The American Cancer Society National Lung Cancer Roundtable strategic plan: Optimizing strategies for lung nodule evaluation and management

Abstract

Lung nodules are frequently detected on low‐dose computed tomography scans performed for lung cancer screening and incidentally detected on imaging performed for other reasons. There is wide variability in how lung nodules are managed by general practitioners and subspecialists, with high rates of guideline‐discordant care. This may be due in part to the level of evidence underlying current practice guideline recommendations (primarily based on findings from uncontrolled studies of diagnostic accuracy). The primary aims of lung nodule management are to minimize harms of diagnostic evaluations while expediting the evaluation, diagnosis, and treatment of lung cancer. Potentially useful tools such as lung cancer probability calculators, automated methods to identify patients with nodules in the electronic health record, and multidisciplinary team evaluation are often underused due to limited availability, accessibility, and/or provider knowledge. Finally, relatively little attention has been paid to identifying and reducing disparities among individuals with screening‐detected or incidentally detected lung nodules. This contribution to the American Cancer Society National Lung Cancer Roundtable Strategic Plan aims to identify and describe these knowledge gaps in lung nodule management and propose recommendations to advance clinical practice and research. Major themes that are addressed include improving the quality of evidence supporting lung nodule evaluation guidelines, strategically leveraging information technology, and placing emphasis on equitable approaches to nodule management. The recommendations outlined in this strategic plan, when carried out through interdisciplinary efforts with a focus on health equity, ultimately aim to improve early detection and reduce the morbidity and mortality of lung cancer.

Plain Language Summary

• Lung nodules may be identified on chest scans of individuals who undergo lung cancer screening (screening‐detected nodules) or among patients for whom a scan was performed for another reason (incidental nodules).

• Although the vast majority of lung nodules are not lung cancer, it is important to have evidence‐based, standardized approaches to the evaluation and management of a lung nodule.

• The primary aims of lung nodule management are to diagnose lung cancer while it is still in an early stage and to avoid unnecessary procedures and other harms.

Short abstract

Given the need to balance the benefits of early‐detection of lung cancer and the risks of diagnostic tests, it is imperative to develop evidence‐based strategies for lung nodule management. This report identifies six gaps in knowledge about lung nodule management and proposes six recommendations to improve the management approaches described in clinical practice guidelines.

BACKGROUND

Lung nodules may be identified by cancer screening or incidentally detected during imaging for other reasons. Nodule detection has become substantially more common, in parallel with the increasing utilization and technological advances of computed tomography (CT) scans. ¹ , ² For example, although uptake of annual low‐dose CT (LDCT) screening remains low overall, the number of lung cancer screening (LCS)‐eligible individuals is estimated to have doubled from 8 to 15 million after the expansion of the United States (US) Preventive Services Task Force criteria in 2021, and consequently the number of screening‐detected lung nodules is expected to rise considerably. ³ , ⁴ This number will expand to over 19 million if there is broad acceptance of the new American Cancer Society lung cancer screening guideline, which eliminates years since quit from the eligibility criteria for individuals who formerly smoked. ⁵ Separately, it is estimated that 30% of diagnostic chest CTs demonstrate an incidental lung nodule, and 1.6 million patients may have a lung nodule identified in the United States every year, with current incidence of CT detected lung nodules likely substantially higher. ¹

The conventional approach to lung nodule management fundamentally involves two steps: 1) risk stratification to determine the probability of lung cancer; and 2) varying intensities of diagnostic evaluation (e.g. follow‐up imaging vs. biopsy procedures) depending primarily on the probability of lung cancer. Management of incidental lung nodules is directed by clinical practice guidelines from the Fleischner Society, the American College of Chest Physicians (CHEST), and the British Thoracic Society (BTS). ⁶ , ⁷ , ⁸ Management of screening‐detected lung nodules is guided by the American College of Radiology (ACR) Lung‐RADS approach, with additional metrics and recommendations from CHEST, the National Comprehensive Cancer Network (NCCN), and the American Cancer Society National Lung Cancer Roundtable (ACS NLCRT). ⁹ , ¹⁰ , ¹¹ , ¹²

However, these recommendations for evaluating lung nodules are based primarily on uncontrolled studies of diagnostic accuracy, with few controlled trials or comparative effectiveness studies to provide evidence that is direct and at low risk of bias. ⁷ , ⁸ In addition, there is substantial variability in nodule management among clinicians, even in subspecialty settings. ⁷ , ⁸ , ¹³ , ¹⁴ Furthermore, nodule management occurs in the broader context of implementing care delivery (e.g., access to specialty care and facilities, infrastructure for follow‐up, and other resources). These challenges further complicate the balance of benefits and harms in lung nodule care, where the primary objectives are to maximize early diagnosis of lung cancer, avoid loss to follow‐up, and minimize the potential harms of diagnostic testing.

