base case assumptions for cancer prevalence (60%), distribution of nonmalignant findings, and degree of follow-up information at a fixed sensitivity of bronchoscopy for malignancy (80%). We calculated DY, the rate of true positives and true negatives (TNs), using four methods. Method 1 considered malignant and specific benign findings at index bronchoscopy as true positives and TNs, respectively. Method 2 included nonspecific benign findings as TNs. Method 3 considered nonspecific benign findings cases as TNs only if follow-up confirmed benign disease. Method 4 counted all cases with a nonmalignant diagnosis as TNs if follow-up confirmed benign disease. A scenario analysis and probabilistic sensitivity analysis were conducted to demonstrate the effect of parameter estimates on DY. A change in DY of >10% was considered clinically meaningful. Results: Across all pairwise comparisons of the four methods, a DY difference of >10% was observed in 76.7% of cases (45,992 of 60,000 comparisons). Method 4 resulted in DY estimates that were >10% higher than estimates made with other methods in >90% of scenarios. Variation in cancer prevalence had a large effect on DY. Conclusions: Across a wide range of clinical scenarios, the categorization of nonmalignant findings at index bronchoscopy and cancer prevalence had the largest impact on DY. The large variability in DY estimates across the four methods limits the interpretation of bronchoscopy studies and warrants standardization.

Uptake of novel systemic therapy: Real world patterns among adults with advanced non-small cell lung cancer.

INTRODUCTION/BACKGROUND: Systemic treatment for advanced non-small cell lung cancer (NSCLC) is shifting from platinum-based chemotherapy to immunotherapy and targeted therapies associated with improved survival in clinical trials. As new therapies are approved for use, examining variations in use for treating patients in community practice can generate additional evidence as to the magnitude of their benefit. PATIENTS AND METHODS: We identified 1,442 patients diagnosed with de novo stage IV NSCLC between 3/1/2012 and 12/31/2020. Patient characteristics and treatment patterns are described overall and by type of first- and second-line systemic therapy received. Prevalence ratios estimate the association of patient and tumor characteristics with receipt of first-line therapy. RESULTS: Within 180 days of diagnosis, 949 (66%) patients received first-line systemic therapy, increasing from 53% in 2012 to 71% in 2020 (p = 0.0004). The proportion of patients receiving first-line immunotherapy+/-chemotherapy (IMO) increased from 14%-66% (p<0.0001). Overall, 380 (26%) patients received both first- and second-line treatment, varying by year between 16%-36% (p = 0.18). The proportion of patients receiving second-line IMO increased from 13%-37% (p<0.0001). Older age and current smoking status were inversely associated with receipt of first-line therapy. Higher BMI, receipt of radiation, and diagnosis year were positively associated with receipt of first-line therapy. No association was found for race, ethnicity, or socioeconomic status. CONCLUSION: The proportion of advanced NSCLC patients receiving first- and second-line treatment increased over time, particularly for IMO treatments. Additional research is needed to better understand the impact of these therapies on patient outcomes, including short-term, long-term, and financial toxicities. MICROABSTRACT: Systemic treatment for non-small cell lung cancer (NSCLC) is shifting from platinum-based therapies to immunotherapy and targeted therapies. Using de novo stage IV NSCLC patients identified from 4 healthcare systems, we examine trends in systemic therapy. We saw an increase in the portion of patients receiving any systemic therapy and a sharp increase in the proportion of patients receiving immunotherapy.

Impact of low-dose computed tomography screening on lung cancer incidence and outcomes.

PURPOSE OF REVIEW: To review findings from clinical trials of lung cancer screening (LCS), assess contemporary issues with implementation in clinical practice, and review emerging strategies to increase the uptake and efficiency of LCS. RECENT FINDINGS: In 2013, the USPSTF recommended annual screening for individuals aged 55-80 years and currently smoke or quit within the past 15 years based on reduced mortality from lung cancer with annual low-dose computed tomography (LDCT) screening in the National Lung Screening Trial. Subsequent trials have demonstrated similar mortality outcomes in individuals with lower pack-year smoking histories. These findings, coupled with evidence for disparities in screening eligibility by race, resulted in updated guidelines by USPSTF to broaden eligibility criteria for screening. Despite this body of evidence, implementation in the United States has been suboptimal with fewer than 20% of eligible individuals receiving a screen. Barriers to efficient implementation are multifactorial and include patient, clinician, and system-level factors. SUMMARY: Multiple randomized trials have established that annual LCS reduces mortality from lung cancer; however, several areas of uncertainty exist on the effectiveness of annual LDCT. Ongoing research is examining approaches to improve the uptake and efficiency of LCS, such as the use of risk-prediction models and biomarkers for identification of high-risk individuals.