As part of a broad initiative to improve outcomes for patients with lung cancer, the ACS NLCRT convened a multistakeholder group to identify gaps in lung nodule management and to propose recommendations to bridge these gaps. This article critically evaluates the following aspects of lung nodule care: 1) risk stratification of lung nodules, 2) diagnostic evaluation of lung nodules, 3) implementation of lung nodule management and care delivery, 4) national quality improvement efforts, and 5) health equity.

MATERIALS AND METHODS

The ACS NLCRT was launched in 2017 to catalyze collaborative engagement among public, private, and voluntary organizations, along with invited experts, advocates, and individuals with lung cancer. ¹⁵ The mission of the ACS NLCRT is to reduce the incidence of lung cancer and promote lung cancer survivorship through awareness and prevention, early detection, and assurance of optimal therapy. ¹⁵

A multidisciplinary group of lung nodule management experts from pulmonary medicine, thoracic surgery, thoracic radiology, and the scientific community was assembled to develop the strategic plan for lung nodule evaluation. Task group objectives were: 1) to identify clinical practice challenges and knowledge gaps in lung nodule detection, evaluation, and management; and 2) to propose solutions that will strengthen guidelines in the field and provide a focus for future research and evidence‐based standards, ultimately maximizing timely diagnosis of lung cancer among suspicious nodules and minimizing the potential harms of testing (Table 1). An iterative process was performed, starting with a comprehensive review of the literature on lung nodule management, focusing on existing guidelines and key research advances. The writing group met on July 28, 2021 to produce and review a draft outline, which was subsequently revised by the task group and the ACS NLCRT Steering Committee. Based on this uniform consensus, a manuscript was developed to describe key gaps and recommendations in lung nodule management.

TABLE 1.

Gaps and recommendations for lung nodule management from the ACS NLCRT.

Gaps	Recommendations
1) Risk stratification of lung nodules: lung cancer prediction models for screening‐detected and incidental lung nodules are not routinely used by clinicians.	Prioritize research that develops, validates, tests, and implements lung cancer probability models for clinical use among diverse and generalizable populations.
2) Diagnostic evaluation of lung nodules: clinical practice guidelines for diagnostic evaluation of screening‐detected and incidental lung nodules are based on limited evidence.	Prioritize high‐quality studies of lung nodule management, including randomized controlled trials, comparative effectiveness trials, and rigorously conducted observational research.
3) Implementation of lung nodule management and care delivery:
a) Evidence‐based strategies for leveraging technology‐based tools for lung cancer risk factor assessment and lung nodule identification and reporting are incompletely understood.	Develop, evaluate, and optimize the EHR and other technology‐based tools for nodule identification, reporting, and tracking.
b) Whether multidisciplinary lung nodule clinics improve guideline‐concordant nodule management and/or diagnostic outcomes is incompletely understood.	Promote research on multidisciplinary lung nodule clinics to assess quality of care (guideline‐concordant evaluation) and clinical impact (patient‐centered outcomes).
4) National quality improvement efforts: there are insufficient longitudinal tracking methods for long‐term management of lung nodules, for both clinical and research purposes.	Promote national quality metrics for lung nodule management and develop lung nodule research consortia to facilitate both quality improvement and translational research.
5) Health equity: the presence of disparities in lung nodule evaluation and management is undefined, and methods for equitable delivery of nodule‐related care are not established.	Prioritize research that seeks to elucidate racial, geographic, and other disparities in lung nodule management and test multi‐level strategies for mitigating health inequities.

Abbreviations: ACS NLCRT, American Cancer Society National Lung Cancer Roundtable; EHR, electronic health record.

RESULTS

Gap 1: Risk stratification—lung cancer prediction models for screening‐detected and incidental lung nodules are not routinely used by clinicians

Pre‐test probability of lung cancer determined by standardized risk calculators can help clinicians approach nodule management more systematically. Risk estimation should be performed routinely in practice. ⁸ Multiple validated models exist to estimate the probability of lung cancer for screening‐detected and incidental lung nodules. ⁷ , ⁸ , ¹⁶ , ¹⁷ However, in one study, only 28% of surveyed clinicians reported using validated prediction models when evaluating lung nodules. ¹⁸ Barriers to the use of such calculators include low levels of evidence supporting use of specific risk calculators; lack of awareness, knowledge, or experience; time limitations; and lack of practical applications embedded into clinical and electronic health record (EHR) workflows. ¹⁸ Even when risk models are used, physician assessment and guideline concordance are often divergent. Specifically, one observational study noted that despite accurate assessment of pretest probability of malignancy, 52% of low‐probability nodules were managed more aggressively than guidelines recommend and 75% of high‐probability nodules were managed more conservatively. ¹³ Moreover, subspecialists may perform better or use risk prediction models more often than generalists in estimating the probability of lung cancer, potentially altering clinical outcomes. ¹³

Additional challenges stem from model performance and validation, thereby limiting adoption into clinical practice. ¹⁹ Model performance—often evaluated by discrimination and calibration—is difficult to measure in terms of clinical utility, which in turn may impact clinical effectiveness. Moreover, model performance may not be validated in populations generalizable to routine clinical practice, and lung cancer prediction models depend on the prevalence of malignancy in the populations in which they are being used. Additionally, at the present time there is limited availability and use of calculators that integrate clinical risk factors, molecular features, and imaging characteristics.

Recommendation 1: Prioritize research that develops, validates, tests, and implements lung cancer probability models for clinical use among diverse and generalizable populations

Clinical practice guidelines should provide more specific guidance on the potential benefits of using risk models to determine nodule management strategies, and future studies should incorporate models into study protocols as standard practice. At a minimum, clinicians should routinely document the estimated probability of lung cancer and the method of determination for this estimate at the time of initial and subsequent lung nodule evaluation. Routine use of risk calculators may lead to clearer guidance related to patient management and a more systematic approach by primary care providers and subspecialists alike.

Scientific priorities should include development of new models, as well as refinement of current models. These studies should focus on usability, generalizability, and performance. Subsequent validation studies of lung cancer probability models should consider discrimination and calibration, as well as sensitivity and specificity based on thresholds for high vs. low risk. Additional steps that are equally important to model performance include testing a model‐based strategy against a standard alternative to measure patient‐centered outcomes, as well as rigorous investigation of clinical utility, cost‐effectiveness, and implementation strategies to maximize effectiveness.

Importantly, models should be optimized to improve clinical utilization by leveraging available EHR data and by their inclusion in EHR systems and clinical workflows to improve accessibility. Finally, studies on communication strategies with patients who have incidental or screening‐detected nodules should include how probability calculators can be incorporated into shared decision‐making when deciding between intensive vs. conservative nodule management approaches.

Gap 2: Diagnostic evaluation—clinical practice guidelines for diagnostic evaluation of screening‐detected and incidental lung nodules are based on limited evidence

Current lung nodule management strategies are derived primarily from uncontrolled observational studies, case series, and expert opinion. This includes the 2013 CHEST clinical practice guidelines, where every recommendation carries an evidence grading of 1C or 2C (corresponding to strong or weak recommendations, both based on “low‐ or very‐low‐quality evidence”). ⁸ The Fleischner Society guidelines also reported an evidence grading based on “low‐ or very‐low‐quality evidence” for three of five recommendations. ⁷ Similarly, nearly all nodule management recommendations in the 2015 British Thoracic Society guidelines received a grading of C or D, corresponding to a body of evidence including case‐control or cohort studies, nonanalytical studies, and expert opinion. ⁶ This creates challenges when characterizing nodule management strategies as more versus less intensive relative to what is recommended by clinical practice guidelines.

Although guideline discordant care is frequent, there is inconclusive evidence that less intensive than recommended diagnostic evaluations are associated with more advanced stage at lung cancer diagnosis. ²⁰ , ²¹ Notably, there is evidence that more intensive than recommended diagnostic evaluations are associated with greater procedural complications, radiation exposure, and health care expenditures. ²¹ Together, these findings demonstrate that major gaps remain in understanding which processes and strategies offer the most benefit to patients with the least diagnostic risk and optimal resource utilization.