Smoking status and the association between patient-level factors and survival among lung cancer patients.

BACKGROUND: Declines in the prevalence of cigarette smoking, advances in targeted therapies, and implementation of lung cancer screening have changed the clinical landscape for lung cancer. The proportion of lung cancer deaths is increasing in those who have never smoked cigarettes. To better understand contemporary patterns in survival among patients with lung cancer, a comprehensive evaluation of factors associated with survival, including differential associations by smoking status, is needed. METHODS: Patients diagnosed with lung cancer between January 1, 2010, and September 30, 2019, were identified. We estimated all-cause and lung cancer-specific median, 5-year, and multivariable restricted mean survival time (RMST) to identify demographic, socioeconomic, and clinical factors associated with survival, overall and stratified by smoking status (never, former, and current). RESULTS: Analyses included 6813 patients with lung cancer: 13.9% never smoked, 54.2% formerly smoked, and 31.9% currently smoked. All-cause RMST through 5 years for those who never, formerly, and currently smoked was 32.1, 25.9, and 23.3 months, respectively. Lung cancer-specific RMST was 36.3 months, 30.3 months, and 26.0 months, respectively. Across most models, female sex, younger age, higher socioeconomic measures, first-course surgery, histology, and body mass index were positively associated, and higher stage was inversely associated with survival. Relative to White patients, Black patients had increased survival among those who formerly smoked. CONCLUSIONS: We identify actionable factors associated with survival between those who never, formerly, and currently smoked cigarettes. These findings illuminate opportunities to address underlying mechanisms driving lung cancer progression, including use of first-course treatment, and enhanced implementation of tailored smoking cessation interventions for individuals diagnosed with cancer.

Reporting Standards for Diagnostic Testing: Guidance for Authors From Editors of Respiratory, Sleep, and Critical Care Journals.

Diagnostic testing is fundamental to medicine. However, studies of diagnostic testing in respiratory medicine vary significantly in terms of their methodology, definitions, and reporting of results. This has led to often conflicting or ambiguous results. To address this issue, a group of 20 respiratory journal editors worked to develop reporting standards for studies of diagnostic testing based on a rigorous methodology to guide authors, peer reviewers, and researchers when conducting studies of diagnostic testing in respiratory medicine. Four key areas are covered, including defining the reference standard of truth, measures of dichotomous test performance when used for dichotomous outcomes, measures of multichotomous test performance for dichotomous outcomes, and what constitutes a useful definition of diagnostic yield. The importance of using contingency tables for reporting results is addressed with examples from the literature. A practical checklist is provided as well for reporting studies of diagnostic testing.

Cell-Free DNA Fragmentomes in the Diagnostic Evaluation of Patients With Symptoms Suggestive of Lung Cancer.

BACKGROUND: The diagnostic workup of individuals suspected of having lung cancer can be complex and protracted because conventional symptoms of lung cancer have low specificity and sensitivity. RESEARCH QUESTION: Among individuals with symptoms of lung cancer, can a blood-based approach to analyze cell-free DNA (cfDNA) fragmentation (the DNA evaluation of fragments for early interception [DELFI] score) enhance evaluation for the possible presence of lung cancer? STUDY DESIGN AND METHODS: Adults were referred to Bispebjerg Hospital (Copenhagen, Denmark) for diagnostic evaluation of initial imaging anomalies and symptoms consistent with lung cancer. Numbers and types of symptoms were extracted from medical records. cfDNA from plasma samples obtained at the prediagnostic visit was isolated, sequenced, and analyzed for genome-wide cfDNA fragmentation patterns. The relationships among clinical presentation, cancer status, and DELFI score were examined. RESULTS: A total of 296 individuals were analyzed. Median DELFI scores were higher for those with lung cancer (n = 98) than those without cancer (n = 198; 0.94 vs 0.19; P < .001). In a multivariate model adjusted for age, smoking history, and presenting symptoms, the addition of the DELFI score improved the prediction of lung cancer for those who demonstrated symptoms (area under the receiver operating characteristic curve, 0.74-0.94). INTERPRETATION: The DELFI score distinguishes individuals with lung cancer from those without cancer better than suspicious symptoms do. These results represent proof-of-concept support that fragmentation-based biomarker approaches may facilitate diagnostic resolution for patients with concerning symptoms of lung cancer.