Additional areas exist where there is a clear lack of high‐quality data. First, it is unclear how the probability of lung cancer is best used as part of a comprehensive approach to lung nodule management—a number of clinical algorithms exist to estimate the probability of cancer, each with inconsistent groupings of very low, low, moderate, or high probability. ¹⁷ , ¹⁹ , ²² , ²³ These wide‐ranging or absent definitions lead to challenges with implementation of surveillance strategies, potentially increasing the risk for loss to follow‐up. Second, an optimal study design for testing the utility of nonsurgical biopsies is not established; existing studies are hampered by inconsistent definitions for diagnostic yield, benign disease, and other limitations in study methodology. ²⁴ Third, a myriad of unanswered clinical management questions remain, such as the benefits and risks of varying intervals and durations of long‐term surveillance including among individuals with a personal history of extrathoracic cancer.

Diagnostic evaluation of lung nodules is made more difficult by variable resources, clinical practices, and expertise across practices, hospitals, academic institutions, and health systems. One study demonstrated that 45% of patients at 15 different Veterans Administration hospitals received lung nodule management inconsistent with existing clinical practice guidelines, and radiologist recommendations were the strongest factors associated with both more‐ and less‐intensive evaluation. ²⁰ A more recent comparative effectiveness research study found that 62% of lung nodule evaluation was inconsistent with Fleischner 2005 guidelines, including 37% receiving less intensive than recommended and 25% receiving more intensive than recommended management. ²¹ Unclear definitions of high versus low risk and guidelines that permit multiple options for larger nodules add additional layers of complexity to nodule management, which also requires nuanced integration of patient preferences and institutional resources. ²⁵ , ²⁶ , ²⁷

Recommendation 2: Prioritize high‐quality studies of lung nodule management, including randomized controlled trials, comparative effectiveness trials, and rigorously conducted observational research

Funders should prioritize studies that will ultimately improve the evidence in lung nodule management. More studies like Watch the Spot, a PCORI cluster‐randomized, pragmatic, comparative effectiveness trial of intensive versus less‐intensive nodule management, are needed to test surveillance and alternative approaches for multiple nodule types. ²⁸ Importantly, a survey study demonstrated that most pulmonary and thoracic subspecialists acknowledge that multiple options for lung nodule management exist and they would be willing to enroll patients in randomized controlled trials (RCTs) comparing strategies for lung nodule evaluation. ²⁹ Although multicenter RCTs are ideal, the scope and cost of additional prospective experimental designs may not be practical. Rigorously conducted observational studies that include methods to enable causal inference can also enhance the available body of evidence. ²⁰ , ²¹ Moreover, studies that include diverse populations are necessary for clinical validation. ³⁰ Timely updates to existing clinical practice guidelines are necessary for clinicians to be able to provide evidence‐based lung nodule management. “Living” guidelines, which are updated on a rolling basis as evidence emerges, is likely an ideal method for keeping pace with development in this field, where there is rapid change in diagnostic procedures across multiple disciplines (including technological changes in imaging and biopsy techniques). For example, although the NELSON trial of lung cancer screening demonstrated that volumetric assessment had high discrimination for lung cancer, this has not yet been added to lung nodule clinical practice guidelines. ³¹ , ³² To our knowledge, all of the major guidelines for incidental lung nodules are currently undergoing evaluation for updates.

Gap 3a: Implementation—evidence‐based strategies for leveraging technology‐based tools for lung cancer risk factor assessment and lung nodule identification and reporting are incompletely understood

The EHR is a powerful tool that can be leveraged to overcome many of the structural and systems‐related barriers across the lung nodule management continuum, from identification to reporting and tracking. ³³

Currently, many health systems have been unable to harness the strengths of the EHR, and in some cases the EHR can even hinder lung nodule evaluation. For example, electronic clinical data are frequently inaccurate and/or inadequate to determine lung cancer risk (i.e., smoking history, comorbid lung disease, family history, or occupational exposures), which may lead to guideline‐discordant evaluation. ³⁴ There is also inconsistent use of the EHR for lung nodule management including low utilization of standardized radiology or provider templates and procedure codes, even among institutions within a single health system. ³⁵ Finally, measurement of clinical outcomes is complicated by unstructured or incomplete information stored in the EHR. ³⁶ , ³⁷ Implementation strategies are underdeveloped and often tested in single‐institution studies, which hinder progress.

These issues can be further exacerbated by fragmented care and inconsistent practices in communication and collaboration, leading to under‐recognition and lack of follow‐up for lung nodules. Poor communication can occur between providers and major incompatibilities also exist among the different capabilities of various EHR systems, Picture Archiving and Communications Systems (PACS), and third‐party tracking software. Technologic capabilities of EHRs far outpace knowledge about the methods for harnessing these systems to improve lung nodule management. Moreover, clinically significant interobserver variability among even experienced thoracic radiologists in characterizing nodule diameter, attenuation, and other characteristics has been described in multiple studies. ³⁸ , ³⁹ , ⁴⁰ Inaccurate or nonstandardized radiologic assessment of lung nodules can have major downstream impacts on evaluation. ²⁰ , ⁴¹

Integrating clinical, radiologic, and potentially molecular factors is critical for evidence‐based lung nodule management. Artificial intelligence (AI), with its ability to synthesize large amounts of information, has the potential to transform multiple aspects of lung nodule management including detection, risk assessment, and tracking. ⁴² , ⁴³ However, there are major gaps in knowledge about optimal methods for AI implementation, and high‐quality, prospective studies are urgently needed. ⁴⁴

Recommendation 3a: Develop, evaluate, and optimize the EHR and other technology‐based tools for nodule identification, reporting, and tracking

Although multiple studies have demonstrated variability in lung nodule identification and reporting, several strategies for leveraging the EHR may have promise in mitigating variability in managing lung nodules. ⁷ For nodule detection, standardization is needed for both technical factors in image acquisition and observer‐related factors affecting nodule characterization on the radiology report. Guidelines such as those from the Fleischner Society addressing lung nodule measurement at CT should be followed to ensure consistency in nodule detection and reporting. ⁴¹ Complementary tools such as AI and machine learning methods can also be implemented to improve detection, and calculation of parameters such as volume doubling time, or even integration of quantitative imaging features, clinical parameters, and genomic analyses could be leveraged for lung cancer probability assessment. ⁴⁵ , ⁴⁶ Technical validation and clinical utility studies to examine the effectiveness and clinical impact of these tools should be prioritized.

For nodule reporting, radiologic results should be entered as structured data, which would allow for systematic alerts for nodules that require surveillance. In one study, implementation of structured reporting using templates and dot phrases or text blocks to standardize nodule documentation into categorical groupings led to a significant increase in early stage lung cancer diagnosis. ³⁷ Similarly, a radiology‐initiated system of tracker phrases, entered into a relational database which harmonized lung cancer risk factors from the EHR, led to an increase in appropriate CT scan follow‐up rates and stage shift toward earlier stage lung cancer. ⁴⁷

For nodule tracking, the EHR and/or computer algorithms can be used to promote nodule follow‐up through clinical decision support and for lung nodule management through electronic prompts. ⁴⁸ In addition, novel approaches for patient communication using the EHR or other technological tools can enhance adherence to follow‐up recommendations. ⁴⁹ Together, these strategies to leverage the EHR’s strengths have great potential to facilitate multiple aspects of lung nodule management. ³³

Gap 3b: Implementation—whether multidisciplinary lung nodule clinics improve guideline‐concordant nodule management and/or diagnostic outcomes is incompletely understood

Analogous to interdisciplinary tumor boards, many academic institutions and referral centers have established multidisciplinary lung nodule conferences to facilitate integrated team approaches for managing patients with screening‐detected and/or incidental lung nodules. Multidisciplinary discussion can improve patient‐centered outcomes including greater adherence to cancer staging (or nodule management) guidelines, more efficient diagnostic and treatment pathways, and increased opportunities for clinical trials enrollment, as well as improvement in overall survival.

Similarly, lung nodule clinics collaboratively and systematically review lung nodules and aim to reduce the harms of diagnostic testing while also expediting evaluation, diagnosis, and treatment for cancer. ⁵⁰ , ⁵¹ These multidisciplinary groups are typically comprised of clinicians in Pulmonary Medicine, Interventional Pulmonology, Thoracic Radiology and Interventional Radiology, advanced practice providers, nurse navigators and Thoracic Surgery. Single‐institution studies have demonstrated that multidisciplinary lung nodule clinics recommend guideline‐concordant care in a majority of cases, and there is high adherence to multidisciplinary recommendations. ¹⁴

However, several common and also highly prevalent barriers to implementation of these interdisciplinary groups exist. There is wide variation in systems‐level resources available to ensure appropriate pulmonary nodule evaluation. ⁵² Access to multidisciplinary groups for nodule evaluation and management is limited. Even in large centers with subspecialist availability, buy‐in from additional stakeholders such as business and practice managers is needed. Consistent and reliable communication between providers is critical for high‐quality lung nodule management, but this often requires an automated process and dedicated personnel such as nurse navigators for successful implementation. ⁵³ Multiple studies describe a major time commitment that is required for clinic preparation and nodule adjudication. ³⁷ , ⁵⁰ Finally, it remains unknown what performance measures and patient‐centered outcomes should be evaluated to define high‐quality lung nodule management.

Recommendation 3b: Promote research on multidisciplinary lung nodule clinics to assess quality of care (guideline‐concordant evaluation) and clinical impact (patient‐centered outcomes)

Additional studies are required to demonstrate the degree to which multidisciplinary management of lung nodules improves quality outcomes, and to identify the critical features of these programs that mediate improvements. Characterizing the nodule subtypes that may benefit most from interdisciplinary review, such as subsolid or cystic lesions, nodules exhibiting very slow growth, or moderate‐probability nodules in individuals with atypical presentations, may also be of value. Measured outcomes may include guideline concordance, stage at lung cancer diagnosis, procedure utilization, or nonmalignant resection rates, as well as patient‐centered outcomes including anxiety associated with nodule evaluation. However, defining accurate and clinically relevant quality measures is complex. With evidence in favor of multidisciplinary nodule clinics or conferences, access to and utilization of such a clinic could serve as an important complementary structural measure of quality.

To fill additional gaps in knowledge, studies should examine the effect of automated referrals and virtual nodule clinics that can provide multidisciplinary review via telemedicine. For centers with active LCS Programs, multidisciplinary review of incidental lung nodules can overlap with LCS clinical teams that are already in place. Navigators can play a key role in facilitating systematic lung nodule review and adjudication. ⁵³ Navigators also serve an essential role in patient outreach, education, and communication and should be considered a fundamental part of any multidisciplinary program. To reinforce the value of the navigator, more work is needed on the potential impact of navigation on reducing loss to follow‐up and even progression of disease. Osarogiagbon and colleagues ⁵¹ described a complementary structure between LCS, lung nodule, and multidisciplinary thoracic oncology programs, which reached different sociodemographic segments of an underserved population with high lung cancer incidence. Additional care pathways should be tested, with attention to consequences such as overutilization of diagnostic testing and value. Finally, it is also critical to evaluate and test optimal patient communication and shared decision‐making processes to decrease patient distress and anxiety during lung nodule evaluation. ²⁹ , ⁵⁴ , ⁵⁵

Gap 4: National quality improvement efforts—there are insufficient longitudinal tracking methods for long‐term management of lung nodules, for both clinical and research purposes

Multi‐level barriers including patient‐, provider‐, and systems‐level challenges may contribute to poor follow‐up of lung nodules. ⁵⁶ At the hospital or health care system level, practices can be put in place to reduce tracking failure of incidental lung nodules. However, there is variability in whether radiologists, ordering providers, or subspecialists are ultimately responsible for tracking and managing lung nodules. A myriad of logistical complexities exist as millions of imaging studies from inpatient and outpatient services and across transitions of care are funneled into PACS and EHR systems. Structured reporting by radiologists can help populate nodule registries and support nodule tracking systems, but only with adequate information technology (IT) infrastructure. Although many health systems have clinical analytics programs to identify incidental lung nodules from radiology reports, these registries provide little clinical benefit without resources and workflows in place to triage nodules and facilitate patient outreach. Furthermore, inclusion criteria and quality measures for nodule tracking must be defined in order to narrow the scope of nodules that require follow‐up, focusing on individuals with lung cancer risk factors and suspicious imaging characteristics.

From a research perspective, nodule registries and biorepositories remain a low priority for research support in the current funding environment. This challenge is a major limitation to harmonizing existing data on lung cancer risk factors, oncologic outcomes, procedures, guideline concordance, and resource utilization, which could advance the field of nodule management. ⁵⁷

Recommendation 4: Promote national quality metrics for lung nodule management and develop lung nodule research consortia to facilitate both quality improvement and translational research

Health policy must prioritize lung nodule management for both clinical and research purposes. National quality metrics and mandates for nodule management should require structured reporting for the presence of nodules and tracking systems. This would drive development of IT systems, guide quality improvement efforts, and lead to measurement of impact of nodule management on patient‐centered outcomes, health care system resource use, and costs. Optimization of safety net protocols could also reduce medical‐legal implications of delayed diagnosis. Establishing quality metrics to require appropriate follow‐up for suspicious lung nodules would also incentivize development of nodule registries, which, for example, have been shown to increase the frequency of diagnosis of stage I lung cancer. ⁴⁷ Expansion of lung nodule programs, including navigation, is also essential for effective management of lung nodule registries and subsequent patient outreach.

Resources should be allocated to develop these nodule registries and biorepositories for research, which can drive scientific discovery and in turn promote evidence‐based nodule care. This could create opportunities for research focused on certain nodule subtypes that might not otherwise be studied in randomized controlled trials, as well as define harms of overly intensive nodule evaluation, validate risk models across varied care settings, enable linkages of clinical data with specimen banks for biomarker testing, and provide opportunities to test new technologies. ⁵⁷ , ⁵⁸ Nodule registries could also be used as recruitment tools for clinical trials and in comparative effectiveness research.

Gap 5: Health equity—the presence of disparities in lung nodule evaluation and management is undefined, and methods for equitable delivery of nodule‐related care are not established

Racial, geographic, and other disparities are clearly identified across the lung cancer continuum, with populations at the highest risk for lung cancer paradoxically experiencing underscreening and receiving lung cancer diagnoses at more advanced stages of disease, undergoing molecular testing less frequently, and receiving surgical resection less often. ⁵⁹ , ⁶⁰ Critical disparities have also been identified in LCS, including identification of eligible patients, access and uptake of LCS, screening adherence, and lung cancer mortality. ⁶¹ , ⁶² , ⁶³ Individuals with lung nodules who are medically underserved also experience societal factors such as systemic racism and classism that promote disparities in care including fragmented evaluation leading to advanced stage at diagnosis. ²⁷ , ⁵⁶ These differences are multifactorial and require multi‐level interventions for improvement. ³⁰

Recommendation 5: Prioritize research that seeks to elucidate racial, geographic, and other disparities in lung nodule management and test multi‐level strategies for mitigating health inequities

Clinical trials in lung nodule management and lung cancer diagnosis must focus on underserved populations and also report outcomes stratified by drivers of disparity including socioeconomic status and access to care. However, emphasis on health equity should transcend the research arena. Health systems should be held accountable for providing equitable access to care in their catchment areas. Efforts to improve clinical care and outcomes at the local and regional levels require investment in supporting public health and community outreach experts, facilitating high‐quality data collection, and encouraging collaboration across institutions, community‐based organizations, funders and support groups, and city and local governments. Furthermore, a united approach to dismantling lung cancer stigma and empowering patient autonomy is essential to building successful relationships with local communities. ⁶⁴

The EHR can also be leveraged to address systemic racism and contributors to social determinants of health, related health disparities, and geographic divides. For example, automated identification of patients with screening‐detected or incidentally identified lung nodules, may lead to more equitable identification of individuals requiring evaluation. However, it is critical to recognize that some marginalized groups may not be easily identified through health system records. Improving nodule clinic availability or other scheduling barriers, or screening for social factors to identify inequities in social determinants of health, may help overcome barriers for underserved populations. Finally, EHR data can be leveraged to identify disparities in lung nodule management within and across health systems. Population cohort data can be used to characterize population centers and identify nodule management needs and allocate resources for vulnerable groups or regions.

In conclusion, this strategic plan from the ACS NLCRT identifies several critical areas for action in the early detection of lung cancer. The need for evidence‐based management for lung nodules is increasing, but many gaps in knowledge remain. We identified knowledge gaps and barriers that, if overcome, could accelerate progress in the field. Major themes include the need for higher‐quality evidence for lung nodule management, characterizing potential gains that can be made through leveraging the EHR, and prioritizing studies in diverse and generalizable cohorts to facilitate equitable health care. These cross‐cutting paradigms align with the 2022 President’s Cancer Panel Goals and Recommendations. ⁶⁵ The Panel highlights the critical importance of improving and aligning communication, facilitating equitable access, strengthening workforce collaborations, and creating effective health IT to close gaps in cancer screening, with direct implications for early detection through lung nodule evaluation and management. The recommendations outlined in this strategic plan, when carried out through interdisciplinary efforts with a focus on health equity, ultimately aim to improve early detection and reduction in the burden of lung cancer.

AUTHOR CONTRIBUTIONS

Julie A. Barta: Conceptualization, writing–original draft, writing–review and editing, investigation, project administration, methodology, and visualization. Farhood Farjah: Investigation, writing–review and editing, methodology, visualization, and conceptualization. Carey Conley Thomson: Writing–review and editing, methodology, visualization, and investigation. Debra S. Dyer: Writing–review and editing. Renda Soylemez Wiener: Writing–review and editing. Christopher G. Slatore: Writing–review and editing. Rebecca Smith‐Bindman: Writing–review and editing. Lauren S. Rosenthal: Writing–review and editing, resources, and project administration. Gerard A. Silvestri: Writing–review and editing. Robert A. Smith: Conceptualization, investigation, supervision, project administration, writing–review and editing, visualization, methodology, and resources. Michael K. Gould: Conceptualization, writing–review and editing, supervision, investigation, methodology, and visualization. All authors participated in acquisition, analysis, and interpretation of data, revising the manuscript, final approval of this manuscript, and agree to be accountable for all aspects of the work.

CONFLICT OF INTEREST STATEMENT

Julie A. Barta reports research grants from the Prevent Cancer Foundation and the Genentech Health Equity Innovations Fund, and consulting for Delfi Diagnostics, Inc, outside the submitted work. Farhood Farjah received funds from the National Institutes of Health (NIH) (R01CA207375, R01CA258352, and U01HL162966) during this project. The NIH was not involved in the design and conduct of the study, collection, management, analysis, and interpretation of the data, preparation, review, or approval of the manuscript, or decision to submit the manuscript for publication. Carey Conley Thomson reports research grants from the American Cancer Society, consulting for Median Technologies to develop technology for lung nodule surveillance, royalties from UpToDate, and editorial fees from Springer outside the submitted work. Debra S. Dyer reports consulting for the Lung Ambition Alliance (that includes AstraZeneca) and Imidex, an AI software development company for CXRs. Debra S. Dyer serves as an unpaid member of the Scientific Advisory Board of the GO2 Foundation. Renda Soylemez Wiener reports receiving research support through her institution from Veterans Affairs Health Services Research and Development Service, Patient‐Centered Outcomes Research Institute, and National Heart, Lung, and Blood Institute. She is supported in part by resources from the VA Boston Healthcare System. The Department of Veterans Affairs did not have a role in the conduct of the study, in the collection, management, analysis, interpretation of data, or in the preparation of the manuscript. The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs or the US Government. Christopher G. Slatore reports he is medical director of lung cancer screening and incidental nodule programs at the institution where he is employed but does not receive additional compensation for these roles. He is supported by resources from the Portland VA Health Care System. His research has been supported by the American Cancer Society (128737‐RSG‐15‐155‐01‐CPPB, Lung Cancer Screening Implementation: Evaluation of Patient‐Centered Care). He currently receives research funding from the Department of Veterans Affairs, Patient‐Centered Outcomes Research Institute, and the NIH. He has received research funding from the Knight Cancer Institute to collaborate with a for‐profit company regarding pulmonary nodule radiomics although neither he nor the Knight Cancer Institute received financial remuneration from this collaboration. Gerard A. Silvestri reports research grants from Biodesix, Nucleix, Delfi, progromiq, Auris, and Olympus and consulting fees from Biodesix and Olympus America. Robert A. Smith reports the American Cancer Society receives grants from private and corporate foundations, including foundations and corporations associated with the health sector, including companies associated with funding for this work. His salary is solely funded through American Cancer Society funds. Michael K. Gould reports receiving research support through his institution from Medial EarlySign to develop machine learning models of lung cancer risk, royalties from UpToDate to coauthor topics on lung cancer diagnosis and staging, and nonemployee compensation from the American Thoracic Society to serve as Deputy Editor of the Annals of the American Thoracic Society.

Barta JA, Farjah F, Thomson CC, et al. The American Cancer Society National Lung Cancer Roundtable strategic plan: Optimizing strategies for lung nodule evaluation and management. Cancer. 2024;130(24):4177‐4187. doi: 10.1002/cncr.35181

DATA AVAILABILITY STATEMENT

Data sharing is not applicable to this article because no new data were created or analyzed in this study.